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A Review of Methods to Forecast Restorative Treatment Needs Sheila M. McGuire, DDS, DMSc Department of Dental Care Administration Harvard School of Dental Medicine 188 Longwood Avenue Boston, MA 021 15
Abstract Decision makers in the areas of health policy, resource allocation, and manpower requirements rely implicitly on estimations of treatment needs on which to base their forecasts. The less specific the treatment-needestimate, the less precise the forecast. In previous decades, high caries rates were so prevalent that the dental profession could risk having inexact projections because overwhelming need and demand existed. However, rampant decay is no longer a common occurrence. Decay levels are declining in our nation‘s children and adults have fewer missing teeth. Therefore, restorative treatment needs and patterns in adult populations are transforming at a time when health care costs are spiraling and budget analysts at all levels of government are questioning the priority of continued support of dental care, dental education, and dental research at current levels. The purpose of this review is to present the existing methods of forecasting restorative treatment needs and to postulate the development of a new method based on the collective experiences of practicing dentists nationwide, an empirical method, to convert surface-specificoral health status data to restorative treatment need information. Need estimations based on empirical data would more accurately reflect the actual distribution of services that practicing dentists provide. Key Words: dental caries, health services needs and demands, dental health surveys. Methods for estimating restorative treatment needs in adult populations have existed for decades. Although originally developed for use in populations of children, one of the first widely applied dental indices to estimate treatment need is still in use today for populations of all ages.The DMF index (decayed,missing, and filled index) was developed for survey purposes by Klein, Palmer, and Knutson over 50 years ago (1). Their revolutionary approach to studying past and present dental disease Funded by NIDR training grant #DEO7l51. Manuscript r e c e i v d 8/16/91; returned to author for revision:11 /5/91; accepted for publication: 2/20/92.
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patternsand future needed care entailed an examination of all surfacesof all teeth present in a child’smouth. Klein et al. recorded and counted the numbers of decayed, filled, and missing teeth for a population of grade-school children. Past experience with decay was measured by the F, or filled, component. For example, results of past experiencewere reported in termsof number and percent of children having one or more filled permanent teeth. Missing permanent teeth also inferred past experienceof decay. Klein et al. measured present experience with decay by the D, or decay, component. Decay levels were reported in terms of number and percent of children having one or more carious permanent teeth requiring fillings. Klein et al. also calculated the increment of new carious surfaces that were to be expected to arise annually in this population. From the data they collected on this population of schoolchildrenin Hagerstown,MD, Klein et al. estimated manpower shortages and suggested policy changes by this crude identificationof accumulated dental needs. In one survey, they identified the disease levels and immediately linked them to the effort needed to treat the decay by estimating time requirements to care for the diseased teeth. Inanageof rampant decay and little treatment, this uncomplicated and primitive index and its rudimentary levels of analysis were sophisticated enough to dramatize the large pool of restorative needs in populations of children. Unfortunately, this technique continues to be the basis for many currently used methods to estimate adult restorative need. Adult restorative needs are more complicated than schoolchildren’s needs. In general, more teeth are remaining in the mouths of the nation’s adult population than in previous decades, but these teeth continue to be plagued by primary and recurrent decay (2). An analysis only of decayed surfacesand decliningnumbers of missing teeth in the formulationof treatment needs will provide estimations that are too general. This review article will outline the ways previous forecastingmethodshave provided treatment need information in insufficient detail. Interpretation and extrapolation of results that are too simplistic could lead to an underestimatfalse sense of security about the effortneeded to treat today’s
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dental care needs--or an overestinrate. The DMF index might be sufficient in forwasting the simple operative needs of children, but its level of sophistication cannot reflect the effect of comorbid conditions-the existence of past or present caries experienceson adjacent surfaces of the same teeth or adjacent teeth. Health policy makers should be provided with specific information on the types and complexitiesof procedures needed to bring an adult population from a diseased to a healthy state, in order to base their decisions on clinical verities. Discussions among dental educators have already begun that would alter the emphasisof certain clinical skills, in order to equip new dentists better to deal with the emerging new reality of more teeth having a long history of caries experiences. However, the exact specifics involved in translating adult restorative needs are unknown and need to be quantified. One aspect of this new reality is the impact of demographic and disease changes in two particular cohorts in America: people over the age of 60 and people under the age of 35. The number of the United States population 65 or older has increased from 20.9 million in 1972 to 31.6 million in 1990, with a projected figure of 64.5 million in the year 2030. Adults are retaining more of their natural teeth (2), thus presenting new challenges and opportunities for the dental profession. We need a clearer understanding of the increased chairside time and skill spent on expanded operative, fixed, and removable prosthodontic procedures for older Americans. Specific and accurate forecasts are needed to meet these needs. Dentists will soon be treating the aging baby-boom generation, a cohort of adults who had 33 percent fewer cavities as children, necessitating a shift in dentists’ caseloads to offset the decreasing need of extensive restorative work in this age group. Klein et al. developed measures to quantify rampant decay in children. By articulatinga clear definition of the problem, an organized attempt to deal with the problem was then possible. Analogous to the index developed by Klein, the dental profession needs a new method of measurement to guide the resource and manpower strategies of the 1990s and into the 21st century. Specificallyquantifymg the restorative needs of the adult population will clarify the uncertainties of restorative needs just as the knowledge gained from the development of the DMF index helped our professionto decrease the rate of caries and treat this problem in children. As number of decayed and missing surfacesdecreases, estimations of treatment need must be more specific and exact-they need to be procedure-specific. Forecasting the treatment of decayed surfaces must incorporate the conditions of adjacent surfacesand teeth (heretoforereferred to as comorbid conditions) to amve at the correct level of complex proceduresneeded to treat the disease. For example, more time, effort,and money are needed to arrest the decay on the mesial of a first molar if a previous
