Journal of patient-centered research and reviews · 2019 · 16 citations · 27 references
PharmacyInternal MedicineOutcomes ResearchPrimary CareClinical Outcome AssessmentDiabetes MellitusHealth Outcomes MeasurementOutcome MeasurementPatient-reported Outcome MeasuresPatient-reported OutcomesDiabetes Care Quality ImprovementDiabetes Mellitus AssessmentPatient-reported Outcome MeasurementPatient-reported Outcome Monitoring
PURPOSE: We sought to describe results of patient-reported outcome measures implemented among primary care patients with diabetes and explore factors associated with changes in scores over time. METHODS: Two organizations serving diverse patient populations collected the PROMIS-29 survey at baseline and 3-month follow-up for patients with type 2 diabetes. Bayesian regression analysis was used to examine the relationship between patient characteristics and changes in PROMIS-29 scores. Exploratory analyses assessed relationships between goal-setting and changes in scores. RESULTS: The study population reported substantially more problems with physical functioning (mean: 42.5 at Site 1 and 38.9 at Site 2) and pain interference (mean: 58.0 at Site 1 and 61.1 at Site 2) compared to the general population (mean: 50; standard deviation: 10). At least 33% of patients had a clinically meaningful change (ie, at least half the standard deviation, or 5 points) in each PROMIS domain. For pain interference, 55% had no change, 22% improved by 5 or more points, and 23% worsened by 5 or more points. Bayesian regression analyses suggest that chronic conditions, insurance status, and Hispanic ethnicity are likely associated with decreased functioning over time. Exploratory analyses found that setting a mental health goal did not appear to be associated with improvement for anxiety or depression. CONCLUSIONS: Use of patient-reported outcome measures in routine clinical care identified areas of functional limitations among people with diabetes. However, changes in participants' PROMIS-29 scores over time were minimal. Research is needed to understand patterns of change in global and domain-specific functioning, particularly among racial/ethnic minorities.
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R: A Language and Environment for Statistical Computing
R Core Team · 2000 · 353K citations · Full text
Natural Sciences, Computer Science, Statistical Computing +10
David Cella, William T. Riley, Arthur A. Stone et al. · Journal of Clinical Epidemiology · 2010 · 5.1K citations · Full text
Pharmacy, Health Services Administration, Health Assessment +15