4.4 Article

When Patients Write the Guidelines: Patient Panel Recommendations for the Treatment of Rheumatoid Arthritis

期刊

ARTHRITIS CARE & RESEARCH
卷 68, 期 1, 页码 26-35

出版社

WILEY
DOI: 10.1002/acr.22758

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资金

  1. AR-PoWER Patient Powered Research Network (Arthritis Power)
  2. NATIONAL INSTITUTE OF ARTHRITIS AND MUSCULOSKELETAL AND SKIN DISEASES [K24AR060231] Funding Source: NIH RePORTER

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Objective. How best to involve patients in the development of clinical practice guideline (CPG) recommendations is not known. We sought to determine the feasibility and value of developing CPG recommendations based on a voting panel composed entirely of patients, with the ultimate goal of comparing the patients' recommendations to ones developed by a physician-dominated voting panel on the same clinical questions. Methods. Ten patients with rheumatoid arthritis completed 8 hours of training on evidence-based medicine and guideline development. They constituted a voting panel and, with 2 American College of Rheumatology staff with expertise in CPG development and a physician facilitator, subsequently met at a face-to-face meeting to develop recommendations. They applied the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) methodology to formulate recommendations on 18 questions for which there was evidence warranting moderate or high confidence. Results. The patient panel developed recommendations for 16 of the 18 questions; for the other 2, the panel thought there were insufficient data to support a recommendation. For 13 of the 16 questions, the patient panel recommended the same course of action as did the physician-dominated panel. Differences were due to how the 2 panels valued the balance between benefits and harms. Conclusion. Patient and physician-dominated panels developed the same recommendations for most questions for which there was evidence warranting moderate to high confidence. Additional experiences are necessary to advance the evidence necessary to determine what panel composition is optimal to produce the best guidelines.

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