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MODL restoration is present, than if the decay was a primary lesion. The implications are even more evident if the first molar was an abutment for a three-unit bridge. There have been many attempts to refine the accuracy of the forecasts since the development of the DMF index. In the present climate of declining dental caries prevalence (3),rising health care costs (4), suggestionsof curtailing operative dentistrycurricula in dental schools(5), and the closing of some dental schools (6), the dental profession should have access to the most exactingmethods of determining restorative treatment needs. Data exist on the oral health status of the adult population based on several recent nationally based surveys. The purpose of this review, therefore, is to present the existing methods of forecasting restorative treatment needs and to postulate the development of a more direct and empirical method for converting surface-specific oral health status data to restorative treatment need information. Review of Literature Previous attempts to assess and predict restorative treatment need in adult populations will be categorized and reviewed by four methodological approaches: surveys of oral health status, surveysof need for dental care, analyses of treatment records or insurance claim forms, and mathematical models used for projecting future needs. Surveys of Oral Health Status.The DMF index and its counterpart for primary teeth, the def index (3,are the most frequently applied indices of oral health status. Cohen and Jago(8)pointed out that they were developed as measurements of complete caries experience, depicting prior treatment as well as need for treatment. As stated earlier, the missing component,M, representspermanent teeth missing due to caries. (The clinical judgment of the examiner differentiatesmissing due to caries from missing due to orthodontic reasons or trauma.) Extraction is thus the prior treatment depicted and need for replacement is inferred.The presentday standard for the filled component, F, includes permanent or temporary restorations placed in permanent teeth due to caries only (2). The decayed, D, component includes both primary and recurrent decay. Two recent national surveys, the NIDR Oral Health Survey of Adults and Senior Citizens and the MANES, distinguish between primary and recurrent decay at the chairside,but collapse the two designations to form the D component. The same operational definitionsexist for primary teeth; the corresponding lower case letters d, m, and f are used. During the calculation of a person’s DMF score, a D ovemdes an F call. If a tooth has a filled surface, the scoring for that tooth is a D if decay is present anywhere on the tooth. The DMF indices and other typical survey methods tend to produce inherent underestimations of disease levels, thus affecting the resulting treatment-need esti-
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mations. According to McKendrick (9), “Neither DMF teeth nor DMF surfaces indices are comprehensive enough by themselves, since a tooth or surface may be both filled and decayed.” Prior to the mid-l970s, the M or missing call by definition was made only when the examiner could determine that the tooth was missingdue to caries. Therefore, Jackson (10) argued that the DMF index should not be used on adults over the age of 25 because periodontal conditions and memory lapses could alter the number of M calls. Since the late 1970s,no distinction has been made for teeth missing due to caries or periodontal disease, although there is a distinction for orthodontic vs nondisease reasons. Additionally, diagnostic radiographs are not used typically in field surveys, resulting in greater underestimation. Long et al. (11) adjusted for the underestimations from lack of radiographs in each dentition type. It is not total DMF that estimates current need for treatment, but usually some ratio of the D and/or M component to the total DMF. Survey results of need from indices based on the proportions of these components have been obtained by Jackson (101, Walsh (ll), and Gluck (13).Their results described need in broad general terms rather than as quantities of care required. One report assessing treatment needs of Finnish children (14) and another comparing needs and services of England, Wales, and the United States (15)used the filled tooth ratio (f/df and F/DMF) as their outcome measure of need. No specific need for restorative treatment estimations was given. The authors of the two papers d o not forecast counts of procedures needed. They characterize treatment needs in broad general terms; e.g., the high filled-to-teeth ratios found in their populations indicate “low treatment needs.” England and Wales’ National Health Services were meeting less of the needs than was the US system because the latter had a higher filled-toteeth ratio. Evidence of past dental treatment led the authors to conclude that marked improvement had been achieved in lowering future restorative needs. Such a low level of sophistication allows great leniency in the interpretation of results made by policy makers. A more detailed division of needs based on components of the DMF and def indices have been attempted by Burt, Doessel, and Long. Burt (16) predicted the amounts of one, two, and three or more surface amalgams, stainless steel crowns, and extractions needed from the decayed component of a survey conducted by Johnsonon a population of six-year-oldsin Alabama. He successfullytested the validity of his predictions against the results of treatment needs recorded chairside by Johnson. Doessel (17) also had the advantage of using a data base that consisted of both dental status and treatment needs data. He derived probabilities for the translation of the decayed component into restorative treatment needs in terms of one-, two-, and three-surface restorations or
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extractions for a population of six-year-old Australian children: Decayed Teeth = .41 (A) + .41 (B)+ .04(C) + .14 (D) A=one surface restoration B=two surface restoration C=three surface restoration D=extraction Theabove mathematical model, based on linear regression principles, estimates that for every 100 teeth given the score of ”D,” 41 will require a one-surface restoration, another 41 will need a twosurface restoration, and a three-surface restoration will be needed for four teeth. Extraction will be indicated for the remaining 14 teeth. As stated earlier, the treatment needs for children are much less complicated than for adults. Doessel’s methods are sufficient for this young population, if you believe in the treatment-need decisionsof his dental examiner. Thechoicesfor restorative materialsand thenumber of comorbid conditions of adjacent surfacesand teeth are limited in six-year-olds. Two attempts have been made to formulate a method to forecast treatment need based on retrospective analyses of oral health examinations and the subsequent treatments planned and delivered. Long et al. (11) developed tables of treatment need estimationbased on caries levels (D + d) and stages of dentition Ke., primary, early mixed, and late mixed) in a population of North Carolina children aged three to 12 who sought dental treatment at the University of North Carolina School of Dentistry. For example, Long et al. projected that 58.33 three-surface amalgams would be required in a population of 100 children with 4-6 surfaces of decay in their primary dentition. Treatment delivered reflected the clinical judgment of the school’s pedodontic faculty. Holloway et al. (18)went one step further. Ina longitudinal study of teeth in a population of English children, they analyzed the actual changes in filled and unfilled surfaces in order to predict subsequent treatment needs from the oral health status data. Treatment-need decisions were made by a slightly broader base of dentists than in the previous examples. These two approaches have not been tested on an adult population. All of the oral health status surveys discussed above used the clinical judgment of a dentist to assess oral health status and the subsequent treatment-need estimates for their respective populations. The use of the judgment of trained lay people to estimate restorative treatment needs has also been attempted. Conchie et al. (19) developed the Simplified Descriptive Survey in 1971 and trained lay people in the Canadian province of British Columbia to recognize and record the most severe type of carious lesion present in a subject. This score was compared to results of a def survey and the treatment plans made by a dentist. The authors reported that the association among the three variables can be used to predict needs of populations denied access to dental
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treatment. This example underscores the crudeness of measures to estimate treatment needs from oral health status survey data. Predictions of the restorative needsof a population from oral health status information is such a gross measure that a nonprofessional can do the estimation, especially in young and /or highdiseased populations. The DMF-indiceshave formed the basis for more intricate approaches, however. Klein et al. began the practice of expressing need in terms of time requirements. In the 1938 seminal article “Dental status and dental needs of elementary schoolchildren,” they made two assumptions: one hour would be required to care adequately for each defective permanent tooth surface and each dentist works a total of 1,800 hours per year. They forecast current and future restorative needs and formulated the subsequent manpower requirements to supply dental services for all permanent teeth of schoolchildren.In the early 1970s, Pickles and Conchie also predicted restorative need for children in terms of time requirements. For adults, Beck (20) discussed the limitations of the timeunit approach, namely, the uncertainty of the decision to replace a missing tooth and the variety of treatments representing a range of treatment times that can be indicated for a tooth that is designated ”D.” Beck attempted to overcome only