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Influence of Patient, Visit, and Oral Health Factors on Dental Service Provision

Identifieur interne : 008474 ( Main/Exploration ); précédent : 008473; suivant : 008475

Influence of Patient, Visit, and Oral Health Factors on Dental Service Provision

Auteurs : David S. Brennan [Australie] ; A. John Spencer [Australie]

Source :

RBID : ISTEX:66B4B528B0DB770FD94291A2CB2C1319D1202104

Descripteurs français

English descriptors

Abstract

Objectives: Service provision should reflect the oral health of the patient. However, patient and visit factors may influence service patterns and the appropriateness of care delivered. The aim of this study was to examine factors associated with variation in dental services and to assess whether variation by patient and visit characteristics persisted after controlling for oral health status. Methods: A random sample of Australian dentists was surveyed during 1997–98 (response rate=60.3%). Private general practitioners (n=345) provided data on service provision, as well as patient, visit and oral health variables from a log of a typical clinical day (n=4,115 patients). Multivariate Poisson regression models were run for eight service areas (e.g., diagnostic, preventive, and restorative). Results: Significant effects (P<.05) were observed for oral health factors in all eight models, visit factors in all eight models, patient demographics in four models, dental knowledge/behavior in one model, and area‐based socioeconomic status in one model. Conclusions: After controlling for oral health, visit characteristics persisted as significant predictors of services, with nonemergency visits, insurance, and capital city location associated with more favorable service mix patterns. Higher socioeconomic status areas and payment scale ratings also were associated with a better service pattern in particular service areas. These findings show that a wide range of factors, in addition to oral health, contribute to variation in service provision.

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DOI: 10.1111/j.1752-7325.2002.tb03436.x


Affiliations:


