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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. 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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. 106