the first problem by modifymg the DMF index. He suggested a separate designation be made to record missing teeth in need of replacement.This new information, together with the knowledge of the number of decayed teeth, more accurately predicted treatment time in his population of dental school patients. Pickles (21) found that a higher number of permanent teeth were diagnosed for treatment in a clinical setting than were diagnosed for treatment in the field. He found the relationship between clinical care diagnoses and survey findings for permanent teeth too weak to be of practical value in predicting service needs from DMF data. Spencer postulated that a dental epidemiologist’s perspective of caries experience and its relation to need for dental care may be at variance with a clinician’s perspective (22). For reliability reasons, the operational definitions for decay and treatment needs must necessarily be less refined for an epidemiologist. Restorative needs assessed during a survey would differ from restorative needs retrospectively translated from survey data by clinicians. Spenser called for further research to validate this translation of survey disease levels to restorative treatment needs based on clinicians’ decisions regarding treatment options. One concern in validating translation of survey data to treatment needs is the issue of clinician variability. Beck (23) acknowledged the fallacy of not accounting for differing treatment philosophies in the design of his pilot study to develop a treatment needs index based on surface-specific oral health status data; ”the unknown r e p
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resentativeness of the findings related to diagnosis and treatment practices is a potentially serious weakness.” This weakness, treatment decisions being made by one or two dentists not calibrated to any standard, is present and unrecognized in the designs of all studies by Klein, Burt, Doessel, and Conchie. No consideration is given to recognizing a range of restorative treatment possibilities. Long et al. recognized that there was no formal calibration of the many examiners used to determine treatments in their study, but they contended the results would nonetheless reflect the choices of their graduates in private practice. In all of the above situations, experts (dentists) assessed need by using their professional judgment to decide the one treatment necessary to restore the surveyed carious or missing tooth. Spencer (22) and Finkelstein et al. (24) termed this type of need as “normative need.” Normative need, the requirement for care as determined by an expert opinion, must be differentiated from perceived need, which is the general recognition that some type of care may be needed as determined by the patient or public. In addressing this issue, this review will put forward a more appropriate method to determine the requirement for care, one that would be based on the collective experiences of practicing dentists nationwide: empirical need. In reality, there is not perfect agreement in the dental profession on how best to restore any carious lesion or missing tooth. Translating oral health status data into restorative treatment needs based on empirical need would result in a distribution of appropriate treatments that reflects what actually occurs in the practice of dentistry. The fallacy described above by Beck would be eliminated or largely controlled using this approach to estimating empirical need for restorative treatments. Surveys of Need for Dental Care. A second methodological approach previously used to assess need for restorative treatment occurs at the time of the survey examination. In addition to the assessment of the oral health status of the tooth or surface under survey, the dental examiner also makes an assessment of the restorative need during the chairside field examination. This method of directly assessing need for restorative treatment was discussed in the previous section, but in a slightly different context. Burt, Doessel, and Long, the authors of several studies of small nonrepresentative samples, developed techniques to translate dental conditions into treatment need predictions. These studies were designed primarily to assess oral health status, although the direct assessment of restorative need was allowed to provide a standard by which to validate the translation techniques. In contrast, the surveys under discussion in this section are designed to assess restorative need directly at the time of the survey examination-the direct treatment plan approach. International and national agencies compile information on need for restorative treatment by directly assess-
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ing treatment needs during the field examination. All three editions of the World Health Organization's "Oral Health Surveys: Basic Methods" include the collectionof information on directly assessed need for restorations. These basic methods have been implemented by many counties to monitor progress in controllingoral diseases within and between countries. In the US, the National Center for Health Statistics (NCHS) gathered information on restorative treatment need as part of the first Health and Nutrition Examination Survey (NHANES I) conducted during 1971-74 (25). Directly assessing restorative treatment need at the time of the field examination has the advantage of quantifying specific treatments needs. As discussed previously, quantities of treatment needs obtained by Milen et al. (14) and Waldman (15) from their translations of oral health status data produced relative results in terms of "low" or "high" treatment needs. Counts of specific procedures are possible with the direct treatment plan approach.WHO is able to tally the number of the following procedures needed to restore the oral conditions found in an observed population: caries-arresting or sealant care one surface fillings two or more surface fillings crowns or bridge abutments bridge elements pulp care extraction need for other care. A count of a slightly different set of restorative procedures was possible from the NHANES I survey: one surface restorations (for primary and permanent teeth) two surface restorations (for primary and permanent teeth) three or more surface restorations (for primary and permanent teeth) crowns replacement of full dentures replacement of partial dentures replacement of bridges. Division of need by type of restorative material-i.e., composite,amalgam,gold-was not ascertainedin either the WHO or NHANES I surveys. As with the first methodologicalapproach-surveysof oral health status-the same critical problem exists with the use of surveys of need for dental care in forecasting restorative treatment needs. Normative restorative need was calculated in these direct treatment plan approaches. Dental examiners used their clinical judgment to determine the restorative procedure. The validity and reliability shortcomings previously outlined for the normative need approach led Schonfeld (26)and his North Carolina colleagues to make a "conscious decision to focus on dental conditions, which could be identified with a high
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degree of objectivity and consistencyfrom one examiner toanother, rather than to record needed treatment, which might be subject to considerable examiner variability" when they designed their study of dental disease in North Carolina. In addition, the National Institute for Dental Research chose to collect only information on dental conditions (caries, periodontal disease, oral cancer, etc.) in its national survey of oral health in US employed adults and seniors in 1985(2). No treatment need assessment was conducted. The US government, due to the shortcomings discussed, no longer uses the direct treatment plan approach. Analyses of Service or Treatment Records. Existing dental care programs, third-party carriers, or even private practitioners could be sources of information necessary to predict treatment needs in various populations. As described above, Long et al. used the documentation of surface-specificoral health status, treatments planned, and treatments delivered, obtained from the records of the University of North Carolina School of Dentistry Pedodontic Clinic, to predict treatment needs. To assist other dental health care providersinitiatingprograms for underprivileged children, Bader (27)analyzed data on treatment requirements found in the patient records for three populations of children in the Appalachian Mountain regions. As is the case for all studies of children with high decay levels and no past history of dental treatment, the translation of oral health status data into treatment needs is uncomplicated. Few comorbid conditions exist and the treatment optionsare minimal. Bader'sapproach was sufficient to get a rough estimateof the effort needed to initiate dental health programs for underprivileged children. Bader has not applied his methodologies to adult populations. As with the previous two methodological approaches, these analyses of service or treatment records to attempt to estimate treatment need were based on the examiningdentist's view, a normativeneedfor-treatment assessment. The American Dental Association's Bureau of Economic Research and Statistics has gathered data on need for dental care. In the 1%5 ADA survey of dental practices (28), a random sample of dentists was asked to estimate the need of dental care from the records of the patients in their practice. Due to the low response rate and findings that were determined to be biased (291, future surveys by the ADA of dental practice did not include the collectionof this need-for-treatmentdata. The ADA determined that a survey of a random sample of dentists to estimate treatment needs was the appropriate way to move away from a normative-need approach to an empirical-need approach in validly estimating treatment needs. As the ADA discovered, however, the problem of ascertaining treatment need estimations from a broad sample of dentists-empirical need-cannot be dealt with by asking them directly about their own patients. No attempt has yet been made to survey a broad
