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LITHUANIAN UNIVERSITY OF HEALTH SCIENCES
MEDICAL ACADEMY
Liubov Kavaliauskienė
ANALYSIS OF THE COST-EFFECTIVENESS
AND COSTS RATIONALIZATION
OF ANTIDEPRESSANTS CONSUMPTION
IN LITHUANIA
Doctoral Dissertation
Biomedical Sciences,
Pharmacy (08B)
Kaunas, 2013
Dissertation prepared in 2008–2012 in Lithuanian University of Health
Sciences.
Scientific Supervisor
Prof. Dr. Rimantas Pečiūra (Lithuanian University of Health Sciences
Medical Academy, Biomedical Sciences, Pharmacy – 08B).
Consultant
Prof. Dr. Virginija Adomaitienė (Lithuanian University of Health Sciences Medical Academy, Biomedical Sciences, Medicine – 06B).
LIETUVOS SVEIKATOS MOKSLŲ UNIVERSITETAS
MEDICINOS AKADEMIJA
Liubov Kavaliauskienė
ANTIDEPRESANTŲ PANAUDOJIMO
LIETUVOJE SĄNAUDŲ EFEKTYVUMO
IR IŠLAIDŲ RACIONALIZAVIMO
ANALIZĖ
Daktaro disertacija
Biomedicinos mokslai,
farmacija (08B)
Kaunas, 2013
3
Disertacija rengta 2008–2012 metais Lietuvos sveikatos mokslų universiteto
Medicinos akademijoje.
Mokslinis vadovas
prof. dr. Rimantas Pečiūra (Lietuvos sveikatos mokslų universiteto
Medicinos akademija, biomedicinos mokslai, farmacija – 08B).
Konsultantė
prof. dr. Virginija Adomaitienė (Lietuvos sveikatos mokslų universiteto
Medicinos akademija, biomedicinos mokslai, medicina – 06B).
4
TABLE OF CONTENTS
ABBREVIATIONS ....................................................................................... 6
INTRODUCTION ......................................................................................... 7
1. LITERATURE REVIEW ...................................................................... 9
1.1. Consumption and costs of antidepressants in Lithuania ................. 9
1.2. Depression epidemiology, usage of antidepressants and risk
factors affecting the rationality of antidepressant consumption .............. 13
1.3. Costs of antidepressants management ........................................... 31
1.4. Cost-effectiveness in depression treatment ................................... 34
2. MATERIALS AND METHODS ......................................................... 40
2.1. Material sources of the research .................................................... 40
2.2. Evaluation methods and criteria .................................................... 42
3. RESEARCH RESULTS AND DISCUSSION .................................... 51
Socio demographic characteristics of the researched population ............ 51
3.1. Analysis of the antidepressant consumption in Lithuania ............. 54
3.2. Analysis of the efficiency of depression diagnosis and treatment
and depression dynamics evaluation ........................................................ 65
3.2.1. Analysis of the efficiency of diagnosis .................................. 65
3.2.2. Inaccuracies in depression treatment ..................................... 66
3.2.3. Evaluation of depression treatment quality ............................ 68
3.2.4. Analysis of the dynamics of depression diagnosis................. 75
3.2.5. Analysis of depression relapse and treatment dependence .... 80
3.3. Analysis of the costs of antidepressants ........................................ 82
3.4. Analysis of the cost-effectiveness and costs rationalization of
antidepressants consumption.................................................................... 90
CONCLUSIONS .......................................................................................... 96
REFERENCES............................................................................................. 97
SCIENTIFIC PUBLICATIONS ................................................................ 106
5
ABBREVIATIONS
AD
ANOVA
ATC
CHIF
CI
CL
CNS
CVD
DALY
DDD
EU
EUROSTAT
GDP
HIF
IMS
INN
IOM
LTL
MAO
MoH
OECD
PDD
SPSS
SSRI
TCA
THIF
WHO
Antidepressants
Analysis of variance
Anatomical Therapeutic Chemical classification
Compulsory Health Insurance Fund
Confidence Interval
Confidence Level
Central Nervous System
Cardiovascular disease
Disability Adjusted Life Year
Defined Daily Dose
European Union
European Union Statistical Office
Gross Domestic Product
Health Insurance Fund
Intercontinental Marketing Services
International Nonproprietary Names
Institute of Medicine
Litas
Monoamine Oxidase
Ministry of Health
Organization for Economic Cooperation and Development
Prescribed Daily Dose
Statistical Package for the Social Sciences
Selective Serotonin Reuptake Inhibitor
Tricyclic Antidepressant
Territorial Health Insurance Funds
World Health Organization
6
INTRODUCTION
The prevalence of depression and the high costs associated with its management heightened the interest in pharmacoeconomic evaluation of drug
treatment [68]. The economic aspects of treating depression are becoming
more frequently evaluated as newer antidepressant medications become
available and as healthcare entities attempt to address increasing costs [10].
In recent years, there has been much debate regarding the real cost effectiveness of new antidepressants [41].
Depressive disorder is a common condition often unrecognized, misdiagnosed, undertreated and usually accompanied by a high level of medical
morbidity [78]. Since depressive disorder is associated with substantial direct and indirect costs, its managed-care systems became a target of special
interest for decision-makers susceptible to be frequently affected by costcontainment policies.
Pharmacoeconomic studies are becoming an essential part of medicine
registration process, medicine pricing and reimbursement policy. Pharmacoeconomic studies analyze various treatment alternatives and thus highlight
their pros and cons presenting decision-makers and providers with robust
data concerning the “best” (i.e., the most cost-effective, the most costbeneficial) treatment alternatives for a given condition [8].
According to the World Health Organization (WHO), more than 150 million individuals suffer from a depressive disorder at any point in time. The
prevalence of depressive disorders and the high costs associated with their
treatment are increasing the interest in pharmacoeconomic evaluations of
antidepressants.
It is important to evaluate the economic and social impact of depression
as treatment costs are exorbitant but generally not recorded. In case of evaluation of this factor, depression treatment would be considered more carefully and responsibly.
The investigated problem involves medicament depression treatment
costs rationalization without any negative impact on the patients’ health
condition.
Enhanced care of depression incurs increased healthcare costs. Therefore,
in deciding whether to adopt these approaches, decision-makers will have to
judge whether the expected benefits can be justified by the required investments. Depression is associated with profound impairments in the quality of
life and daily function, and the health benefits that might be expected are
comparable to many interventions already funded by healthcare systems.
7
These decisions can be made on the basis of a large and robust clinical and
economic evidence base.
Pharmacoeconomic methods are means of measuring the related advantages and costs and provide guidance in medicine selection [102].
The aim of the research. To investigate and assess the possibilities of a
more rational use of the public and private funds of the Lithuanian population in the cases of medicament depression treatment.
The tasks of the research:
1. To perform a comparative analysis of the antidepressant consumption in the years 2004 to 2009 in Lithuania.
2. To evaluate depression diagnosis and treatment effectiveness and
depression diagnosis dynamics in Lithuania from 2004 to 2009.
3. To perform antidepressant cost analysis from 2004 to 2009 in Lithuania.
4. To perform the cost-effectiveness analysis of depression treatment
and propose the possible ways for costs rationalization.
Scientific novelty of the research. For the first time, depression relapse
rate was used as a medicament depression treatment effectiveness evaluation indicator in assessing the rationality of the costs of treatment with antidepressants.
Pharmacoeconomics in Lithuania is highly relevant and both the provision of medicines and savings on health insurance and people resources can
be achieved. The economic side of depression treatment (as well as of improper treatment or untimely diagnosis) must also be assessed to calculate
how much the state pays for the patients with depression and what preventive means must be taken.
Practical and theoretical implementation. The impact of depression on
health economics and the society in Lithuania has not been assessed yet.
This disease has a large epidemiological scale, is often misdiagnosed and
not properly treated. Depression is associated with the economic and social
losses of a certain family and all society [7].
The survey data can be used in practice when dealing with antidepressants consumption and the improvement of the effectiveness of evaluation
and reimbursement systems in Lithuania.
According to the Ministry of Health, in Lithuania, generic medicine policies were one of the priority areas of pharmaceutical policy during the recent years. The suggested treatment effectiveness criteria can be included in
the update of the Minister of Health-approved methods of depression treatment.
8
1.
1.1.
LITERATURE REVIEW
Consumption and costs of antidepressants in Lithuania
The costs of reimbursable medicines are increasing in all the countries;
this becomes a problem even for the wealthy countries. This issue is even
more important for such countries as Lithuania which are unable to allocate
the funds necessary for the reimbursement of medicines to meet their everincreasing demand. New technologies, as well as modern and often expensive medicines, appear in the Lithuanian market each year, and, of course,
the need of the Lithuanian people for treatment is not less than in the Western European countries.
On September 13, 2005, the Decision No. 994 of the Government approved the procedure for the base price calculation of reimbursable medicines, which is valid at the moment. The approved procedure for the base
price calculation has the following major differences from the previously
valid procedure: first, the prices of a medicines manufacturer, which are
used to calculate the base medicines prices in our country, cannot exceed 95
per cent of the average producer prices in Latvia, Estonia, Poland, Czech
Republic, Slovakia, and Hungary. Secondly, for the first time, the procedure
of the base price calculation determined the basic principles for the base
price of the medicine grouping [99].
Reimbursable medicines are mostly intended for the treatment of the patients having chronic diseases. This is especially important for the lowincome and socially-supported patients, as well as pensioners.
In 2009, the surcharges for reimbursable medicines and medical devices
of the population amounted to 20 per cent of the total costs in Lithuania.
Figure 1.1.1 shows the costs of the Compulsory Health Insurance Fund
(CHIF) budget for reimbursable medicines and medical devices, according
to Level I of the Anatomical Therapeutic Chemical (ATC) Classification
[99].
Based on the data presented above, the costs of the medicines that affect
the nervous system form a great part of the CHIF costs and account for 15
per cent of the total cost of reimbursable medicines and medical devices.
9
C - Cardiology
L - Antineoplastic
9%
25%
6%
N - Nervous system
8%
A - Gastrointestinal tract
and metabolism
R - Respiratory system
8%
17%
12%
Medical Aid devices
B - Blood circulation
15%
Other
Figure 1.1.1. Compulsory Health Insurance Fund expenses distribution
by ATC classes
According to the the data of the Health Insurance Fund, in 2009, the
CHIF budget allocated 653 mln. LTL for reimbursable medicines and medical devices, while another 165 mln. LTL were paid by the patients. The
same surcharge rate covered by the population remained in recent years as
well which reveals the stability in the distribution of the costs of reimbursable medicines in Lithuania. 20 per cent of all reimbursed medicines expenses are population-covered expenses.
In recent years the surcharge paid by the population for the medicines
that affect the nervous system amounted to 13 per cent and 14 per cent of
the total costs of reimbursable medicines, respectively, which is much less
compared to the trends of the total cost distribution in Lithuania.
The surcharge paid by the population for the medicines that affect the
nervous system is significantly lower than that for reimbursable medicines
and medical devices in general; thus, on the one hand, a bigger part of the
costs needs to be covered by the CHIF budget while on the other hand
smaller private surcharges for medicines prevents the population from the
excess purchase of medicines.
Therefore, the rationalization of the cots for the medicament treatment of
depression would largely affect the rationalization of the CHIF budget costs
and the antidepressant consumption.
10
According to the data of the State Health Insurance Fund under the Ministry of Health, in 2007, the costs of the CHIF for antidepressants amounted
to 15.57 mln. LTL in Lithuania.
99.2 per cent of depression treatment costs represent adult treatment
(Figure 1.1.2).
0.80%
Adults
Children
99.20%
Figure 1.1.2. Compulsory Health Insurance Fund expences for
antidepressants in 2007
According to the IMS Health data, in 2007, the costs of antidepressants
in Lithuania reached 25 mln. LTL.
This data suggests that in 2007 the costs of antidepressants from the
CHIF budget accounted for 86 per cent of the total cost for medicines in this
group while the surcharges/expenses covered by the population accounted
for the remaining 14 per cent.
This data correlates with the data of the State Health Insurance Fund under the Ministry of Health, and leads to the conclusion that almost all antidepressants in Lithuania are to be exempt under the passport for the reimbursed prescriptions and funded by the CHIF. The planned researches of the
cost-efficiency and the rationalization of the antidepressant costs should
largely affect the state budget.
About 10 per cent of the gross expenditure on health constitutes medicines expenditure (Figure 1.1.3).
11
7%
4%
2%
Hospitals
6%
33%
Physicians/clinical
services
Pharmaceuticals
7%
Other professionals
Nursing homes
8%
Private insurance
administration
Equipment/supplies
10%
23%
Home care
Others
Figure 1.1.3. Health expenditure distribution in Lithuania in 2009
As it is shown in Figure 1.1.4, income and expenditure of the
Compulsory Health Insurance Fund budget are constantly growing up. In
2009, the expenditure of Compulsory Health Insurance Fund was lower than
the income.
4500
4000
Mln. LTL
3500
3000
2500
2000
Income
1500
Expenditure
1000
500
0
2004
2005
2006
2007
Year
2008
2009
Figure 1.1.4. Compulsory Health Insurance Fund budget from 2004 to 2009
12
These values form a constant trend of cost ratio, and the results are wellcorrelated with other European countries.
1.2. Depression epidemiology, usage of antidepressants and risk
factors affecting the rationality of antidepressant consumption
Around 1 in 5 people experience an episode of major depressive illness at
some time in their lives, and 70-80 per cent of the victims experience relapse [1].
About 30 per cent of patients remain depressed despite the initial antidepressants therapy [87]. Depression was also associated with an increased
mortality risk of 1.81 (1.58-2.07) in a meta-analysis of 25 community surveys involving more than 100,000 subjects [14].
In recent years, an increasing number of cases of relapsed depression is
recorded which greatly increases the overall number of patients with this
disease [42].
Mental health is a key aspect of well-being and quality of life. Marked
differences are found between countries when overall mental health is considered [17].
The Second European Quality of Life Survey findings show that the
highest scores for good mental health are seen in the Norway, the Netherlands, Ireland, Germany, Denmark and Sweden. Turkey comes at the bottom, at 47, followed by Malta, Romania, Macedonia and Latvia (all between
53 and 55). Lithuania got 58 per cent of the mean mental health index and is
not far from the lowest level countries (Figure 1.2.1).
The use of antidepressants has increased in all Western countries during
the past 15-20 years. In Finland, the increase between 1990 and 2006 was
nearly 8-fold [92], from 7.09 defined daily doses (DDD) expressed for
1,000 inhabitants a day in 1990 to 55.47 DDDs in 2006. Similar trends have
been reported elsewhere [75].
The trend of the continuing high level of antidepressant use has led the
government to establish very recently a national committee on ‘rationalizing
psychotropic medication use in Belgium [34].
Although consumption of antidepressants at the population level has increased notably, population-based studies with all psychotropics and antidepressants in particular suggest that the increased prescribing may not have
markedly improved the mental health of the population [1].
When analyzing the trends of consumption of antidepressants, attention
is paid to the gender of patients with this disease [103, 104]. It is assessed
that generally women suffer from this disease twice as frequently as men
[87].
13
656666676767676770
Norway
Ireland
Denmark
Belgium
Finland
Hungary
Czech Republic
Slovenia
Greece
Portugal
Italy
Lithuania
Bulgaria
Latvia
Romania
Turkey
%
70
60606060606162626363
5556575858585959
60 47535454
50
40
30
20
10
0
Figure 1.2.1. Mean mental health index (%) in European countries
According to a Eurostat report on the causes of deaths in the EU (2006),
depression is relapsed even in 50 per cent of those with depression and those
who had been treated. After a repetitive treatment, about 70 per cent of patients fall into depression for the third time, and after three treatments, even
90 per cent do.
Just as there are different types of depression, there are different treatments for the different varieties of mood disorders and in this section the
main therapeutic approaches will be highlighted. Reactive depression is best
treated by helping the individual to understand the personal significance of
the upsetting event in their life and getting them to identify their emotional
“blind spot”. This is done through a process called psychotherapy, of which
there are many varieties. Some of the more severe varieties of this form of
depression may need to be treated initially with some sedative medication
before psychotherapy can proceed.
Antidepressant medications are the mainstay of treatment for endogenous
depression and their effectiveness in dealing with this variety of mood disorder has been clearly demonstrated. Depressions which are particularly
severe or have been shown to be resistant to antidepressant medication will
require electro-convulsive therapy (ECT). This treatment remains the single
most effective therapy for patients with severe biological depressions.
Patients, who have relapsed endogenous or unipolar depression with a
particularly disruptive effect on their lives, may require ongoing antidepressant medication or the mood stabilizer, Lithii carbonas, to prevent relapses
rather than start treatment each time depression re-emerges.
14
Depressions have a marked effect on many facets of the patient’s life and
that of their families [55].
Controlled comparisons of the available antidepressants have usually led
to the conclusion that they are roughly equivalent medicines. Although this
may be true for groups of patients, individual patients may for uncertain
reasons fare better on one medicine than on another. European studies show
that patients depressed enough to be hospitalized respond better to classic
tricyclics than to monotherapy with SSRIs. Meta-analyses of outpatient
studies also show greater efficacy of tricyclics in comparison with SSRIs
inpatients who complete trials. The greater tolerability of the SSRIs, however, makes them the preferred agent for most patients. At high doses (> 225
mg), venlafaxine also shows greater efficacy than the SSRIs. Thus finding
the right medicine and the right dose for the individual patient must be accomplished empirically.
The past history of the patient’s medicines experience is the most valuable guide. At times, such a history may lead to the exclusion of tricyclics, as
in the case of patients who have responded well in the past to MAO inhibitors.
Tricyclics and the second- and third-generation agents differ mainly in
the degree of sedation they produce (greater with amitriptyline, doxepin,
trazodone, and mirtazapine) and their antimuscarinic effects (greatest with
amitriptyline and doxepin). SSRIs are generally free of sedative effects and
remarkably safe in overdose. Combined with the ease of once-a-day dosing,
these qualities may explain why they have become the most widely prescribed antidepressants.
No special indications for particular types of depression have been found
for the selective serotonin reuptake inhibitors or other newer antidepressants. The popularity of these medicines, despite their higher cost, is due
principally to their greater acceptance by patients [18].
Adverse effects of various ADs are summarized in Table 1.2.1. Most
common unwanted effects are minor, but they seriously affect the patient
compliance; the more seriously depressed the patient is, the more likely it is
that unwanted effects will be tolerated [18].
