Download Comm Dent Oral Epid - 2017 - Shaw - Comparing human resource planning models in dentistry A case study using Canadian

Received: 22 January 2016
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Accepted: 23 November 2016
DOI: 10.1111/cdoe.12277
ORIGINAL ARTICLE
Comparing human resource planning models in dentistry:
A case study using Canadian Armed Forces dental clinics
Jodi L. Shaw1 | Julie W. Farmer1 | Peter C. Coyte2 | Herenia P. Lawrence1
1
The Discipline of Dental Public Health,
Faculty of Dentistry, University of Toronto,
Toronto, Ontario, Canada
Abstract
Objectives: To compare two methods of allocating general dentists to Canadian
2
The Institute of Health Policy,
Management and Evaluation, University of
Toronto, Toronto, Ontario, Canada
Correspondence
Jodi L. Shaw, The Discipline of Dental Public
Health, Faculty of Dentistry, University of
Toronto, Toronto, Ontario, Canada.
Email: [email protected]
Armed Forces (CAF) dental detachments: a dentist-to-population ratio model and a
needs-based model.
Methods: Data obtained from CAF sources were analysed to compare models.
Times assigned to treatment plan procedures were used as a proxy for treatment
needs. Full-time equivalents (FTEs) were used as an indicator for the number of
dentists allocated to each detachment. FTE values were adjusted for military dentists to account for time spent on compulsory nonclinical duties. The paired-samples
t test was used to assess differences between the models for all clinics (dental
detachments) and by clinic size.
Results: The dentist-to-population ratio model for the CAF population (n=68 183)
estimated an allocation of 83.25 FTE general dentists to CAF dental detachments.
Based on a systematic sample of the CAF population (n=2226), the needs-based
model estimated the requirement for 64.71 FTE general dentists. The average difference between models was 0.71 FTE (SE=0.273), which was statistically significant
(P=0.015). In terms of differences by clinic size, differences were more pronounced
in clinics serving more than 4000 CAF personnel (2.63 FTEs, SE=0.613, P=0.008).
Conclusions: The findings reveal differences between estimation models of <1 FTE,
with higher estimates produced from the dentist-to-population ratio model. A larger
difference was found in clinics with larger populations. The perceived overestimation of dental human resource requirements suggests that changing to a needsbased model may result in cost savings.
KEYWORDS
Canadian Armed Forces, distribution, human resources, manpower, military, personnel, supply,
workforce
1 | INTRODUCTION
essential that decisions are relevant to the financing and organization
of its oral healthcare systems, population distribution and needs.
Human resource planning in dentistry is the process of determining
The Royal Canadian Dental Corps (RCDC; formerly the Canadian
the appropriate number and allocation of dental personnel able to
Forces Dental Services [CFDS]) consists of 26 full-time dental clinics
deliver oral healthcare services to achieve an established goal or
(known as “dental detachments”) and 18 satellite clinics (full- or part-
desired outcome.1,2 From a payer perspective, efficient allocation of
time) located on Canadian Armed Forces (CAF) bases dispersed
resources assists in minimizing unnecessary costs. In addition, it is
throughout Canada, with two of the dental detachments located in
Community Dent Oral Epidemiol. 2017;45:209–215
wileyonlinelibrary.com/journal/cdoe
© 2017 John Wiley & Sons A/S.
Published by John Wiley & Sons Ltd
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Europe (Belgium and Germany). The RCDC is responsible for the
ET AL.
ratio model were derived from established CAF policy documents
provision of oral healthcare services to approximately 68 000 Regu-
and existing staffing models. FTEs for the needs-based model were
lar Force CAF members between 18 and 60 years of age.3 CAF per-
calculated using secondary oral health surveillance data from a
sonnel typically work on a base where a dental clinic is located and
cross-sectional sample of CAF personnel (n=2226) collected in 2014.
reside either on or within a certain geographical distance of the
To ensure adequate statistical power, a sample size calculation was
base. This access to care, coupled with the requirement for CAF per-
performed using the formula for a two-sided paired t test and a lib-
sonnel to visit the dentist annually, is a distinct advantage when allo-
eral hypothesized fourfold standard deviation of two, expecting to
cating human resources in a CAF context, as the challenges
achieve an effect size of at least 0.5 FTE difference between the
associated with widely dispersed civilian patient populations and
two models, with 80% power at the 0.05 significance level. As the
financial barriers are irrelevant.