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sample of dentists regarding their restorative treatment decisions about patients not directly under their care. Mathematical Models Used to Project Future Needs. Models have been used extensively to project dental expenditures, an indirect way of forecasting treatment needs. For the purpose of this review, the discussion of mathematical projection models will only focus on their contributions to directly estimating restorative treatment needs. An assessment of their abilities to estimate such entities as dental expenditures, actuarial risks, etc., is beyond the scope of this review. Gillings et al. (30)reported that the two primary methods used to project national dental expenditures are econometric and actuarial. For example, the Feldstein and Roehrig econometric model determines the effectsof government policies on dental prices and incomes and the overall dental health of the population. The model uses ”visit type,” a method of grouping predefined services for a segment of the population, i.e., comprehensive care for adults. The ”lumping” of all types of restorations with periodontic treatment, diagnosis, etc., into a “visit type’’ makes it possible to determine estimates for specific services. Third-party payers typically obtain their predictionsof future risks from actuarial models that are based on past experiencesi.e., utilization patterns of their subscribers or current distribution of dental services (30).Gillings et al. developed a modified actuarial model to predict national care needs. They included the variable “need,” using the normative need-for-treatment data gathered in NHANES I. Douglass and Gammon applied this needsbased model to Canada to estimate their future need for dental treatment in terms of hours of care for operative dentistry and periodontal treatment. While this sophisticated model was useful in suggesting general directions for the dental policies of the US and Canada, the calculations were nonetheless based on normative need data, previously shown to be of questionable validity. Decision makers in the areas of health policy, manpower requirements, and resource allocation require conversion of restorative treatment need data into dental expenditure and manpower estimations. Future Direction While the four methodological approaches presented above have aided the dental profession and government officials to estimate restorative need, they do not fully use the available regional and national data on surface-specific oral health status. More exacting methods are necessary to make precise calculations of procedures needed to treat conditions requiring a restoration or replacement tooth. To take this next step of forecasting needed amounts of specific procedures, the dental profession should no longer concentrate on normative need assessments, i.e., treatment decisions based on one or a few dental examiners.
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Since there is no perfect agreement in the dental professionon the one way to restore a caries lesion or missing tooth, the use of one dentist’s judgment as the true treatment need for all patients presenting with a particular clinical problem is invalid. A variety of operative or prosthodontic procedures can restore a caries lesion or missing tooth correctly. The identification and subsequent quantification of the actual variety of procedures in the form of probability distribution of treatments used by practicing dentists is the necessary first step to an accurate and valid appraisal of the restorative efforts needed to treat a population under study. A subsequent article will present the details of such an approach to gathering the distribution of treatments used by practicing dentists nationwide to restore a caries lesion or missing tooth. The results of a mailed survey of clinical scenarios will document the variety of treatments, the probability distributions of dentists choosing a procedure, and the factors affecting the differences in treatment choice. The probability distributions of treatments for a given clinical scenario of a caries lesion or missing tooth could then be applied to surface-specific oral health status epidemiologicdata gathered on a population under study, to produce a count of needed procedures. Empirical need assessments based on these collective experiences of dentists nationwide should be employed to refine our prognostic skills. Acknowledgments The author wishes to thank Dr. Chester Douglass for his expert guidance and editorial assistance.
References 1. Klein H, Palmer C, Knutson J. Studies on dental canes. Public Health Rep 1938;53:751-65. 2. National Institute of Dental Research. Oral health of United States adults. The national survey of oral health in US employed adults and seniors: 1986. Bethesda, M D National Institutes of Health, 1987;NIH pub no 87-2868. 3. Burt B. The future of the canes decline. J Public Health Dent 1985;45261-9. 4. Lowenstein H, Fisher RW. Monthly labor review. Washington, DC: US Department of Labor, Bureau of Labor Statistics, Nov 1988;111(11). 5. Reed M, Mann W. Decreased prevalence of dental caries: influence on curriculum design. J Dent Educ 1983;47262-6. 6. Fisch S.Dental school announces its plans to close. ADA News 1989 Apr 171. 7. Gruebbel A. Measurement of dental canes prevalence and treatment service for deciduous teeth. J Dent Res 1944;23:163-8. 8. Cohen L, Jag0 J. Toward the formulation of sociodental indicators. Int J Health Serv 1976;6(4):681-99. 9. McKendrick A. The economics of canes prevention by dental hygienists. Public Health (London) 1971;85:219-27. 10. Jackson D. An index for assessing the efficacy of dental treatment in the control of dental canes. Dent Pract 1961;11:22&9. 11. Long L, Rozier R, Bawden J. Estimation of actual canes prevalence and treatment needs from field survey canes information on a child population in USA. Community Dent Oral Epidemiol1979;7322-9. 12. Walsh J. International patterns of oral health care-the example of New Zealand. N Z Dent J 1970;66:143-52. 13. Gluck GM, Knox CD, Glass RL, Wolfman M. Dental health of Puerto Rican migrant workers. Health Serv Rep 1972;8745660. 14. Milen A, Hausen J, Tala H, Heinonen 0. Dental health and treatment of Finnish children. Acta Odontol Pediatr 1984;5(2):75-82. 15. Waldman H. Dental care needs and services for children: England,
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298 Wales, and United States compared. J Dent Child 1983;50(1):4854. 16. Burt 8. A method of comparing the expenditures on twoalterna tive
national dental programs for persons aged 6-21. Final report to Division of Dentistry, Health Resources Administration, Public Heath Service, Department of Health, Education and Welfare. Ann Arbor: University of Michigan School of Public Health, 1975. 17. Doessel D. A cost-benefit analysis of water fluoridation in Towns ville; a report to the Economic and Financial Research Fund of the Reserve Bank of Australia. Brisbane, Queensland: University Queensland, 1977. 18 Holloway F, Downer M. The benefit of preventive procedures for high-risk groups.Int Dent J 1979;29:11824. 19. Conchie J, Scott K, Philion J. A simplified method of determining a population’s needs for dental treatment. J Public Health Dent 197121(2):84-95. 20. Beck J, Field H. Pilot results of DMFtreatment time index. Community Dent Oral Epidemioll980;8:52-5. 21. Pickles T. The rela tionship of caries prevalence data and diagnosed treatment needs in a child population. Med Care 1970;8:463-73. 22. Spencer A. The estimation of need for dental care. J Public Health Dent 1980;40(4):311-27. 23. Beck J, Luebke N. An index of treatment needs for population groups: a pilot study. J Public Health Dent 1978;38(3):212-22.
