Clinical Performance Feedback Intervention Theory (CP-FIT): a new theory for designing, implementing, and evaluating feedback in health care based on a systematic review and meta-synthesis of qualitative research

Benjamin Brown, Wouter T Gude, Thomas Blakeman, Sabine N van der Veer, Noah Ivers, Jill J Francis, Fabiana Lorencatto, Justin Presseau, Niels Peek, Gavin Daker-White, Benjamin Brown, Wouter T Gude, Thomas Blakeman, Sabine N van der Veer, Noah Ivers, Jill J Francis, Fabiana Lorencatto, Justin Presseau, Niels Peek, Gavin Daker-White

Abstract

Background: Providing health professionals with quantitative summaries of their clinical performance when treating specific groups of patients ("feedback") is a widely used quality improvement strategy, yet systematic reviews show it has varying success. Theory could help explain what factors influence feedback success, and guide approaches to enhance effectiveness. However, existing theories lack comprehensiveness and specificity to health care. To address this problem, we conducted the first systematic review and synthesis of qualitative evaluations of feedback interventions, using findings to develop a comprehensive new health care-specific feedback theory.

Methods: We searched MEDLINE, EMBASE, CINAHL, Web of Science, and Google Scholar from inception until 2016 inclusive. Data were synthesised by coding individual papers, building on pre-existing theories to formulate hypotheses, iteratively testing and improving hypotheses, assessing confidence in hypotheses using the GRADE-CERQual method, and summarising high-confidence hypotheses into a set of propositions.

Results: We synthesised 65 papers evaluating 73 feedback interventions from countries spanning five continents. From our synthesis we developed Clinical Performance Feedback Intervention Theory (CP-FIT), which builds on 30 pre-existing theories and has 42 high-confidence hypotheses. CP-FIT states that effective feedback works in a cycle of sequential processes; it becomes less effective if any individual process fails, thus halting progress round the cycle. Feedback's success is influenced by several factors operating via a set of common explanatory mechanisms: the feedback method used, health professional receiving feedback, and context in which feedback takes place. CP-FIT summarises these effects in three propositions: (1) health care professionals and organisations have a finite capacity to engage with feedback, (2) these parties have strong beliefs regarding how patient care should be provided that influence their interactions with feedback, and (3) feedback that directly supports clinical behaviours is most effective.

Conclusions: This is the first qualitative meta-synthesis of feedback interventions, and the first comprehensive theory of feedback designed specifically for health care. Our findings contribute new knowledge about how feedback works and factors that influence its effectiveness. Internationally, practitioners, researchers, and policy-makers can use CP-FIT to design, implement, and evaluate feedback. Doing so could improve care for large numbers of patients, reduce opportunity costs, and improve returns on financial investments.

Trial registration: PROSPERO, CRD42015017541.

Keywords: Clinical audit; Feedback; Learning health system; Performance measurement; Qualitative evidence synthesis; Qualitative research; Quality improvement; Theory.

Conflict of interest statement

Authors’ information

BB, TB and NI are academic primary care physicians. They have extensive experience as recipients, practitioners, and researchers of feedback. BB is expert in informatics-based feedback interventions. TB is expert in qualitative research methods. NI led the latest Cochrane review on feedback, and is internationally recognised as a leading authority on feedback interventions.

WG is a PhD candidate in Health Informatics, whose thesis focuses on evaluating feedback interventions.

SNV and NP are Health Informatics researchers. They have conducted influential systematic reviews on feedback interventions, and have extensive experience as practitioners and researchers of feedback – particularly in the fields of cardiac rehabilitation and intensive care. Their work has led to the national adoption of feedback interventions across The Netherlands.

JJ, FL and JP are academic psychologists and experts in behaviour change theory. They have extensive experience as practitioners and researchers of feedback. They have been involved in national trials in the UK aiming to optimise feedback regarding blood transfusions in hospital.

GDW is an experienced qualitative researcher and expert in its meta-synthesis. He has written influential guidance on meta-synthesis methods.

BB, NI, WG, NP, JJ, FL, and JP are founding members of the A&F MetaLab (www.ohri.ca/auditfeedback/): an international network of researchers promoting and facilitating the advancement of feedback research.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

JP is an Associate Editor for Implementation Science but was not involved in any editorial decisions for this manuscript. The other authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
Data synthesis process
Fig. 2
Fig. 2
Flowchart of study screening process
Fig. 3
Fig. 3
Clinical Performance Feedback Intervention Theory’s variables and explanatory mechanisms, and their influence on the feedback cycle. Solid arrows are necessary pathways for successful feedback. Dotted arrows represent potential pathways

