The role of dentist, practice and patient factors in the provision of dental services

Abstract

Service provision varies by dentist, practice and patient factors. However, limited subsets of these potential influences on service rates have been explored. More comprehensive models could improve our understanding of the factors influencing the pattern of care delivered. The aim of this study was to examine variation in dental services by dentist (treatment choice, practice beliefs, preferences for patients, demographics), practice (type, location, size and volume of practice) and patient (visit, demographic, oral health and socio-economic) characteristics. A random sample of Australian dentists was surveyed in 1997-98 (response rate=60.3%). Private general practitioners (n=345) provided dentist and practice data, and service provision and patient variables were collected from a log of a typical clinical day (n=4,115 patients). Multivariate negative binomial regression models were fitted for diagnostic, preventive, restorative, extraction and prosthodontic services. Significant dentist factors included (P<0.05; RR=rate ratio): lower diagnostic rates (RR=0.78) for dentists with stronger practice beliefs for giving information about cost and treatment options; preventive rates were lower (RR=0.74) for male dentists and higher (RR=1.48) for younger dentists aged 20-29 years; restorative rates were higher (RR=1.27) for dentists that rated patient preferences more highly in treatment choice and in the dentist age group 30-39 years (RR=1.25); extraction rates were lower (RR=0.61) for dentists with stronger preferences for patients that would adhere with treatment but higher (RR=1.57) for dentists with stronger preferences for sociable patients; and prosthodontic rates were lower (RR=0.38) for dentists with stronger preferences for adaptable patients who were willing to cooperate when expected to do so. Practice factors included: higher preventive (RR=1.28) and prosthodontic rates (RR=2.07) in solo practice; higher preventive (RR=1.34) but lower prosthodontic rates (RR=0.42) in capital cities; lower diagnostic (RR=0.82) and extraction rates (RR=0.55) in practices with fewer other dentists; higher diagnostic (RR=1.33) and extraction (RR=1.62) rates but lower restorative rates (RR=0.84) in practices with lower patient visits per year. Patient factors included: lower preventive (RR=0.76) but higher extraction rates (RR=1.45) for emergency visits; lower extraction rates (RR=0.60) for the insured; higher diagnostic rates (RR=1.17) for new patients; higher restorative (RR=1.31) but lower prosthodontic rates (RR=0.46) for patients with decayed teeth; higher prosthodontic rates (RR=2.14) for those with dentures; and lower preventive (RR=0.66), but higher extraction (RR=2.22) and prosthodontic rates (RR=1.82) for patients from lower socio-economic status areas. Dental service rates were influenced by large number of small effects from a wide range of dentist, practice and patient factors. Socio-economic and geographic barriers may need broad policy innovations to be addressed, but factors such as insurance and visit type have the potential to be altered to achieve better service outcomes and there is scope for research into clinical outcomes to improve the knowledge upon which treatment decisions are based.