List of variables.

<div><p>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.</p></div>