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Primary care physician practice styles and quality, cost, and productivity.

Luft HS, Liang SY, Eaton LJ, & Chung S.
Am J Manag Care. 26(4):e127-e134. doi: 10.37765/ajmc.2020.42840.
2020-04-01

Abstract

OBJECTIVES: To assess quality, cost, physician productivity, and patient experience for 2 primary care physician (PCP) practice styles: the focused, who typically address only the patient's acute problem, versus the max-packers, who typically address additional conditions also.

STUDY DESIGN: Retrospective observational study using administrative data, electronic health record (EHR) data, and patient surveys. Data represent 285 PCPs (779 PCP-years) in a large, multispecialty group practice during 2011, 2012, and 2013.

METHODS: PCPs were ranked each year by their number of additional conditions addressed during acute care visits. The top one-third (max-packers) addressed 25.4% more "other problems" than expected, while focused PCPs (bottom one-third) addressed 20.3% fewer than expected. Outcomes were resource use, clinical quality metrics, patient-reported experience, physician time using the EHR, and physician productivity. All measures were risk-adjusted to account for patient mix. T tests were used to compare measures.

RESULTS: Relative to a focused pattern of care, max-packing was associated with 3.4% lower overall resource use, consistently better scores for the available clinical quality metrics, and comparable patient experience (except for worse wait time ratings). Patients of focused PCPs used 7.3% more specialist services, in terms of costs, than patients of max-packers ($1218 vs $1136; P <.001). Max-packers spent 40 minutes more per clinical day using the EHR. PCPs with less appointment availability and who used a mix of appointment slots were more likely to be max-packers.

CONCLUSIONS: Max-packing behavior yields desirable outcomes at lower overall cost but involves more conventionally uncompensated PCP time. Alternatives to compensation just for face-to-face visits and using more flexible scheduling may be needed to support max-packing.

Su-Ying Liang, Ph.D.
Su-Ying Liang, Ph.D.
Principal investigator
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