References

    1. Boaden R, Harvey G, Moxham C, Proudlove N. Quality improvement: theory and practice in healthcare. London: NHS Institute for Innovation and Improvement; 2008.
    1. Scrivener R, Morrell C, Baker R, Redsell S, Shaw E, Stevenson K, et al. Principles for best practice in clinical audit. Oxon: Radcliffe Medical Press; 2002.
    1. Freeman T. Using performance indicators to improve health care quality in the public sector: a review of the literature. Health Serv Manag Res. 2002;15(May):126–137. doi: 10.1258/0951484021912897.
    1. Dowding D, Randell R, Gardner P, Fitzpatrick G, Dykes P, Favela J, et al. Dashboards for improving patient care: review of the literature. Int J Med Inform. 2015;84(2):87–100. doi: 10.1016/j.ijmedinf.2014.10.001.
    1. Ivers NM, Sales A, Colquhoun H, Michie S, Foy R, Francis JJ, et al. No more ‘business as usual’ with audit and feedback interventions: towards an agenda for a reinvigorated intervention. Implement Sci. 2014;9(1):14. doi: 10.1186/1748-5908-9-14.
    1. Pawson R, Tilley N. Realistic evaluation. London: Sage Publications; 1997. p. 256.
    1. Ivers NM, Grimshaw JM, Jamtvedt G, Flottorp S, O’Brien MA, French SD, et al. Growing literature, stagnant science? Systematic review, meta-regression and cumulative analysis of audit and feedback interventions in health care. J Gen Intern Med. 2014;29:1534. doi: 10.1007/s11606-014-2913-y.
    1. Ivers N, Jamtvedt G, Flottorp S, Young JM, Odgaard-Jensen J, French SD, et al. Audit and feedback: effects on professional practice and healthcare outcomes. In: Ivers N, et al., editors. Cochrane database of systematic reviews. Chichester: Wiley; 2012. pp. 1–227.
    1. Farley TA, Dalal MA, Mostashari F, Frieden TR. Deaths preventable in the U.S. by improvements in use of clinical preventive services. Am J Prev Med. 2010;38(6):600–609. doi: 10.1016/j.amepre.2010.02.016.
    1. O’Neill J. Antimicrobial resistance: tackling a crisis for the health and wealth of nations. London: Review on Antimicrobial Resistance; 2014.
    1. Brehaut JC, Colquhoun HL, Eva KW, Carroll K, Sales A, Michie S, et al. Practice feedback interventions: 15 suggestions for optimizing effectiveness. Ann Intern Med. 2016;164:435–441. doi: 10.7326/M15-2248.
    1. Colquhoun HL, Brehaut JC, Sales A, Ivers N, Grimshaw J, Michie S, et al. A systematic review of the use of theory in randomized controlled trials of audit and feedback. Implement Sci. 2013;8(1):66. doi: 10.1186/1748-5908-8-66.
    1. Michie S, West R, Campbell R, Brown J, Gainforth H. ABC of behaviour change theories. London: Silverback Publishing; 2014.
    1. Carver CS, Scheier MF. Control theory: a useful conceptual framework for personality-social, clinical, and health psychology. Psychol Bull. 1982;92:111–135. doi: 10.1037/0033-2909.92.1.111.
    1. Locke EA, Latham GP. Building a practically useful theory of goal setting and task motivation. A 35-year odyssey. Am Psychol. 2002;57:705–717. doi: 10.1037/0003-066X.57.9.705.
    1. Kluger A, DeNisi A. The effects of feedback interventions on performance: a historical review, a meta-analysis, and a preliminary feedback intervention theory. Psychol Bull. 1996;119:254–284. doi: 10.1037/0033-2909.119.2.254.
    1. Moore G, Audrey S, Barker M, Bonell C, Hardeman W, Moore L, et al. Process evaluation of complex interventions: UK Medical Research Council (MRC) guidance. 2014.
    1. Goud R, van Engen-Verheul M, de Keizer NF, Bal R, Hasman A, Hellemans IM, et al. The effect of computerized decision support on barriers to guideline implementation: a qualitative study in outpatient cardiac rehabilitation. Int J Med Inform. 2010;79(6):430–437. doi: 10.1016/j.ijmedinf.2010.03.001.
    1. Millery M, Shelley D, Wu D, Ferrari P, Tseng T-Y, Kopal H. Qualitative evaluation to explain success of multifaceted technology-driven hypertension intervention. Am J Manag Care. 2011;17(12):SP95–S102.
    1. Barnett-Page E, Thomas J. Methods for the synthesis of qualitative research: a critical review. BMC Med Res Methodol. 2009;9:59. doi: 10.1186/1471-2288-9-59.
    1. Noyes J, Popay J. Directly observed therapy and tuberculosis: how can a systematic review of qualitative research contribute to improving services? A qualitative meta-synthesis. J Adv Nurs. 2007;57(3):227–243. doi: 10.1111/j.1365-2648.2006.04092.x.
    1. Fishwick D, McGregor M, Drury M, Webster J, Rick J, Carroll C. BOHRF smoking cessation review. Buxton: Health and Safety Laboratory; 2012.
    1. Lorenc T, Pearson M, Jamal F, Cooper C, Garside R. The role of systematic reviews of qualitative evidence in evaluating interventions: a case study. Res Synth Methods. 2012;3(1):1–10. doi: 10.1002/jrsm.1036.