CAF employs part-time and full-time clinical dentists, a 0.5 FTE dif-
The CAF uses a dentist-to-population ratio model to allocate
general practitioner dentists to each of their dental detachments.
ference was used. The calculation yielded a minimum sample size of
502 participants, which was met with the large data set available.
The model reflects the ratio of full-time equivalent dentists to the
population served. The main advantages of this model are that it is
easy to understand and it involves neither complex data nor compli-
2.2 | Setting
cated analysis.2,4 However, it is often criticized for its subjective and
As mentioned above, the RCDC uses a dentist-to-population ratio
arbitrary derivation of the standard ratio and its lack of consideration
approach for the allocation of general dentists. While there is no
of need.2,4,5 As this model does not consider population-specific
published information that discusses the CAF’s staffing arrangement,
dental treatment needs, such variations may result in a greater or
there is a policy guidance document, CFDS RESTORE - An Establish-
lesser demand for dentists.
ment Review of the Canadian Forces Dental Services, which provides
Internationally, dental human resource requirements have been
detailed information on the current construct, but limited insight on
estimated through the dentist-to-population ratio,6 demand-based7-9
how it came into existence.14 This document also describes the five
10,11
and needs-based models.
The needs-based model requires some
form of treatment needs data, such as normative or sociodental
different types of RCDC dental clinics, which are categorized from I
to V based on the total patient population served (Table 1).
need, in order for it to be operationalized; however, estimates pro-
Military and civilian dental care providers working in CAF dental
duced from these approaches are sensitive to the choice of need
clinics use the Canadian Forces Dental Care Program (CFDCP) as
assessed.10 Sociodental needs have been preferred over normative
their guiding document for the delivery of dental care in the CAF.
needs as normative needs do not consider health behaviour and
The CFDCP defines the normative needs of the CAF population and
patient compliance, although both affect utilization of dental ser-
details the conditions that must be met to justify diagnosis and
vices.12 Given that Regular Force CAF personnel are required to
treatment plan decisions. The CFDCP also stipulates the standard of
have an annual dental examination in order to assess whether they
knowledge and practice expected of dentists, both military and civil-
are dentally fit for deployment and to establish a treatment plan for
ian, working in CAF dental clinics. This, coupled with the training
13
a normative
dentists receive from the CAF, helps to ensure that the provision of
needs-based model may yield more accurate estimates of dental
treatment is consistent with the CFDCP parameters, reduces subjec-
human resource requirements in this context.
tivity in treatment planning philosophies across providers and
the provision of care, when treatment is needed,
At present, it is not known whether the current dental resource
enables comparisons between RCDC providers and clinics. Given this
allocation model used for CAF dental detachments allocates an
context, normative needs based on clinical judgment are considered
appropriate number of general practitioner dentists to meet the
a realistic and appropriate approach to needs assessment.
treatment needs of the CAF population. In addition, no study has
compared estimates between different dental human resource allocation methods. Therefore, the purpose of this study was to com-
2.3 | Dentist-to-population ratio model
pare the number of dentists currently allocated to CAF dental
Two policy documents were used to populate the dentist-to-popula-
detachments using the dentist-to-population ratio model to the num-
tion ratio model for each provider type: CFDS RESTORE and the
ber of dentists that would be allocated using a needs-based model.
