Evaluating the effect of a web-based quality improvement system with feedback and outreach visits on guideline concordance in the field of cardiac rehabilitation: rationale and study protocol

BackgroundImplementation of clinical practice guidelines into daily care is hampered by a variety of barriers related to professional knowledge and collaboration in teams and organizations. To improve guideline concordance by changing the clinical decision-making behavior of professionals, computerized decision support (CDS) has been shown to be one of the most effective instruments. However, to address barriers at the organizational level, additional interventions are needed. Continuous monitoring and systematic improvement of quality are increasingly used to achieve change at this level in complex health care systems. The study aims to assess the effectiveness of a web-based quality improvement (QI) system with indicator-based performance feedback and educational outreach visits to overcome organizational barriers for guideline concordance in multidisciplinary teams in the field of cardiac rehabilitation (CR).MethodsA multicenter cluster-randomized trial with a balanced incomplete block design will be conducted in 18 Dutch CR clinics using an electronic patient record with CDS at the point of care. The intervention consists of (i) periodic performance feedback on quality indicators for CR and (ii) educational outreach visits to support local multidisciplinary QI teams focussing on systematically improving the care they provide. The intervention is supported by a web-based system which provides an overview of the feedback and facilitates development and monitoring of local QI plans. The primary outcome will be concordance to national CR guidelines with respect to the CR needs assessment and therapy indication procedure. Secondary outcomes are changes in performance of CR clinics as measured by structure, process and outcome indicators, and changes in practice variation on these indicators. We will also conduct a qualitative process evaluation (concept-mapping methodology) to assess experiences from participating CR clinics and to gain insight into factors which influence the implementation of the intervention.DiscussionTo our knowledge, this will be the first study to evaluate the effect of providing performance feedback with a web-based system that incorporates underlying QI concepts. The results may contribute to improving CR in the Netherlands, increasing knowledge on facilitators of guideline implementation in multidisciplinary health care teams and identifying success factors of multifaceted feedback interventions.Trial registrationNTR3251.

[1]  Kathrin Damm,et al.  Effectiveness of nonpharmacological secondary prevention of coronary heart disease , 2010, European journal of cardiovascular prevention and rehabilitation : official journal of the European Society of Cardiology, Working Groups on Epidemiology & Prevention and Cardiac Rehabilitation and Exercise Physiology.

[2]  M. Cabana,et al.  Why don't physicians follow clinical practice guidelines? A framework for improvement. , 1999, JAMA.

[3]  D. Bates,et al.  Mixed-Effects Models in S and S-PLUS , 2001 .

[4]  Reulings Pg,et al.  [Cardiac rehabilitation with lifestyle counselling after myocardial infarction: it helps, but not everyone undergoes it]. , 2012 .

[5]  A. Hasman,et al.  Effect of guideline based computerised decision support on decision making of multidisciplinary teams: cluster randomised trial in cardiac rehabilitation , 2009, BMJ : British Medical Journal.

[6]  Receipt of outpatient cardiac rehabilitation among heart attack survivors--United States, 2005. , 2008, MMWR. Morbidity and mortality weekly report.

[7]  N. D. de Keizer,et al.  Revision of the Dutch clinical algorithm for assessing patient needs in cardiac rehabilitation based on identified implementation problems , 2012, European journal of preventive cardiology.

[8]  E. A. Locke,et al.  Building a practically useful theory of goal setting and task motivation. A 35-year odyssey. , 2002, The American psychologist.

[9]  Gail Ironson,et al.  A short social support measure for patients recovering from myocardial infarction: the ENRICHD Social Support Inventory. , 2003, Journal of cardiopulmonary rehabilitation.

[10]  Mary Kane,et al.  Concept Mapping for Planning and Evaluation , 2006 .

[11]  S. Powell,et al.  Psychometric characteristics of the Multidimensional Scale of Perceived Social Support. , 1990, Journal of personality assessment.

[12]  A. Hasman,et al.  Effect of guideline based computerised decision support on decision making of multidisciplinary teams: cluster randomised trial in cardiac rehabilitation , 2009, BMJ : British Medical Journal.