24. FinkelsteinM, DouglassCW,Chauncey HH. Cumulative inadence of need for restorative dental treatment. J Dent Educ 1985;49(11): 757-62. , 25. Department of Health,Education,andWelfare,NationalCenterfor Health Statistics. Plan and operation of the Health and Nutrition Examination Survey: UnitedStates1971-73,1973;DHEW pubno (HSM)73-1310(Vital and Health Statistics; series 1; no 10). 26. Schonfeld W. Estimating dental treatment needs from epidemie logical data. J Public Health Dent 1981;41(1):25-32. 27. Bader J, MullinsM, Webster D. Aspects of planning and evaluation of children’s dental care in Appalachia. J Public Health Dent 1979; 3927-34. 28. American Dental Assodation, Bureau of Economic Research and Statistics. Survey of needs for dental care, 1%5; 11. Dental needs according toageandsexofpatients.JAmDentAssoc 1966;73:135565. 29. Waldman H, Shakun M. The ADA survey of dental practice. J Am Coll Dent 1974;41:235-48. 30. Gillings D, Solledto W, Douglass CW. A need-based model to project national dental expenditures. J Public Health Dent 1983; 43(i):a25. 31. Douglas C W ,Gammon M. The future need for dental treatment in Canada. J Can Dent Assoc 1985;8:583-90.
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A Review of Methods to Forecast Restorative Treatment Needs Sheila M. McGuire, DDS, DMSc Department of Dental Care Administration Harvard School of Dental Medicine 188 Longwood Avenue Boston, MA 021 15
Abstract Decision makers in the areas of health policy, resource allocation, and manpower requirements rely implicitly on estimations of treatment needs on which to base their forecasts. The less specific the treatment-needestimate, the less precise the forecast. In previous decades, high caries rates were so prevalent that the dental profession could risk having inexact projections because overwhelming need and demand existed. However, rampant decay is no longer a common occurrence. Decay levels are declining in our nation‘s children and adults have fewer missing teeth. Therefore, restorative treatment needs and patterns in adult populations are transforming at a time when health care costs are spiraling and budget analysts at all levels of government are questioning the priority of continued support of dental care, dental education, and dental research at current levels. The purpose of this review is to present the existing methods of forecasting restorative treatment needs and to postulate the development of a new method based on the collective experiences of practicing dentists nationwide, an empirical method, to convert surface-specificoral health status data to restorative treatment need information. Need estimations based on empirical data would more accurately reflect the actual distribution of services that practicing dentists provide. Key Words: dental caries, health services needs and demands, dental health surveys. Methods for estimating restorative treatment needs in adult populations have existed for decades. Although originally developed for use in populations of children, one of the first widely applied dental indices to estimate treatment need is still in use today for populations of all ages.The DMF index (decayed,missing, and filled index) was developed for survey purposes by Klein, Palmer, and Knutson over 50 years ago (1). Their revolutionary approach to studying past and present dental disease Funded by NIDR training grant #DEO7l51. Manuscript r e c e i v d 8/16/91; returned to author for revision:11 /5/91; accepted for publication: 2/20/92.
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patternsand future needed care entailed an examination of all surfacesof all teeth present in a child’smouth. Klein et al. recorded and counted the numbers of decayed, filled, and missing teeth for a population of grade-school children. Past experience with decay was measured by the F, or filled, component. For example, results of past experiencewere reported in termsof number and percent of children having one or more filled permanent teeth. Missing permanent teeth also inferred past experienceof decay. Klein et al. measured present experience with decay by the D, or decay, component. Decay levels were reported in terms of number and percent of children having one or more carious permanent teeth requiring fillings. Klein et al. also calculated the increment of new carious surfaces that were to be expected to arise annually in this population. From the data they collected on this population of schoolchildrenin Hagerstown,MD, Klein et al. estimated manpower shortages and suggested policy changes by this crude identificationof accumulated dental needs. In one survey, they identified the disease levels and immediately linked them to the effort needed to treat the decay by estimating time requirements to care for the diseased teeth. Inanageof rampant decay and little treatment, this uncomplicated and primitive index and its rudimentary levels of analysis were sophisticated enough to dramatize the large pool of restorative needs in populations of children. Unfortunately, this technique continues to be the basis for many currently used methods to estimate adult restorative need. Adult restorative needs are more complicated than schoolchildren’s needs. In general, more teeth are remaining in the mouths of the nation’s adult population than in previous decades, but these teeth continue to be plagued by primary and recurrent decay (2). An analysis only of decayed surfacesand decliningnumbers of missing teeth in the formulationof treatment needs will provide estimations that are too general. This review article will outline the ways previous forecastingmethodshave provided treatment need information in insufficient detail. Interpretation and extrapolation of results that are too simplistic could lead to an underestimatfalse sense of security about the effortneeded to treat today’s
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dental care needs--or an overestinrate. The DMF index might be sufficient in forwasting the simple operative needs of children, but its level of sophistication cannot reflect the effect of comorbid conditions-the existence of past or present caries experienceson adjacent surfaces of the same teeth or adjacent teeth. Health policy makers should be provided with specific information on the types and complexitiesof procedures needed to bring an adult population from a diseased to a healthy state, in order to base their decisions on clinical verities. Discussions among dental educators have already begun that would alter the emphasisof certain clinical skills, in order to equip new dentists better to deal with the emerging new reality of more teeth having a long history of caries experiences. However, the exact specifics involved in translating adult restorative needs are unknown and need to be quantified. One aspect of this new reality is the impact of demographic and disease changes in two particular cohorts in America: people over the age of 60 and people under the age of 35. The number of the United States population 65 or older has increased from 20.9 million in 1972 to 31.6 million in 1990, with a projected figure of 64.5 million in the year 2030. Adults are retaining more of their natural teeth (2), thus presenting new challenges and opportunities for the dental profession. We need a clearer understanding of the increased chairside time and skill spent on expanded operative, fixed, and removable prosthodontic procedures for older Americans. Specific and accurate forecasts are needed to meet these needs. Dentists will soon be treating the aging baby-boom generation, a cohort of adults who had 33 percent fewer cavities as children, necessitating a shift in dentists’ caseloads to offset the decreasing need of extensive restorative work in this age group. Klein et al. developed measures to quantify rampant decay in children. By articulatinga clear definition of the problem, an organized attempt to deal with the problem was then possible. Analogous to the index developed by Klein, the dental profession needs a new method of measurement to guide the resource and manpower strategies of the 1990s and into the 21st century. Specificallyquantifymg the restorative needs of the adult population will clarify the uncertainties of restorative needs just as the knowledge gained from the development of the DMF index helped our professionto decrease the rate of caries and treat this problem in children. As number of decayed and missing surfacesdecreases, estimations of treatment need must be more specific and exact-they need to be procedure-specific. Forecasting the treatment of decayed surfaces must incorporate the conditions of adjacent surfacesand teeth (heretoforereferred to as comorbid conditions) to amve at the correct level of complex proceduresneeded to treat the disease. For example, more time, effort,and money are needed to arrest the decay on the mesial of a first molar if a previous