    1. Lins S, Hayder-Beichel D, Rucker G, Motschall E, Antes G, Meyer G, et al. Efficacy and experiences of telephone counselling for informal carers of people with dementia. Cochrane Database Syst Rev. 2014;9(1469–493X (Electronic)):CD009126.
    1. Brown B, Jameson D, Daker-White G, Buchan I, Ivers N, Peek N, et al. A meta-synthesis of findings from qualitative studies of audit and feedback interventions (CRD42015017541) 2015.
    1. Walters LA, Wilczynski NL, Haynes RB. Developing optimal search strategies for retrieving clinically relevant qualitative studies in EMBASE. Qual Health Res. 2006;16(1):162–168. doi: 10.1177/1049732305284027.
    1. Wilczynski NL, Marks S, Haynes RB. Search strategies for identifying qualitative studies in CINAHL. Qual Health Res. 2007;17(5):705–710. doi: 10.1177/1049732306294515.
    1. UTHealth. Search filters for various databases: Ovid Medline [Internet]: The University of Texas. University of Texas School of Public Health Library; 2014. Available from: . [Cited 8 Jan 2015]
    1. Boyce MB, Browne JP. Does providing feedback on patient-reported outcomes to healthcare professionals result in better outcomes for patients? A systematic review. Qual Life Res. 2013;22(9):2265–2278. doi: 10.1007/s11136-013-0390-0.
    1. Landis-Lewis Z, Brehaut JC, Hochheiser H, Douglas GP, Jacobson RS. Computer-supported feedback message tailoring: theory-informed adaptation of clinical audit and feedback for learning and behavior change. Implement Sci. 2015;10(1):1–12. doi: 10.1186/s13012-014-0203-z.
    1. Foy R, Eccles MP, Jamtvedt G, Young J, Grimshaw JM, Baker R. What do we know about how to do audit and feedback? Pitfalls in applying evidence from a systematic review. BMC Health Serv Res. 2005;5:50. doi: 10.1186/1472-6963-5-50.
    1. Foy R, MacLennan G, Grimshaw J, Penney G, Campbell M, Grol R. Attributes of clinical recommendations that influence change in practice following audit and feedback. J Clin Epidemiol. 2002;55(7):717–722. doi: 10.1016/S0895-4356(02)00403-1.
    1. Gardner B, Whittington C, McAteer J, Eccles MP, Michie S. Using theory to synthesise evidence from behaviour change interventions: the example of audit and feedback. Soc Sci Med. 2010;70(10):1618–1625. doi: 10.1016/j.socscimed.2010.01.039.
    1. Hysong SJ. Meta-analysis: audit and feedback features impact effectiveness on care quality. Med Care. 2009;47(3):356–363. doi: 10.1097/MLR.0b013e3181893f6b.
    1. van der Veer SN, de Keizer NF, Ravelli ACJ, Tenkink S, Jager KJ. Improving quality of care. A systematic review on how medical registries provide information feedback to health care providers. Int J Med Inform. 2010;79(5):305–323. doi: 10.1016/j.ijmedinf.2010.01.011.
    1. Brehaut JC, Eva KW. Building theories of knowledge translation interventions: use the entire menu of constructs. Implement Sci. 2012;7(1):114. doi: 10.1186/1748-5908-7-114.
    1. Lipworth W, Taylor N, Braithwaite J. Can the theoretical domains framework account for the implementation of clinical quality interventions? BMC Health Serv Res. 2013;13:530. doi: 10.1186/1472-6963-13-530.
    1. Booth A. Chapter 3: searching for studies. In: Booth A, Hannes K, Harden A, Harris J, Lewin S, Lockwood C, editors. Supplementary guidance for inclusion of qualitative research in Cochrane Systematic Reviews of Interventions. Adelaide: Cochrane Collaboration Qualitative Methods Group; 2011.
    1. Tong A, Sainsbury P, Craig J. Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups. Int J Qual Health Care. 2007;19(6):349–357. doi: 10.1093/intqhc/mzm042.
    1. Michie S, Richardson M, Johnston M, Abraham C, Francis J, Hardeman W, et al. The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: building an international consensus for the reporting of behavior change interventions. Ann Behav Med. 2013;46(1):81–95. doi: 10.1007/s12160-013-9486-6.
    1. Colquhoun H, Michie S, Sales A, Ivers N, Grimshaw JM, Carroll K, et al. Reporting and design elements of audit and feedback interventions: a secondary review. BMJ Qual Saf. 2016;(January):1–7.
    1. Walsh D, Downe S. Appraising the quality of qualitative research. Midwifery. 2006;22(2):108–119. doi: 10.1016/j.midw.2005.05.004.
    1. Campbell R, Pound P, Morgan M, Daker-White G, Britten N, Pill R, et al. Evaluating meta-ethnography: systematic analysis and synthesis of qualitative research. Health Technol Assess. 2011;15(1366–5278 (Print)):1–164.
    1. Ritchie J, Spencer L. Qualitative data analysis for applied policy research. In: Bryman A, Burgess R, editors. Analysing Qualitative Data. London: Routledge; 1994. p. 173–94.