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Le document en format XML

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<term>Australian institute</term>
<term>Better service pattern</term>
<term>Bivariate associations</term>
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<term>Capital city location</term>
<term>Clinical decision</term>
<term>Community dent</term>
<term>Consistent increase</term>
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<term>Decayed knowledge scale</term>
<term>Decayed teeth</term>
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<term>Dent educ</term>
<term>Dental</term>
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<term>Dental knowledge</term>
<term>Dental practice</term>
<term>Dental service patterns</term>
<term>Dental service provision</term>
<term>Dental service rates</term>
<term>Dental services</term>
<term>Dentate</term>
<term>Dentate adults</term>
<term>Dentist</term>
<term>Dentist service rates</term>
<term>Dentistry</term>
<term>Denture</term>
<term>Emergency visits</term>
<term>Endodontic</term>
<term>Endodontic services</term>
<term>Extraction</term>
<term>Female dentists</term>
<term>General practice</term>
<term>Geographic location</term>
<term>Health card</term>
<term>Health status</term>
<term>Higher extraction rate</term>
<term>Higher payment scale ratings</term>
<term>Higher percentage</term>
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<term>Higher rates</term>
<term>Higherdental knowledge rating</term>
<term>Independent variables</term>
<term>Infrequent attenders</term>
<term>Insurance coverage</term>
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<term>Knowledge rating</term>
<term>Lower extraction rates</term>
<term>Lower provision</term>
<term>Lower rates</term>
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<term>Male dentists</term>
<term>Male patients</term>
<term>Moderate effects</term>
<term>Multivariate</term>
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<term>Nonemergency</term>
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<term>Older adults</term>
<term>Oral health</term>
<term>Oral health factors</term>
<term>Oral health status</term>
<term>Oral health variables</term>
<term>Other factors</term>
<term>Payment scale</term>
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<term>Periodontal disease</term>
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<term>Potential bias</term>
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<term>Preventive orientation</term>
<term>Preventive services</term>
<term>Previous location capital city noncapital denture status</term>
<term>Private practice</term>
<term>Private sector</term>
<term>Prosthodontic</term>
<term>Prosthodontic services</term>
<term>Public health</term>
<term>Public health dent</term>
<term>Public health dentistry</term>
<term>Public sector</term>
<term>Random sample</term>
<term>Rate ratio</term>
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<term>Ratingt seifa index</term>
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<term>Research unit</term>
<term>Resident population</term>
<term>Restorative demand</term>
<term>Restorative services</term>
<term>Restorative treatment thresholds</term>
<term>Sampling period</term>
<term>Seifa index</term>
<term>Service areas</term>
<term>Service data</term>
<term>Service patterns</term>
<term>Service provision</term>
<term>Service provision models</term>
<term>Service provision patterns</term>
<term>Service rates</term>
<term>Significant differences</term>
<term>Socioeconomic status</term>
<term>Strong effects</term>
<term>Thigher rating</term>
<term>Tooth loss</term>
<term>Treatment decisions</term>
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<term>Uninsured patient status</term>
<term>Visit characteristics</term>
<term>Visit factors</term>
<term>Visit type</term>
<term>Visit type emergency nonemergency insurance status</term>
<term>Weak effects</term>
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<term>Absent number</term>
<term>Attendance patterns</term>
<term>Aust dent</term>
<term>Australian bureau</term>
<term>Australian institute</term>
<term>Better service pattern</term>
<term>Bivariate associations</term>
<term>Bridge services</term>
<term>Capital city location</term>
<term>Clinical decision</term>
<term>Community dent</term>
<term>Consistent increase</term>
<term>Decay knowledge scale</term>
<term>Decayed knowledge scale</term>
<term>Decayed teeth</term>
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<term>Dental</term>
<term>Dental care</term>
<term>Dental knowledge</term>
<term>Dental practice</term>
<term>Dental service patterns</term>
<term>Dental service provision</term>
<term>Dental service rates</term>
<term>Dental services</term>
<term>Dentate</term>
<term>Dentate adults</term>
<term>Dentist</term>
<term>Dentist service rates</term>
<term>Dentistry</term>
<term>Denture</term>
<term>Emergency visits</term>
<term>Endodontic</term>
<term>Endodontic services</term>
<term>Extraction</term>
<term>Female dentists</term>
<term>General practice</term>
<term>Geographic location</term>
<term>Health card</term>
<term>Health status</term>
<term>Higher extraction rate</term>
<term>Higher payment scale ratings</term>
<term>Higher percentage</term>
<term>Higher percentages</term>
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<term>Higher rates</term>
<term>Higherdental knowledge rating</term>
<term>Independent variables</term>
<term>Infrequent attenders</term>
<term>Insurance coverage</term>
<term>Insurance status</term>
<term>Interaction terms</term>
<term>Knowledge rating</term>
<term>Lower extraction rates</term>
<term>Lower provision</term>
<term>Lower rates</term>
<term>Lowest income group</term>
<term>Main areas</term>
<term>Male dentists</term>
<term>Male patients</term>
<term>Moderate effects</term>
<term>Multivariate</term>
<term>Multivariate models</term>
<term>Multivariate poisson regression models</term>
<term>Natural dentition</term>
<term>Nonemergency</term>
<term>Nonemergency visits</term>
<term>Older adults</term>
<term>Oral health</term>
<term>Oral health factors</term>
<term>Oral health status</term>
<term>Oral health variables</term>
<term>Other factors</term>
<term>Payment scale</term>
<term>Payment scale ratings</term>
<term>Periodontal disease</term>
<term>Poisson</term>
<term>Poisson regression</term>
<term>Postal code</term>
<term>Postal code area</term>
<term>Potential bias</term>
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<term>Preventive orientation</term>
<term>Preventive services</term>
<term>Previous location capital city noncapital denture status</term>
<term>Private practice</term>
<term>Private sector</term>
<term>Prosthodontic</term>
<term>Prosthodontic services</term>
<term>Public health</term>
<term>Public health dent</term>
<term>Public health dentistry</term>
<term>Public sector</term>
<term>Random sample</term>
<term>Rate ratio</term>
<term>Rating</term>
<term>Ratingt seifa index</term>
<term>Reference reference reference reference reference reference reference reference reference reference reference reference reference reference reference reference reference reference reference reference reference reference reference reference reference reference reference reference reference reference reference reference reference reference reference reference reference reference reference reference reference reference reference reference reference reference reference reference</term>
<term>Research unit</term>
<term>Resident population</term>
<term>Restorative demand</term>
<term>Restorative services</term>
<term>Restorative treatment thresholds</term>
<term>Sampling period</term>
<term>Seifa index</term>
<term>Service areas</term>
<term>Service data</term>
<term>Service patterns</term>
<term>Service provision</term>
<term>Service provision models</term>
<term>Service provision patterns</term>
<term>Service rates</term>
<term>Significant differences</term>
<term>Socioeconomic status</term>
<term>Strong effects</term>
<term>Thigher rating</term>
<term>Tooth loss</term>
<term>Treatment decisions</term>
<term>Treatment selection</term>
<term>Uninsured patient status</term>
<term>Visit characteristics</term>
<term>Visit factors</term>
<term>Visit type</term>
<term>Visit type emergency nonemergency insurance status</term>
<term>Weak effects</term>
<term>Wide range</term>
<term>Years patient</term>
<term>Years years years</term>
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<front>
<div type="abstract" xml:lang="en">Objectives: Service provision should reflect the oral health of the patient. However, patient and visit factors may influence service patterns and the appropriateness of care delivered. The aim of this study was to examine factors associated with variation in dental services and to assess whether variation by patient and visit characteristics persisted after controlling for oral health status. Methods: A random sample of Australian dentists was surveyed during 1997–98 (response rate=60.3%). Private general practitioners (n=345) provided data on service provision, as well as patient, visit and oral health variables from a log of a typical clinical day (n=4,115 patients). Multivariate Poisson regression models were run for eight service areas (e.g., diagnostic, preventive, and restorative). Results: Significant effects (P<.05) were observed for oral health factors in all eight models, visit factors in all eight models, patient demographics in four models, dental knowledge/behavior in one model, and area‐based socioeconomic status in one model. Conclusions: After controlling for oral health, visit characteristics persisted as significant predictors of services, with nonemergency visits, insurance, and capital city location associated with more favorable service mix patterns. Higher socioeconomic status areas and payment scale ratings also were associated with a better service pattern in particular service areas. These findings show that a wide range of factors, in addition to oral health, contribute to variation in service provision.</div>
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