Table 1.2.2 illustrates the priority of ADs selection in Lithuania [24]. It
explains that amitriptyline should be the first choice medication for treatment of depression disorders for adults when patients are not contraindicated for TCAs.
15
Table 1.2.1. Adverse effects of antidepressants
Antidepressants
Tricyclics
MAO inhibitors
Mirtazapine
Venlafaxine
Bupropion
Fluoxetine and
other SSRIs
Adverse effects
Sedation (sleepiness, additive effects with other sedative medicines)
Sympathomimetic (tremor, insomnia)
Antimuscarinic (blurred vision, constipation, urinary hesitancy, confusion)
Cardiovascular (orthostatic hypotension, conduction defects, arrhythmias)
Psychiatric (aggravation of psychosis, withdrawal syndrome)
Neurologic (seizures)
Metabolic-endocrine (weight gain, sexual disturbances)
Sleep disturbances, weight gain, postural hypotension, sexual disturbances (phenelzine)
Somnolence, increased appetite, weight gain, dizziness
Nausea, somnolence, sweating, dizziness, sexual disturbances, hypertension, anxiety
Dizziness, dry mouth, sweating, tremor, aggravation of psychosis,
potential for seizures at high doses
Gastrointestinal symptoms, decreased libido, sexual dysfunction,
anxiety (acutely), insomnia, tremor.
Table 1.2.2. Priority of ADs selection for treatment of depressive disorders
TCA
Amitriptyline
SSRI*
Fluoxetine
Citalopram +
Escitalopram +
Paroxetine
Sertraline +
Fluvoxamine
First Choice
Other
Mirtazapine *+
Reboxetine*
Bupropion
Venlafaxine
Tianeptine+
SSRI
Fluoxetine
Citalopram
Paroxetine
Sertraline
Fluvoxamine
Second Choice
Other
Mirtazapine
Reboxetine
Bupropion
Venlafaxine
Tianeptine
* For children and patients who are contraindicated for TCA.
+ Elderly patients (> 65 years)
Factors affecting rationality of antidepressants use
Political factors
In Lithuania, mental health services are provided by four sectors: residential psychiatric hospitals, mental health centers, non-governmental organizations and the private sector.
Since 2007, the right to diagnose depression for the first time and to prescribe the treatment has been provided to family doctors in Lithuania.
16
While treating the starting or acute depression, the effect of medicament
preparations should be observed already after 4 weeks, and the improvement
of the course of disease after 8 weeks.
Lithuania is currently running the following legislation and programs:
 Mental Healthcare Act (adopted in 1995, i.e. one of the first in the
Central and Eastern Europe),
 The Law on the Patients’ Rights and Compensation,
 National Suicide Prevention Program,
 National Mental Health Protection Program.
Specialists point out that although the legislation and programs do exist,
the lack of a common strategy in the field of the mental healthcare can be
observed. The mental health services are only partially combined with prevention programs, social care and protection, education, employment and
housing. There is no mechanism to ensure the service quality. Some institutions of the mental healthcare have an internal audit, but such an audit is not
performed at the national level.
The availability of medicines is ensured by the mechanism for the medicine reimbursement, the pharmacies working 24 hours a day, the receptions
of the psychiatric hospitals and the doctors on duty.
The mechanism that ensures that people with mental health problems
possess the right to complain about the treatment is legally valid, but in
practice it is poorly operating. The patients and their families really do not
know what authorities they should address their complaints to [84].
Economic factors
According to the data of the State Health Insurance Fund (HIF) under the
Ministry of Health (MoH), in the first quarter of 2009, 82 per cent of all the
reimbursable prescription medicines were sold at the level of the prices of
generic medicines (without the evaluation of the surcharges paid by the patient).
 The highest costs for the reimbursement are associated with the original patented medicines which makes 52 per cent of the total reimbursement
budget.
 35 per cent of the prescriptions are issued for the original unpatented
medicines which together with generic medicines (47 per cent of all the prescriptions) represent 48 per cent of the total costs.
As long as the reimbursable price is based on the cheapest medicines at
the same International Nonproprietary Names (INN) Group, there is no difference for the Health Insurance Fund whether to reimburse an original unpatented medicine or a generic medicine. For this reason, 82 per cent of all
17
the prescriptions are paid at a price determined in accordance with the
cheapest level of generics. 18 per cent of all the prescriptions issued for the
original patented medicines (having no equivalent among generics) correspond to 52 per cent of the reimbursable costs.
In order to rationalize the medicament treatment of depression in Lithuania, it is necessary to encourage the user to choose generic medicines whenever possible thus saving the money of the state and the patient.
Three pharmaceutical categories taking the highest positions in terms of
the costs – C (the medicines that affect the cardiovascular system), N (the
medicines that affect the nervous system) and L (the antineoplastic and immunomodulation agents) – make up 60 per cent of the total cost of the
Health Insurance Funds for reimbursable medicines.
As much as 27 per cent of the total cost is composed of ethical unpatented medicines within Category N (the medicines that affect the nervous system); the rationalization of this segment of costs is necessary to save the
funds designed for the medicament treatment of depression.
In the case of Categories C and N, more than 50 per cent of funds are designed for the reimbursement of medicines when the reimbursable cost is
determined based on the cheapest generics.
According to the IMS Health data, the penetration of generic medicines
in the Baltic countries in the second quarter of 2009 year amounted to 22–26
per cent in terms of value and to 24–25 per cent in terms of quantities.
Compared with the other Baltic countries, the share of generic medicines
is the highest in Lithuania.
As it has been mentioned above, as much as 60 per cent of the costs of
the Health Insurance Fund for reimbursable medicines involve only three
categories of medicines (according to the ATC Classification), one of which
is the Medicines that affect the nervous system.
In terms of costs of their consumption, antidepressants can be divided into relatively expensive (in terms of money) and relatively cheap ones.
A group of expensive medicines usually consists of the ethical medicines
by pharmaceutical companies. A group of the relatively cheap medicines
consists of the so-called generic medicines.
According to the IMS Health data, during the period of 2004 to 2009, the
market share of generic medicines was decreasing. When comparing the
value, the market share of generic medicines remains more or less stable. If
compared with the data of 2008, in 2009, the costs of antidepressants decreased (it amounted to 26.75 and 23.92 mln. LTL respectively) while the
trend of the cost growth ceased. It happened after generic medicines – the
selective sertraline reuptake inhibitors (SSRI) – entered the market. This
18
data suggests that the penetration of generic medicines in the market has a
direct impact on the reduction in the costs for the treatment of depression.
In 2009, the costs of antidepressants decreased and the trend of the cost
growth ceased. It is probable that it happened after generic medicines – the
selective sertraline reuptake inhibitors (SSRI) – entered the market.
The entry of a generic equivalent of a patented medicine into the market
caused the significant reduction of expenses of patients as well as the state
for these medicines.
Dramatic changes in pharmaceutical markets make it imperative for generic medicine producers to work with governments in order to create the
best conditions for developing, manufacturing and marketing their medicines [82].
The European Generic Medicines Association study concludes that these
traditional instruments — reference-pricing systems, prescribing budgets,
generic substitution, patient co-payments, information campaigns — can
indeed be effective in stimulating generic up-take but that they must be designed to stimulate competition. The EU report on the competition in the
pharmaceutical sector research states that in order to develop a generic medicines market, supply-side measures need to be supplemented by demandside policies thus creating incentives for physicians, pharmacists and patients to use generic medicines. Indeed, this report demonstrates that demand-side policies are critical to a sustainable generic medicines market.
The study clearly identifies the importance of a high-volume share of the
market for generic medicines in order for the EU generic medicines industry
to compete effectively: the ability of the generic medicines industry to deliver competitive prices can only be achieved and sustained if it is assured a
high volume of the pharmaceutical market. The high volume according to
the European Generic Medicines Association is dependent on the demandside policies.
According to the European Research Centre for Pharmaceutical Care and
Pharmacoeconomics, the experience of European countries shows that there
is no single approach towards developing a generic medicines market. For
instance, the demand for generic medicines in mature markets is driven by
generic substitution by pharmacists in Denmark and the Netherlands, a favorable attitude of physicians towards generic medicines in Poland or physician budgets in Germany and the United Kingdom. Also, the development
of a generic medicines market needs to be actively sustained by a generic
medicines policy. Consequently, countries that promoted generic medicines
for 10-15 years (e.g. Denmark, Germany, the Netherlands) naturally have a
more mature generic medicines market than the countries that only recently
19
implemented measures to stimulate the use of generic medicines (e.g. Austria, Belgium, Portugal).
Countries have drawn on supply-side policies relating to pricing and reimbursement to develop their generic medicines market. Limiting the policy
to supply-side measures only, as is the case of Austria, is insufficient in realizing the full potential of a generic medicines market. To develop a generic
medicines market, supply-side measures need to be supplemented by demand-side policies in order to create incentives for physicians, pharmacists
and patients to use generic medicines. Furthermore, generic medicines policy grew incrementally in countries over time and reflects demographic, cultural, economic and institutional constraints. Therefore, there is no reference
set of policy measures that countries can adopt to promote their generic
medicines market [94].
The ability of the generic medicines industry to deliver competitive prices can only be achieved and sustained if it is ensured a high volume of the
pharmaceutical market. This high volume is dependent on demand-side policies. On the one hand, countries with mature generic medicines markets
have in place incentives for physicians, pharmacists and/or patients to demand generic medicines [81]. On the other hand, there are few incentives to
stimulate generic medicines consumption in countries with developing generic medicines markets. In Italy and Spain, the limited volume of generic
medicines consumption in combination with low medicine prices has undermined the economic viability of the generic medicines market [69].
Countries do not fully recognize the role that patients play in generic
medicines consumption. Generally, few policy measures are in place that
either incite patients to demand generic medicines or penalize patients for
not demanding generic medicines. The extent to which patients contribute to
the cost of medicines is likely to play a role in the use of generic medicines
[50].
Several countries including Belgium, Italy, Portugal, Spain and the United Kingdom launched advertising campaigns to inform patients of generic
medicines. In Belgium, the campaign was short-lived and had limited exposure. In Portugal, pro-generic-medicine media campaigns aimed at physicians and pharmacists in addition to patients appear to have contributed to
the increasing demand for generic medicines. No formal evaluations of the
impact of advertising campaigns on generic medicines consumption exist
[22].
Countries need to incite patients to demand generic medicines or penalize
patients who do not demand generic medicines. This may take the form of
financial incentives that reduce co-payment on generic medicines or impose
higher co-payment on originator medicines.
20
Furthermore, countries can increase patient awareness of generic medicines by means of advertising campaigns. Initiatives that attempt to influence consumption patterns by personally contacting patients can also be envisaged [20].
In many cases, the data of the survey conducted in the Pharmaceutical
sector by the offices of the Directorate-General (DG) for Competition of the
European Commission disclose the interference of medicinal companies in
the procedures of national government authorities (rather than in the procedures of patent offices). The companies producing patented medicines intervened when the companies providers of generic medicines were applying
for the permission to sell their products and expressed dissatisfaction due to
their status of pricing and reimbursement. The companies producers of patented medicines argued that generic medicines are less safe, less effective,
and (or) of lower quality. They also claimed that the marketing permissions
and (or) the granting of pricing or reimbursement status could violate their
patent rights although the authorities providing the marketing permissions
might disregard this claim. The intervention of the companies producers of
patented medicines was often associated with several medicines from which
a high turnover could be received.
In the cases when the patent-related issues reached a trial, the claims of
the companies producers of patented medicines were satisfied only in 2 per
cent of all the cases, which suggests that the arguments presented against the
generic medicines could not be justified.
Due to the intervention and litigation of the companies producers of patented medicines and because of the intervention in the administrative proceedings concerning generic medicines, the market entry of generic medicines may be delayed. The detailed examination of the data related to the
sample medicines reveals that in the cases of the intervention the market
permissions were issued on average four months later.
According to the data of the offices of the DG for Competition of the European Commission, the companies producers of patented medicines spent
an average 23 per cent of their turnover on the marketing and advertising of
their medicines. While implementing their business strategies, the companies producers of patented medicines not only advertise their medicines to
doctors and other healthcare professionals but also seem to take the actions
and to call into question the quality of generic medicines.
The mainstream economic theory generally assumes that the characteristics of the medicines are obvious for the consumer who can choose between
any given medicine on the basis of prices and preferences. This simplistic
presentation of medicine qualities is discussed by many researchers in socio-economics. The Lithuanian authorities legally defined the generic medi21
cines as identical in essence to the original medicines but a myriad of small
differences remain in its presentation.
Generic medicines are chemically equivalent and bioequivalent to originator brands, but can be significantly cheaper because they are allowed to
enter the market after the patent expiry of the originator brand. In this way,
generic manufacturers do not incur Research and Development costs and are
able to offer a significant price advantage over the originator brand. As a
result, health insurance is keen to promote the use of generics among patients as well as encourage generic competition by using a variety of policies with a view to maximizing savings on the medicines bill. Given the
emphasis on healthcare cost containment and the pursuit of efficiency in
resource allocation, generic policies and their perceived and actual effectiveness have been at the center of attention for many years in the majority
of countries.
Policies encouraging the use of generics within healthcare systems have
been at the center of attention over the past decade for a number of reasons.
First, as healthcare costs as a proportion of GDP have continued to rise over
the past decade, governments and health insurers have been trying to contain their rate of growth as well as improve the efficiency in the use of
scarce resources. Second, the implementation of generic policies necessitates policy action both on the supply- as well as the demand-side of
healthcare economies. Consequently, multiple actors and stakeholders are
involved, incentivized or affected by such policies. Among them are physicians, who need to be convinced to prescribe generics, pharmacists, who, in
order to dispense generics need an appropriate incentive structure on margins, and patients, who are at times skeptical about whether generics provide
the same quality of care as originator brands. Given the multiplicity of actors and stakeholders, different policy measures and incentives need to be
made available to each of these making generic policy a complex policy
area which has, on several occasions, taken a long time to deliver low prices
for off-patent medicines, high levels of penetration, and, by implication,
high savings to health insurance. Third, despite the emphasis on generic policies, there is little knowledge of their actual effectiveness in different environments, whether they indeed result in sustainable price reductions and
whether they diffuse fast in different environments [44].
In the Second European Brain Policy Forum, the 12 brain diseases that
are most costly for Europe were determined. According to the data from
2004, the affective disorders required 106 billion Euros. In the second place,
diseases caused by various addictions could be found, followed by the disorders of dementia, psychosis and anxiety. Depression is the costliest brain
disease, for which Europe currently allocates 118 billion Euros.
22
The costs allocated to depression consist of the direct and indirect costs.
The direct costs are associated with the working of the healthcare staff in the
case of the people already having depression, i.e. when a patient comes to a
specialist, e.g. at a clinic, or hospital emergency department. Also, the direct
costs include the loss of work or activity measured in the duration of the
days of unemployment. The burden of the indirect costs of depression falls
mainly on the surroundings of the patient – the family members, employers,
and, during the period of the acute disease, the colleagues who must partially take over his/her work. The journal “Medicine” states that 90 per cent of
the costs of depression treatment consist of the indirect expenses that relate
to the quality of life [86].
The treatment costs and the rational use of funds has become an integral
part of the health system solutions. European countries use different methodologies for this assessment. Methodologies are different as well as health
systems and their financing. Taking into account the comparable domestic
economic and social conditions, the Baltic countries (Lithuania, Latvia and
Estonia) have decided to apply the same recommendations for the pharmacoeconomic analysis of medicines. According to the order by the Minister of Health of the Republic of Lithuania on the approval of the recommendations for the pharmacoeconomic analysis, these recommendations are to
be referred to during the assessment of any medicine that is requested to be
included in the list of medicines reimbursable from the budget of the Mandatory Health Insurance Fund as well as in the methods of disease diagnosis
and outpatient treatment.
While the medical science and technology have advanced at an extraordinary pace, the healthcare provision system has floundered. As currently
structured, the healthcare structure does not make the best use of its resources [13].
Healthcare delivery has been relatively untouched by the revolution in information technology that has been transforming nearly every other aspect
of society. The Institute of Medicine (IOM) in the United States of America
Committee believes that information technology must play a central role in
the redesign of the healthcare system if a substantial improvement in quality
and safety is to be achieved over the coming decade.
In the absence of a national commitment and financial support to build a
national health information infrastructure, progress on quality and safety
improvement will be painfully slow.
Social factors
Mental health problems have been estimated to account for approximately 20 per cent of the total burden of ill health across Europe. Unipolar de23
pressive disorders accounted for the highest proportion of total Disability
Adjusted Life Years (DALY) in Austria (9.8 per cent of the total), Belgium
(9.7 per cent), Cyprus (6.9 per cent), Denmark (8.1 per cent), Finland (10.8
per cent), France (10.3 per cent), Ireland (8.3 per cent), Italy (6.8 per cent),
the Netherlands (7.8 per cent), Norway (8.9 per cent), Slovenia (9 per cent),
Spain (5.6 per cent) and Sweden (9.7 per cent). In Finland and Sweden, the
most prevalent cause of death after Cardiovascular disease (CVD) was Alzheimer’s disease and other dementia. Mental health problems affect a great
many people; one in four experiences a significant episode of mental illness
during their lifetime. Data from the Global Burden of Disease Study indicates that four of the six leading causes of years lived with disability are
attributable to mental health problems: depression, schizophrenia, bipolar
disorders and alcohol-use disorders. Depressive disorders are most common,
making up nearly one third of all mental health problems. One recent attempt to address this deficit was a systematic review of all available epidemiological studies on a variety of mental disorders affecting individuals
aged between 18 and 65 conducted at a community level across the EU27,
plus Norway, Iceland and Switzerland (Table 1.2.3).
Table 1.2.3. European prevalence rates of mental disorders and an estimated number of individuals affected annually
Diagnosis
Alcohol dependence
Illicit substance dependence
Psychotic disorders
Major depression
Bipolar disorder
Panic disorder
Agoraphobia
Social phobia
General anxiety disorder
Specific phobias
Obsessive compulsive disorder
Somatoform disorders
Eating disorders
Any mental disorder
12-month prevalence
median and range (per
cent)
2.4 (0.1–6.6)
0.5 (0.1–2.2)
0.8 (0.2–2.6)
6.9 (3.1–10.0)
0.9 (0.2–1.1)
1.8 (0.7–3.1)
1.3 (0.1–10.5)
2.3 (0.6–7.9)
1.7 (0.2–4.3)
6.4 (0.8–11.1)
0.7 (0.1–2.3)
6.3 (1.1–11.0)
0.4 (0.2–0.7)
27.0
Number of EU individuals affected in any
one year (mln.)