    1. Pawson R. Evidence-based policy:a realist perspective. London: SAGE Publications; 2006.
    1. Byng R, Norman I, Redfern S. Using realistic evaluation to evaluate a practice-level intervention to improve primary healthcare for patients with long-term mental illness. Evaluation. 2005;11(1):69–93. doi: 10.1177/1356389005053198.
    1. Lewin S, Glenton C, Munthe-Kaas H, Carlsen B, Colvin CJ, Gülmezoglu M, et al. Using qualitative evidence in decision making for health and social interventions: an approach to assess confidence in findings from qualitative evidence syntheses (GRADE-CERQual) PLoS Med. 2015;12(10):e1001895. doi: 10.1371/journal.pmed.1001895.
    1. Ilgen DR, Fisher CD, Taylor MS. Consequences of individual feedback on behavior in organizations. J Appl Psychol. 1979;64(4):349–371. doi: 10.1037/0021-9010.64.4.349.
    1. Coiera E. Designing and evaluating information and communication systems. Guide to health informatics. 3. Boca Raton: CRC Press; 2015. pp. 151–154.
    1. Payne VL, Hysong SJ. Model depicting aspects of audit and feedback that impact physicians’ acceptance of clinical performance feedback. BMC Health Serv Res. 2016;16(1):260. doi: 10.1186/s12913-016-1486-3.
    1. Nouwens E, van Lieshout J, Wensing M. Determinants of impact of a practice accreditation program in primary care: a qualitative study. BMC Fam Pract. 2015;16:78. doi: 10.1186/s12875-015-0294-x.
    1. Boyce MB, Browne JP, Greenhalgh J. Surgeon’s experiences of receiving peer benchmarked feedback using patient-reported outcome measures: a qualitative study. Implement Sci. 2014;9(1):84. doi: 10.1186/1748-5908-9-84.
    1. Siddiqi K, Newell J. What were the lessons learned from implementing clinical audit in Latin America? Clin Gov An Int J. 2009;14(3):215–225. doi: 10.1108/14777270910976157.
    1. Ramsay AIG, Turner S, Cavell G, Oborne CA, Thomas RE, Cookson G, et al. Governing patient safety: lessons learned from a mixed methods evaluation of implementing a ward-level medication safety scorecard in two English NHS hospitals. BMJ Qual Saf. 2014;23(2):136–146. doi: 10.1136/bmjqs-2012-001730.
    1. Yi SG, Wray NP, Jones SL, Bass BL, Nishioka J, Brann S, et al. Surgeon-specific performance reports in general surgery: an observational study of initial implementation and adoption. J Am Coll Surg. 2013;217(4):636–647.e1. doi: 10.1016/j.jamcollsurg.2013.04.040.
    1. Festinger L. A theory of cognitive dissonance. Evanston: Row Peterson; 1957.
    1. Steele C. The psychology of self-affirmation: sustaining the integrity of the self. Adv Exp Soc Psychol. 1988;21:261–302.
    1. Damschroder LJ, Robinson CH, Francis J, Bentley DR, Krein SL, Rosland AM, et al. Effects of performance measure implementation on clinical manager and provider motivation. J Gen Intern Med. 2014;29(4):877–884. doi: 10.1007/s11606-014-3020-9.
    1. Meijers JMM, Halfens RJG, Mijnarends DM, Mostert H, Schols JMGA. A feedback system to improve the quality of nutritional care. Nutrition. 2013;29(7–8):1037–1041. doi: 10.1016/j.nut.2013.02.007.
    1. Deci EL, Ryan RM. Intrinsic motivation and self-determination in human behaviour. New York: Plenum Publishing Co.; 1985.
    1. Michie S, van Stralen MM, West R. The behaviour change wheel: a new method for characterising and designing behaviour change interventions. Implement Sci. 2011;6(1):42. doi: 10.1186/1748-5908-6-42.
    1. Gort M, Broekhuis M, Regts G. How teams use indicators for quality improvement - a multiple-case study on the use of multiple indicators in multidisciplinary breast cancer teams. Soc Sci Med. 2013;96:69–77. doi: 10.1016/j.socscimed.2013.06.001.
    1. Rotter JB. Internal versus external control of reinforcement: a case history of a variable. 1990. pp. 489–493.
    1. Wilkinson EK, McColl A, Exworthy M, Roderick P, Smith H, Moore M, et al. Reactions to the use of evidence-based performance indicators in primary care: a qualitative study. Qual Health Care. 2000;9(3):166–174. doi: 10.1136/qhc.9.3.166.
    1. Greenhalgh T, Robert G, Bate P, Kyriakidou O, Macfarlane F, Peacock R. How to spread good ideas: a systematic review of the literature on diffusion, dissemination and sustainability of innovations in health service delivery and organisation. London: National Coordinating Centre for the Service Delivery and Organisation; 2004.
    1. Venkatesh V, Bala H. Technology acceptance model 3 and a research agenda on interventions. Decis Sci. 2008;39(2):273–315. doi: 10.1111/j.1540-5915.2008.00192.x.