2014 Position Charter.15 The staffing model and dentist-to-population
ratios proposed in CFDS RESTORE were used to develop the 2014
2 | METHODS
2.1 | Study design
Position Charter.14,15 The latter is a database that enumerates all
positions associated with each CAF dental detachment, as well as a
crude FTE count for each position.15 The RCDC assigns patient loads
to civilian and military general dentists and military advanced general
This study compares two dental human resource planning models for
dentists (AGDs) based on provider-to-patient ratios. There are
general dentistry procedures using the CAF population: the dentist-
also military oral and maxillofacial surgeons, periodontists and
to-population ratio model and the normative needs-based model.
prosthodontists working in some RCDC clinics. As these specialists
Full-time equivalent (FTE) estimates for the dentist-to-population
provide treatment based on referrals from general dentists, they are
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211
T A B L E 1 Canadian Armed Forces clinic types
Clinic type
I
Number of clinics
Population
II
III
IV
7
<1000
<1000
1000-2000
2000-4000
>4000
DH
GD
DH
GD
DH
GD
DH
GD
AGD
Specialists
Stand-alone
Stand-alone
Stand-alone
Regional
specialty centre
Providers
Clinic operations
Satellite
Patient demographics
No difference
9
V
18
4
6
DH, dental hygienist; GD, general dentist; AGD, advanced general dentist.
not assigned patient loads. The dentist-to-population ratios for civil-
assigned to the respective detachment who had not already under-
ian and military general dentists are 1:800 and 1:600, respectively.
gone an annual dental examination in calendar year 2014. Appoint-
For military personnel in command positions, patient loads are
ments during this period may have also been assigned to patients
reduced to account for compulsory leadership-related nonclinical
who contacted the detachment to book one.
duties required in these roles.14,15 As AGDs devote treatment time
Two other databases were used to populate the needs-based
to a combination of primary dental care and advanced-level proce-
model. The Dental Information System (DentIS) maintains a record
dures based primarily on referrals from general dentists, they are
of all dental treatment that a service member receives in CAF dental
assigned a lower patient load, resulting in a dentist-to-population
clinics throughout his/her military career and also provides informa-
ratio of 1:300 for AGDs.
tion on patient-specific oral health measures such as caries risk and
In order to compare estimates between allocation models, ratios
periodontal status.16,17 DentIS permitted the selection of patients by
were converted to FTEs, which represent the standard measure of
procedure code and date, which built the research database to
hours worked by a full-time dentist. Understanding that civilian den-
include patients who had an annual examination during the 3-week
tists work more clinical hours than military dentists, one standardized
surveillance period. The final database used was the Human
FTE was established as 1229.5 hours of routine clinical dentistry per
Resource Management System (HRMS), the application used to track
year provided by civilian dentists. To produce FTE estimates for mili-
information pertaining to personnel management of CAF members.18
tary dentists and military dentists in leadership positions, the number
Data from CFHIS, DentIS and HRMS were deterministically linked
of clinical hours was adjusted by dividing military FTEs by the stan-
by unique military service identifiers and anonymized for analyses.
dardized (ie, civilian) value (950.0/1229.5); the resulting 0.773 repre-
To calculate estimates from the needs-based model, the total
sents one military FTE adjusted to one standardized FTE. In addition,
treatment time (hours) per base required for general dentistry proce-
to account for variations in clinical hours worked by military dentists
dures was calculated from the treatment plans of the sample popula-
in leadership positions, nonclinical time was subtracted from the FTE
tion using the formula,
value and then calculated as 0.232-0.696 FTE depending on rank
and position.
total base treatment time (hours) ¼
ðA þ BÞ
Base sample size
Total base patient population
2.4 | Needs-based model
The main database used for the needs-based model was the Cana-
where A represents the total hours assigned for treatment in annual
dian Forces Health Information System (CFHIS). This database con-
treatment plans created during the surveillance period and B refers
tains electronic health records, including annual dental treatment
to the total hours used to perform annual examinations over surveil-
plans, for CAF personnel. As part of an RCDC strategic initiative to
lance period (number of patients seen over the surveillance per-
gather population surveillance information, treatment plan data
iod91/3 hour per examination).