7.2
2.0
3.7
18.4
2.4
5.3
4.0
6.7
5.9
18.5
2.7
18.9
1.2
82.7
The review identified 24 country-specific and 3 cross-national studies;
one striking finding being that no population-based data at all was available
24
from 12 countries (Cyprus, Estonia, Greece, Ireland, Latvia, Lithuania, Luxembourg, Malta, Poland, Portugal, Slovakia and Slovenia), representing
54.8 mln. inhabitants (17.5 per cent) in the age range under scrutiny. By
using this data, the study estimated that 82.7 mln. people (27 per cent of the
population) across Europe (including Iceland, Norway and Switzerland) are
affected by a mental disorder during any 12-month period [63].
It is estimated that up to 6 per cent of males and 12 per cent of females
experience at least one episode of clinical depression during their lifetimes.
An episode of depression can be mild to severe, or it can be chronic (dysthymia), lasting for at least two years. An estimated 70 to 80 per cent of patients with depression can be treated successfully, and usually feel better
within weeks of beginning treatment. As depression is biochemical in nature, antidepressant medications are successful as a first-line defense in its
treatment.
Patients with a depressive disorder are treated in outpatient settings by
general practitioners (or family doctors, GPs) or by specialists for psychiatry. GPs play a key role as they are often the first healthcare providers for
the recognition, diagnosis, referral, and treatment of depression. Depression
is rather common in primary care: it is estimated to affect about 10 per cent
of all primary care attendees [28], [95], [115]. Recent studies in Germany
show that 11.5 per cent of the adult population suffer from affective disorders, 8.3 per cent of the population have experienced a major depression
during the past 12 months, and that every fourth patient in general practice
fulfills the criteria for depression.
According to recent data of the United States of America and Canada
[11], [49], [120], the German study of Wittchen and colleagues revealed that
only a half of depressed patients ever contacted a healthcare institution, and
only one third of these patients ever received intervention [118]. Another
problem relates to delayed referrals to specialists or psychiatric hospitals
[77], [97]. Reasons for this situation in primary care are various, and a range
of patient, doctor and organizational factors contribute to this problem [35],
[52], [95], [110].
In addition to GPs, specialists such as psychiatrists, psychotherapists or
neuropsychiatrists have an important function in outpatient care. Depressive
disorders are the most significant and frequent illnesses treated by these
specialists [58]. However, there is empirical evidence of underdiagnoses and
undertreatment, even by psychiatrists [47].
The fact that guideline-oriented treatment leads to distinct improvement
in the treatment of depression was established in international studies [53].
Unfortunately, such guidelines [27], [40] are still underused in practice. The
adherence to a multi-level care model between general practitioners and
25
specialists also brings about evident improvement in the treatment of depression [118], [45]. Moreover, the efficacy of specific quality management
programs in reducing deficits in the diagnosis and treatment of depression
has been shown [45], [48].
In Sweden, only 1 of 5 patients is treated with antidepressants. The suicide risk for the patients with depression treated with antidepressants is 141/
100,000 patients per year while the risk of the untreated patients with depression is 259/ 100,000 patients per year, i.e. 1.8 times higher than in the
case of those treated with antidepressants [29].
In conclusion, because depression is underdiagnosed and undertreated,
screening in a primary care setting should be routine, especially when there
are comorbidities [107].
The analysis of the mental health rates in Lithuania reveals that in the
long-term last period perspective (during the period of the years 2007
through 2011), the incidence and prevalence of mental disorders has been
increasing (Figure 1.2.2). This dynamics correlates with the growing numbers of depression diagnosis and especially with the dynamics of relapsed
depression cases in Lithuania.
In addition, the remission itself is not easy to achieve. Only 1 out of 3 patients are lucky to achieve the remission with the first medication prescribed, and the successive antidepressants further decrease this likelihood.
A recent research reveals that the increase in the likelihood of achieving
remission can be determined by the fast response to the treatment, i.e. if the
medicine starts to work within the first two weeks. Unfortunately, the onset
of an action of the most common conventional antidepressant is 3-4 weeks
[112].
26
Cases per 100 thousand inhabitants
6,000
5,000
4,864
4,955
4,956
5,082
5,124
4,000
Incidence
3,000
Prevalence
2,000
1,000
250
259
267
269
292
2007
2008
2009
2010
2011
-
Figure 1.2.2. Incidence and prevalence of depression in Lithuania
from 2007 to 2011
The International guidelines for mild depression offers to prescribe psychotherapy; only Canada and the U.S. also refer to certain cases which
should be treated with antidepressants [71].
All the guidelines advise to treat the average depression with an antidepressant or psychotherapy, or with an antidepressant and psychotherapy
[51].
Antidepressants should always be prescribed for the treatment of severe
depression, which also can be combined with other means of treatment.
In order to improve the mental health of the Lithuanian population, more
attention should be provided to the institution of a family doctor. According
to the data of the Department of Statistics under the Government of the Republic of Lithuania, the number of family doctors working in the primary
healthcare facilities reached 1,792 in 2006, and was 2.6 times bigger than
compared to 2000 when the figure merely reached 692. In 2008, family doctors provided their services to 76 per cent of the residents while temporary
teams worked with 24 per cent of the population [122]. This indicates that
the institution of a family doctor is a particularly important part of
healthcare. Family doctors are the closest to the people; the patients’ health
status is often dependent only on the expertise and knowledge of a family
doctor. In providing efficient primary healthcare services of high quality, it
may be possible to determine the risk factors in time, to identify the disease
27
early, to prevent the disease complications and exacerbations, to reduce the
number of the addresses to specialists as well as the necessity of hospitalization [30].
Technological factors
Health insurance has been implemented in Lithuania since July 1997
while the pharmacoeconomic assessment of the reimbursement of the medications designed for the outpatient treatment has been carried out from the
budget of the Mandatory Health Insurance Fund since August 1, 1997. The
centralized purchases of medical devices and a part of medicines was
launched in 1998 by the State Health Insurance Fund.
The Division for the Medical Technology Assessment of the State Health
Insurance Fund was formed in April 1999. Medical technology assessment
is a very broad term that includes technical measures applied in medicine as
well as the installation of scientific innovations; it can also be treated as
medical service assessment. Medical service assessment intended for medical technology better quality, is associated with a number of institutions: the
Health Committee of the Lithuanian Parliament (the Seimas), the Ministry
of Health, the State Health Insurance Fund, other health authorities, health
professionals and their associations, patients, their associations, the suppliers of medical devices or medicines. The State Health Insurance Fund performs the analysis of the costs of healthcare services and presents suggestions on ways to modify the order of payment for various services (e.g. for
the emergency medicament treatment or primary healthcare). Together with
the MoH and individual experts in different fields, the services are detailed,
and the prices are set (e.g. for tuberculosis, psychiatry, intensive care).
After the presentation of psychiatry services in greater detail and the introduction of the new payment fees, the costs of psychiatry increased by 16
per cent; on the other hand, the costs of services provided within this profile
of disease treatment are allocated more appropriately, and the HIF is aware
of what services and for what quantity of them are to be paid. This data facilitates the performance of an expert analysis. The HIF, together with the
MoH, advises healthcare facilities on the installation of new medical technologies and carries out their assessment [130].
In accordance with the Public Procurement Act and other regulations, the
HIF exercised the centralized procurement of various medical devices and
some medicines. All the devices centrally procured by the HIF are approved
for the use in Lithuania. Under the established conditions of competition,
foreign producers are required to provide international quality certificates.
At the moment, virtually all of the medical devices centrally procured by the
HIF are manufactured in the Western countries. The need for medical de28
vices (pacemakers, blood clotting factors, etc.) designed for the emergency
medical aid is fully satisfied. Due to financial difficulties, the need of the
medical devices used for the planned medical aid is not fully satisfied because the queues are formed for some of these devices (e.g. patients need to
wait for the planned joint replacement surgery for about two years). The
patient receives a centrally procured medical device for free, i.e. he/she does
not have to pay any surcharges. The list of the centrally procured medical
devices approved by the Order No. 67 as of February 4, 2000 by the MoH,
includes the devices of 22 names for which 37 mln. LTL is allocated.
Currently, the following scheme for the access of a new device to the list
of the centrally procured devices is formed: the supplier’s proposal, recommendations of healthcare professionals as well as patients’ requests, are presented, the analysis of the experience of other countries, the potential assessment of costs and the financial capability of the Fund are carried out,
and the decision by the Mandatory Health Insurance Council is also necessary.
According to the State Patient Fund, the benefit of the centralized procurement is that the allocated considerable resources tend to attract more
suppliers and increase their competition; this in its turn leads to a greater
supply of goods, a better quality and lower prices. More medical devices or
medications can be procured for the same budget.
Logical model of antidepressants utilization and its interaction with external factors
Antidepressants as a means (tools) used in cases of mental health problems application affecting factors model can be constructed by the interactions of three functional systems (Figure 1.2.3).
In the social-economic models of the system, the following entities are
involved: the population (patients), professionals (doctors and pharmacists),
cultural development entities that affect the patients’ behavior (family,
school, work environment, the community), social and health policy-making
institutions (public policy and management bodies, specialized departments), monitoring and control models (epidemiological observations, resource accounting: Statistics Department in Lithuania, Institute of Hygiene
at the Ministry of Health of Lithuania, the Health Insurance Fund of Ministry of Health and others).
Besides, in the economic-financial models of the system, medicines price
reimbursement mechanism ensuring institutions and bodies (Compulsory
Health Insurance Fund, Health Insurance Fund) and generic penetration
providers (Ministry of Health of Lithuania, generic medicines companies)
also operate.
29
IC M ODELS
M
NO Physicians
Pharmacists
Social and
health policy
makers
Patients
Cultural
development
entities
Monitoring and
control models
EC
ON
FINAN
C
IC I AL
OM
SOCIAL - E
CO
The functioning of innovation-financial models is ensured by such subjects as scientific research institutions (universities, laboratories) as well as
ethical pharmaceutical companies introducing new medicines and new medicament treatments by initiating new medicament treatment policies and
setting new trends in pharmacotherapy.
Drug
reimbursement
system
Universities
Laboratories
ELS
O
NN
NC
OD
I
Ethical pharmaceutical
industry
M
MODELS
L
A
I
Generic Drug Policy
VE - F
I
VATI
B
NA
Figure 1.2.3. Logical model for antidepressant use affecting factors
According to the rational antidepressants consumption evaluation in
Lithuania carried out in the PEST analysis, it was found that the technological and policy factors (legislation, modern antidepressants registration in
Lithuania, medicines reimbursement system regulation) do not ensure a rational use of certain medicines. The basic risk factors of efficient and rational use of antidepressants consist of social and economic factors (healthcare
professionals’ qualification, patients’ behavior, relatively slow penetration
of generic medicines into the market) (Table 1.2.4).
30
Table 1.2.4. Evaluation of the risk factors of rational antidepressants consumption evaluation
High risk
Family doctors qualification
Patients’ behavior
Medium risk
Generic medicines politics
Inefficient use of pharmacist
competence in health activities
Information system database
management
Low risk
Medicines reimbursement system
The legal regulation of antidepressants use
According to the results of the situational analysis, there are numbers of
factors associated with the depression diagnosis, treatment and antidepressants use and its costs in the healthcare industry that need to be improved.
According to this survey, certain tasks were selected, the result of which had
to be the definition of certain logical models of continuous failure as well as
the adjustment of the current model of depression treatment in order to rationalize the use of antidepressants and increase the depression treatment
costs effectiveness in Lithuania.
1.3. Costs of antidepressants management
Pharmacoeconomic analysis of medicines involves the application of analytical methods in order to link the costs of the medicament treatment or
other interventions with the treatment results as well as to address the issues
of the rational allocation of resources for the healthcare.
The application of the pharmacoeconomic methods helps to avoid errors
while including new medications into the list of the reimbursed medicines
and to use the funds allocated to medicines more rationally. The pharmacoeconomic analysis should justify that the ratio between the price and the
efficiency of the proposed medication is optimal, i.e. that it is safe; moreover, a comparative analysis of any other medicines for the treatment of the
same disease should be performed. If this analysis reveals that a more expensive medicine is less effective and less safe, it cannot be reimbursed.
Although different healthcare systems exist in various countries, they all
address virtually the same challenges: how to improve the quality and accessibility of healthcare services while maintaining a stable funding at the
same time. The constantly rising costs for the reimbursement of medicines
obliges the state authorities involved in the medicine reimbursement system
31
to seek different measures to help reduce the growth in the medicines spending.
In Lithuania, as well as in other EU countries, there is a problem that the
cost of medicines is growing faster than the costs in other sectors of the
health system. Therefore, it is necessary to prevent the increase in the costs
of medicines through the application of various cost control techniques. The
effective cost control is determined not only by rational allocation of the
budget funds but also by other measures that help to reduce the growth in
the costs of medicines.
According to the Minister of Health of Lithuania, the measures of the
medicines cost control can be divided into the following groups: the regulatory measures of the medicines supply and demand control and other
measures such as the generic medicines policy, the development of the parallel import of medicines and the installation of information technologies
within the system of the medicine reimbursement.
The measures of the medicines supply control include: the measures to
reduce the prices of medicines, the application of contracts concerning the
prices of medicines and the scope of sales, the reference pricing application
in the pricing of medicines and the application of the science of health economics in making the decisions on the reimbursement of medicines.
The regulatory measures for the medicines demand are the measures applied to doctors issuing prescriptions for reimbursable medicines (the increase in the economic awareness of doctors), to the structuring of the negative and positive lists of the reimbursed medicines, to the medicines prescription procedures, to the determination of the medicines budgets and to
the surcharges to medicines.
In addition to these measures, a number of control mechanisms are employed (licensing, centralized purchases of medications, structuring of the
list of medicines, the revenue analysis of pharmaceutical companies and the
regulation of the medicines-issuing entities). The methods of payment for
services must reduce the motivation of the service provider to prescribe the
expensive or unnecessary medicines. It is exercised by determining the
methods of disease treatment by providing audits of medicines prescription,
by determining bonuses for the ability to stay within the medicines budget,
by determining the surcharges imposed on the population for reimbursable
medicines.
The nature of the performance and the reasonable measure used for the
assessment of the quality of life (standard or prepared for the assessment of
a particular disease) must be indicated. The methods of the health performance ratio are also recommended to apply by the Minister of Health of
Lithuania.
32
A significant amount of funds is allotted to the treatment of patients with
various forms of depression. Not only is the money spent by the mentioned
patients or their family members on buying antidepressants but also the expenses incurred by the state (insurance, social funds) have already been calculated for a long time. Depression impairs or disrupts the working capacity
of an ill individual for a long time, complicates the live of his/ her family
members and requires additional funds for social care services.
Two groups of expenses are related with depression – direct and indirect
ones. Their importance not only to patient but also to the society is undeniable. It is normal to pay the greatest attention to the direct expenses related
with treatment; however, it is just the tip of the iceberg if compared with
depression-related indirect costs which include the loss of working capacity
caused by the disease and the related increase of mortality [39].
Pharmacological aspects of depression treatment have already been assessed for a long time. For example, in 2004, the total expenses of treatment
of patients with various depression forms were estimated to be 118 billion
Euros in Europe or on average 253 Euros per capita per year [100]. Researches showed that the direct costs of depression treatment accounted for
only a small proportion – about 13 per cent – of the total amount of diseaserelated costs. The annual spending on depression in the United States of
America is 43.7 billion dollars, in England and Wales – about 3.4 billion
Pounds. While analyzing the costs of the disease, all researches showed that
the expenses on medicines accounted for only a small part of the direct costs
(10-12 per cent) and only for 1-2 per cent of the total cost of the disease
[73].
The growing treatment costs encourage to study and assess whether the
treatment is reasonable. While assessing the rationality of treatment of this
disease, the need for medicines, psychological support of the patient and
cooperation of his/ her relatives and that of the treating doctor is considered.
Relapses of depression after a successful response to antidepressant medication have been reported in a number of recent studies of ongoing treatment. During routine pharmacotherapy for depression, it is unknown how
common it is for psychiatrists eventually to find a need to raise medication
dosages after achieving a marked remission according to WHO. Evidence
suggests that relapse rates in depression may range from 20 per cent to as
high as 44 per cent depending on the length of treatment with the maintained use of selective serotonin reuptake inhibitors (SSRIs) [100]. In contrast, with tricyclic antidepressants (TCAs), the relapse during an ongoing
treatment to maintain remission from depression appears relatively rare
[73].
33
The costs of depression treatment increase in Lithuania due to the degree
of depression relapse; they accounted for 6.95 mln. Euros of direct expenses
in 2009.
The growing number of depression relapse in Lithuania shows the need
to analyze the rationality of treatment of first-time depression.
1.4. Cost-effectiveness in depression treatment
Pharmacoeconomics has been defined as “the description and analysis of
the costs of medicines therapy to healthcare systems and society” [119].
Pharmacoeconomic research identifies, measures, and compares the costs
(i.e., resources consumed) and consequences (i.e., clinical, economic, humanistic) of pharmaceutical medicines and services. Within this framework
the research methods related to cost-minimization, cost-effectiveness, cost–
benefit, cost-of-illness, cost-utility, cost-consequences, and decision analysis as well as quality-of-life and other humanistic assessments are included
[64].
By definition, pharmacoeconomic evaluations include any study designed to assess the costs (i.e., resources consumed) and consequences (clinical, humanistic) of alternative therapies. This includes such methodologies
as cost-benefit, cost-utility, and cost-effectiveness [15] (Table 1.4.1).
Table 1.4.1. Pharmacoeconomic methodologies
Methodology
Pharmacoeconomic methodologies
Cost
Outcome unit
measurement unit
Cost-benefit
Currency unit
Currency unit
Cost-effectiveness
Currency unit
Cost-minimization
Currency unit
Natural units (life-years gained, mg/dL
blood glucose, mm Hg blood pressure)
Assume to be equivalent in comparative
groups
Cost-utility
Currency unit
Quality-adjusted life-year or other utilities
Cost-effectiveness analysis is a technique designed to assist a decisionmaker in identifying a preferred choice among possible alternatives. Generally, cost-effectiveness is defined as a series of analytical and mathematical
procedures that aid in the selection of a course of action from various alternative approaches. Cost-effectiveness analysis has been applied to health
matters where the program’s inputs can be readily measured in currency
34
units, but the program’s outputs are more appropriately stated in terms of
health improvement created (e.g., life-years extended, clinical cures) [89].