    1. Cameron M, Penney G, Maclennan G, McLeer S, Walker A. Impact on maternity professionals of novel approaches to clinical audit feedback. Eval Health Prof. 2007;30(1):75–95. doi: 10.1177/0163278706297337.
    1. Palmer C, Bycroft J, Healey K, Field A, Ghafel M. Can formal collaborative methodologies improve quality in primary health care in New Zealand? Insights from the EQUIPPED Auckland Collaborative. J Prim Health Care. 2012;4(4):328–336. doi: 10.1071/HC12328.
    1. Groene O, Klazinga N, Kazandjian V, Lombrail P, Bartels P. The World Health Organization Performance Assessment Tool for Quality Improvement in Hospitals (PATH): an analysis of the pilot implementation in 37 hospitals. Int J Qual Health Care. 2008;20(3):155–161. doi: 10.1093/intqhc/mzn010.
    1. Chadwick LM, Macphail A, Ibrahim JE, Mcauliffe L, Koch S, Wells Y. Senior staff perspectives of a quality indicator program in public sector residential aged care services: a qualitative cross-sectional study in Victoria, Australia. Aust Health Rev. 2016;40(1):54–62. doi: 10.1071/AH14197.
    1. Kristensen H, Hounsgaard L. Evaluating the impact of audits and feedback as methods for implementation of evidence in stroke rehabilitation. Br J Occup Ther. 2014;77(5):251–259. doi: 10.4276/030802214X13990455043520.
    1. Nessim C, Bensimon CM, Hales B, Laflamme C, Fenech D, Smith A. Surgical site infection prevention: a qualitative analysis of an individualized audit and feedback model. J Am Coll Surg. 2012;215(6):850–857. doi: 10.1016/j.jamcollsurg.2012.08.007.
    1. Jeffs L, Beswick S, Lo J, Lai Y, Chhun A, Campbell H. Insights from staff nurses and managers on unit-specific nursing performance dashboards: a qualitative study. BMJ Qual Saf. 2014;23(September):1–6.
    1. Mannion R, Goddard M. Impact of published clinical outcomes data: case study in NHS hospital trusts. BMJ. 2001;323(7307):260–263. doi: 10.1136/bmj.323.7307.260.
    1. Kirschner K, Braspenning J, Jacobs JEA, Grol R. Experiences of general practices with a participatory pay-for-performance program: a qualitative study in primary care. Aust J Prim Health. 2013;19(2):102–106. doi: 10.1071/PY12032.
    1. Vessey I. Cognitive fit: a theory-based analysis of the graphs versus tables literature. Decis Sci. 1991;22(2):219–240. doi: 10.1111/j.1540-5915.1991.tb00344.x.
    1. Festinger L. A theory of social comparison processes. Hum Relat. 1954;7:117–140. doi: 10.1177/001872675400700202.
    1. Cialdini RB. Influence: the psychology of persuasion. Cambridge: Collins; 2007. pp. 1–30.
    1. Merton RK. Continuities in the theory of reference groups and social structure. In: Merton RK, editor. Social theory and social structure. Glencoe: Free Press; 1957.
    1. Ammenwerth E, Iller C, Mahler C. IT-adoption and the interaction of task, technology and individuals: a fit framework and a case study. BMC Med Inform Decis Mak. 2006;6:3. doi: 10.1186/1472-6947-6-3.
    1. DeLone WH, McLean E. The DeLone and McLean model of information systems success: a ten-year updated. J Manag Inf Syst. 2003;19(4):9–30. doi: 10.1080/07421222.2003.11045748.
    1. Guldberg TL, Vedsted P, Lauritzen T, Zoffmann V. Suboptimal quality of type 2 diabetes care discovered through electronic feedback led to increased nurse-GP cooperation. A qualitative study. Prim Care Diabetes. 2010;4(1):33–39. doi: 10.1016/j.pcd.2010.01.001.
    1. Sweller J, van Merrienboer JJG, Paas FGWC. Cognitive architecture and instructional design. Educ Psychol Rev. 1998;10(3):251–296. doi: 10.1023/A:1022193728205.
    1. Shepherd N, Meehan TJ, Davidson F, Stedman T. An evaluation of a benchmarking initiative in extended treatment mental health services. Aust Health Rev. 2010;34(3):328–333. doi: 10.1071/AH09698.
    1. Exworthy M, Wilkinson EK, McColl A, Moore M, Roderick P, Smith H, et al. The role of performance indicators in changing the autonomy of the general practice profession in the UK. Soc Sci Med. 2003;56(7):1493–1504. doi: 10.1016/S0277-9536(02)00151-X.
    1. Cresswell KM, Sadler S, Rodgers S, Avery A, Cantrill J, Murray SA, et al. An embedded longitudinal multi-faceted qualitative evaluation of a complex cluster randomized controlled trial aiming to reduce clinically important errors in medicines management in general practice. Trials. 2012;13(1):78. doi: 10.1186/1745-6215-13-78.
    1. Dixon-Woods M, Redwood S, Leslie M, Minion J, Martin GP, Coleman JJ. Improving quality and safety of care using “technovigilance”: an ethnographic case study of secondary use of data from an electronic prescribing and decision support system. Milbank Q. 2013;91(3):424–454. doi: 10.1111/1468-0009.12021.
