Karen E Schifferdecker1,2, Susan E Yount3, Karen Kaiser3, Anna Adachi-Mejia4,5,6, David Cella3, Kathleen L Carluzzo5, Amy Eisenstein3,7, Michael A Kallen3, George J Greene3, David T Eton8, Elliott S Fisher6. 1. Community and Family Medicine, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA. karen.e.schifferdecker@dartmouth.edu. 2. Center for Program Design and Evaluation at Dartmouth, Geisel School of Medicine at Dartmouth, 21 Lafayette Street, #373, Lebanon, NH, 03766, USA. karen.e.schifferdecker@dartmouth.edu. 3. Department of Medical Social Sciences, Northwestern University's Feinberg School of Medicine, Chicago, IL, USA. 4. Community and Family Medicine, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA. 5. Center for Program Design and Evaluation at Dartmouth, Geisel School of Medicine at Dartmouth, 21 Lafayette Street, #373, Lebanon, NH, 03766, USA. 6. The Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA. 7. Leonard Schanfield Research Institute at CJE SeniorLife, Chicago, IL, USA. 8. Department of Health Sciences Research, Division of Health Care Policy and Research, Mayo Clinic, Rochester, MN, USA.
Abstract
PURPOSE: Patient-reported outcome measures (PROMs), which are generic or condition-specific, are used for a number of reasons, including clinical care, clinical trials, and in national-level efforts to monitor the quality of health care delivery. Creating PROMs that meet different purposes without overburdening patients, healthcare systems, providers, and data systems is paramount. The objective of this study was to test a generalizable method to incorporate condition-specific issues into generic PROM measures as a first step to producing PROMs that efficiently provide a standardized score. This paper outlines the method and preliminary findings focused on a PROM for osteoarthritis of the knee (OA-K). METHODS: We used a mixed-methods approach and PROMIS® measures to test development of a combined generic and OA-K-specific PROM. Qualitative methods included patient focus groups and provider interviews to identify impacts of OA-K important to patients. We then conducted a thematic analysis and an item gap analysis: identified areas covered by existing generic PROMIS measures, identified "gap" areas not covered, compared gap areas to legacy instruments to verify relevance, and developed new items to address gaps. We then performed cognitive testing on new items and drafted an OA-K-specific instrument based on findings. RESULTS: We identified 52 existing PROMIS items and developed 24 new items across 14 domains. CONCLUSIONS: We developed a process for creating condition-specific instruments that bridge gaps in existing generic measures. If successful, the methodology will create instruments that efficiently gather the patient's perspective while allowing health systems, researchers, and other interested parties to monitor and compare outcomes over time, conditions, and populations.
PURPOSE:Patient-reported outcome measures (PROMs), which are generic or condition-specific, are used for a number of reasons, including clinical care, clinical trials, and in national-level efforts to monitor the quality of health care delivery. Creating PROMs that meet different purposes without overburdening patients, healthcare systems, providers, and data systems is paramount. The objective of this study was to test a generalizable method to incorporate condition-specific issues into generic PROM measures as a first step to producing PROMs that efficiently provide a standardized score. This paper outlines the method and preliminary findings focused on a PROM for osteoarthritis of the knee (OA-K). METHODS: We used a mixed-methods approach and PROMIS® measures to test development of a combined generic and OA-K-specific PROM. Qualitative methods included patient focus groups and provider interviews to identify impacts of OA-K important to patients. We then conducted a thematic analysis and an item gap analysis: identified areas covered by existing generic PROMIS measures, identified "gap" areas not covered, compared gap areas to legacy instruments to verify relevance, and developed new items to address gaps. We then performed cognitive testing on new items and drafted an OA-K-specific instrument based on findings. RESULTS: We identified 52 existing PROMIS items and developed 24 new items across 14 domains. CONCLUSIONS: We developed a process for creating condition-specific instruments that bridge gaps in existing generic measures. If successful, the methodology will create instruments that efficiently gather the patient's perspective while allowing health systems, researchers, and other interested parties to monitor and compare outcomes over time, conditions, and populations.
Entities:
Keywords:
Healthcare quality; Mixed methods; Osteoarthritis of the knee; Patient-reported outcome measure
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