Pharmacoeconomic research is the process of identifying, measuring, and
comparing the costs, risks and benefits of programs, services or therapies
and determining which alternative procedures the best health outcome for
the resource invested. For most pharmacists this translates into weighing the
cost of providing a pharmacy medicine or service against the consequences
realized by using the medicine or service in order to determine which alternative yields the optimal outcome [111].
In a series of recent studies, the quality and cost-effectiveness of care for
severely depressed patients treated under different payment systems by general medical clinicians and mental healthcare professionals (psychiatrists,
psychologists and master-level therapists) were examined. The conclusion
was that the overall quality of care for depression is less than optimal, and
the cost-effectiveness of care as currently delivered is low. Among seriously
depressed patients, many do not receive appropriate care even in the mental
health specialty sector but instead receive care for some problem other than
depression or receive treatments that are ineffective for depression. Such
mistakes are a waste of resources: the healthcare system could get far higher
returns for the money it spends when treating depressed patients by spending a little more to improve the quality of care – that is, by appropriately
treating more of the depressed patients who are already receiving some care
anyway. This potential for improving the cost-effectiveness of care is especially great for depressed patients who visit general medical providers such
as internists or family doctors [39].
In the aim to evaluate the pharmacoeconomic benefits of treating depression and to compare the available therapies by reviewing the current academic writings on economic analyses of depression, a PubMed search of the
English-language literature relating to economic analyses of depression was
conducted. The key search terms included depression, antidepressants, economics, pharmacoeconomics, outcomes and costs. Additional literature was
collected from the reference lists of articles found as a result of the MEDLINE search. Table 1.4.2 shows the results of the review and meta-analysis
of various pharmacoeconomic studies. According to this, new antidepressants in most cases show better tolerability and cost-effectiveness of depression treatment [14].
35
Table 1.4.2. Pharmacoeconomic depression treatment studies conducted
worldwide
Publication
Type
MetaAnalysis
Comparators
Fluoxetine vs
TCAs
Resume of Results and Conclusions
Fluoxetine could be beneficial to the society provided values a year of human life above a determined
threshold. Fluoxetine may induce short-term financial savings for the society [56].
Despite higher acquisition costs, paroxetine and
other SSRIs are no more costly than TCAs when the
total costs per successfully treated patient or the
expected costs per patient are considered. Paroxetine
should be considered as an effective alternative to
TCAs as a first-line treatment of depression [16].
The reviewed studies generally showed that overall
treatment costs with sertraline and other SSRIs are
no greater than those for TCAs; this is despite the
lower acquisition costs of the latter agents. Two
studies stated that sertraline was more cost-effective
than TCAs. Sertraline can be considered as a firstline alternative to TCAs and other SSRIs for the
treatment of depression on both clinical and pharmacoeconomic grounds [37].
Insufficient evidence to support the use of SSRIs as
a cost-effective first-line treatment of depression.
There is no evidence to suggest that SSRIs are more
cost-effective than TCAs [86].
Review
Paroxetine vs
SSRIs/TCAs
Review
Sertraline vs
SSRIs/TCAs
MetaAnalysis
SSRIs vs TCAs
Review
Venlafaxine vs
SSRIs/
TCAs/HCAs
Venlafaxine suggests a reduction in the overall costs
associated with treating depression in hospitalized
patients. Venlafaxine was found to be more costeffective than SSRIs and TCAs [38].
Review
SSRIs vs TCAs
Available evidence across all groups of patients
suggests that SSRIs may be more cost-effective than
TCAs [66].
Review
SSRIs vs
TCAs/SSRIs
SSRIs have its costs offset by lower medicament
utilization costs when compared to TCAs. Fluoxetine seems to be more favorable economically than
sertraline [105].
Review
Fluoxetine vs
TCAs/SSRIs
Total health costs are lower or similar for fluoxetine
(vs TCAs). No economic differences were observed
between fluoxetine and other SSRIs [29].
36
Table 1.4.2. Continued
Publication
Type
Comparators
Resume of Results and Conclusions
Review
SSRIs vs TCAs/SSRIs
Review
SSRIs vs TCAs
SSRIs, despite higher prescription costs, have
been demonstrated to be a more cost-effective
option than the TCAs. There is evidence that
the emerging clinical differences between
SSRIs may translate into significantly different
economic outcomes within the group [67].
Pharmacoeconomic studies show that apparently cheaper antidepressants TCAs may turn out
to be more expensive than the better tolerated
antidepressants (SSRIs) [123].
Review
Fluoxetine vs TCAs/
SSRIs/Nefazodone
Review
SSRIs vs TCAs/SSRIs
Review
Mirtazapine vs amitriptyline/fluoxetine
Review
SSRIs vs TCAs
Review
Venlafaxine/SSRIs vs
TCAs
Review
SSRIs vs TCAs/SSRIs
Nefazodone was associated with slightly lower
lifetime direct medicament costs and slightly
more QALYs per patient. The total healthcare
costs for patients who start with fluoxetine are
similar to, or lower than, those for patients who
start therapy with TCAs or other SSRIs. The
evidence that fluoxetine has cost advantages
over other SSRIs requires confirmation [9].
SSRIs may be more cost-effective than TCAs
in the treatment of acute depression. There is no
clear evidence of greater cost-effectiveness of
any agent within the SSRIs class [10].
Available data suggests that mirtazapine is a
cost-effective alternative to amitriptyline and
fluoxetine for the treatment of depression [36].
First-line use of SSRIs in the treatment of depression is clinically warranted and represents
good value for money [98].
Venlafaxine is more cost effective for inpatient
treatment and as second-line therapy than
TCAs. SSRIs at least offset or more than offset
their higher acquisitions costs compared to
TCAs [125].
Compared to TCAs, SSRIs offset or more than
offset their higher acquisitions costs. Studies
from mid-1990s onwards show general equivalence in terms of cost within the SSRIs class
[26].
37
Table 1.4.2. Continued
Publication
Type
Comparators
Resume of Results and Conclusions
Review
SSRIs/SNRIs vs TCAs
Review
Venlafaxine vs
SSRIs/TCAs
Review
SSRIs vs TCAs/SSRIs
Review
Escitalopram vs
SSRIs/SNRI (venlafaxine XR)
Review
Escitalopram vs
SSRIs/SNRI (venlafaxine XR)
Escitalopram vs
SSRIs/SNRI (venlafaxine XR)
The available data does not allow the conclusion that SSRIs should be preferred over TCAs
with the argument that the treatment as a whole
is more cost effective in spite of the higher
costs [53].
In both inpatient and outpatient settings both
immediate release and venlafaxine have a lower
expected cost than comparable treatment [68].
SSRIs are more cost-effective than TCAs when
overall healthcare utilization and expenses are
considered. Further research is needed to examine the cost-effectiveness within the SSRIs
class [79].
Escitalopram holds a cost-effectiveness and
cost-utility advantage over the other SSRIs
(citalopram, fluoxetine, sertraline) and venlafaxine. Pharmacoeconomic data supports the
use of escitalopram as first-line therapy in patients with depression [11].
Escitalopram holds a cost-effectiveness and
cost-utility advantage over the other SSRIs
(citalopram, fluoxetine) and venlafaxine [121].
Escitalopram holds a cost-effectiveness and
cost-utility advantage over the other SSRIs
(citalopram, fluoxetine, sertraline) and venlafaxine. Pharmacoeconomic data supports the
use of escitalopram as first-line therapy in patients with depression [12].
It is not possible to identify the most costeffective strategy Venlafaxine/ Mirtazapine for
alleviating the symptoms of depression although Nefazodone, SSRIs and newer antidepressants consistently appear more costeffective than TCAs in many patient groups.
Better quality economic evidence is needed [3].
Venlafaxine has a lower average cost per patient achieving remission or per symptom-free
day compared with SSRIs. Venlafaxine is a
cost-effective strategy for the treatment of depression [31].
Review
Review +
Metaanalysis
SSRIs vs TCAs
Review
Venlafaxine vs SSRIs
38
Table 1.4.2. Continued
Publication
Type
Comparators
Resume of Results and Conclusions
Review
Escitalopram vs
SSRIs/SNRI (venlafaxine XR)
MetaAnalysis
Venlafaxine XR vs
duloxetine
Escitalopram holds a cost-effectiveness and
cost-utility advantage over the other SSRIs
(citalopram, fluoxetine, sertraline) and venlafaxine XR (SNRI). Pharmacoeconomic data
supports the use of escitalopram as a first-line
therapy in patients with depression [70].
Modest differences in pharmacoeconomic outcomes favor venlafaxine over duloxetine [117].
Review
Venlafaxine vs
SSRIs/TCAs
Venlafaxine generates lower total costs (due to
the reduction of treatment failure costs) than
SSRI and TCA for the treatment of depression
[2].
The economic aspects of treating depression are becoming more frequently evaluated as newer antidepressant medications become available
and as healthcare entities attempt to address the increasing costs. In general,
most pharmacoeconomic research on depression has been conducted on one
of the SSRIs in comparison with various tricyclic antidepressants. These
studies frequently use simulation techniques and rely heavily on data from
clinical trials. Few studies have compared the newer antidepressants, and no
clear evidence exists that any one of these agents is more cost-effective than
others. Even fewer studies have addressed the pharmacoeconomics of medication management of depression in various healthcare environments (e.g.,
public mental healthcare vs. private psychiatry vs. primary care).
In Lithuania, depression pharmacoeconomic studies were conducted on
the trends of antidepressants consumption in the years 2002 to 2004, on the
duration of unemployment and depression in Lithuania, on screening for
depression and anxiety disorders in primary care patients in Lithuania, efficacy, tolerability, and preference of mirtazapine orally disintegrating tablets
in depressed patients; this was a 17-week naturalistic study in Lithuania.
No studies were found regarding depression relapse and first-time depression medicament treatment impact on the depression treatment costs and
its impact on society.
39
2. MATERIALS AND METHODS
The object of the research is the cost of consumption of antidepressants
in Lithuania in the years 2004 through 2009.
2.1. Material sources of the research
IMS Health Incorporated data
Data on sales of antidepressants in the Lithuanian market was collected
and provided by IMS Health Incorporated. The value of this data is that it
reflects the supply (and, hence, purchases) of specific medications.
The annual aggregate number of packs (sale units) distributed each year
for each product relevant to the treatment of depression for the period January 2004 to December 2009 were calculated. The data reflects sales by major manufacturers and wholesalers operating in Lithuania. The data on the
volume and value of medicines sales was employed. The value of antidepressants sales in Lithuania was obtained as manufacturers declared medicine prices and converted them to the DDD prices in order to conduct a
costs rationalization and cost-effectiveness research. This data was used to
obtain antidepressant consumption rates, to evaluate the sales and expenses
on medicament depression treatment rates during specific periods in Lithuania, to determine the reference price, depression treatment cost rationalization percentages and the cost-effectiveness of depression treatment. Usage
measured in units of defined daily doses (DDDs) per 1,000 persons per day,
was then calculated.
SVEIDRA database
The analyzed data of the prescribed reimbursable medicines was obtained
from the SVEIDRA database at the Territorial Health Insurance Funds
(THIF) of Kaunas City in the years 2004 through 2009 in Kaunas and Marijampolė Counties. The research group data records the number of visits,
diagnosis, a patient’s date of birth, gender, date of visit, the prescribed medicine(s), its/their quantity and the reimbursable price. The total of 335,030
records from 25,576 patients (99 per cent CI; n=128,726) is analyzed.
Prescriptions recorded in the SVEIDRA database include the patient’s
name and surname. In the provided data, the patient’s number provides the
possibility to anonymously identify prescriptions for the same individual
without the name and surname data and also to link it to the information on
the age, gender and date. This is performed by using an encrypted patient
identification number (PIN) so that the patient’s confidentiality is protected.
40
In this research, the data was obtained on people who were prescribed antidepressants during the period of January 2004 to December 2009. In this
research, this data was used to investigate the patterns of the use of antidepressants in Lithuania.
The analysis was carried out with an objective to analyze the schemes of
treatment of the patients suffering from depression. While evaluating certain
patient treatment costs and depression relapse rates, the data of the period
from January 2004 to December 2009 was analyzed. This research had an
objective to determine the most effective first-time depression treatment and
according to this to prepare the cost-effectiveness and rationalization analysis. First-time depression cases were analyzed in terms of treatment methods, terms as well as costs and compared with one another. Depression relapse was determined by depression relapse code (F33) appearance in the
treatment course during the researched period. After depression relapse code
(F33) appears, all subsequent relapses are also marked with the same illness
code, and these cases were analyzed as the totality of the depression relapse
phenomenon without being differentiated by cases. First-time depression
(F32) episode costs were evaluated by reimbursed antidepressants prices
and compared by using cost-effectiveness analysis.
During the analysis of the available data, the grouping by year, gender
and age was performed; in addition, the grouping of prescriptions according
to the active substances and medicine groups, the amount of the prescribed
medications and costs was calculated for these groups.
The initial presentation of the analyzed data is made by using the descriptive statistical methods.
State Mental Health Centre data
The data of depression diagnosis was obtained from State Mental Health
Centre and expressed as the total number of diagnoses as well as according
to the type of depression and the gender of the patients.
The State Mental Health Centre (SMHC) contains data on episodes of
depression for patients, including demographic, geographic data, depression
type and patients’ gender data.
This data was used to define depression diagnosis trends in Lithuania
from January 2004 to December 2009, to determine probable depression
diagnosis rates and growth causes, its relapse rates, first-time depression
diagnosis rates during the research period and to analyze these tendencies in
terms of gender and geographic area.
Survey data
In 2009, the following professionals working in Lithuania were interviewed: 361 pharmacists or pharmacy technicians (95 per cent CI; n=5,923),
317 falimy doctors (95 per cent CI; n=1,822) and 280 psychiatrists (95 per
41
cent CI; n=1,030). The confidence level (CL) sets the boundaries of a confidence interval (CI); this is conventionally set at 95 per cent to coincide with
the 5 per cent convention of statistical significance in hypothesis testing.
The 95 per cent CI is the interval of 95 per cent certainty of containing the
true population value in comparison with the estimation from a significantly
more extensive study.
Questionnaires with five questions regarding depression treatment, its relapse rates, treatment monitoring and illness frequency were presented to the
participants. A questionnaire survey was selected for data collection as it is
perfect for measuring quantitative characteristics. The form of research
sample constituted the so-called available cases: the data was collected from
doctors and pharmacists by visiting them during their working hours, at
their training events, conferences, contacting them in writing and orally, in
medical institutions and pharmacies.
The questionnaire survey had an objective to evaluate depression treatment rationality according to health care professionals’ and pharmacists’
opinion and to determine the problem urgency and risk factors rates.
2.2.
Evaluation methods and criteria
Calculation of defined daily dose per 1,000 inhabitants per day
Medication usage measured as defined daily doses (DDDs) per 1,000 inhabitants per day (DDD/1,000 inhabitants/1 day) was used in this research
to compare antidepressant sales and reimbursed prescriptions dispensed
over time and across medicament groups where information about the actual
medicines consumption is not available. The information in this research is
based on data prepared and supplied by IMS Health Incorporated and the
data from the SVEIDRA database reports.
For each medication, the relevant DDD was obtained from the website of
the World Health Organization Collaborating Centre for Drug Statistics
Methodology. The DDD is defined as ‘the assumed average maintenance
dose per day for a drug used for its main indication in adults’. The DDD is
used internationally as a unit of measurement for drug utilization studies.
Each medication pack or sale unit (for the IMS Health Inc. data) or quantity
dispensed (for the SVEIDRA database data) is converted to a number of
DDDs per unit or item.
For each of these items, the DDD per 1,000 inhabitants per day is then
calculated by using the following formula:
42
N × M × Q × 1,000
DDD/1,000 persons/1 day =
DDD × P × D
where
N
=
total number of reimbursed prescriptions dispensed per year
(the SVEIDRA database data) or the total number of items
sold per year (the IMS Health Inc. data)
M
=
mass of each dosage unit (e.g. mg per tablet dose)
Q
=
the total number of dosage units dispensed per prescription or
sold unit
P
=
mid-year Lithuanian population for the year of data collection
D
=
number of days in the year
The DDD/1,000 inhabitants/1 day for individual medications is then
summed across the members of each group of medications to estimate the
total number of DDD/1,000 inhabitants/1 day for each antidepressant class.
The prescribed daily dose (PDD) is defined as the average dose prescribed according to a representative sample of prescriptions. The PDD was
determined from prescription studies on SVEIDRA database records.
According to WHO, when there is a substantial discrepancy between the
PDD and the defined daily dose (DDD), it is important to take this into consideration when evaluating and interpreting medicine utilization figures.
Effectiveness evaluation criteria
Depression is a common condition that typically has a relapsing course.
Effective interventions targeting relapse have the potential to dramatically
reduce the point prevalence of the condition. The primary goal of the study
was the reduction in the rate of depression relapse and the improvement in
the patient’s health condition level while rationalizing the medicament depression treatment costs.
Therefore in order to discover better opportunities of antidepressant consumption rationality monitoring (efficiency and cost ratio), the selected targets (indicators) were assessed such as the relapsed depressive episode
(F33), a manifestation of which would mean inefficient or lack of treatment
efficacy while the absence of relapse would mean the result of an effective
treatment.
According to TLK-10-AM, depression relapse case (F33 code) can be
differentiated from the first-time depression case (F32 code) by the illness
code. By using this opportunity in this research, the depression treatment
result is evaluated as health improvement or depression relapse. Health im43
provement means that no depression relapse appeared during the researched
period (Figure 2.2.1). Depression relapse in this case means adverse treatment results and a negative impact on the patient’s condition (Figure 2.2.2).
+
Treatment by
antidepresants
=
LoC 1
Health improvement
(no depression relapse)
<
First- time
depression
LoC 2 LoC 1
LoC 2
Figure 2.2.1. Expected depression treatment results
First- time
depression
+
Treatment by
antidepresants
=
Depression
relapse
LoC 2
LoC 1
LoC 2
LoC 1
Figure 2.2.2. Adverse depression treatment results
LoC1 – first-time depression condition level;
LoC2 – condition level after medicament depression treatment.
Cost-effectiveness analysis
During this research, an attempt was made in order to indicate the pricing
limits for the antidepressants considering the similar therapeutic effects and
safety within different antidepressant classes. Pharmacoeconomic calculations were conducted by using the cost-effectiveness analysis for the obtained data of antidepressant expenditures.
In terms of antidepressant effectiveness when using depression relapse
and probability to heal after first time depression, the treatment costeffectiveness analysis of effective depression case treatment was performed.
