4.6 Article

Evaluating a Model to Predict Primary Care Physician-Defined Complexity in a Large Academic Primary Care Practice-Based Research Network

Journal

JOURNAL OF GENERAL INTERNAL MEDICINE
Volume 30, Issue 12, Pages 1741-1747

Publisher

SPRINGER
DOI: 10.1007/s11606-015-3357-8

Keywords

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Funding

  1. Partners Community Healthcare, Inc
  2. Massachusetts General Hospital Primary Care Practice-Based Research and Quality Improvement Network
  3. KL2/Catalyst Medical Research Investigator Training award from Harvard Catalyst, The Harvard Clinical and Translational Science Center (National Center for Research Resources, National Institutes of Health)
  4. KL2/Catalyst Medical Research Investigator Training award from Harvard Catalyst, The Harvard Clinical and Translational Science Center (National Center for Advancing Translational Sciences, National Institutes of Health) [KL2 TR001100]

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Improving the ability to risk-stratify patients is critical for efficiently allocating resources within healthcare systems. The purpose of this study was to evaluate a physician-defined complexity prediction model against outpatient Charlson score (OCS) and a commercial risk predictor (CRP). Using a cohort in which primary care physicians reviewed 4302 of their adult patients, we developed a predictive model for estimated physician-defined complexity (ePDC) and categorized our population using ePDC, OCS and CRP. 143,372 primary care patients in a practice-based research network participated in the study. For all patients categorized as complex in 2007 by one or more risk-stratification method, we calculated the percentage of total person time from 2008-2011 for which eligible cancer screening was incomplete, HbA1c was a parts per thousand yen 9 %, and LDL was a parts per thousand yen 130 mg/dl (in patients with cardiovascular disease). We also calculated the number of emergency department (ED) visits and hospital admissions per person year (ppy). There was modest agreement among individuals classified as complex using ePDC compared with OCS (36.7 %) and CRP (39.6 %). Over 4 follow-up years, eligible ePDC-complex patients had higher proportions (p < 0.001) of time with: incomplete cervical (17.8 % vs. 13.3 % for OCS; 19.4 % vs. 11.2 % for CRP), breast (21.4 % vs. 14.9 % for OCS; 22.7 % vs. 15.0 % for CRP), and colon (25.9 % vs. 18.7 % for OCS; 27.0 % vs. 18.2 % for CRP) cancer screening; HbA1c a parts per thousand yenaEuro parts per thousand 9 % (15.6 % vs. 8.1 % for OCS; 15.9 % vs. 6.9 % for CRP); and LDL a parts per thousand yenaEuro parts per thousand 130 mg/dl (12.4 % vs. 7.9 % for OCS; 11.8 % vs 9.0 % for CRP). ePDC-complex patients had higher rates (p < 0.003) of: ED visits (0.21 vs. 0.11 ppy for OCS; 0.17 vs. 0.15 ppy for CRP), and admissions in patients 45-64 and a parts per thousand yen 65 years old (0.11 vs. 0.10 ppy AND 0.24 vs. 0.21 ppy for OCS). Our measure for estimated physician-defined complexity compared favorably to commonly used risk-prediction approaches in identifying future suboptimal quality and utilization outcomes.

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