recorded during routine annual examinations that took place at the
The FTEs for the needs-based model per base were then derived
26 CAF dental detachments over a continuous 3-week period some-
by dividing the total treatment time (hours) by the annual treatment
time between 5 May 2014 and 10 October 2014 were extracted
time allocated to one FTE dentist. Given the military context, the com-
from CFHIS and formed the database for this study. The 3-week
mand positions at each detachment, namely the Dental Detachment
surveillance block for each detachment was determined by the Den-
Commander (DDC) and Dental Detachment Second in Command
tal Detachment Commander. To fill appointments, administrative
(2IC), must be filled by uniformed personnel. As such, the yearly chair-
staff contacted patients in alphabetical order from a list of personnel
side time associated with these positions was adjusted accordingly:
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No. FTE per base ¼
ET AL.
½ðTotal base tx time (hours)Þ ðDDC+2IC gen dentistry clinic time (hours)Þ
þ ðDDC+2IC gen dentistry FTEsÞ
Annual tx time by one FTE dentist (hours)
Regardless of the total number of patients served by a dental
available treatment time exceeds that required to meet the needs of
detachment, there must be a dentist available to provide clinical
the base population. In these cases, subtracting the chairside time
care. On some bases, given the patient load or the treatment needs,
for the Dental Detachment Commander, and the Dental Detach-
the detachment would ideally be staffed with one military dentist
ment Second in Command where applicable, from the total treat-
and a part-time civilian dentist. This is not always possible, however,
ment needs time yields a negative value. For the purpose of
as it can be difficult to find civilian dentists willing to work part-time
subsequent calculations, the negative time values were replaced
hours, especially in clinics located in remote regions. Consequently,
with zero, meaning that no dentist besides the military dentist(s)
two military dentists would be assigned despite that their combined
who hold command positions are required using the needs-based
T A B L E 2 Profile comparison: sample population and general Canadian Armed Forces (CAF) population
CAF (analysis sample)
Characteristics
% (95% CI)
CAF (Regular force population)
n
% (95% CI)
P-valuea
n
Age (y)
18-19
1.2 (0.8-1.6)
27
0.6 (0.5-0.7)
404
20-29
31.0 (29.1-32.9)
703
27.7 (27.4-28.0)
18 886
30-39
32.9 (31.0-34.8)
745
34.9 (34.5-35.3)
23 826
40-49
24.5 (22.7-26.3)
555
24.1 (23.8-24.4)
16 429
50-59
10.4 (9.1-11.7)
236
12.5 (12.3-12.7)
8491
Female
15.6 (14.1-17.1)
353
15.2 (14.9-15.5)
10 366
Male
84.4 (82.9-85.9)
1913
84.8 (84.5-85.1)
57 817
Officer
21.2 (19.5-22.9)
484
24.9 (24.6-25.2)
17 002
NCM
78.4 (76.7-80.1)
1782
75.1 (74.8-75.4)
51 181
Army
51.0 (48.9-53.1)
1155
53.6 (53.2-54.0)
36 551
Air force
33.3 (31.4--35.2)
754
29.1 (28.8-29.4)
19 845
Navy
51.0 (48.9-53.1)
1155
17.3 (17.0-17.6)
11 787
English
74.6 (72.8-76.4)
1690
73.1 (72.8-73.4)
49 855
French
25.4 (23.6-27.2)
576
26.9 (26.6-27.2)
18 328
<0.001
Sex
0.625
Rank class
<0.001
Element
<0.001
First official language
0.122
Periodontal screening and recording
0
0.2 (0.0-0.4)
5
70
0.2 (0.2-0.2)
3.6 (3.5-3.7)
136
1
3.1 (2.4-3.8)
2
61.3 (59.3-63.3)
1385
62.9 (62.5-63.3)
42 861
3
29.6 (27.7-31.5)
668
25.5 (25.2-25.8)
17 398
4
5.8 (4.8-6.8)
130
5.2 (5.0-5.4)
Low
75.5 (73.7-77.3)
1710
78.0 (77.7-78.3)
53 167
Moderate
17.8 (16.2-19.4)
404
13.8 (13.5-14.1)
9383
6.1 (5.1-7.1)
139
2.9 (2.8-3.0)
1957
No
77.2 (75.5-78.9)
1750
76.1 (75.8-76.4)
51 857
Yes
22.2 (20.5-23.9)
504
19.2 (18.9-19.5)
13 066
0.003
2447
3539
Caries risk
High
<0.001
Tobacco use
CI, confidence interval.