This analysis involved medicament depression treatment costs and benefits (on the basis of treatment effectiveness by depression relapse rates) following the published guidelines on the analysis of cost-effectiveness. All the
costs were expressed in Litas (LTL). The effectiveness of treatment was
expressed in terms of depression relapse rates in order to reflect the most
rational depression treatment medicines, the calculated effective depression
treatment episode terms and the price. Incremental cost-effectiveness ratios
were calculated as the additional cost divided by the additional benefit of
44
one strategy versus the next less costly strategy and were reported as cost
per effective treatment.
The selection of patients for the research
By taking into account the individual depression treatment inefficiency
determinants (irrational behavior in the use of medicines, the public mental
health level, skills gap of healthcare professionals, etc.), in order to
eliminate or reduce the impact of these determinants on the treatment
efficacy, a large sample of subjects (25.5 thousand patients) was studied by
using SVEIDRA database source from Kaunas and Marijampolė regions.
All the available information about the patients during the resesarch period
was analyzed.
While assessing the size of the sample (taking into regards a general
number of the patients with depression in Lithuania), it was calculated by
employing the formula
1
n
1
2 
N
where:
n – the size of the sample.
ε – error of the sample
N – the size of the sample.
During the calculation, it was assumed that N=100.000, ε=1 and the size
of the sample is 8.763. The 25.576 patient records analyzed during the study
suggest that the results analysis is suitable for the generalization and that the
analyzed part is representative.
The personal information of the patients remained protected as for this
research no personal information of patients was collected.
Evaluation of environmental determinants (PEST analysis)
To set a direction and goals of the paper, the problematic environment as
well as the direct and indirect factors affecting the costs and efficiency of
antidepressant consumption were assessed.
The evaluation was performed by using a methodological tool of the strategic planning, i.e. the method of PEST (political, economic, social and
technological factors evaluation) analysis. PEST analysis was carried out on
the grounds of literature research.
Classification of diseases
The classification of diseases can be characterized by a system of categories in which diseases are classified according to the established criteria.
There are different principles for the classification, but the selected principle
depends on the applied method of statistical processing of the accumulated
data. The statistical classification of diseases is to encompass all the condi45
tions of health problems and group them with the help of the easily maintained amount of categories.
TLK-10-AM is applied to all Healthcare Institutions (HCIs), providing
the outpatient, inpatient and/or daycare surgery services. TLK-10-AM classification of depressive disorders is formed as follows:
 F32 Depressive episode.
 F33 Relapsed depressive disorder.
This paper analyzes the cases of the relapse of depression, the methodology of pharmacological treatment of these cases and the cases of the firsttime depression using this as the basis for finding the most efficient scheme
for the treatment of the initial depression cases.
Phases of research
In this research PEST analysis, SVEIDRA database and IMS Health Inc.
data were linked one with each other.
According to the literature analysis and antidepressant consumption in
Lithuania rationality PEST analysis, technological and political factors (legislation, modern range of antidepressants and medicine reimbursement system function) are not a problematic aspect of the rational use of medicines.
The highest risk regarding excess antidepressant costs is caused by economic and social factors (ethic and generic companies in the market competition, population behavior, public mental health level, doctors’ motivation to
improve their knowledge, etc.).
In this research, social and economic factors were selected for the rationalization and improvement of medicament depression treatment and costeffectiveness of dealing with the illness. According to the situation screening results, there are many factors to be improved in the healthcare sector
regarding depression diagnosis, treatment and antidepressant consumption
and costs. According to this, specific research tasks were selected for the
prospective investigation, the result of which would provide determination
of logic permanent mistakes in certain modules as well as it‘s dissolving or
correcting current depression treatment model in order to rationalize the antidepressant consumption and improve cost of depression effectiveness in
Lithuania.
According to the below presented data, two evaluation trends were defined: medicament depression treatment choice (Table 2.2.1) and volume
dynamics analysis and economic rationality evaluation (Table 2.2.2).
46
Table 2.2.1. Medicament depression treatment choice and volume dynamics
analysis
Methods of
achievement
Indicators of the
expected outcome
To perform the
analysis of the
dynamics of the
cases of depression diagnosis
in Lithuania
Secondary
data analysis,
descriptive
statistics
Distribution for
different years by
age, gender,
amount of the prescribed active substance
To perform the
analysis of medicine consumption in 2004 to
2009 according
to the methodology of DDD
(Defined Daily
Dose) and the
antidepressant
cost analysis
To perform the
analysis of the
reimbursable
antidepressant
consumption in
2004 to 2009
Secondary
data analysis,
descriptive
statistics
DDD and the cost
of antidepressants
Secondary
source analysis, forecast,
caeteris paribus
Quantities and
costs of the prescribed medications by year
Task
47
Indicators of
the obtained
outcome
assessment
Variation in
the patients
with depression according
to gender, age,
the most frequently prescribed active
substance in
different years
DDD comparison with PDD
(Prescribed
Daily Dose),
comparison of
costs
Obtained
outcome
assessment
techniques
Comparative
analysis of
the absolute
and relative
numbers
(higher values mean
higher costs,
quantities)
Reliability,
availability of
the trend forecast (caeteris
paribus)
Comparative
analysis of
the absolute
and relative
numbers.
Comparative
analysis of
the absolute
and relative
numbers, the
evaluation
of the statistically significant
differences
Table 2.2.2. Antidepressant consumption economic rationality evaluation
Indicators of
the obtained
outcome
assessment
Comparative
values of the
treatment
costs, comparative values of
the duration of
treatment
Methods of
achievement
Indicators of
the expected
outcome
To perform the
comparative
analysis of the
change in the
initial and relapsed depressive episodes in
2004 to 2009
Descriptive
statistical
methods,
analysis of
variance
Quantities of
the prescribed
medications
according to the
active substance
and in terms of
the reimbursable costs
To perform the
analysis of
depression
relapse dependence on l
treatment and
to identify the
most effective
and costeffective treatment for the
cases of the
first-time depression
Descriptive
statistical
methods,
analysis of
variance,
costeffectiveness analysis
Quantities of
the prescribed
medications
according to the
active substance, according to the treatment costs per
patient for one
day, the duration of treatment, effective
treatment costs
Comparison of
the treatment
costs, comparison of the
duration of
treatment,
DDD and
PDD comparison
Based on the
results, to give
the possible
ways of cost
rationalization,
suggestions
and recommendations
Comparative analysis of the
outcomes
Values of DDD,
the duration of
treatment,
treatment costs
Significance
of the variation in the
received DDD,
costs, the duration of
treatment
Task
Obtained
outcome
assessment
techniques
Comparative
analysis of the
absolute and relative numbers
(higher values
mean higher
costs, bigger prescribed quantities,
longer duration of
treatment)
PDD and DDD
comparison in
accordance to the
statistical criteria,
evaluation of the
statistically significant differences,
comparison of the
treatment costs
(higher values
mean higher
costs).
Size of differences in the selected scale of
evaluation.
Comparative
analysis of the
absolute and relative numbers,
presentation of the
summarization of
the obtained results
Statistical analysis
Statistical analysis was used to perform the analysis of the reimbursable
antidepressant consumption, to compare these results between male and female and different age groups, to perform the comparative analysis of the
change in the initial and relapsed depressive episodes, analysis of depression
48
relapse dependence on first treatment and to identify the most effective and
cost-effective treatment for the cases of the first-time depression as well as
to analyze health care specialists survey results.
Statistical analysis of SVEIDRA database data was performed by using
MS Excel and the statistical data processing program SPSS 16.0 for Windows (Statistical Package for Social Sciences). Student’s criteria for paired
samples were used for the comparison of averages of two interrelated
groups. For the comparison of averages of two or more independent groups,
the analysis of variance (ANOVA) was used. On the grounds of the obtained tables, the significance of the criterion, the degrees of freedom (df)
and the statistical significance (p value) were determined. While testing the
statistical hypotheses, the criterion significance level was set at α=0.05. The
difference was considered to be statistically significant when p<0.05, very
significant when p<0.01, and extremely significant when p <0.001.
To evaluate the effectiveness of the depression treatment, the Odds ratio
in binary logistic regression was used. The odds ratio is the ratio of the odds
of an event occurring in one group to the odds of it occurring in another
group. The term is also used to refer to sample-based estimates of this ratio.
These groups might be males and females, an experimental group and a control group, or any other dichotomous classification. If the probabilities of the
event in each of the groups are p1 (first group) and p2 (second group), then
the odds ratio is:
where qx = 1 − px. An odds ratio of 1 indicates that the condition or
event under research is equally likely to occur in both groups. An odds ratio
greater than 1 indicates that the condition or event is more likely to occur in
the first group while an odds ratio lower than 1 indicates that the condition
or event is less likely to occur in the first group. The odds ratio must be nonnegative if it is defined. It is undefined if p2q1 equals zero, i.e., if p2 equals
zero or p1 equals one.
The calculations were carried out according to the formula
where p1 is the probability that F32 will not be replaced by F33 during
the treatment. In assessing the odds ratio, it is considered that the closer the
ratio is to 1, the higher the probability is that for a patient with the diagnosed first-time depression (F32) the diagnosis will not be replaced by F33
during the period of 6 months.
49
The questionnaire survey data was processed by using SPSS data processing package Windows/SPSS (Statistical Package for the Social Sciences), Version 16, and presented with the help of descriptive statistics.
All prescribed antidepressants were grouped in this research into four
classes according to the ATC classification while also defining their DDD
values:
1. Tricyclic antidepressants (TCAs): amitriptyline, clomipramine, doxepin, nortriptyline, imipramine, dosulepin;
2. Selective serotonin reuptake inhibitors (SSRI): sertraline, fluoxetine,
paroxetine, citalopram, escitalopram, fluvoxamine;
3. Other (more recent) antidepressants: mirtazapine, bupropion, tianeptine, venlafaxine, trazodone, agomelatine, mianserin, reboxetine, duloxetine;
4. Lithii carbonas.
The DU95 percentage was used as the quality indicator of prescribing the
medicines. The amount of medicines contributing to 95 per cent of sales or
consumption as a proportion of the total amount was calculated for each
year.
Limitations of research
The nature of the IMS data is that it contains no information on the characteristics of the purchasers or consumers. Furthermore, socioeconomic and
geographical trends and differentials in the utilization of medicines cannot
be assessed by using this data.
Most antidepressants in Lithuania are being reimbursed by THIF. However, some antidepressants are frequently purchased without a reimbursed
prescription. Hence the SVEIDRA database data only records antidepressants purchased with a reimbursable prescription merely reflects a section of
the Lithuanian population and substantially underestimates the total usage.
The SVEIDRA database does not collect any information on the underlying disease(s) or the reasons for prescribing. Thus, there is no way of identifying whether a patient using these medications has any additional diseases.
In this research, the data of the years 2004 through 2009 was evaluated
and analyzed. The limitation of statistical analysis was some data loss and
the insufficiency of data in new cases. During the studied period, some new
generation antidepressants did not develop sufficiently long treatment history for F33 illness code to appear which has to be continuous permanent
monitoring of F33 determination cases for the determination of certain
treatment results.
50
3.
RESEARCH RESULTS AND DISCUSSION
Socio demographic characteristics of the researched population
On the grounds of the SVEIDRA database, depression diagnosis cases
during the period of 2004 through 2009 in the research group were analyzed
(codes F32 and F33). During the entire analyzed period, 25,576 patients visited doctors in the research group. During the first visit, the youngest patient
was 1 year old while the oldest one was 104 years old. The average age of
the patients at their first visit was 51.64 (st. deviation was set at 18.04), the
median of age was established at 52 years old, the mode of age was 55 years
old.
In this research, the whole research group population of depressive patients was analyzed in two aspects: by age and by gender. It was because of
the future evaluation of socioeconomic inequalities in depression treatment,
strategies of decision makers for tackling inequality in depression advising
and the economic impact of depression on the working-age population
group and GDP in Lithuania.
While distributing the patients by age groups, the results are shown in
Table 3.1.
Table 3.1. Population analysis by age
Age group
Under 18 years old
18–41.5 years old
41.5–65 years old
Over 65 years old
Amount
1,010
6,475
11,581
6,510
Percentage
3.9
25.3
45.3
25.5
The largest share of depression patients is 41.5 to 65 years old; it is the
working-age group. This means that the impact of depression on the society
is extremely important (Figure 3.1).
It is important to note that 25.3% of depressed individuals are 18 to 41.5
years old. Hence young people depression episodes also influence their parents who are in the 41.5 to 65-year-old group of working age population
which increases the influence of the depression on the society.
51
60.00%
50.00%
40.00%
F32
30.00%
F33
20.00%
10.00%
0.00%
< 18
18-41,5
41,5-65
> 65
Figure 3.1. Depression diagnosis distribution by age
While analysing depression diagnosis distribution by gender, even 80.4
per cent of all depression diagnoses belong to the group of females (Figure
3.2).
90.00%
80.00%
70.00%
60.00%
F32
50.00%
F33
40.00%
30.00%
20.00%
10.00%
0.00%
Females
Males
Figure 3.2. Depression diagnosis distribution by gender
52
For 9,722 of all the 25,576 patients, the diagnosis was changed during the
course of the disease:
 From F32 to F33 for 72.5 per cent, i.e. for 7,048 patients.
 From F33 to F32 for 27.5 per cent, i.e., 2,674 patients.
The initial diagnosis of F32 was not determined for the individuals under
the age of 18. While analyzing first time and relapsed depression tendencies
between gender and age groups, the same tendencies of diagnosis distribution were found (Table 3.2 - 3.5).
Table 3.2. F32 changes to F33 by age
Group
Percentage (%)
7.4
63.3
29.3
18–41.5 years old
41.5–65 years old
Over 65 years old
Table 3.3. F32 changes to F33 by gender
Group
Percentage (%)
22.2
77.8
Males
Females
In first-time depression cases, the largest share of patients by age is constituted of the 41.5 to 61 year-old patients; by gender – of women making
up more than two-thirds of all the patients.
Table 3.4. F33 diagnosis distribution by age
Group
18–41.5 years old
41.5–65 years old
Over 65 years old
Percentage (%)
3.5
61.6
34.9
Table 3.5. F33 diagnosis distribution by gender
Group
Percentage (%)
18.4
81.6
Males
Females
Among all the patients with the changed diagnosis, 315 patients visited
the doctor 2 times, 309 patients did it 3 times. The highest number of times
a patient visited a doctor is 143. On average, each patient visited the doctor
30.62 times.
53
3.1. Analysis of the antidepressant consumption in Lithuania
The total consumption of antidepressants in Lithuania increased by 48
per cent during the six years period (from 10.17 DDD/1,000 inhabitants/1
day in 2004 to 15.10 DDD/1,000 inhabitants/1 day in 2009).
However, the frequency of consumption of single preparations and certain classes of antidepressants during this period changed (Figure 3.1.1).
16.00
DDD/1000 inhabitants/1 day
14.00
12.00
Total AD consumption
10.00
SSRI
8.00
TCA
6.00
Others
Lithii carbonas
4.00
2.00
0.00
2004 2005 2006 2007 2008 2009
Figure 3.1.1. The consumption of antidepressant classes in the years,
2004 to 2009
The changes of consumption within antidepressant classes during the six
years (2004 through 2009) are the following:
 the proportion of consumption of TCAs in six years declined by 42
per cent (from 2.03 to 1.18 DDD/1,000 inhabitants/1 day);
 the consumption of SSRIs showed the pronounced increase of 45 per
cent (from 6.38 to 9.25 DDD/1,000 inhabitants/1 day); therefore SSRIs were
the most used antidepressants during the six years;
 the consumption of the newest medicines classified as “other antidepressants” increased significantly (almost three times) over the research period (from 1.61 to 4.63 DDD/1,000 inhabitants/1 day). However, that is associated with the expanded use of mirtazapine, tianeptine, bupropion and
54
venlafaxine as in 2004 bupropion and venlafaxine appeared in the antidepressants segment.
 there were modest changes in the consumption of Lithii carbonas.
In comparison among proportions of different ADs classes, it appeared
that the proportion of SSRIs remained almost the same (62 per cent) during
the research period although their consumption increased while the proportion of other (newer) ADs increased almost two times reaching 31 per cent
of the total market share (Figure 3.1.2).
100
90
80
70
Lithii carbonas
60
Others
50
SSRI
40
TCA
30
20
10
0
2004
2005
2006
2007
2008
2009
Figure 3.1.2. The share (%) of different ADs classes over the six years
During the research period, the consumption of sertraline remained on
top of the list. Besides, the results show that the proportion of sertraline consumption decreased from a quarter of all ADs (24.5 per cent) to 22.6 per
cent and in parallel the share of amitriptyline consumption declined more
than twice from 14.33 per cent to 6.71 per cent. Table 3.1.1 illustrates the
increased use of paroxetine, mirtazapine and escitalopram; however the use
of other SSRIs (fluoxetine, citalopram, fluvoxamine) decreased.
55
Table 3.1.1. The percentage of the consumption of certain antidepressants
during the years 2004 through 2009
Class
SSRI
TCA
Other
Active substance
2004
2005
2006
2007
2008
2009
Sertraline
24.50
19.58
21.93
21.57
22.05
22.63
Escitalopram
6.05
12.64
12.49
14.97
15.06
16.18
Paroxetine
11.01
11.32
11.37
11.88
12.62
12.74
Citalopram
6.86
4.14
4.62
5.14
5.60
5.17
Fluoxetine
9.25
6.88
5.78
4.53
3.55
2.97
Fluvoxamine
5.01
3.78
2.92
2.54
2.07
1.60
Amitriptyline
14.33
13.41
11.54
8.86
7.46
6.71
Clomipramine
Amitriptyline
(modif.)
0.90
0.77
0.57
0.48
0.40
0.35
1.82
0.76
0.00
0.00
0.00
0.00
Nortriptyline
0.61
0.60
0.45
0.43
0.37
0.29
Doxepin
1.76
0.73
0.76
0.77
0.67
0.45
Mirtazapine
Bupropion (modif.)
8.02
11.97
14.04
16.07
16.25
15.54
2.55
2.71
2.88
2.33
1.79
2.35
Reboxetine
Trazodone
0.18
0.51
2.30
0.14
0.67
2.45
0.11
0.61
2.16
0.01
0.57
2.63
0.00
0.61
2.94
0.00
0.35
2.62
2.27
5.64
6.76
3.83
3.95
4.31
0.00
0.00
0.46
2.35
3.71
4.91
1.53
1.45
0.18
0.06
0.20
0.22
Tianeptine
Venlafaxine
(modif.)