[13]  N. Oldridge,et al.  The MacNew heart disease health-related quality of life instrument: Reference data for users , 2002, Quality of Life Research.

[14]  R. Spitzer,et al.  Validation and utility of a self-report version of PRIME-MD: the PHQ primary care study. Primary Care Evaluation of Mental Disorders. Patient Health Questionnaire. , 1999, JAMA.

[15]  J. Denollet,et al.  Poor perceived social support in implantable cardioverter defibrillator (ICD) patients and their partners: cross-validation of the multidimensional scale of perceived social support. , 2009, Psychosomatics.

[16]  H. McGee,et al.  Cardiac rehabilitation in Europe: results from the European Cardiac Rehabilitation Inventory Survey , 2010, European journal of cardiovascular prevention and rehabilitation : official journal of the European Society of Cardiology, Working Groups on Epidemiology & Prevention and Cardiac Rehabilitation and Exercise Physiology.

[17]  G. J. Langley,et al.  The improvement guide : a practical approach to enhancing organizational performance , 1996 .

[18]  F. Carre,et al.  Secondary prevention through cardiac rehabilitation: physical activity counselling and exercise training: key components of the position paper from the Cardiac Rehabilitation Section of the European Association of Cardiovascular Prevention and Rehabilitation. , 2010, European heart journal.

[19]  J. Grimshaw,et al.  From best evidence to best practice: effective implementation of change in patients' care , 2003, The Lancet.

[20]  P. Fayers,et al.  Determinants of the intracluster correlation coefficient in cluster randomized trials: the case of implementation research , 2005, Clinical trials.

[21]  Arie Hasman,et al.  Development of a guideline-based decision support system with explanation facilities for outpatient therapy , 2008, Comput. Methods Programs Biomed..

[22]  A. Beck,et al.  An inventory for measuring clinical anxiety: psychometric properties. , 1988, Journal of consulting and clinical psychology.

[23]  P. G. Reulings,et al.  [Cardiac rehabilitation with lifestyle counselling after myocardial infarction: it helps, but not everyone undergoes it]. , 2012, Nederlands tijdschrift voor geneeskunde.

[24]  Rosemary K. Rushmer,et al.  Healthcare professionals’ views on clinician engagement in quality improvement , 2007 .

[25]  G. Murphy,et al.  Concept mapping for planning and evaluation , 2007, Journal of Management & Organization.

[26]  Niels Peek,et al.  Cardiac rehabilitation uptake and its determinants in the Netherlands , 2013, European journal of preventive cardiology.

[27]  S. Vanheule,et al.  Pilot Study: Does the Five Shot Questionnaire Give an Indication of the Severity of Alcohol Use–Related Problems? , 2007, Substance use & misuse.

[28]  P. Sillanaukee,et al.  Five-shot questionnaire on heavy drinking. , 1998, Alcoholism, clinical and experimental research.

[29]  J M Grimshaw,et al.  Effectiveness and efficiency of guideline dissemination and implementation strategies , 2004, International Journal of Technology Assessment in Health Care.

[30]  Arie Hasman,et al.  A parallel guideline development and formalization strategy to improve the quality of clinical practice guidelines , 2009, Int. J. Medical Informatics.

[31]  Jane M. Young,et al.  Audit and feedback: effects on professional practice and healthcare outcomes. , 2012, The Cochrane database of systematic reviews.

[32]  P. Ades.  Cardiac rehabilitation and secondary prevention of coronary heart disease. , 2001, The New England journal of medicine.

[33]  R. Grol,et al.  Implementing guidelines and innovations in general practice: which interventions are effective? , 1998, The British journal of general practice : the journal of the Royal College of General Practitioners.

[34]  Anita L. Tucker,et al.  Why Hospitals Don't Learn from Failures: Organizational and Psychological Dynamics That Inhibit System Change , 2003 .

[35]  R Brian Haynes,et al.  Computerized clinical decision support systems for chronic disease management: A decision-maker-researcher partnership systematic review , 2011, Implementation science : IS.

[36]  Anke J. E. de Veer,et al.  Factors influencing the implementation of clinical guidelines for health care professionals: A systematic meta-review , 2008, BMC Medical Informatics Decis. Mak..

