Risk Adjustment Using Administrative Data-Based and Survey-Derived Methods for Explaining Physician Utilization
Bibliographic Data
| ID | 9104098 |
|---|---|
| Authors | Lyn M Sibley (0009-0004-6510-2654, University of Toronto, corresponding author), Rahim Moineddin (0000-0002-5506-084X, University of Toronto, corresponding author), Mohammad Agha (University of Toronto), Mohammad M Agha, Richard H Glazier (0000-0002-7952-8320, Institute for Clinical Evaluative Sciences, corresponding author) |
| Year | 2010 |
| Volume | 48 |
| Issue | 2 |
| Pages | 175-182 |
| Publication date | 2010-02-01 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Medical Care (JOURNAL) |
| Journal identifiers | ISSN: 0025-7079 • E-ISSN: 1537-1948 |
| Publisher | Ovid Technologies (Wolters Kluwer Health) (PUBLISHER) |
| DOI | 10.1097/mlr.0b013e3181c16102 |
| PMID | 19927013 |
| OpenAlex | W2085317785 |
| Language | EN |
| Citations received | 10 |
| References cited | 17 |
OBJECTIVES: The objective of this study was to evaluate an administrative data-based risk adjustment method for predicting physician utilization and the contribution of survey-derived indicators of health status. The results of this study will support the use of administrative data for planning, reimbursement, and assessing equity of physician utilization. METHODS: The Ontario portion of the 2000-2001 Canadian Community Health Survey was linked with administrative physician claims data from 2002-2003 and 2003-2004. Explanatory models of family physician (FP) and specialist physician (SP) utilization were run using demographic information and The Johns Hopkins University Adjusted Clinical Groups (ACG) Case-mix System. Survey-based measures of health status were then added to the models. The coefficient of determination, R, indicated the models' explanatory power. RESULTS: The study sample consisted of 25,558 individuals aged 20 to 79 years representing approximately 7.8 million people. Over the 2 years of study period, 82.5% of the study population had a FP visit with a median of 6 visits and 53.2% had a SP visit with a median of 1 visit. The R values based on administrative data alone were 33% and 21% for the frequency of FP and SP visits and 16% and 35% for having one or more visit to an FPs and SPs, respectively. The addition of the survey-based measures to the administrative data-based models produced less than a 2% increase in explanatory power for any outcome. CONCLUSION: Administrative data-based measures of morbidity burden are valid and useful indicators of future physician utilization. The survey-derived measures used in this study did not contribute significantly to models on the basis of administrative data-based measures. These findings support the future use of administrative data-based data and Adjusted Clinical Groups for planning, reimbursement, and research
Actuarial science · Business · Family medicine · MEDLINE · Political science · Statistics · Survey data collection · Healthcare Policy and Management · Mathematics · Medicine · Patient Satisfaction in Healthcare · Primary Care and Health Outcomes
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| Citations per year | 0.63 |
|---|---|
| Citation span | 2010 - 2021 (12) |
| Highly cited | No |