Chris Gibbons1, Ian Porter2, Daniela C Gonçalves-Bradley3,4, Stanimir Stoilov5, Ignacio Ricci-Cabello6, Elena Tsangaris7, Jaheeda Gangannagaripalli8, Antoinette Davey8, Elizabeth J Gibbons9, Anna Kotzeva10, Jonathan Evans8, Philip J van der Wees11, Evangelos Kontopantelis12, Joanne Greenhalgh13, Peter Bower14, Jordi Alonso15, Jose M Valderas16. 1. Harvard Medical School, Boston, MA, USA. 2. Health Services & Policy Research, University of Exeter Medical School, Exeter, UK. 3. Center for Health Technology and Services Research (CINTESIS), Porto, Portugal. 4. Nuffield Department of Population Health, University of Oxford, Oxford, UK. 5. College of Medicine and Health, University of Exeter Medical School, University of Exeter, Exeter, UK. 6. Primary Care Research Unit, Instituto de Investigación Sanitaria Illes Balears, Palma de Mallorca, Spain. 7. Department of Surgery, Harvard Medical School, Boston, USA. 8. Health Services and Policy Research Group, University of Exeter Medical School, Exeter, UK. 9. PROM Group, Nuffield Department of Population Health, University of Oxford, Oxford, UK. 10. Health Technology Assessment Department, Agency for Health Quality and Assessment of Catalonia (AQuAS), Barcelona, Spain. 11. Radboud University Medical Center, Radboud Institute for Health Sciences, Scientific Institute for Quality of Healthcare (IQ healthcare), Nijmegen, Netherlands. 12. Centre for Health Informatics, Institute of Population Health, The University of Manchester, Manchester, UK. 13. School of Sociology and Social Policy, University of Leeds, Leeds, UK. 14. NIHR School for Primary Care Research, Manchester Academic Health Science Centre, Division of Population Health, Health Services Research and Primary Care, University of Manchester, Manchester, UK. 15. CIBER Epidemiologia y Salud Publica (CIBERESP), IMIM-Hospital del mar, Barcelona, Spain. 16. Health Services & Policy Research, Exeter Collaboration for Academic Primary Care (APEx), NIHR School for Primary Care Research, NIHR ARC South West Peninsula (PenARC), University of Exeter, Exeter, UK.
Abstract
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.
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.
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