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MODL restoration is present, than if the decay was a primary lesion. The implications are even more evident if the first molar was an abutment for a three-unit bridge. There have been many attempts to refine the accuracy of the forecasts since the development of the DMF index. In the present climate of declining dental caries prevalence (3),rising health care costs (4), suggestionsof curtailing operative dentistrycurricula in dental schools(5), and the closing of some dental schools (6), the dental profession should have access to the most exactingmethods of determining restorative treatment needs. Data exist on the oral health status of the adult population based on several recent nationally based surveys. The purpose of this review, therefore, is to present the existing methods of forecasting restorative treatment needs and to postulate the development of a more direct and empirical method for converting surface-specific oral health status data to restorative treatment need information. Review of Literature Previous attempts to assess and predict restorative treatment need in adult populations will be categorized and reviewed by four methodological approaches: surveys of oral health status, surveysof need for dental care, analyses of treatment records or insurance claim forms, and mathematical models used for projecting future needs. Surveys of Oral Health Status.The DMF index and its counterpart for primary teeth, the def index (3,are the most frequently applied indices of oral health status. Cohen and Jago(8)pointed out that they were developed as measurements of complete caries experience, depicting prior treatment as well as need for treatment. As stated earlier, the missing component,M, representspermanent teeth missing due to caries. (The clinical judgment of the examiner differentiatesmissing due to caries from missing due to orthodontic reasons or trauma.) Extraction is thus the prior treatment depicted and need for replacement is inferred.The presentday standard for the filled component, F, includes permanent or temporary restorations placed in permanent teeth due to caries only (2). The decayed, D, component includes both primary and recurrent decay. Two recent national surveys, the NIDR Oral Health Survey of Adults and Senior Citizens and the MANES, distinguish between primary and recurrent decay at the chairside,but collapse the two designations to form the D component. The same operational definitionsexist for primary teeth; the corresponding lower case letters d, m, and f are used. During the calculation of a person’s DMF score, a D ovemdes an F call. If a tooth has a filled surface, the scoring for that tooth is a D if decay is present anywhere on the tooth. The DMF indices and other typical survey methods tend to produce inherent underestimations of disease levels, thus affecting the resulting treatment-need esti-
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mations. According to McKendrick (9), “Neither DMF teeth nor DMF surfaces indices are comprehensive enough by themselves, since a tooth or surface may be both filled and decayed.” Prior to the mid-l970s, the M or missing call by definition was made only when the examiner could determine that the tooth was missingdue to caries. Therefore, Jackson (10) argued that the DMF index should not be used on adults over the age of 25 because periodontal conditions and memory lapses could alter the number of M calls. Since the late 1970s,no distinction has been made for teeth missing due to caries or periodontal disease, although there is a distinction for orthodontic vs nondisease reasons. Additionally, diagnostic radiographs are not used typically in field surveys, resulting in greater underestimation. Long et al. (11) adjusted for the underestimations from lack of radiographs in each dentition type. It is not total DMF that estimates current need for treatment, but usually some ratio of the D and/or M component to the total DMF. Survey results of need from indices based on the proportions of these components have been obtained by Jackson (101, Walsh (ll), and Gluck (13).Their results described need in broad general terms rather than as quantities of care required. One report assessing treatment needs of Finnish children (14) and another comparing needs and services of England, Wales, and the United States (15)used the filled tooth ratio (f/df and F/DMF) as their outcome measure of need. No specific need for restorative treatment estimations was given. The authors of the two papers d o not forecast counts of procedures needed. They characterize treatment needs in broad general terms; e.g., the high filled-to-teeth ratios found in their populations indicate “low treatment needs.” England and Wales’ National Health Services were meeting less of the needs than was the US system because the latter had a higher filled-toteeth ratio. Evidence of past dental treatment led the authors to conclude that marked improvement had been achieved in lowering future restorative needs. Such a low level of sophistication allows great leniency in the interpretation of results made by policy makers. A more detailed division of needs based on components of the DMF and def indices have been attempted by Burt, Doessel, and Long. Burt (16) predicted the amounts of one, two, and three or more surface amalgams, stainless steel crowns, and extractions needed from the decayed component of a survey conducted by Johnsonon a population of six-year-oldsin Alabama. He successfullytested the validity of his predictions against the results of treatment needs recorded chairside by Johnson. Doessel (17) also had the advantage of using a data base that consisted of both dental status and treatment needs data. He derived probabilities for the translation of the decayed component into restorative treatment needs in terms of one-, two-, and three-surface restorations or
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extractions for a population of six-year-old Australian children: Decayed Teeth = .41 (A) + .41 (B)+ .04(C) + .14 (D) A=one surface restoration B=two surface restoration C=three surface restoration D=extraction Theabove mathematical model, based on linear regression principles, estimates that for every 100 teeth given the score of ”D,” 41 will require a one-surface restoration, another 41 will need a twosurface restoration, and a three-surface restoration will be needed for four teeth. Extraction will be indicated for the remaining 14 teeth. As stated earlier, the treatment needs for children are much less complicated than for adults. Doessel’s methods are sufficient for this young population, if you believe in the treatment-need decisionsof his dental examiner. Thechoicesfor restorative materialsand thenumber of comorbid conditions of adjacent surfacesand teeth are limited in six-year-olds. Two attempts have been made to formulate a method to forecast treatment need based on retrospective analyses of oral health examinations and the subsequent treatments planned and delivered. Long et al. (11) developed tables of treatment need estimationbased on caries levels (D + d) and stages of dentition Ke., primary, early mixed, and late mixed) in a population of North Carolina children aged three to 12 who sought dental treatment at the University of North Carolina School of Dentistry. For example, Long et al. projected that 58.33 three-surface amalgams would be required in a population of 100 children with 4-6 surfaces of decay in their primary dentition. Treatment delivered reflected the clinical judgment of the school’s pedodontic faculty. Holloway et al. (18)went one step further. Ina longitudinal study of teeth in a population of English children, they analyzed the actual changes in filled and unfilled surfaces in order to predict subsequent treatment needs from the oral health status data. Treatment-need decisions were made by a slightly broader base of dentists than in the previous examples. These two approaches have not been tested on an adult population. All of the oral health status surveys discussed above used the clinical judgment of a dentist to assess oral health status and the subsequent treatment-need estimates for their respective populations. The use of the judgment of trained lay people to estimate restorative treatment needs has also been attempted. Conchie et al. (19) developed the Simplified Descriptive Survey in 1971 and trained lay people in the Canadian province of British Columbia to recognize and record the most severe type of carious lesion present in a subject. This score was compared to results of a def survey and the treatment plans made by a dentist. The authors reported that the association among the three variables can be used to predict needs of populations denied access to dental