Duloxetine
Lithii
carbonas
Percentage (%)
Lithii carbonas
From 2004 to 2009, the consumption of reimbursed medicines in the research group increased from 3.90 DDD/1,000 inhabitants/1 day to 6.88
DDD/1,000 inhabitants/1 day.
The average consumption of antidepressants in the group of females during the researched period was 6.31 DDD/1,000 inhabitants/1 day while in
the group of males it amounted to 1.15 DDD/1,000 inhabitants/1 day.
The majority of antidepressants is consumed by females from 41.5 to 65
years of age.
The most frequently used substances in the researched period were sertraline, escitalopram, mirtazapine and venlafaxine (the modified release
56
1.40
1.20
1.00
0.80
0.60
0.40
0.20
0.00
Males
Amitriptyline
Amitriptyline (modif.)
Bupropione (modif.)
Citalopram
Clomipramine
Duloxetine
Escitalopram
Fluoxetine
Fluvoxamine
Mirtazapine
Paroxetine
Sertraline
Tianeptine
Venlafaxine
Venlafaxine (modif.)
DDD/1000 inhabitants/1 day
form). The same trends were observed in male and female groups (Figure
3.1.3).
Females
Figure 3.1.3. Analysis of antidepressant consumption by gender
(DDD/1,000 inhabitants/1 day)
When comparing the schemes of male and female treatment, no statistically significant differences were found (chi-square test; p=0.485>0.05).
Of all the patients for whom the original F32 remained unchanged during
the treatment, the patients were usually treated only with the medications
from the SSRI class (32.8 per cent, or 3,236 patients), only with other antidepressants (25.7 per cent (or 2,536 patients), only with benzodiazepines –
12 per cent (or 1,188 patients), only with TCA – 4 per cent (or 402 patients),
with the combination of SSRIs and antidepressants of a new generation –
10.4 per cent (or 1.025 patients), and with the combination of SSRIs and
benzodiazepines – 1.2 per cent (121 patients). Other consumed medications
formed a lower percentage.
The analysis suggests that the medications from SSRI class are used most
frequently (alone or in combination with other medicines).
The average duration of the patients’ treatment is 160.7 days prior to the
diagnosis of F33 (Figure 3.1.4).
57
600
514.88
500
400
365.3
F32 does not change
300
F32 changes to F33
200
101.09
100
27.71
33.3
28.99
SSRI
Others
018.33
0
TCA
Lithii
carbonas
Figure 3.1.4. F32 and F33 treatment terms in days
For the purposes of ANOVA (analysis of variance) while comparing the
duration of treatment and treatment costs in different schemes, the statistically significant difference was determined (p=0.000 <0.05).
It is obvious that the patients with a diagnosis changed during the course
of disease from F32 to F33 were treated significantly longer than the patients whose diagnosis was not altered.
Comparison of DDD and PDD (prescribed daily dose) is shown in Figure
3.1.5.
In this case, Student’s t-test results indicate that the differences are statistically significant (p=0.001 <0.05), which means that the prescribed daily
doses of antidepressants do not meet the set standards.
This means that PDD of antidepressants in some cases does not suit DDD
of a specific medicine. Bupropion, mirtazapine, sertraline and venlafaxine
PDDs exceed DDD while in other cases, PDD is less than DDD.
58
250
200
150
100
50
DDD
PDD
Venlafaxine (modif.)
Venlafaxine
Tianeptine
Sertraline
Paroxetine
Mirtazapine
Fluvoxamine
Fluoxetine
Escitalopram
Duloxetine
Clomipramine
Citalopram
Bupropione (modif.)
Amitriptyline (modif.)
Amitriptyline
0
Figure 3.1.5. PDD and DDD comparison
According to SVEIDRA database, the consumption of antidepressants in
the research group in DDD/1,000 inhabitants/1 day in terms of classes and
in total during the research period is shown in Figure 3.1.6. The total reimbursed antidepressant consumption almost doubled.
8.00
DDD/1000 inhabitants/1 day
7.00
6.00
Total
5.00
SSRI
4.00
Others
3.00
TCA
2.00
Lithii carbonas
1.00
0.00
2004
2005
2006
2007
2008
2009
Figure 3.1.6. Reimbursed antidepressant consumption in terms of classes
from 2004 to 2009
59
The analysis of the results of reimbursed antidepressant consumption
within different classes is presented in Figures 3.1.7-3.1.9. According to the
database analysis in the SSRI class, escitalopram consumption grew up significantly, growth trends were also observed in sertraline and citalopram
medicines while the consumption of all other active substances decreased
(Figure 3.1.7).
DDD/1000 inhabitants/1 day
2
1.8
1.6
1.4
Citalopram
1.2
Escitalopram
Fluoxetine
1
0.8
Fluvoxamine
0.6
Paroxetine
0.4
Sertraline
0.2
0
2004
2005
2006
2007
2008
2009
Figure 3.1.7. SSRI class antidepressant consumption from 2004 to 2009
While analysing the class of other new antidepressants, growth
tendencies are observed in the consumption of almost all active substances
except for clomipramine, duloxetine and venlafaxine (Figure 3.1.8).
60
DDD/1000 inhabitants/1 day
1.6
1.4
Bupropion (modif)
1.2
Clomipramine
1
Duloxetine
0.8
Mirtazapine
0.6
Tianeptine
0.4
Venlafaxine
0.2
Venlafaxine (modif.)
0
2004
2005
2006
2007
2008
2009
Figure 3.1.8. Other’s class antidepressant consumption from 2004 to 2009
The consumption of TCA class antidepressants decreased during the
research period from 0.18 to 0.11 DDD/1,000 inhabitants/1 day (Figure
3.1.9).
Total antidepressant consumption in Lithuania is more than 2 times
higher than reimbursed antidepressants consumption (Figure 3.1.10).
DDD/1000 inhabitants/1 day
0.16
0.14
0.12
0.1
Amitriptyline
0.08
Amitriptyline (modif.)
0.06
0.04
0.02
0
2004 2005 2006 2007 2008 2009
Figure 3.1.9. TCA class antidepressant consumption from 2004 to 2009
61
DDD/1000 inhabitants/1 day
16.00
14.00
12.00
10.00
8.00
Reimbursed antidepressant
consumption
6.00
Total antidepressant
consumption
4.00
2.00
0.00
2004 2005 2006 2007 2008 2009
Figure 3.1.10. Reimbursed antidepressant consumption and total
atidepressant consumption trends from 2004 to 2009
Trends of the prescribed daily doses in the research group stayed the
same during the analyzed period (Figure 3.1.11).
250.00
PDD
200.00
150.00
2004
100.00
2005
Venlafaxine
Venlafaxine (modif.)
Tianeptine
Sertraline
Paroxetine
Mirtazapine
Fluvoxamine
Fluoxetine
Escitalopram
Duloxetine
Citalopram
Clomipramine
2006
Bupropione (modif.)
Amitriptyline
0.00
Amitriptyline…
50.00
2007
2008
2009
Figure 3.1.11. Comparison of prescribed daily doses (PDD) in depression
treatment
62
1.80
1.60
1.40
1.20
1.00
0.80
0.60
0.40
0.20
0.00
2004
Venlafaxine (modif.)
Venlafaxine
Tianeptine
Duloxetine
Clomipramine
Sertraline
Paroxetine
Mirtazapine
Fluvoxamine
Fluoxetine
Escitalopram
Citalopram
2006
Bupropione (modif)
Amitriptyline…
2005
Amitriptyline
DDD/1000 inhabitants/1 day
The evaluation of PDD in different years using ANOVA of the blocked
data enabled the determination of the statistically significant differences at
p=0.005.
The evaluation of DDD/1,000 inhabitants/1 day in different years in the
research group is shown in Figure 3.1.12; the trends during the researched
period persist while DDD/1,000 inhabitants/1 day in different years differs
significantly.
2007
2008
2009
Figure 3.1.12. Antidepressant consumption analysis by year
The evaluation of DDD/1,000 inhabitants/1 day in different years by using ANOVA of the blocked data enabled the determination of the statistically significant differences such as p=0.002.
According to the results of age analysis, the evaluation of DDD among
different age groups/1,000 inhabitants/1 day during different years by using
ANOVA (analysis of variance) enabled the determination of the statistically
significant differences such as p=0.002. According to this, even 15.02
DDD/1,000 inhabitants/1 day medicines are consumed by patients older
than 65 years (Figure 3.1.13).
63
Venlafaxine (modif.)
Venlafaxine
Tianeptine
Sertraline
Paroxetine
Mirtazapine
Fluvoxamine
Fluoxetine
Escitalopram
Duloxetine
Clomipramine
Citalopram
18-41,5
Bupropione (modif.)
Amitriptyline…
< 18
Amitriptyline
DDD/1000 inhabitants/1 day
3.00
2.50
2.00
1.50
1.00
0.50
0.00
41,5-65
> 65
Figure 3.1.13. Antidepressant consumption analysis by age
The results of our research show an increase in the consumption of antidepressants during the years 2004 through 2009. The biggest impact on consumption growth was produced by SSRI and the use of the newest “Other
antidepressants”. This trend is parallel with the data from other European
countries and the United States where SSRIs belong to the first-line medicines [114]. However, in accordance with the recommendation for depression treatment and the priority of antidepressant selection in Lithuania, the
medicine of choice for the treatment of depression should be amitriptyline
unless tricyclic antidepressants are contraindicated in a patient and/ or
his/her age is under 18 or more than 65. In the view of the major share of
SSRI medicines, the use of ADs was not consistent with the recommendations for the treatment of depression in Lithuania. Due to high toxicity of
TCAs, these antidepressants are used less frequently and for shorter periods
than recommended [43].
The increased use of selective serotonin reuptake inhibitors and other
nontricyclic antidepressants is probably related to their superior tolerability,
improved risk-benefit ratio, and lower toxicity in case of overdose. The
share of different antidepressant classes is also unexpected: during the six
years covered in the research, the share of SSRIs remained almost the same
while the newer “Other” antidepressant share almost doubled in the context
of the total use of antidepressants. Over the researched period, the consumption of sertraline remained on the top of the whole antidepressant consumption list while the newest antidepressants follow; the most prominent growth
64
is observed in the use of paroxetine, mirtazapine and escitalopram. According to this the hypothesis that the reason of depression relapse growing up
may be in modern and newest medicines consumption what can be unreasonable in today depression treatment appears.
3.2.
Analysis of the efficiency of depression diagnosis and treatment
and depression dynamics evaluation
3.2.1. Analysis of the efficiency of diagnosis
In 12,750 out of 25,576 patients, the disease diagnosis was determined/defined incorrectly (52.14 per cent) (Figure 3.2.1.1).
During the first visit, 66.1 per cent of patients had the diagnosis of F32
recorded (16,902 patients) while the rest had the diagnosis of F33 recorded
(8,674 patients). As the data was collected only since 2004, it is likely that
prior to the diagnosis of F33, some patients had been treated for F32.
The diagnosis does not change during the course of treatment for 9,854
of patients (for 58.3 per cent the former initial F32 batch it remained unchanged). The initial diagnosis of F33 remained unchanged for 6,000 patients (69.1 per cent).
10.46%
24.41%
F32 does not change to
F33
F33 does not change
F32 changes to F33 and
back to F32
F32 does not change but
have to
38.53%
23.46%
3.15%
F33 changes to F32
Figure 3.2.1.1. Depression diagnosis code definition analysis
According to the rules, the first time depression diagnosed to a patient is
always assigned F32 illness code. Every subsequent depression occurrence
65
after the recovery is supposed to be marked as F33, i.e. relapsed depression.
F33 depression code cannot ever be reversed to F32 during the remaining
lifetime of the patient. The only case of F32 never becoming F33 is when
the patient recovers and the illness never relapses.
For 12,750 of the 25,576 patients, the disease diagnosis was determined/defined incorrectly. There is no relevant monitoring of the system of
depression type code (F32 and F33) compliance with the illness type control.
3.2.2. Inaccuracies in depression treatment
It is important to note that the consumption of benzodiazepines in the
cases of depression is growing in Lithuania. Benzodiazepines were prescribed for 5,007 patients (19.58 per cent) in the course of treatment, the
number of prescriptions was 42,033 while the reimbursable amount totalled
178,726.32 LTL.
For 1,680 patients, benzodiazepines were prescribed only once during the
treatment, for 651 it was twice while for 380 patients it was done three
times.
Most depression treatment guidelines emphasize treatment with antidepressant medication and recommend that the use of benzodiazepine should
be minimized, particularly among elderly patients. However, little is known
about the patterns of benzodiazepine use in mental health settings.
Antidepressant medications are the recommended pharmacological
treatment for depression, and many antidepressants are effective for both the
core symptoms of depression and for the coexisting anxiety [5, 74]. However, the beneficial effects of antidepressants often do not occur for several
weeks, and physicians may prescribe benzodiazepines for a more immediate
relief.
Although the use of benzodiazepines was declining, many individuals,
particularly elderly patients, continue to use these agents [93, 108, 113].
Although benzodiazepine consumption is widespread, the benefits of prescribing these medications for depressed patients are unclear. Most randomized, controlled trials examining benzodiazepines as the primary pharmacological treatment for depression have concluded that these medications are
less effective than antidepressants as they address sleeplessness and restlessness but not the other core depressive symptoms [6].
Academic writings contain conflicting reports about the risks arising
from long-term benzodiazepine use [90]. Long-term users can develop
withdrawal symptoms if benzodiazepines are tapered rapidly or discontinued abruptly [32]. Cognitive impairments indisputably occur with the acute
66
administration of benzodiazepines; however, studies differ regarding the
significance of cognitive impairments among long-term users. Some studies
report continued cognitive difficulties with chronic use [62], whereas others
report only modest impairments among healthy long-term users [80]. Several observational studies linked chronic benzodiazepine use with the subsequent development of dementia [23], although one nested case-control study
reported a decreased risk of Alzheimer’s disease among chronic benzodiazepine users [33]. Presumably because of the cognitive and psychomotor effects of benzodiazepines, many but not all studies have found benzodiazepines to be associated with increased rates of motor vehicle crashes, falls,
and hip fractures among elderly patients [19].
Long-term benzodiazepine users, such as alcoholics and barbituratedependent patients, are often depressed, and the depression may first appear
during prolonged benzodiazepine use. Benzodiazepines may both cause and
aggravate depression, possibly by reducing the brain’s output of neurotransmitters such as serotonin and norepinephrine (noradrenaline). However,
anxiety and depression often co-exist and benzodiazepines are frequently
prescribed for mixed anxiety and depression. Sometimes the medicines
seem to precipitate suicidal tendencies in such patients. In 1988, the Committee on Safety of Medicines in the United Kingdom recommended that
“benzodiazepines should not be used alone to treat depression or anxiety
associated with depression. Suicide may be precipitated in such patients”
[6].
Benzodiazepines do not cause depression; yet their use may lead to depression as well as thoughts of suicide with the attempted suicide or without
it.
As shown in Figure 3.2.2.1, the discrepancy of expenses for medicament
depression treatment over the research period grew from 24.7 thousand LTL
to 44.7 thousand LTL (1.8 times).
67
44,692
45,000
41,384
40,000
37,233
37,925
2006
2007
35,000
28,837
LTL
30,000
24,721
25,000
20,000
15,000
10,000
5,000
2004
2005
2008
2009
Figure 3.2.2.1. Discrepancy of expenses on medicament depression treatment (reimbursed by depression code by mistake) in LTL
This money was spent on medicines which do not belong to depression
treatment schemes and government-approved reimbursement lists.
According to academic researches, benzodiazepines are not suitable for
depression treatment; moreover, they can induce suicides. This data raises
doubts about the treatment of depression and benzodiazepine consumption
adequacy.
Discrepancy of expenses on medicament depression treatment over the
covered period increases 1.8 times. These expenses are supposed to be treated as mistakes made by doctors or pharmacists. This money was spent on
medicines which do not belong to depression treatment schemes and government-approved reimbursement lists.
3.2.3. Evaluation of depression treatment quality
It should be noted that in Lithuania in 2007 the right to diagnose depression and to prescribe treatment was given to family doctors. According to
their responses in the questionnaire it is evident that in 12.6 per cent cases
family doctors refrain from prescription of treatment by themselves (Figure
3.2.3.1).
68
12.60%
0.60%
Send to psychiatrist, who
prescribe a medicines
Prescribe the same
medicine as local
psychiatrist
Prescribe medicine by
themselves
86.80%
Figure 3.2.3.1. Answers of family doctors to the question
“How do you treat your patients’ depression?”
When prescribing antidepressants, general practitioners usually choose
sertraline, a medicine of SSRI (selective serotonin reuptake inhibitors) class
(24.9 per cent), alprazolam (21.2 per cent) and bromazepam (16.7 percent)
(medicines of benzodiazepine class) follow in the second and third place.
After polling psychiatrists, the tendency to prescribe medicine of SSRI
class, i.e., sertraline (40.8 per cent) and escitalopram (27.6 per cent) showed
up more frequently while the third most frequently selected medicine is
mirtazapine (9.2 per cent) (Figure 3.2.3.2).
69
Psychiatrists
Other
Lorazepam
Alprazolam
Bromazepam
Amitriptiline
Fluvoxamine
Tianeptine
Paroxetine
Duloxetine
Mirtazapine
Escitalopram
Family doctors
Sertraline
%
45
40
35
30
25
20
15
10
5
0
Figure 3.2.3.2. The most popular antidepressants as prescribed by family
doctors and psychiatrists
One third of the surveyed Lithuanian family doctors indicated that they
review the impact of different medicines after 1 to 2 months while 17 per
cent did it only after half a year (Figure 3.2.3.3).
26.8
32.3
28.8
25
17.3
12.5
13.1
8.5
Psychiatrists
Family doctors
Other
After 6 months
After 3-4 months
After 1-2 months
1.4
After 2 weeks
%
34.3
35
30
25
20
15
10
5
0
Figure 3.2.3.3. Monitoring of antidepressant efficiency by family doctors
and psychiatrists
70
Psychiatrists stated that they always or often adjust the dose of medicine
for almost a half of their patients during the treatment (27 per cent and 34
per cent, respectively). This emphasizes the higher quality of the patients’
monitoring by these professionals and the higher efficiency of depression
treatment.
The share of cases of depression relapse is large in Lithuania. The data of
the present survey correlates well with the depression epidemiology data by
the State Mental Health Center. This is confirmed both by surveys of family
doctors and psychiatrists: about 35 per cent of respondents of both groups
indicated recording the cases of relapsed depression, however, the numbers
of cases of relapsed depression differ significantly (Figure 3.2.3.4).
