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Received: 22 January 2016 | 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 | 209 210 | SHAW 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 SHAW | ET AL. 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: | 212 SHAW 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 SHAW | 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). 214 | SHAW 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 SHAW | ET AL. 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. 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