Routine provision of feedback from patient-reported outcome measurements to healthcare providers and patients in clinical practice.

BACKGROUND: Patient-reported outcomes measures (PROMs) assess a patient's subjective appraisal of health outcomes from their own perspective. Despite hypothesised benefits that feedback  on PROMs can support decision-making in clinical practice and improve outcomes, there is uncertainty surrounding the effectiveness of PROMs feedback. OBJECTIVES: To assess the effects of PROMs feedback to patients, or healthcare workers, or both on patient-reported health outcomes and processes of care. SEARCH METHODS: We searched MEDLINE, Embase, CENTRAL, two other databases and two clinical trial registries on 5 October 2020. We searched grey literature and consulted experts in the field. SELECTION CRITERIA: Two review authors independently screened and selected studies for inclusion. We included randomised trials directly comparing the effects on outcomes and processes of care of PROMs feedback to healthcare professionals and patients, or both with the impact of not providing such information. DATA COLLECTION AND ANALYSIS: Two groups of two authors independently extracted data from the included studies and evaluated study quality. We followed standard methodological procedures expected by Cochrane and EPOC. We used the GRADE approach to assess the certainty of the evidence. We conducted meta-analyses of the results where possible. MAIN RESULTS: We identified 116 randomised trials which assessed the effectiveness of PROMs feedback in improving processes or outcomes of care, or both in a broad range of disciplines including psychiatry, primary care, and oncology. Studies were conducted across diverse ambulatory primary and secondary care settings in North America, Europe and Australasia. A total of 49,785 patients were included across all the studies. The certainty of the evidence varied between very low and moderate. Many of the studies included in the review were at risk of performance and detection bias. The evidence suggests moderate certainty that PROMs feedback probably improves quality of life (standardised mean difference (SMD) 0.15, 95% confidence interval (CI) 0.05 to 0.26; 11 studies; 2687 participants), and leads to an increase in patient-physician communication (SMD 0.36, 95% CI 0.21 to 0.52; 5 studies; 658 participants), diagnosis and notation (risk ratio (RR) 1.73, 95% CI 1.44 to 2.08; 21 studies; 7223 participants), and disease control (RR 1.25, 95% CI 1.10 to 1.41; 14 studies; 2806 participants). The intervention probably makes little or no difference for general health perceptions (SMD 0.04, 95% CI -0.17 to 0.24; 2 studies, 552 participants; low-certainty evidence), social functioning (SMD 0.02, 95% CI -0.06 to 0.09; 15 studies; 2632 participants; moderate-certainty evidence), and pain (SMD 0.00, 95% CI -0.09 to 0.08; 9 studies; 2386 participants; moderate-certainty evidence). We are uncertain about the effect of PROMs feedback on physical functioning (14 studies; 2788 participants) and mental functioning (34 studies; 7782 participants), as well as fatigue (4 studies; 741 participants), as the certainty of the evidence was very low. We did not find studies reporting on adverse effects defined as distress following or related to PROM completion. AUTHORS' CONCLUSIONS: PROM feedback probably produces moderate improvements in communication between healthcare professionals and patients as well as in diagnosis and notation, and disease control, and small improvements to quality of life. Our confidence in the effects is limited by the risk of bias, heterogeneity and small number of trials conducted to assess outcomes of interest. It is unclear whether   many of these improvements are clinically meaningful or sustainable in the long term. There is a need for more high-quality studies in this area, particularly studies which employ cluster designs and utilise techniques to maintain allocation concealment.

Non-linear renal function decline is frequent in patients with type 2 diabetes who progress fast to end-stage renal disease and is associated with African-Caribbean ethnicity and HbA1c variability.

To our knowledge, there are no studies examining eGFR trajectories in an ethnically diverse cohort of T2DM patients with established DKD and long follow-up. We conducted a retrospective analysis of medical records of T2DM patients attending a specialist diabetes renal clinic in order to identify risk factors and specific eGFR trajectories associated with ESRD. There is limited information and long term follow-up on eGFR trajectories in ethnically diverse cohorts of T2DM patients with established diabetic kidney disease. We conducted a retrospective analysis of medical records of 398 T2DM patients (46.5% African-Carribean ethnicity) to identify risk factors and specific eGFR trajectories associated with end-stage renal disease (ESRD). A non-linear eGFR trajectory was observed in 59% of the 71 patients who reached ESRD. African-Caribbean ethnicity and glycaemic variability are independently associated with distinct non-linear eGFR trajectories that result in fast progression to ESRD. Clinicians should be aware that non-linear eGFR decline is frequent in patients with T2DM who have fast progression to ESRD. Predicting renal function decline based on patterns and early changes in eGFR trajectories and associated risk factors, may better enable individualized risk stratification and care for those at highest risk of rapid progression to ESRD.