40
35.7
35
30
27.5 26.8
30
23.2
%
25
18.3
20
Psychiatrists
15
5
6.9
3.9
2.8
6.8
10
0
1.3
Family doctors
Other
80-100%
50-80%
20-50%
5-20%
< 5%
0
Figure 3.2.3.4. Depression relapse percentage in the regular practice
in the opinion of general practitioners and psychiatrists
At least 60 per cent of people who experienced one major depressive episode will have another, mostly within 2 years of the index episode [54].
Seventy per cent of those who had two episodes will have a third, and 90
per cent of those with three episodes will have a fourth. Effective interventions targeting relapse, particularly in people with a history of three or more
episodes of depression, could dramatically reduce the prevalence of the
condition [101].
Obviously, in the case of relapsed depression, quality of life declines
once again in all measures that assess therapeutic efficacy of antidepressants in quality of life aspects.
71
After diagnosing a relapsed depression, family doctors refer patients to
psychiatrists immediately (61.7 per cent of all cases). When meeting these
patients, psychiatrists prescribe the medicine which had been prescribed
earlier even in 73.36 per cent of the cases.
It is important to note that the consumption of benzodiazepines in the
cases of depression is growing in Lithuania (Figure 3.2.3.5). This is also
prominent in terms of the costs of the reimbursable benzodiazepines in the
case of the growing trend of the diagnosis of depression.
400,000
350,000
300,000
250,000
200,000
Volume, units
150,000
Value, LTL
100,000
50,000
2004
2005
2006
2007
2008
2009
Figure 3.2.3.5. Trends the use of benzodiazepines in depression treatment
This data raises doubts concerning the treatment of depression and the
adequacy of benzodiazepine consumption.
Pharmacists evaluate medicament treatment in depression cases rather
negatively (Figure 3.2.3.6).
Irresponsible behavior of depressed patients or their relatives is characterized by trying to self-medicate oneself or avoiding doctoral care: as many
as 46 per cent of the surveyed pharmacists point out that they are being daily asked for antidepressants without prescription by their pharmacy customers (Figure 3.2.3.7).
72
Yes
12.90%
17.50%
No, they get too much
medication and over-dosage
34.10%
No, they get too narrow range
of active substances
24.70%
10.80%
No, they get too poor special
care and monitoring during
their treatment at home
Other
Figure 3.2.3.6. Pharmacists’ answers to the question
“Do you think that depressed patients are treated rather rationally and
effectively in Lithuania?”
13.30%
4.20%
17.50%
17.70%
10 or more times a day
At least 2 times a day
Every or almost every day
2-3 times a month
Almost never
Other
22.40%
24.90%
Figure 3.2.3.7. Pharmacists’ answers to the question
“How often are you being asked for antidepressants without prescription by
pharmacy customers?”
73
There were 15 antidepressant active substances in 2009 in Lithuania, the
choice of which depends on a family doctor’s or psychiatrist’s decision.
However, in accordance with the recommendation on depression treatment
and the priority of antidepressants selection in Lithuania, the medicines of
choice for the treatment of depression should be amitriptyline unless tricyclic antidepressants (TCAs) are contraindicated in a patient and/or his/her
age is under 18 or more than 65. In the view of the large share of SSRI medicines mentioned by respondents, the use of antidepressants was not consistent with the recommendations for the treatment of depression in Lithuania. Due to high toxicity of TCAs, these antidepressants are used less frequently and for shorter periods than recommended [46].
Attention should be paid to the selection of medicine prescribed for depression treatment by family doctors: medicines of the benzodiazepine class
are not suitable for depression treatment; they are more often prescribed in
cases of anxiety [76]. The most negative aspect is that the medicines of the
benzodiazepine class can stimulate suicide [7].
The next stage of depression treatment after medicine prescription is the
monitoring of the patient’s condition. When treating the initiating or acute
depression, the impact of a medicine should already be noticed after 4
weeks while the improvement of the course of the disease should be observed after 8 weeks [109]. A third of the surveyed Lithuanian family doctors indicated that they reviewed the impact of different medicines after 1 or
2 months while 17 per cent only after half a year. Psychiatrists said that they
always or often adjusted the dose of a medicine for almost a half of the patients during treatment (27 per cent and 34 per cent, respectively). This emphasizes the higher quality of patient monitoring by these professionals and
the higher effectiveness of depression treatment.
The share of cases of depression relapse is high in Lithuania. The present
survey data correlates well with the depression epidemiology data of the
State Mental Health Center. This is confirmed by surveys of both family
doctors and psychiatrists: about 35 per cent of the respondents of both
groups indicated recording cases of relapsed depression; however, the numbers of cases of relapsed depression differ significantly. While analyzing the
results of the above responses, the work efficiency of family doctors and
psychiatrists might be evaluated and the appropriate proposals might be put
forward thus saving funds and seeking economic and social effects.
This research suggests that improving the quality of depression care is
necessary to raise the value of care and enhance the benefit of treatment
costs. From the patient’s perspective, quality improvement leads to the patient’s improved well-being and this benefit could increase the patient’s satisfaction.
74
The majority of the surveyed psychiatrists possessed a relatively long
working experience. However, experienced professionals probably not always evaluate the causes of depression carefully. For example, during the
period of the physical beauty cult, the cause of depression may have been
obesity [59] or previously experienced serious diseases [85], etc.
When treating an individual with relapsed depression, the disease should
be looked into even more closely: the reasons for relapse of depression may
be not only the inappropriate selected medicine or the incorrectly identified
diagnosis [60] but also the too-early-terminated previous treatment, newly
arising psychological problems, the changed social status, etc. [124]. In particular, it is important to communicate frequently with the patient, to monitor his/her condition at the beginning of treatment and to react in time if
there are no signs of improvement in appropriate time [96].
In today’s cost-conscious environment, suggestions for the improvement
of the quality of care are not favorably received because the improving quality generally means higher total healthcare costs. The value of care, or costeffectiveness, should be an equally important consideration. Yet, health
plans give little incentive to pick up the tab for increased treatment costs
because plans contribute to the achievement of none of these benefits directly; instead, doctors are under pressure from their employers to keep treatment costs down. This research suggests that cost-effectiveness has an important place in the debate.
Recent studies and the experience of professionals show that medicine is
not enough for depression treatment – the combination of individually selected medicine and psychological help is needed. Family doctors and psychiatrists with a long-time experience should re-evaluate the altered context
and causes of depression, cooperate more closely with pharmacists seeking
to find out about the latest antidepressants.
The abundance of cases of relapsed depression, especially recorded by
family doctors who had already treated the same depressive patients, encourages one to look at the training of family doctors in terms of how to
treat this disease anew. It is recommended to provide more depressionrelated information and training to doctors. It should also be encouraged to
refer the individuals with depression to psychiatrists immediately in order to
avoid a long-term ineffective treatment.
3.2.4. Analysis of the dynamics of depression diagnosis
The scope of total depression diagnoses grows up during the six years
from 20,381 diagnoses in 2004 to 22.821 in 2009. The amount of first-time
diagnosed depression (F32) grows up not so significantly as of that relapsed
75
depression diagnoses (F33) – from 8,300 in 2004 to 10,514 in 2009 (Figure
3.2.4.1).
Figure 3.2.4.1. First time (F32), relapsed (F33) and total depression
diagnosis trends in Lithuania in the years 2004 through 2009
Figure 3.2.4.2 shows that depression was diagnosed for women approximately 4 times more often than for men. Cases of relapsed depression were
recorded accordingly.
Each year, there are more and more cases of depression diagnosed in
Lithuania. Statistics of diseases demonstrates a continuously increasing
number of relapsed depression diagnoses. According to this, depression diagnosis numbers increase because of depression relapse rates in Lithuania.
According to the data of researchers of United States of America, this
disorder is relapsed even for 50 per cent of those with depression and those
who have been treated previously. Other figures are even more alarming as
after a repetitive treatment of depression, about 70 per cent of patients fall
into depression for the third time, and after three treatments even 90 per cent
do. Each case of a relapsed occurrence means that a previous treatment was
unsuccessful [88].
The biggest part of depression patients is 41.5 to 65 years old. It means
that the impact of depression on the society is extremely important.
76
20,000
18,000
16,000
14,000
12,000
10,000
8,000
6,000
4,000
2,000
-
First time
depression
Depression
relapse
2004
2005
2006
2007
2008
Males
Females
Males
Females
Males
Females
Males
Females
Males
Females
Males
Females
Total
2009
Figure 3.2.4.2. First time and relapsed depression diagnosis trends by
gender in Lithuania the years 2004 through 2009
Comparing total, first time and relapsed depression diagnosis tendencies
by gender, another issue appears, the results show that women were diagnosed with depression more frequently than men were. Moreover, depression relapse numbers in the women group grow up drastically during the six
years of research.
According to the European Pact for Mental Health and Well-being, depression is stated by the specialists and the society not only as a disease,
which may be treated but also as a serious condition of an individual depending on various psychological and social elements and having impact on
the whole society [71]. Depressive disorders were estimated to be the fourth
leading cause of the disease burden, accounting for 4.4 per cent of the total
disability-adjusted life-years in the year 2000, and it causes the largest
amount of non-fatal burden by accounting for almost 12 per cent of all total
years lived with a disability worldwide [116]. Depression was also associated with an increased mortality risk of 1.81 (1.58-2.07) in a meta-analysis of
25 community surveys involving more than 100,000 subjects [14].
In recent years, an increasing number of cases of relapsed depression is
recorded, which greatly increases the overall number of patients with this
disease. The number of suicides also increases together with the spreading
depression, e.g. 59 thousand people killed themselves because of the impact
77
of depression in 2006 in the whole territory of Europe according to a Eurostat report on the causes of deaths in the EU.
After starting considering depression more broadly and looking for its
causes, the quality-of-life index was started to be employed as well getting
the cost of living, culture and relaxation, economics, environment, level of
freedom, health protection, safety and risk, climate assessed. The magazine
“International Living” published the list of 194 countries where countries
are listed according to the quality-of-life index. Lithuania was in a relatively
high, 22nd, position.
When analyzing the trends of consumption of antidepressants, attention
is paid to the gender of patients with this disease. It is assessed that generally females suffer from this disease twice more frequently than males [17].
Besides physiological reasons, e.g., maturation difficulties, childbearing,
menopause, etc., various social phenomena also influence the susceptibility
to depression such as inequality between men and women, cultural stereotypes, violence in family, a high burden of responsibility, etc. Statistics
shows that Lithuania does not significantly differ in this area from the other
countries in the world. Depression was diagnosed for women just about 4
times more frequently than for men. Cases of relapsed depression were recorded accordingly. The high incidence of depression in women must be taken into account. Statistics demonstrates only recorded cases of diagnosis;
however, there is no doubt that actually there are significantly more women
who suffer from depression.
Among the above mentioned causes of incidence of depression in women, statistical indices of Lithuania only confirm the quite poor social situation of women. In the beginning of 2009, 53.5 per cent of women and 46.5
per cent of men constituted the population of Lithuania, i.e., 1,151 women
for 1,000 men. According to the data of Statistics Department in Lithuania,
women in 2009 in Lithuania live approximately 12 years longer than men,
for 78.6 and 67.5 years, respectively.
The Statistics Department in Lithuania provides unemployment statistics
showing that there were significantly more employed women than men during the 1st quarter of 2009; the unemployment level among men was 23.2
per cent and 13.1 per cent among women. However, although women are
noticeably more educated than men, they still earn significantly less: the
gross average salary in 2009 was 1,990 LTL among women and 2,349 LTL
among men.
However, women do not experience more mental illnesses than men;
they are simply more prone to depression and anxiety, whereas men are
more likely to have addictive disorders and personality disorders. The effects of stress, violence, poverty, inequality, sexism, care giving, relational
78
problems, low self-esteem, and ruminative cognitive styles probably increase vulnerability to depression in women. Predictive factors for depression include previous depression, feeling out of control or overwhelmed,
chronic health problems, traumatic events in childhood or young adulthood,
lack of emotional support, lone parenthood, and low sense of mastery. Special considerations are required for analyzing the risk factors influencing the
women’s physical health [43].
The present results confirm the findings in an international research that
there is a gender gap in depression across Europe. Socioeconomics-related
factors as well as family-related characteristics moderate the relationship
between gender and depression. The largest gender differences in depression were found in a number of Southern European countries and in certain
Eastern European countries. Until recently, many studies characterized
Southern European countries as traditional, male breadwinner systems. In
contrast, the Eastern European countries, especially the former Soviet Union
countries, have a history of the socialist policy that encourages dualbreadwinner households [25]. However, both Southern and Eastern European countries are currently in transition. During the past decade, the Southern
countries have been confronted with a rapid expansion of women’s employment, which forced them to be innovative in how they manage household responsibilities. Changes in men’s behavior, especially in relation to
the unpaid work of care giving, were nevertheless relatively small [57]. For
example, in Portugal, where the largest gender gap in depression is found,
there is a relatively large number of mothers who are employed full time
and dual full-time income earners predominate, along with relatively low
levels of formal childcare provision [83].
The impact of depression on the society has not yet been assessed in
Lithuania. This disease carries a considerable epidemiological impact, and is
often misdiagnosed and mistreated as well; depression imposes an enormous
burden on the society resulting from its high prevalence, under-diagnosis
and under-treatment. Depression has many costs and consequences, including a decreased quality of life for patients and their families, high morbidity
and mortality, and substantial economic losses [65].
Thus, in terms of depression as well as other major chronic illnesses, it is
important to consider the global disease management. Hence, a proper use
of all the remedies available to date can really improve not only the clinical
but also the economic component of the management of patients suffering
from depression thus producing global savings for the health system [106].
The increasing consumption of antidepressants and compliance with the
growing numbers of depression diagnoses urge to have a closer look at the
causes of the disease: physiological, psychological and social ones. When
79
comparing first-time and relapsed depression diagnoses, the results are surprising – while the level of first time depression diagnoses stays almost the
same, relapsed depression numbers grow up significantly in all the researched years. The results of our research show that depression diagnosis
numbers are growing up because of depression relapse in women.
3.2.5. Analysis of depression relapse and treatment dependence
On the grounds of the definition of tendencies of antidepressant use in
first-time and relapsed depression cases, depression relapse dependence on
the first-time depression treatment algorithm was analyzed.
All cases of first-time depression when F32 illness code does not change
to F33 were treated as recovery. All cases of F32 changes to F33 (relapsed
depression illness code) were treated as depression relapse. According to
this, depression relapse analysis by treatment schemes was carried out (Table 3.2.5.1).
Table 3.2.5.1. Depression relapse analysis by treatment schemes
Class
TCA
Other
SSRI
F32 does not
change
402
2,536
3,236
F32 changes to F33
8
667
4,304
Probability of healing
from depression
0.98
0.79
0.43
The biggest probability of no relapse of depression was determined for
TCAs and other new antidepressants. This can be explained by the fact that
using TCA is not popular and the treatment with this medicine has a series
of side effects while other new generation antidepressants do not have a
long enough treatment history for F33 to appear. It takes to be continuous
and permanent monitoring of F33 determination cases to obtain the determination of certain treatment results.
According to this, a more profound analysis in terms of antidepressant
active substances was carried out (Table 3.2.5.2).
The most effective treatment of depression without relapse can be observed when using amitriptyline (TCA class), venlafaxine (Other new generation antidepressants) and citalopram (SSRI class).
80
Table 3.2.5.2. F33 manifestation probability analysis by active substances
Depression analysis
Active substance
F32 does not
change
F32 changes
F33
Probability to heal
Amitriptyline (TCA)
402
8
0.98
Venlafaxine (Other)
Duloxetine (Other)
Bupropion (Other)
Citalopram (SSRI)
300
576
696
627
1,093
1,197
141
12
57
105
486
942
1,245
468
0.96
0.91
0.87
0.56
0.54
0.49
0.23
Escitalopram (SRRI)
Sertraline (SSRI)
Paroxetine (SRRI)
160
140
120
100
80
60
40
20
0
PDD
Sertraline (SSRI)
Paroxetine (SRRI)
Escitalopram (SRRI)
Citalopram (SSRI)
Venlafaxine (others)
Duloxetine (others)
Bupropion (others)
DDD
Amitriptyline (TCA)
Mg
According to the fact that venlafaxine is not used due to side effects and
modified release form introduction and that duloxetine is a rather new medicament with a short history, bupropion was selected for future pharmacoeconomic depression treatment cost rationalizations in terms of depression
relapse rates from the other antidepressants class.
The most effective depression treatment doses are shown in Figure
3.2.5.1.
Figure 3.2.5.1. The most effective F32 case treatment doses (PDD) and defined daily dose (DDD) comparative analysis
81
While comparing the schemes for the treatment of men and women, no
statistically significant differences were determined (chi-square test,
p=0.485> 0.05).
During the treatment of the patients in case their diagnosis is F32, the diagnosis was changed to F33 for 7,048 patients. For 15 per cent of patients
(1,077), the change to diagnosis F32 was again replaced by F33 during the
course of the treatment. After the replacement by F33, some of the patients
(748 patients) did not visit the doctor for some time, and after a longer time
(almost a year or more), they were diagnosed with F32 again.
The duration of treatment of F32 prior to F33 ranges from 15 days up to
15.23 months, and on average is equal to 125.015 days or 4.17 months. An
average duration of women’s treatment is 114.9 days or 3.83 months while
that of men’s treatment is 160.4 days or 5.35 months.
For F32, an average duration of treatment of patients from 18 to 41.5
years of age is 20.3 months while that of patients from 41.5 to 65 years of
age is 13.2 months, and that of patients older than 65 years of age is 5.8
months.
An average duration of treatment is 160.7 days prior to the diagnosis of
F33.
3.3. Analysis of the costs of antidepressants
The findings show that the total expenditure on antidepressants in Lithuania increased from 22.59 mln. LTL in 2004 to 26.85 mln. LTL in 2008 although it decreased to 23.98 mln. LTL in 2009 (Figure 3.28). The expenditure decrease in 2009 was based on the antidepressants price decrease because of generic medicines entering the market.
As it is shown, extremely high costs are shown for SSRIs that include the
largest part of all antidepressants costs (66 per cent in 2004; 54 per cent in
2009). However, in comparison with the costs of SSRIs, the costs of TCAs
are low and declined modestly over the six years (from 1.19 to 0.59 mln.
LTL). The costs of other antidepressants increased significantly over the
researched period as their consumption increased.
While analyzing the data of IMS Health, generic medicines coming to the
market significantly influence the expenses on ethic medicines. As it is
shown in Figures 3.3.1-3.3.10, sales in units of any active substance medicine and their values decreased after generic medicines entering the market.