    1. Turner S, Higginson J, Oborne CA, Thomas RE, Ramsay AIG, Fulop NJ. Codifying knowledge to improve patient safety: a qualitative study of practice-based interventions. Soc Sci Med. 2014;113:169–176. doi: 10.1016/j.socscimed.2014.05.031.
    1. Vachon B, Desorcy B, Camirand M, Rodrigue J, Quesnel L, Guimond C, et al. Engaging primary care practitioners in quality improvement: making explicit the program theory of an interprofessional education intervention. BMC Health Serv Res. 2013;13:106. doi: 10.1186/1472-6963-13-106.
    1. Ivers N, Barnsley J, Upshur R, Tu K, Shah B, Grimshaw J, et al. My approach to this job is... one person at a time. Can Fam Physician. 2014;60:258–266.
    1. Morrell C, Harvey G, Kitson A. Practitioner based quality improvement: a review of the Royal College of Nursing’s dynamic standard setting system. Qual Health Care. 1997;6(1):29–34. doi: 10.1136/qshc.6.1.29.
    1. Grant AM, Guthrie B, Dreischulte T. Developing a complex intervention to improve prescribing safety in primary care: mixed methods feasibility and optimisation pilot study. BMJ Open. 2014;4(1):e004153 A.M. Grant, Quality, Safety and Informatics Group, Medical Research Institute, University of Dundee, Dundee, United Kingdom. E-mail: a.m.grant@dundee.ac.uk: BMJ Publishing Group (Tavistock Square, London WC1H 9JR, United Kingdom).
    1. Ölander F, ThØgersen J. Understanding of consumer behaviour as a prerequisite for environmental protection. J Consum Policy. 1995;18(4):345–385. doi: 10.1007/BF01024160.
    1. Tierney S, Kislov R, Deaton C. A qualitative study of a primary-care based intervention to improve the management of patients with heart failure: the dynamic relationship between facilitation and context. BMC Fam Pract. 2014;15(153):1–10.
    1. Powell AA, White KM, Partin MR, Halek K, Hysong SJ, Zarling E, et al. More than a score: a qualitative study of ancillary benefits of performance measurement. BMJ Qual Saf. 2014;23(February):1–8.
    1. Ferlie E, Shortell S. Improving the quality of health care in the United Kingdom and the United States: a framework for change. Milbank Q. 2000;79(2):281–315. doi: 10.1111/1468-0009.00206.
    1. Siddiqi K, Volz A, Armas L, Otero L, Ugaz R, Ochoa E, et al. Could clinical audit improve the diagnosis of pulmonary tuberculosis in Cuba, Peru and Bolivia? Tropical Med Int Health. 2008;13(4):566–578. doi: 10.1111/j.1365-3156.2008.02035.x.
    1. Hysong SJ, Knox MK, Haidet P. Examining clinical performance feedback in patient-aligned care teams. J Gen Intern Med. 2014;29(Suppl 2):S667–S674. doi: 10.1007/s11606-013-2707-7.
    1. Damschroder LJ, Aron DC, Keith RE, Kirsh SR, Alexander JA, Lowery JC. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implement Sci. 2009;4:50. doi: 10.1186/1748-5908-4-50.
    1. Asch SE. Studies of independence and conformity: I. A minority of one against a unanimous majority. Psychol Monogr Gen Appl. 1956;70(9):1–70. doi: 10.1037/h0093718.
    1. Wright FC, Fitch M, Coates AJ, Simunovic M. A qualitative assessment of a provincial quality improvement strategy for pancreatic cancer surgery. Ann Surg Oncol. 2011;18(3):629–635. doi: 10.1245/s10434-010-1337-0.
    1. Dixon-Woods M, Leslie M, Bion J, Tarrant C. What counts? An ethnographic study of infection data reported to a patient safety program. Milbank Q. 2012;90(3):548–591. doi: 10.1111/j.1468-0009.2012.00674.x.
    1. Cabana Michael D., Rand Cynthia S., Powe Neil R., Wu Albert W., Wilson Modena H., Abboud Paul-André C., Rubin Haya R. Why Don't Physicians Follow Clinical Practice Guidelines? JAMA. 1999;282(15):1458. doi: 10.1001/jama.282.15.1458.
    1. Pawson R, Greenhalgh J, Brennan C. Demand management for planned care: a realist synthesis. 2016;4(2).
    1. Powell AA, White KM, Partin MR, Halek K, Christianson JB, Neil B, et al. Unintended consequences of implementing a national performance measurement system into local practice. J Gen Intern Med. 2012;27(4):405–412. doi: 10.1007/s11606-011-1906-3.
    1. Miller NE, Dollard J. Social learning and imitation. London: Kegan Paul; 1945.
    1. Beckman H, Suchman AL, Curtin K, Greene RA. Physician reactions to quantitative individual performance reports. Am J Med Qual. 2006;21:192–199. doi: 10.1177/1062860606287577.
    1. Rogers EM. Diffusion of innovations. Illinois: Free Press of Glencoe; 1962. p. 367.
    1. Bandura A. Self-efficacy: toward a unifying theory of behavioral change. Psychological review. 1977. pp. 191–215.
    1. Healthcare Quality Improvement Partnership . The National Clinical Audit Programme. 2018.
    1. Nelson EC, Dixon-Woods M, Batalden PB, Homa K, Van Citters AD, Morgan TS, et al. Patient focused registries can improve health, care, and science. BMJ. 2016;354(July):1–6.
