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BACKGROUND: Enhancing quality of life for people with long-term conditions by monitoring patient-reported outcome measure scores is a key domain of health care policy. This study investigated the responsiveness of patient-reported outcome measures for long-term conditions. METHODS: A cohort survey was conducted in 33 primary care practices and 4485 patients (1334 asthma, 567 chronic obstructive pulmonary disease, 1121 diabetes, 525 epilepsy, 520 heart failure and 418 stroke) were sent a baseline survey containing a generic (EQ-5D) and a disease-specific measure. Baseline respondents were sent a follow-up after 1 year. Differences in scores for each long-term condition were assessed by paired t-tests. The relationship between scores and self-reported 'change in health' was assessed by analysis of variance. RESULTS: The baseline achieved a 38.4% response rate and the follow-up 71.5%. The only significant difference for the EQ-5D was found for the Visual Analogue Scale in heart failure between baseline and follow-up, and for change in health. Significant differences between baseline and follow-up scores were found on the disease-specific measures for 1 asthma dimension and 1 stroke dimension. No significant differences were found for other conditions. Significant differences between self-reported change in health and the disease-specific measures were found for 4 asthma dimensions and 2 stroke dimensions. CONCLUSIONS: Few significant differences were found between the baseline and follow up or between 'change in health' and PROMs scores. This could be explained by the time frame of one year being too short for change to occur or by the PROMs not being responsive enough to change in a primary care sample. The latter is unlikely as the PROMs were in part chosen for their responsiveness to change. The baseline response rates may mean that the sample is not representative, and stable patients may have been more likely to participate. If PROMs are to be used routinely to monitor outcomes in LTCs, further research is needed to maximize response rates, to ensure that the PROMs used are reliable, valid and sensitive enough to detect change and that the time frame for data collection is appropriate.

Original publication




Journal article


Health Qual Life Outcomes

Publication Date





Adult, Aged, Aged, 80 and over, Asthma, Chronic Disease, Cohort Studies, Diabetes Mellitus, Disease Progression, Epilepsy, Female, Health Status, Health Status Indicators, Heart Failure, Humans, Male, Middle Aged, Patient Outcome Assessment, Primary Health Care, Pulmonary Disease, Chronic Obstructive, Quality of Life, Self Report, Stroke, Young Adult