4.4 Article

Feasibility of Distinguishing Performance Among Provider Groups Using Patient-reported Outcome Measures in Older Adults With Multiple Chronic Conditions

Journal

MEDICAL CARE
Volume 57, Issue 3, Pages 180-186

Publisher

LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/MLR.0000000000001013

Keywords

research methods; patient-reported outcomes; performance measures; quality of life; geriatrics; comorbidity

Funding

  1. NIH NIA [HHSN271201500064C]

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Objective: To examine minimum sample sizes and follow-up times required for patient-reported outcome-based performance measures (PMs) to achieve acceptable reliability as PMs. Participants: We used 2 groups of patients age 65+ with at least 2 of 13 chronic conditions. The first was a sample of Medicare Advantage beneficiaries, who reported health-related quality of life (HRQoL) at baseline and 2 years. The second was a sample of primary care patients, who reported HRQoL at baseline and 6 months. Measures: Medicare Advantage beneficiaries completed the Veterans RAND 12-Item Short Form (VR-12), while the primary care sample completed the Patient-Reported Outcomes Measurement Information System 29-Item Profile Measure (PROMIS-29). We constructed binary candidate PMs indicating stable or improved physical or mental HRQoL at follow-up, and continuous PMs measuring mean change over time. Results: In the Medicare Advantage sample, with a sample size per entity profiled of 160, the most promising PM achieved a reliability of 0.32 as a PM. A sample size of 882 per entity would have been needed for this PM to achieve an acceptable reliability of 0.7. In the prospective sample, with a sample size of 27 per clinic, the most promising PM achieved a reliability of 0.16 as a PM. A sample size of 341 patients (at the clinic level) would have been needed for this PM to achieve a reliability of 0.7. Conclusions: Achieving acceptable reliability for these PMs and conditions would have required minimum sample sizes of 341 at the clinic level or 880 at the health plan level. These estimates can guide the design of future patient-reported outcome-based PMs.

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