P-values derived from chi-squared tests.
a
0.009
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ET AL.
model. The allocation of military dentists to dental detachments that
T A B L E 3 Full-time equivalents by clinic type and model
support a patient population less than the maximum patient load of
the dentist(s) will result in an overestimation of FTEs for these
detachments.
Total FTE general dentists
Clinic
typea
CAF base
II
Casteau
0.70
0.70
0.00
Gander
0.70
0.70
0.00
2.5 | Analysis
The first step in the analytical approach was to determine the external validity of the surveillance sample for the CAF population. This
was accomplished by using the CFHIS and HRMS data to calculate
the 95% confidence intervals for several demographic characteristics
and clinical measures of the sample and the overall CAF population.
Comparisons were made for age, sex, rank class (officer or noncom-
III
Dentist-topopulation
Needsbased
Difference
Geilenkirchen
0.70
0.70
0.00
Moose Jaw
0.70
0.93
0.23
North Bay
0.70
0.70
0.00
St. John’s
0.70
0.70
0.00
Toronto
1.50
0.87
0.63
Bagotville
1.31
1.31
0.00
missioned member), element (army, navy or air force), first official
Cold Lake
1.70
1.66
0.04
language (English or French), periodontal screening and recording
Comox
2.11
1.31
0.80
score, caries risk and tobacco use, and the differences were tested
Greenwood
2.11
1.40
0.71
using chi-squared tests.
Longue-Pointe
1.50
0.93
0.57
Subsequent analyses were performed at the base and clinic
Saint-Jean
2.86
1.79
1.07
type levels using the paired-samples t test to examine whether
Shilo
1.31
1.31
0.00
there were differences in dentist allocation between the dentist-
Wainwright
0.70
1.68
0.98
Winnipeg
2.11
1.31
0.80
Borden
4.07
4.45
0.38
Gagetown
5.07
6.15
1.08
Kingston
4.47
2.89
1.58
to-population ratio model and the needs-based model. Nonparametric tests were also performed to confirm differences between
IV
the allocation models using the Wilcoxon signed-ranked test. The
level of FTE agreement between the two models was assessed
using the intraclass correlation coefficient and the Bland-Altman
plot. Statistical tests were carried out using the IBM Statistical
19
Package for the Social Sciences for Windows, version 22.0.
All
V
Trenton
3.50
4.24
0.74
Edmonton
6.04
3.70
2.34
statistical tests were two-tailed, and the significance level was set
Esquimalt
5.44
3.64
1.80
at P<0.05.
Halifax
10.59
5.28
5.31
Ottawa
10.21
6.84
3.37
5.99
4.36
1.63
6.46
5.16
1.30
83.25
64.71
Petawawa
3 | RESULTS
Valcartier
SUM
The 3-week surveillance period generated a sample of 2266 patients,
namely 3.31% of the overall CAF population, which was 68 183 at
the time of the surveillance initiative. The sample population and the
overall CAF population were compared on several demographic characteristics (Table 2). There were statistically significant differences
between the sample and general CAF population for some of the
213
AVERAGE (SE)
3.20 (0.56)
2.49 (0.38)
–
0.71 (0.27)b
CAF, Canadian Armed Forces; FTE, full-time equivalents; SE, standard
error.
a
Population supported by clinic type: II (<1000); III (1000-2000); IV
(2000-4000); V (>4000).
b
Paired t test P-value=0.015; Wilcoxon signed-rank test P-value=0.014.
characteristics measured.
