{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T02:28:25Z","timestamp":1792722505940,"version":"4.5.0"},"reference-count":37,"publisher":"BMJ","issue":"4","content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":["BMJ Qual Saf"],"accepted":{"date-parts":[[2016,3,21]]},"published-print":{"date-parts":[[2017,4]]},"abstract":"<jats:sec>\n                  <jats:title>Objective<\/jats:title>\n                  <jats:p>To identify factors that influence the intentions of health professionals to improve their practice when confronted with clinical performance feedback, which is an essential first step in the audit and feedback mechanism.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>We conducted a theory-driven laboratory experiment with 41 individual professionals, and a field study in 18 centres in the context of a cluster-randomised trial of electronic audit and feedback in cardiac rehabilitation. Feedback reports were provided through a web-based application, and included performance scores and benchmark comparisons (high, intermediate or low performance) for a set of process and outcome indicators. From each report participants selected indicators for improvement into their action plan. Our unit of observation was an indicator presented in a feedback report (selected yes\/no); we considered selecting an indicator to reflect an intention to improve.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>We analysed 767 observations in the laboratory experiment and 614 in the field study, respectively. Each 10% decrease in performance score increased the probability of an indicator being selected by 54% (OR, 1.54; 95% CI 1.29% to 1.83%) in the laboratory experiment, and 25% (OR, 1.25; 95% CI 1.13% to 1.39%) in the field study. Also, performance being benchmarked as low and intermediate increased this probability in laboratory settings. Still, participants ignored the benchmarks in 34% (laboratory experiment) and 48% (field study) of their selections.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusions<\/jats:title>\n                  <jats:p>When confronted with clinical performance feedback, performance scores and benchmark comparisons influenced health professionals' intentions to improve practice. However, there was substantial variation in these intentions, because professionals disagreed with benchmarks, deemed improvement unfeasible or did not consider the indicator an essential aspect of care quality. These phenomena impede intentions to improve practice, and are thus likely to dilute the effects of audit and feedback interventions.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Trial registration number<\/jats:title>\n                  <jats:p>NTR3251, pre-results.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1136\/bmjqs-2015-004795","type":"journal-article","created":{"date-parts":[[2016,4,11]],"date-time":"2016-04-11T23:58:56Z","timestamp":1460419136000},"page":"279-287","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":46,"title":["How does audit and feedback influence intentions of health professionals to improve practice? A laboratory experiment and field study in cardiac rehabilitation"],"prefix":"10.1136","volume":"26","clinical-trial-number":[{"clinical-trial-number":"ntr3251","registry":"10.18810\/dutch-trial-register","type":"preResults"}],"author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7941-5281","authenticated-orcid":false,"given":"Wouter T","family":"Gude","sequence":"first","affiliation":[{"name":"Department of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mari\u00ebtte M","family":"van Engen-Verheul","sequence":"additional","affiliation":[{"name":"Department of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sabine N","family":"van der Veer","sequence":"additional","affiliation":[{"name":"Institute of Population Health, University of Manchester, Manchester, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nicolette F","family":"de Keizer","sequence":"additional","affiliation":[{"name":"Department of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Niels","family":"Peek","sequence":"additional","affiliation":[{"name":"Institute of Population Health, University of Manchester, Manchester, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"239","published-online":{"date-parts":[[2016,4,11]]},"reference":[{"key":"2025090410102916000_26.4.279.1","unstructured":"Damberg CL , Sorbero ME , Lovejoy SL , et al . 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