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treatment. This example underscores the crudeness of measures to estimate treatment needs from oral health status survey data. Predictions of the restorative needsof a population from oral health status information is such a gross measure that a nonprofessional can do the estimation, especially in young and /or highdiseased populations. The DMF-indiceshave formed the basis for more intricate approaches, however. Klein et al. began the practice of expressing need in terms of time requirements. In the 1938 seminal article “Dental status and dental needs of elementary schoolchildren,” they made two assumptions: one hour would be required to care adequately for each defective permanent tooth surface and each dentist works a total of 1,800 hours per year. They forecast current and future restorative needs and formulated the subsequent manpower requirements to supply dental services for all permanent teeth of schoolchildren.In the early 1970s, Pickles and Conchie also predicted restorative need for children in terms of time requirements. For adults, Beck (20) discussed the limitations of the timeunit approach, namely, the uncertainty of the decision to replace a missing tooth and the variety of treatments representing a range of treatment times that can be indicated for a tooth that is designated ”D.” Beck attempted to overcome only the first problem by modifymg the DMF index. He suggested a separate designation be made to record missing teeth in need of replacement.This new information, together with the knowledge of the number of decayed teeth, more accurately predicted treatment time in his population of dental school patients. Pickles (21) found that a higher number of permanent teeth were diagnosed for treatment in a clinical setting than were diagnosed for treatment in the field. He found the relationship between clinical care diagnoses and survey findings for permanent teeth too weak to be of practical value in predicting service needs from DMF data. Spencer postulated that a dental epidemiologist’s perspective of caries experience and its relation to need for dental care may be at variance with a clinician’s perspective (22). For reliability reasons, the operational definitions for decay and treatment needs must necessarily be less refined for an epidemiologist. Restorative needs assessed during a survey would differ from restorative needs retrospectively translated from survey data by clinicians. Spenser called for further research to validate this translation of survey disease levels to restorative treatment needs based on clinicians’ decisions regarding treatment options. One concern in validating translation of survey data to treatment needs is the issue of clinician variability. Beck (23) acknowledged the fallacy of not accounting for differing treatment philosophies in the design of his pilot study to develop a treatment needs index based on surface-specific oral health status data; ”the unknown r e p
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resentativeness of the findings related to diagnosis and treatment practices is a potentially serious weakness.” This weakness, treatment decisions being made by one or two dentists not calibrated to any standard, is present and unrecognized in the designs of all studies by Klein, Burt, Doessel, and Conchie. No consideration is given to recognizing a range of restorative treatment possibilities. Long et al. recognized that there was no formal calibration of the many examiners used to determine treatments in their study, but they contended the results would nonetheless reflect the choices of their graduates in private practice. In all of the above situations, experts (dentists) assessed need by using their professional judgment to decide the one treatment necessary to restore the surveyed carious or missing tooth. Spencer (22) and Finkelstein et al. (24) termed this type of need as “normative need.” Normative need, the requirement for care as determined by an expert opinion, must be differentiated from perceived need, which is the general recognition that some type of care may be needed as determined by the patient or public. In addressing this issue, this review will put forward a more appropriate method to determine the requirement for care, one that would be based on the collective experiences of practicing dentists nationwide: empirical need. In reality, there is not perfect agreement in the dental profession on how best to restore any carious lesion or missing tooth. Translating oral health status data into restorative treatment needs based on empirical need would result in a distribution of appropriate treatments that reflects what actually occurs in the practice of dentistry. The fallacy described above by Beck would be eliminated or largely controlled using this approach to estimating empirical need for restorative treatments. Surveys of Need for Dental Care. A second methodological approach previously used to assess need for restorative treatment occurs at the time of the survey examination. In addition to the assessment of the oral health status of the tooth or surface under survey, the dental examiner also makes an assessment of the restorative need during the chairside field examination. This method of directly assessing need for restorative treatment was discussed in the previous section, but in a slightly different context. Burt, Doessel, and Long, the authors of several studies of small nonrepresentative samples, developed techniques to translate dental conditions into treatment need predictions. These studies were designed primarily to assess oral health status, although the direct assessment of restorative need was allowed to provide a standard by which to validate the translation techniques. In contrast, the surveys under discussion in this section are designed to assess restorative need directly at the time of the survey examination-the direct treatment plan approach. International and national agencies compile information on need for restorative treatment by directly assess-
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ing treatment needs during the field examination. All three editions of the World Health Organization's "Oral Health Surveys: Basic Methods" include the collectionof information on directly assessed need for restorations. These basic methods have been implemented by many counties to monitor progress in controllingoral diseases within and between countries. In the US, the National Center for Health Statistics (NCHS) gathered information on restorative treatment need as part of the first Health and Nutrition Examination Survey (NHANES I) conducted during 1971-74 (25). Directly assessing restorative treatment need at the time of the field examination has the advantage of quantifying specific treatments needs. As discussed previously, quantities of treatment needs obtained by Milen et al. (14) and Waldman (15) from their translations of oral health status data produced relative results in terms of "low" or "high" treatment needs. Counts of specific procedures are possible with the direct treatment plan approach.WHO is able to tally the number of the following procedures needed to restore the oral conditions found in an observed population: caries-arresting or sealant care one surface fillings two or more surface fillings crowns or bridge abutments bridge elements pulp care extraction need for other care. A count of a slightly different set of restorative procedures was possible from the NHANES I survey: one surface restorations (for primary and permanent teeth) two surface restorations (for primary and permanent teeth) three or more surface restorations (for primary and permanent teeth) crowns replacement of full dentures replacement of partial dentures replacement of bridges. Division of need by type of restorative material-i.e., composite,amalgam,gold-was not ascertainedin either the WHO or NHANES I surveys. As with the first methodologicalapproach-surveysof oral health status-the same critical problem exists with the use of surveys of need for dental care in forecasting restorative treatment needs. Normative restorative need was calculated in these direct treatment plan approaches. Dental examiners used their clinical judgment to determine the restorative procedure. The validity and reliability shortcomings previously outlined for the normative need approach led Schonfeld (26)and his North Carolina colleagues to make a "conscious decision to focus on dental conditions, which could be identified with a high