82
30.00
25.00
Mln. LTL
20.00
Total
SSRI
15.00
Others
TCA
10.00
Lithii carbonas
5.00
0.00
2004
2005
2006
2007
2008
2009
Figure 3.3.1. Costs of antidepressants during the six years (2004 to 2009)
8,000,000
100,000
7,000,000
90,000
80,000
6,000,000
Units
60,000
4,000,000
50,000
3,000,000
40,000
30,000
2,000,000
Value, LTL
70,000
5,000,000
Ethic
Generic
Ethic
Generic
20,000
1,000,000
10,000
0
0
2004 2005 2006 2007 2008 2009
Figure 3.3.2. Analysis of ethic and generic escitalopram sales in units (left
axis) and values in LTL (right axis) analysis
83
120,000
4,000,000
3,500,000
100,000
Units
2,500,000
60,000
2,000,000
1,500,000
40,000
Value, LTL
3,000,000
80,000
Generic
Ethic
Generic
1,000,000
20,000
Ethic
500,000
0
0
2004 2005 2006 2007 2008 2009
Figure 3.3.3. Analysis of ethic and generic sertraline sales in units (left
axis) and values in LTL (right axis)
50,000
2,500,000
45,000
40,000
2,000,000
Units
30,000
1,500,000
25,000
20,000
1,000,000
15,000
Value, LTL
35,000
Ethic
Generic
Ethic
Generic
10,000
500,000
5,000
0
0
2004 2005 2006 2007 2008 2009
Figure 3.3.4. Analysis of ethic and generic paroxetine sales in units (left
axis) and values in LTL (right axis)
84
4,000,000
80,000
3,500,000
70,000
3,000,000
Units
60,000
2,500,000
50,000
2,000,000
40,000
1,500,000
30,000
20,000
1,000,000
10,000
500,000
0
Value, LTL
90,000
Ethic
Generic
Ethic
Generic
0
2004 2005 2006 2007 2008 2009
Figure 3.3.5. Analysis of ethic and generic mirtazapine sales in units (left
axis) and values in LTL (right axis)
45,000
3,500,000
40,000
3,000,000
35,000
Units
25,000
2,000,000
20,000
1,500,000
15,000
1,000,000
Value, LTL
2,500,000
30,000
Ethic
Generic
Ethic
Generic
10,000
500,000
5,000
0
0
2004 2005 2006 2007 2008 2009
Figure 3.3.6. Analysis of ethic and generic venlafaxine sales in units (left
axis) and values in LTL (right axis)
85
35,000
1,200,000
30,000
1,000,000
25,000
Units
20,000
600,000
15,000
Value, LTL
800,000
400,000
10,000
Ethic
Generic
Ethic
Generic
200,000
5,000
0
0
2004 2005 2006 2007 2008 2009
Figure 3.3.7. Analysis of ethic and generic citalopram sales in units (left
axis) and values in LTL (right axis)
45,000
700,000
40,000
600,000
35,000
Units
25,000
400,000
20,000
300,000
15,000
200,000
Value, LTL
500,000
30,000
Ethic
Generic
Ethic
Generic
10,000
100,000
5,000
0
0
2004 2005 2006 2007 2008 2009
Figure 3.3.8. Analysis of ethic and generic fluoxetine sales in units (left
axis) and values in LTL (right axis)
86
14,000
900,000
800,000
12,000
700,000
600,000
8,000
500,000
6,000
400,000
Value, LTL
Units
10,000
300,000
4,000
Ethic
Generic
Ethic
Generic
200,000
2,000
100,000
0
0
2004 2005 2006 2007 2008 2009
Figure 3.3.9. Analysis of ethic and generic bupropion sales in units (left
axis) and values in LTL (right axis)
120,000
450,000
400,000
100,000
350,000
300,000
250,000
60,000
200,000
40,000
150,000
Value, LTL
Units
80,000
Ethic
Generic
Ethic
Generic
100,000
20,000
50,000
0
0
2004 2005 2006 2007 2008 2009
Figure 3.3.10. Analysis of ethic and generic amitriptyline sales in units (left
axis) and values in LTL (right axis)
87
Amounts of generic antidepressants in the market during the studied period are presented in Table 3.3.1.
Table 3.3.1. Amounts of generic antidepressants in the Lithuanian market
Generic medicines, amounts in the market
2004
2005
2006
2007
2008
2009
Venlafaxine
Active substance
0
0
1
2
4
9
Citalopram
3
3
4
5
6
5
Mirtazapine
1
2
3
4
4
5
1
1
Escitalopram
Fluoxetine
7
7
7
7
7
7
Amitriptyline
1
2
2
2
2
1
Sertraline
3
4
6
7
7
7
Paroxetine
1
1
3
5
5
5
1
1
1
Bupropion
If comparing the prices of one antidepressants DDD, the TCAs prices in
2009 range from 0.22 LTL/DDD (amitriptyline) to 1.81 LTL/DDD (doxepin) (Figures 3.3.11–3.3.13).
3
DDD price, LTL
2.5
Sertraline
2
Escitalopram
Paroxetine
1.5
Citalopram
1
Fluoxetine
Fluvoxamine
0.5
0
2004
2005
2006
2007
2008
2009
Figure 3.3.11. DDD prices of SSRI class antidepressants from 2004 to
2009
88
2.5
Amitriptyline
2
DDD price, LTL
Clomipramine
1.5
Imipramine
Amitriptyline
(modified release)
1
Nortriptyline
0.5
Doxepin
0
2004
2005
2006
2007
2008
2009
Figure 3.3.12. DDD prices of TCA class antidepressants from 2004 to 2009
5
Mirtazapine
4.5
Bupropion (modified
release)
Reboxetine
DDD price, LTL
4
3.5
3
Mianserin
2.5
Agomelatine
2
1.5
Trazodone
1
Tianeptine
0.5
0
2004 2005 2006 2007 2008 2009
Venlafaxine (modified
release)
Duloxetine
Figure 3.3.13. DDD prices of ‘Other’ class antidepressants from 2004 to
2009
The cheapest ADs in the SSRI class is fluoxetine (0.46 LTL/DDD) and
the most expensive is fluvoxamine (2.23 LTL /DDD). The prices of SSRI
class antidepressants decreased in certain period. The prices of other ADs
89
class balance between 1.17 and 3.81 LTL /DDD. The most expensive positions are those of the newest other ADs class medicines.
3.4. Analysis of the cost-effectiveness and costs rationalization of
antidepressants consumption
While assessing the socio-economic benefits of the substitution of an ethic medicine with a generic one, the costs for the specific active substances
are recalculated according to an average price of a generic medicine in a
given year. As it can be seen in the table below, the rationalization of the
costs for certain antidepressants active substances in the treatment of depression and the promotion of the use of generic medicines in the event of
such a medicine entering the market allows 10.9 mln. LTL to be saved, i.e. 9
per cent of all costs incurred by antidepressant consumption during the period of 2004 to 2009 in Lithuania (Table 3.4.1).
Table 3.4.1. Medicament depression treatment rationalization proposals by
generic medicines promotion policies
Real expenses, Lt
Prognoses
expenses, Lt
Savings,
Lt
Savings,
%
Escitalopram
31,550,827
28,349,809
3,201,017
10%
Sertraline
23,080,076
21,622,366
1,457,710
6%
Paroxetine
13,593,442
13,000,697
592,746
4%
Mirtazapine
22,102,239
19,740,859
2,361,380
11%
Venlafaxine
11,498,042
9,538,294
1,959,747
17%
Citalopram
5,937,172
5,098,061
839,111
14%
Fluoxetine
2,793,201
2,584,196
209,005
7%
Bupropion
3,838,485
3,693,659
144,825
4%
Amitriptyline
2,386,213
2,226,488
159,725
7%
116,779,697
105,854,429
10,925,268
9%
Active substance
Total:
According to the following analysis, proliferation of generic antidepressants in the market dynamics correlates with the dynamics of savings each
year (Figure 3.4.1).
90
45
40
Proliferation of generic
antidepressants in the
market dynamics
35
30
25
Savings dynamics (mln.
LTL)
R² = 0.9858
R² = 0.9911
20
15
Linear (Proliferation of
generic antidepressants
in the market
dynamics)
10
5
0
2004
2005
2006
2007
2008
2009
Figure 3.4.1. The proliferation of generic antidepressants in the market and
saving dynamics in 2004 to 2009 in Lithuania
During this research, an attempt was made in order to indicate the pricing
limits of the ADs considering the similarity of therapeutic effects within
different AD classes. Pharmacoeconomic calculations were conducted by
using the cost-effectiveness analysis for obtained data of AD expenditures.
According to antidepressants effectiveness evaluated by depression relapse rates and probability to heal after first time depression treatment costeffectiveness analysis was performed (Table 3.4.2).
Table 3.4.2. Depression treatment cost-effectiveness analysis
Active substance
EffecTreatment
tiveness terms in days
DDD
price,
LTL
Treatment
price, LTL
Effective
treatment
price, LTL
Amitriptyline (TCA)
98%
27.71
0.22
6.10
6.22
Venlafaxine (Other)
96%
29.27
0.45
13.17
13.72
Duloxetine (Other)
91%
27.83
3.58
99.63
109.49
Bupropion (Other)
87%
30.12
1.78
53.61
61.62
Citalopram (SSRI)
56%
35.72
0.84
30.00
53.58
Escitalopram (SRRI)
54%
32.17
1.77
56.94
105.45
Sertraline (SSRI)
49%
32.25
0.75
24.19
49.36
Paroxetine (SRRI)
23%
32.7
1.02
33.35
145.02
91
According to the depression treatment cost-effectiveness analysis, the
most cost-effective active substances for depression treatment are amitriptyline for TCA class, venlafaxine from Other class and sertraline from SSRI
class. As it was already pointed out, venlafaxine is not used after its modified release form entered the market; that is why for the future depression
treatment cost rationalization analysis bupropion from Other class was selected.
Setting the reference price of ADs in different classes according to their
cost-effectiveness (amitriptyline 0.22 LTL/DDD among TCAs, sertraline
0.75 LTL /DDD among SSRIs and bupropion 1.78 LTL /DDD among other
ADs), the total savings estimated respectively 258,687 LTL for TCAs,
4,325,935 LTL for SSRIs and 1,988,255 LTL for other ADs (Table 3.4.3).
The total savings for the year 2009 would be 6,572,877 LTL.
Table 3.4.3. Pharmacoeconomic calculations by using the cost-effectiveness
analysis for antidepressant expenditures in 2009
DDD
Price/DDD
(LTL)
Costs
(LTL)
Reference
price/
DDD
(LTL)
Costs using
reference
price (LTL)
Amitriptyline
1,274,683
0.22
281,420
0.22
281,420
Clomipramine
66,967
1.70
114,156
0.22
14,784
0.22
0
0.22
30
0.22
0
Active substance
TCAs
Dosulepin
Imipramine
138
0.33
45
Amitriptyline
(modif.)
Nortriptyline
55,767
0.62
34,521
0.22
12,311
Doxepin
86,258
1.81
156,136
0.22
19,043
Total costs:
586,279
Saved by:
258,687
327,591
SSRIs
Sertraline
4,301,076
0.75
3,237,846
0.75
3,237,846
Paroxetine
2,420,835
1.02
2,478,920
0.75
1,822,402
92
Table 3.4.3. Continued
Active
substance
262,537
Reference
price/ DDD
(LTL)
0.46
Costs using
reference
price (LTL)
260,080
DDD
Price/DDD
(LTL)
Costs (LTL)
Fluoxetine
565,392
0.46
Citalopram
981,652
0.84
826,839
0.75
738,987
Escitalopram
3,074,548
1.77
5,444,599
0.75
2,314,517
Fluvoxamine
303,695
2.23
677,647
0.75
228,621
Total costs:
12,928,388
Saved by:
4,325,935
8,602,453
Other ADs
Mirtazapine
2,952,600
1.17
3,467,042
1.17
3,467,042
Bupropion
445,680
1.78
791,930
1.78
791,930
Mianserin
100
2.76
276
1.78
177
Agomelatine
88,004
1.48
130,305
1.48
130,305
Trazodone
66,170
3.81
251,892
1.78
117,577
Tianeptine
498,010
2.13
1,059,177
1.78
884,916
819,513
1.68
1,372,843
1.68
1,372,843
933,520
3.58
3,338,356
1.78
1,658,775
Total costs:
Saved by:
10,411,825
1,988,255
Venlafaxine
(modif.)
Duloxetine
8,423,570
The total savings during the research period (2004 to 2009) by setting the
reference price according to the medicine effectiveness and safety within
different AD classes would reach 46.3 mln. LTL (Table 3.4.4).
Table 3.4.4. Total saving forecast during the research period (2004 to
2009) by setting the reference price
Year
Total costs (LTL)
Costs using reference
price
Savings (LTL)
2004
22,543,195
18,469,607
1,737,084
2005
21,010,116
14,815,575
6,194,541
2006
36,773,717
15,350,046
21,423,671
2007
18,076,615
16,531,503
1,545,112
2008
26,758,587
17,900,592
8,857,996
2009
23,926,492
17,353,615
6,572,877
Total:
149,088,723
100,420,937
46,331,282
93
According to antidepressants use rationalizing setting the reference price
by medicines cost-effectiveness and economic evaluation, the total pharmacoeconomic saving results reach 31 per cent of all costs.
Since the early 1970s, most industrialized countries began creating
mechanisms aimed at containing pharmaceutical costs in the face of rising
prices and limited health service budgets. Price control is one of the oldest
and still more widespread forms of pharmaceutical cost-containment, but
even in the narrower context of direct medicine price control, there are a
large number of modalities and variations in the way price regulation is designed and implemented.
In recent years, many countries have introduced the practice of External
Reference Pricing (ERP) where the nationally regulated price is derived
from or somehow related to those in a range of reference countries.
The use of ERP appears to be more justified for those countries which
have a limited technical capacity or resources required for more complex
price regulation mechanisms such as pharmacoeconomic analysis.
For example, the German reference pricing system defines a referent
price for groups of pharmaceuticals. Pharmaceuticals are grouped according
to certain criteria by the Federal Joint Committee. To make different active
ingredients comparable, the so-called reference values are defined. Compared to other instruments of price-regulation, reference pricing seems to be
a good alternative to controlled pharmaceutical prices since rationing is kept
as little as possible.
The high price of medicines is a major concern for policy-makers, insurers and patients. High prices can make medicines unaffordable, compromising equitable access to them, and threaten the financial sustainability of public health systems. This applies especially to new highly priced medicines
which are protected by exclusive market rights such as patents and data protection.
Taking in account the total expenses on medicament depression treatment
in Lithuania and the potential rationalization percentages based on reference
price setting in this research (31 per cent) and rationalization percentages
based on the promotion of generic medicines in the market (9 per cent), approximate savings in Lithuania would have reached 57.2 mln. LTL during
the years 2004 through 2009.
On the grounds of the results of this research, the following recommendations for medicament depression treatment rationalization in Lithuania are
provided:
1. To ensure effective monitoring and management of medicament depression treatment according to the selected method of assessment of antide94
pressant efficiency indicator, namely, the depression relapse recorded as
code F33.
2. To improve the information system SVEIDRA database management
program in order to prevent mistakes regarding illness registration codes
and not recommended for certain disease medicines reimbursement.
3. To introduce innovations in Lithuania by following the positive experience of generic policy and practice in foreign countries.
95
CONCLUSIONS
1. A comparative analysis of the antidepressant consumption in the years
2004 to 2009 in Lithuania showed that the total consumption of antidepressants in Lithuania was increasing due to the consumption growth of reimbursable antidepressant.
2. Depression diagnosis and treatment effectiveness analysis showed that in
52 per cent of studied cases, the depression diagnosis was defined by the
wrong code. Depression treatment in Lithuania is not efficient enough as
depression relapse rates continuously increase (in the years 2004 to 2009,
the rates increased by 27 per cent).
3. The costs of antidepressants in the years 2004 to 2009 in Lithuania increased by 6 per cent. A positive relationship was found between the proliferation of generic antidepressants in the market and costs reduction during
the relevant years.
4. According to the cost-effectiveness analysis and the total costs of antidepressants in Lithuania, the following potential ways of costs rationalization
were suggested: to introduce the reference pricing rates and to encourage
more active substitution of ethical antidepressants by generic medicine. It is
estimated that the introduction of the suggested tools in the years 2004 to
2009 would have saved 40 per cent of the total antidepressant costs in Lithuania.
96
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SCIENTIFIC PUBLICATIONS
1. Kavaliauskienė L, Pečiūra R, Adomaitienė V, Masteikova R. Depression relapse and antidepressants consumption in quality of life aspect.
Ceska a Slovenska Farmacie, 2010; 59, 199-204.
2. Kavaliauskienė L, Pečiūra R, Adomaitienė V, Masteikova R. Improving the quality and cost-effectiveness of depression treatment. Ceska a
Slovenska Farmacie, 2011 (accepted).
3. Kavaliauskienė L, Pečiūra R, Adomaitienė V. Medication rationality
in treating depression. Acta Medica Lituanica, 2011 Vol. 18. No. 2. P.
92–96.
4. Kavaliauskienė L, Pečiūra R, Adomaitienė V. Trends in depression
diagnoses and antidepressants consumption in Lithuania in 20042009. Acta Medica Lituanica, 2011. Vol. 18. No. 1, 17–22.
Posters and speech presentations, congresses, conferences:
1. L. Kavaliauskiene, V. Adomaitiene, R. Peciura. "Cost-effectiveness in
the pharmacoeconomics of depression treatment", The Journal of the
European College of Neuropsychopharmacology, Volume 19 (2009)
Supplement 2, Page S150.
2. Kavaliauskienė L, Pečiūra R, Adomaitienė V. Cost effectiveness in
the pharmacoeconomics of depression treatment. The International
Conference on Pharmaceutical Sciences and Pharmacy Practice dedicated to 225th Anniversary of Pharmaceutical education in Lithuania
in connection with 25th Congress of Lithuanian Pharmaceutical Association. Main Theme: Bringing Innovations into Pharmacy: Abstract
book: October 15-17, 2010 Kaunas, Lithuania. p. 49-52.
3. Kavaliauskienė L, Pečiūra R, Adomaitienė V. Trends in depression
diagnoses and antidepressants consumption in Lithuania in 2004–
2009. European neuropsychopharmacology: Papers of the 11th ECNP
Regional Meeting: 14-16 April 2011 St. Petersburg, Russia: Elsevier.
ISSN 0924-977X. 20011, vol. 21, suppl. 2, p. S137.
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