Abstract

Having a regular medical doctor is associated with better process of care and health outcomes. The goal of this study was to harness the richness in health administrative data to create a measure which accurately predicted whether patients self-identified as having a regular medical doctor. The Canadian Community Health Survey (2007-2012) was linked with health administrative data (HAD) (2002-2012) from Quebec, Canada's second largest province. The Canadian Community Health Survey includes respondents' answer to whether they have a regular medical doctor, but health administrative data does not. We therefore used LASSO and Random Forests to build prediction models that predict whether a patient reports having a regular medical doctor using their data only available in the HAD. Our results show that predicting patient responses to 'do you have a regular medical doctor?' using an average of single-year Usual Provider Continuity over 3 years results in an area under the receiver operator characteristic curve of 0.782 (0.778-0.787). This was almost a 14% improvement in predictive accuracy compared to the frequently used single-year Usual Provider Continuity (0.688 (0.683-0.694)). We have called this new measure the Reporting a Regular Medical Doctor (RRMD) index. The RRMD index is easy to implement in HAD, is an elegant solution to the difficulties associated with low-users having unstable UPC scores, and brings a patient-oriented perspective to previous efforts to capture patient-physician affiliations in HAD. We recommend that researchers seeking to measure whether patients have a regular medical doctor using HAD consider using the RRMD index.

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