The total number of FTE general dentists currently allocated to
both parametric (P=0.015) and nonparametric methods (P=0.014).
CAF dental detachments using the dentist-to-population ratio model
The intraclass correlation coefficient was 0.807, suggesting that
is 83.25, with a range of 0.70-10.59 FTEs per detachment. When
80.7% of the total variability in FTEs was between-base variability
the needs-based model was applied, the general dentistry workforce
and not between-model variability.
requirements were 64.71 FTEs (Table 3).
The Bland-Altman plot revealed that the 95% limits of agreement
At the detachment level, the average difference between the
between the two human resource planning methods ranged from
two models was 0.71 FTE (Table 3). Fourteen of the 26 detachments
2.01 to 3.44 and that the disagreement increased as the means of
(53.8%) allocated more dentists under the dentist-to-population ratio
the two models grew higher at larger FTEs (Figure 1).
model, while the opposite was true for five detachments (19.2%).
An analysis based on clinic type showed a requirement for on
The remaining seven detachments (26.9%) showed no difference in
average 2.63 more FTE general dentists for Type V clinics using the
number of dentists required between models. The overall difference
dentist-to-population ratio model than when the needs-based model
between the two allocation models was statistically significant using
was used, which was statistically significant (Table 4).
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ET AL.
age group, and the confidence interval was (0.5-0.7). This resulted in
a 0.6% difference between the two-point estimates and 0.1%
between the two confidence intervals. In other words, after tests of
comparison, these differences were not clinically important and were
indeed reflective of the large sample size. As such, there is likely no
substantive threat of selection bias to the generalizability of the findings to the entire CAF population.
In the analyses, 14 of the 26 dental detachments allocated more
FTE general dentists under the current dentist-to-population ratio
model than what would be allocated using a needs-based model. At
the detachment level, the average difference between the two models
was 0.71 FTEs. Although the dentist-to-population ratio model
appears methodologically easier than the treatment needs approach,
there are many factors within this model that can alter final workforce
estimates. Coyte and colleagues discuss that provider characteristics,
such as age and sex, may affect productivity, thereby impacting the
F I G U R E 1 Bland-Altman plot of the differences between
allocation models for general dentists (n=26 CAF dental
detachments)
number of providers required to support a population.20 As provider
characteristics were not included in the data set, assigning different
chairside hours to specific positions based on varying job requirements helped account for potential differences in productivity.
T A B L E 4 Differences in allocation models for general dentists by
clinic type
Interestingly, the analysis by clinic type showed that the dentistto-population ratio model may overestimate the number of FTEs
required at the largest clinics, as a notably larger number of dentists
Allocation model (FTE)
were required for Type V clinics under the current model. This sug-
Clinic
typea
Number
Dentist-topopulation
(SE)
II
7
0.81 (0.11)
0.76 (0.04)
III
9
1.75 (0.21)
IV
4
V
6
Needsbased (SE)
Difference
(SE)
gests that the normative needs for general dentistry do not increase
P-valueb,c
proportionately with size of the population. A mean difference of
0.06 (0.10)
0.591
2.67 FTE between models for Type V clinics suggest that implement-
1.41 (0.09)
0.33 (0.21)
0.152
ing a needs-based allocation model in the CAF context could result
4.28 (0.33)
4.43 (0.69)
0.16 (0.60)
0.812
in cost savings, as less dental health human resources would be
7.46 (0.94)
4.83 (0.49)
2.63 (0.61)
0.008
required in these clinics. However, Type V clinics should be examined individually, with consideration given to using the needs-based
FTE, full-time equivalent; SE, standard error.
a
Population supported by clinic type: II (<1000); III (1000-2000); IV
(2000-4000); V (>4000).
b
P-values derived from paired t tests.
c
The statistical significance was confirmed with Wilcoxon signed-rank
tests.
model for some or all locations.