[37]  J. Grimshaw,et al.  Potential benefits, limitations, and harms of clinical guidelines , 1999, BMJ.

[38]  H. Dalal,et al.  Cardiac rehabilitation in the United Kingdom , 2008, Heart.

[39]  Nicolette de Keizer,et al.  A Web-based System to Facilitate Local, Systematic Quality Improvement by Multidisciplinary Care Teams: Development and First Experiences of CARDSS Online , 2013, MedInfo.

[40]  N. Oldridge,et al.  Quality of Life After Myocardial Infarction: Translation and Validation of the MacNew Questionnaire for a Dutch Population , 2004, Quality of Life Research.

[41]  Leo Smith,et al.  American Association of Cardiovascular and Pulmonary Rehabilitation , 1986 .

[42]  Nicolette de Keizer,et al.  Modified Rand Method to Derive Quality Indicators: a Case Study in Cardiac Rehabilitation , 2011, MIE.

[43]  B. Löwe,et al.  A brief measure for assessing generalized anxiety disorder: the GAD-7. , 2006, Archives of internal medicine.

[44]  M. Lauer,et al.  Cardiac rehabilitation and secondary prevention of coronary heart disease: an American Heart Association scientific statement from the Council on Clinical Cardiology (Subcommittee on Exercise, Cardiac Rehabilitation, and Prevention) and the Council on Nutrition, Physical Activity, and Metabolism (Su , 2005, Circulation.

[45]  I. Piña,et al.  AACVPR/ACC/AHA 2007 performance measures on cardiac rehabilitation for referral to and delivery of cardiac rehabilitation/secondary prevention services endorsed by the American College of Chest Physicians, American College of Sports Medicine, American Physical Therapy Association, Canadian Associati , 2007, Journal of the American College of Cardiology.

[46]  Nicolette de Keizer,et al.  Design of a continuous multifaceted guideline-implementation strategy based on computerized decision support , 2010, MedInfo.

[47]  R Brian Haynes,et al.  Features of effective computerised clinical decision support systems: meta-regression of 162 randomised trials , 2013, BMJ : British Medical Journal.

[48]  K. Lorig,et al.  Balanced Incomplete Block Design: Description, Case Study, and Implications for Practice , 1995, Health education quarterly.

[49]  Karina Lovell,et al.  Patient Health Questionnaire , 2013 .

[50]  Martin Eccles,et al.  Implementing clinical guidelines: current evidence and future implications. , 2004, The Journal of continuing education in the health professions.

[51]  A. Cohen-Solal,et al.  Standards for the use of cardiopulmonary exercise testing for the functional evaluation of cardiac patients: a report from the Exercise Physiology Section of the European Association for Cardiovascular Prevention and Rehabilitation , 2009, European journal of cardiovascular prevention and rehabilitation : official journal of the European Society of Cardiology, Working Groups on Epidemiology & Prevention and Cardiac Rehabilitation and Exercise Physiology.

[52]  A. Beck,et al.  Comparison of Beck Depression Inventories -IA and -II in psychiatric outpatients. , 1996, Journal of personality assessment.

[53]  J. Ormel,et al.  A validation study of the Hospital Anxiety and Depression Scale (HADS) in different groups of Dutch subjects , 1997, Psychological Medicine.

[54]  J M Grimshaw,et al.  Effect of clinical guidelines on medical practice: a systematic review of rigorous evaluations. , 1994, Lancet.

[55]  Paul Dendale,et al.  Secondary prevention through cardiac rehabilitation: from knowledge to implementation. A position paper from the Cardiac Rehabilitation Section of the European Association of Cardiovascular Prevention and Rehabilitation , 2010, European journal of cardiovascular prevention and rehabilitation : official journal of the European Society of Cardiology, Working Groups on Epidemiology & Prevention and Cardiac Rehabilitation and Exercise Physiology.

[56]  V. Hasselblad,et al.  Effect of Clinical Decision-Support Systems , 2012, Annals of Internal Medicine.

[57]  Nicolette de Keizer,et al.  The effect of computerized decision support on barriers to guideline implementation: A qualitative study in outpatient cardiac rehabilitation , 2010, Int. J. Medical Informatics.