    1. Foskett-Tharby R, Hex N, Chuter A, Gill P. Challenges of incentivising patient centred care. BMJ. 2017;359:6–11.
    1. Roland M, Guthrie B. Quality and outcomes framework: what have we learnt? BMJ. 2016;354:i4060. doi: 10.1136/bmj.i4060.
    1. Committee on the Learning Health Care Systemin America . Best care at lower cost: the path to continuously learning health care in America. Washington DC: The National Academies Press; 2013. pp. 27–36.
    1. Tuti T, Nzinga J, Njoroge M, Brown B, Peek N, English M, et al. A systematic review of use of behaviour change theory in electronic audit and feedback interventions: intervention effectiveness and use of behaviour change theory. Implement Sci. 2017;12:61. doi: 10.1186/s13012-017-0590-z.
    1. Redwood S, Ngwenya NB, Hodson J, Ferner RE, Coleman JJ. Effects of a computerized feedback intervention on safety performance by junior doctors: results from a randomized mixed method study. BMC Med Inf Decis Mak. 2013;13(1):63. doi: 10.1186/1472-6947-13-63.
    1. Gude W, van der Veer S, de Keizer N, Coiera E, Peek N. Optimising digital health informatics through non-obstrusive quantitative process evaluation. Stud Health Technol Inform. 2016;228:594.
    1. Brown B, Peek N, Buchan I. The case for conceptual and computable cross-fertilization between audit and feedback and clinical decision support. Stud Heal Technol Inform. 2015;216:419–423.
    1. Goodhue DL, Thompson RL, Goodhue BDL. Task-technology fit and individual performance. MIS Q. 1995;19(2):213–236. doi: 10.2307/249689.
    1. Boyce MB, Browne JP, Greenhalgh J. The experiences of professionals with using information from patient-reported outcome measures to improve the quality of healthcare: a systematic review of qualitative research. BMJ Qual Saf. 2014;23(6):508–518. doi: 10.1136/bmjqs-2013-002524.
    1. Greenhalgh J, Dalkin S, Gooding K, Gibbons E, Wright J, Meads D, et al. Functionality and feedback: a realist synthesis of the collation, interpretation and utilisation of patient-reported outcome measures data to improve patient care. Heal Serv. 2017;5(2):1.
    1. Colquhoun HL, Carroll K, Eva KW, Grimshaw JM, Ivers N, Michie S, et al. Advancing the literature on designing audit and feedback interventions: identifying theory-informed hypotheses. Implement Sci. 2017;12(1):1–10. doi: 10.1186/s13012-016-0533-0.
    1. Harvey Gill, Jas Pauline, Walshe Kieran. Analysing organisational context: case studies on the contribution of absorptive capacity theory to understanding inter-organisational variation in performance improvement. BMJ Quality & Safety. 2014;24(1):48–55. doi: 10.1136/bmjqs-2014-002928.
    1. Dolan JG, Veazie PJ, Russ AJ. Development and initial evaluation of a treatment decision dashboard. BMC Med Inform Decis Mak. 2013;13:51. doi: 10.1186/1472-6947-13-51.
    1. Mangera A, Parys B. BAUS Section of Endourology national Ureteroscopy audit: Setting the standards for revalidation. J Clin Urol. 2013;6:45–49. doi: 10.1177/1875974212465536.
    1. Lester HE, Hannon KL, Campbell SM. Identifying unintended consequences of quality indicators: a qualitative study. BMJ Qual Saf. 2011;20(12):1057–1061. doi: 10.1136/bmjqs.2010.048371.
    1. Bowles EJA, Geller BM. Best ways to provide feedback to radiologists on mammography performance. AJR Am J Roentgenol. 2009;193(1):157–164. doi: 10.2214/AJR.08.2051.
    1. Harrison Christopher J., Könings Karen D., Schuwirth Lambert, Wass Valerie, van der Vleuten Cees. Barriers to the uptake and use of feedback in the context of summative assessment. Advances in Health Sciences Education. 2014;20(1):229–245. doi: 10.1007/s10459-014-9524-6.
    1. de Korne DF, van Wijngaarden JDH, Sol KJCA, Betz R, Thomas RC, Schein OD, et al. Hospital benchmarking: are U.S. eye hospitals ready? Health Care Manag Rev. 2012;37(2):187–198. doi: 10.1097/HMR.0b013e31822aa46d.
    1. Friedberg MW, SteelFisher GK, Karp M, Schneider EC. Physician groups’ use of data from patient experience surveys. J Gen Intern Med. 2011;26(5):498–504. doi: 10.1007/s11606-010-1597-1.
    1. Robinson AC, Roth RE, MacEachren AM. Designing a web-based learning portal for geographic visualization and analysis in public health. Heal Informatics J. 2011;17(3):191–208. doi: 10.1177/1460458211409718.
    1. EPOC. Data collection checklist. Oxford: Cochrane Effective Practice and Organisation of Care Review Group; 2002.
    1. Sargeant J, Lockyer J, Mann K, Holmboe E, Silver I, Armson H, et al. Facilitated reflective performance feedback: developing an evidence- and theory-based model that builds relationship, explores reactions and content, and coaches for performance change (R2C2) Acad Med. 2015;90(12):1698. doi: 10.1097/ACM.0000000000000809.