Several recent international studies assessed dental workforce
requirements. Some used a health demand model,7-9 while others
de
ration dentaire internaapplied the World Health Organization-Fe
tionale model.21,22 Both models focused on needs determined either
by a provider’s clinical assessment or by trends in dental utilization.
4 | DISCUSSION
In addition, a more recent study used oral morbidity and sociodemographic data to estimate demand for future workforce supply in Ger-
Evaluating allocation methods for dental health human resources is
many.23 All studies emphasized the importance of patient-specific
essential for ensuring efficient and appropriate use of resources. This
treatment information in assessing human resource planning. How-
study compared two methods of allocating general dentists to CAF
ever, one of the principle drawbacks to employing the needs-based
dental detachments: a dentist-to-population ratio model and a
or demands-based model is that prevalence data are used to predict
needs-based model. It then compared dental health human resource
future disease, and thus future treatment needs or demands,2 yet dis-
estimates by the size of the respective clinic populations served, as
ease incidence is not constant over time. Although it is understood
represented by clinic type.
that providers may induce demand for dental care through treatment
The comparison between the sample and general populations
planning and that sociodemographic characteristics can influence
based on demographic characteristics revealed some statistically sig-
patients’ utilization patterns, the CAF has standards for the provision
nificant differences. These differences are a reflection of the very
of dental care, so treatment planning is less subjective to the treat-
large sample sizes and the resulting narrow confidence intervals
ment philosophies of individual providers.
around the point estimates. For example, in the sample population,
One of the drawbacks of a needs-based model is its reliance on a
1.2% were in the 18- to 19-year age group, with a 95% confidence
sufficient amount of reliable clinical data to render the findings mean-
interval of (0.8-1.2). In the general CAF population, 0.6% fell in this
ingful. In addition, a lack of interexaminer reliability may result in
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inconsistent disease diagnosis and treatment planning across a population.5 For example, using treatment times assigned by dentists as a
proxy to measure normative needs may result in different time allocation for similar procedures. In addition, assigning standardized times
to procedures entered into treatment plans would reduce the interexaminer variability. This, however, would not allow the flexibility in
treatment time that is needed to account for the variations in procedure difficulty and provider experience. Improvements to the validity
of the data could be gained by using more detailed information to
account for provider activities, specifically the precise number of days
and hours spent providing patient care versus doing nonclinical tasks.
Further precision would be gained by incorporating the treatment rendered by the military dentists who occupy full-time nonclinical positions, but who still provide patient care at CAF clinics on a
part-time basis. More granularity on treatment services provided by
CAF dental specialists and the impact this has on the two allocation
models would also prove helpful. Data on dentist productivity based
on demographic characteristics such as years since graduation, age,
sex and years of military service would also improve the analysis.
Finally, considering elements of the clinic model that may impact
productivity, such as number of dental chairs per provider and the
dentist-to-dental assistant ratio, could further refine the assessment.
The findings revealed a statistically significant difference in the
number of FTE general dentists allocated to CAF dental clinics under
the two dental health human resource planning models. These differences were more pronounced in clinics serving larger populations (Type
V clinics), which suggests that implementing a needs-based model may
result in cost savings. One should be cautious when interpreting findings for the dental detachments for which the sample size was small.
Extrapolating treatment needs to the base level using limited treatment
plan data could lead to an over- or underestimation of human
resources, depending on the oral health status of those sampled.
ACKNOWLEDGEMENTS
The authors would like to acknowledge the Royal Canadian Dental
Corps for their support of this research, most notably Major Constantine Batsos for his ideas and vision and Evlida Covrk for her
tremendous technical assistance.
REFERENCES
1. World Health Organization. Oral Health Care Systems: An International Collaborative Study Coordinated by WHO. London: Quintessence; 1985.