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degree of objectivity and consistencyfrom one examiner toanother, rather than to record needed treatment, which might be subject to considerable examiner variability" when they designed their study of dental disease in North Carolina. In addition, the National Institute for Dental Research chose to collect only information on dental conditions (caries, periodontal disease, oral cancer, etc.) in its national survey of oral health in US employed adults and seniors in 1985(2). No treatment need assessment was conducted. The US government, due to the shortcomings discussed, no longer uses the direct treatment plan approach. Analyses of Service or Treatment Records. Existing dental care programs, third-party carriers, or even private practitioners could be sources of information necessary to predict treatment needs in various populations. As described above, Long et al. used the documentation of surface-specificoral health status, treatments planned, and treatments delivered, obtained from the records of the University of North Carolina School of Dentistry Pedodontic Clinic, to predict treatment needs. To assist other dental health care providersinitiatingprograms for underprivileged children, Bader (27)analyzed data on treatment requirements found in the patient records for three populations of children in the Appalachian Mountain regions. As is the case for all studies of children with high decay levels and no past history of dental treatment, the translation of oral health status data into treatment needs is uncomplicated. Few comorbid conditions exist and the treatment optionsare minimal. Bader'sapproach was sufficient to get a rough estimateof the effort needed to initiate dental health programs for underprivileged children. Bader has not applied his methodologies to adult populations. As with the previous two methodological approaches, these analyses of service or treatment records to attempt to estimate treatment need were based on the examiningdentist's view, a normativeneedfor-treatment assessment. The American Dental Association's Bureau of Economic Research and Statistics has gathered data on need for dental care. In the 1%5 ADA survey of dental practices (28), a random sample of dentists was asked to estimate the need of dental care from the records of the patients in their practice. Due to the low response rate and findings that were determined to be biased (291, future surveys by the ADA of dental practice did not include the collectionof this need-for-treatmentdata. The ADA determined that a survey of a random sample of dentists to estimate treatment needs was the appropriate way to move away from a normative-need approach to an empirical-need approach in validly estimating treatment needs. As the ADA discovered, however, the problem of ascertaining treatment need estimations from a broad sample of dentists-empirical need-cannot be dealt with by asking them directly about their own patients. No attempt has yet been made to survey a broad
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sample of dentists regarding their restorative treatment decisions about patients not directly under their care. Mathematical Models Used to Project Future Needs. Models have been used extensively to project dental expenditures, an indirect way of forecasting treatment needs. For the purpose of this review, the discussion of mathematical projection models will only focus on their contributions to directly estimating restorative treatment needs. An assessment of their abilities to estimate such entities as dental expenditures, actuarial risks, etc., is beyond the scope of this review. Gillings et al. (30)reported that the two primary methods used to project national dental expenditures are econometric and actuarial. For example, the Feldstein and Roehrig econometric model determines the effectsof government policies on dental prices and incomes and the overall dental health of the population. The model uses ”visit type,” a method of grouping predefined services for a segment of the population, i.e., comprehensive care for adults. The ”lumping” of all types of restorations with periodontic treatment, diagnosis, etc., into a “visit type’’ makes it possible to determine estimates for specific services. Third-party payers typically obtain their predictionsof future risks from actuarial models that are based on past experiencesi.e., utilization patterns of their subscribers or current distribution of dental services (30).Gillings et al. developed a modified actuarial model to predict national care needs. They included the variable “need,” using the normative need-for-treatment data gathered in NHANES I. Douglass and Gammon applied this needsbased model to Canada to estimate their future need for dental treatment in terms of hours of care for operative dentistry and periodontal treatment. While this sophisticated model was useful in suggesting general directions for the dental policies of the US and Canada, the calculations were nonetheless based on normative need data, previously shown to be of questionable validity. Decision makers in the areas of health policy, manpower requirements, and resource allocation require conversion of restorative treatment need data into dental expenditure and manpower estimations. Future Direction While the four methodological approaches presented above have aided the dental profession and government officials to estimate restorative need, they do not fully use the available regional and national data on surface-specific oral health status. More exacting methods are necessary to make precise calculations of procedures needed to treat conditions requiring a restoration or replacement tooth. To take this next step of forecasting needed amounts of specific procedures, the dental profession should no longer concentrate on normative need assessments, i.e., treatment decisions based on one or a few dental examiners.
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Since there is no perfect agreement in the dental professionon the one way to restore a caries lesion or missing tooth, the use of one dentist’s judgment as the true treatment need for all patients presenting with a particular clinical problem is invalid. A variety of operative or prosthodontic procedures can restore a caries lesion or missing tooth correctly. The identification and subsequent quantification of the actual variety of procedures in the form of probability distribution of treatments used by practicing dentists is the necessary first step to an accurate and valid appraisal of the restorative efforts needed to treat a population under study. A subsequent article will present the details of such an approach to gathering the distribution of treatments used by practicing dentists nationwide to restore a caries lesion or missing tooth. The results of a mailed survey of clinical scenarios will document the variety of treatments, the probability distributions of dentists choosing a procedure, and the factors affecting the differences in treatment choice. The probability distributions of treatments for a given clinical scenario of a caries lesion or missing tooth could then be applied to surface-specific oral health status epidemiologicdata gathered on a population under study, to produce a count of needed procedures. Empirical need assessments based on these collective experiences of dentists nationwide should be employed to refine our prognostic skills. Acknowledgments The author wishes to thank Dr. Chester Douglass for his expert guidance and editorial assistance.
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