    1. HQIP. Criteria and indicators of best practice in clinical audit. London: Healthcare Quality Improvement Partnership; 2009.
    1. Ahearn MD, Kerr SJ. General practitioners’ perceptions of the pharmaceutical decision-support tools in their prescribing software. Med J Aust. 2003;179(1):34–37.
    1. Lucock M, Halstead J, Leach C, Barkham M, Tucker S, Randal C, et al. A mixed-method investigation of patient monitoring and enhanced feedback in routine practice: barriers and facilitators. Psychother Res. 2015;25(6):633–646. doi: 10.1080/10503307.2015.1051163.
    1. Andersen RS, Hansen RP, Sondergaard J, Bro F. Learning based on patient case reviews: an interview study. BMC Med Educ. 2008;8:43. doi: 10.1186/1472-6920-8-43.
    1. Zaydfudim V, Dossett LA, Starmer JM, Arbogast PG, Feurer ID, Ray WA, et al. Implementation of a real-time compliance dashboard to help reduce SICU ventilator-associated pneumonia with the ventilator bundle. Arch Surg. 2009;144(7):656–662. doi: 10.1001/archsurg.2009.117.
    1. Carter P, Ozieranski P, McNicol S, Power M, Dixon-Woods M. How collaborative are quality improvement collaboratives: a qualitative study in stroke care. Implement Sci. 2014;9(1):32. doi: 10.1186/1748-5908-9-32.
    1. Hysong SJ, Best RG, Pugh JA. Audit and feedback and clinical practice guideline adherence: making feedback actionable. Implement Sci. 2006;1(1):9. doi: 10.1186/1748-5908-1-9.
    1. Noyes J, Booth A, Hannes K, Harden A, Harris J, Lewin S, et al. Supplementary guidance for inclusion of qualitative research in Cochrane Systematic Reviews of Interventions: Cochrane Collaboration Qualitative Methods Group; 2011.
    1. Rodriguez HP, Von Glahn T, Elliott MN, Rogers WH, Safran DG. The effect of performance-based financial incentives on improving patient care experiences: a statewide evaluation. J Gen Intern Med. 2009;24(12):1281–1288. doi: 10.1007/s11606-009-1122-6.
    1. Prior M, Elouafkaoui P, Elders A, Young L, Duncan EM, Newlands R, et al. Evaluating an audit and feedback intervention for reducing antibiotic prescribing behaviour in general dental practice (the RAPiD trial): a partial factorial cluster randomised trial protocol. Implement Sci. 2014;9:50. doi: 10.1186/1748-5908-9-50.
    1. B. H. Audits: Pitfalls and good practice. Pharmaceutical Journal. B. Hebron, City and Sandwell Hospitals, Birmingham: Pharmaceutical Press; 2008. p. 250.
    1. Brand C, Lam SKL, Roberts C, Gorelik A, Amatya B, Smallwood D, et al. Measuring performance to drive improvement: development of a clinical indicator set for general medicine. Intern Med J. 2009;39(6):361–369. doi: 10.1111/j.1445-5994.2009.01913.x.
    1. Bachlani AM, Gibson J. Why not patient feedback on psychiatric services? Psychiatrist. 2011;35:117. doi: 10.1192/pb.35.3.117a.
    1. Schoonover-Shoffner KL. The usefulness of formal objective performance feedback: an exploration of meaning. Lawrence: University of Kansas; 1995.
    1. Grando VT, Rantz MJ, Maas M. Nursing home staff’s views on quality improvement interventions: a follow-up study. J Gerontol Nurs. 2007;33(1):40–47.
    1. Mcdonald R, Roland M. Pay for performance in primary care in England and California: comparison of unintended consequences. 2009. pp. 121–127.
    1. Ajzen I. The theory of planned behavior. Organ Behav Hum Decis Process. 1991;50(2):179–211. doi: 10.1016/0749-5978(91)90020-T.
    1. Milgram S. Obedience to authority: an experimental view. New York: Harper & Row; 1974.
    1. Berkowitz AD. The social norms approach: theory, research, and annotated bibliography. 2004.
    1. McDonald R, White J, Marmor TR. Paying for performance in primary medical care: learning about and learning from “success” and “failure” in England and California. J Health Polit Policy Law. 2009;34(5):747–776. doi: 10.1215/03616878-2009-024.
    1. Sondergaard J, Andersen M, Kragstrup J, Hansen P, Freng GL. Why has postal prescriber feedback no substantial impact on general practitioners’ prescribing practice? A qualitative study. Eur J Clin Pharmacol. 2002;58(2):133–136. doi: 10.1007/s00228-002-0455-4.
    1. Ross Joseph S, Williams Linda, Damush Teresa M, Matthias Marianne. Physician and other healthcare personnel responses to hospital stroke quality of care performance feedback: a qualitative study. BMJ Quality & Safety. 2015;25(6):441–447. doi: 10.1136/bmjqs-2015-004197.

Source: PubMed

Sponzoři a spolupracovníci

Zdravotní podmínky

Drogové intervence

3
Předplatit