2. Goodman HS, Weyant RJ. Dental health personnel planning: a
review of the literature. J Public Health Dent. 1990;50:48–63.
3. National Defence and the Canadian Armed Forces. Government of
Canada. Frequently Asked Questions. http://www.forces.gc.ca/en/ab
out/faq.page#q12. Accessed November 11, 2016.
4. Born DO. Dental manpower planning and distribution: a survey of
the literature. Adv Sociodent Res. 1975;2:v–xxvi.
5. DeFriese GH, Barker BD. The status of dental manpower research.
J Dent Educ. 1983;47:728–737.
215
6. Barnard PD. Australian dentist: population ratios. Aust Dent J.
1965;10:233–238.
7. Health Workforce Australia. Oral Health, Supply and Demand Methodology. Adelaide: Health Workforce Australia; 2014.
8. NHS Education or Scotland. Dental Workforce Report. Scotland:
NHS Education for Scotland; 2012.
9. Robinson PG, Patrick A, Newton T. Modelling the dental workforce
supply in England. University of Sheffield; 2011.
10. Ab-Murat N, Sheiham A, Tsakos G, Watt R. Periodontal treatment
needs and workforce requirements: comparisons between the normative and sociodental approaches using different skill mix models.
Community Dent Oral Epidemiol. 2015;43:106–115.
11. Alves FN, de Andrade CL, Vettore MV. Planning oral health care
using the sociodental approach and the index of family living conditions: a cross-sectional study in Brazilian adolescents. BMC Res
Notes. 2015;8:588.
12. Sheiham A, Tsakos G. Oral health needs assessment. In: Pine CM,
Harris R, eds. Community Oral Health, 2nd edn. New Malden: Quintessence; 2007:59–77.
13. Royal Canadian Air Force. Annual Personnel Readiness Verification
Report. RCAF-EX2012B-03. 1 Canadian Air Division Orders; 2012.
14. Becker SA. CFDS RESTORE: an establishment review of the Canadian
Forces Dental Services. Ottawa: Canadian Forces Dental Services; 2007.
15. Anonymous. 1 Dental Unit. 2014 Position Charter. Ottawa: Royal
Canadian Dental Corps; 2014.
16. Groves RR. Dental fitness classification in the Canadian Forces. Mil
Med. 2008;173:18–22.
17. Batsos C. Dental Treatment Workload and Cost of Newly Enrolled
Personnel in the Canadian Forces. Toronto: University of Toronto;
2010.
18. National Defence and the Canadian Armed Forces. DAOD 5050-1,
Canadian Forces Personnel Records of the Director General Military
Careers and the Director Human Resources Information Management, and Service Estate Records of the Judge Advocate General.
Government of Canada; 2013.
19. IBM Corp. IBM SPSS Statistics for Windows, Version 22.0. Armonk,
NY: IBM Corp; 2013.
20. Coyte PC, Catz M, Stricker M. Distribution of physicians in
Ontario. Where are there too few or too many family physicians
and general practitioners? Can Fam Physician. 1997;43:677–683,
733.
21. Bourgeois D, Leclercq MH, Barmes DE, Dieudonne B. The application of the theoretical model WHO/FDI planning system to an
industrialised country: France. Int Dent J. 1993;43:50–58.
22. Doughan B, Kassak K, Bourgeois D. Planning dental manpower in
Lebanon: scenarios for the year 2015. East Mediterr Health J.
2005;11:943–951.
23. J€
ager R, Berg N, Hoffmann W, Jordan RA, Schwendicke F. Estimating future dental services’ demand and supply: a model for
Northern Germany. Community Dent Oral Epidemiol. 2016;44:169–
179.
How to cite this article: Shaw JL, Farmer JW, Coyte PC, and
Lawrence HP. Comparing human resource planning models in
dentistry: A case study using Canadian Armed Forces dental
clinics. Community Dent Oral Epidemiol. 2017;45:209–215.
doi:10.1111/cdoe.12277.