Irene M. Hellemans

Physical activity for primary and secondary prevention. Position paper of the Working Group on Cardiac Rehabilitation and Exercise Physiology of the European Society of Cardiology.

There is now clear scientific evidence linking regular aerobic physical activity to a significant cardiovascular risk reduction, and a sedentary lifestyle is currently considered one of the five major risk factors for cardiovascular disease. In the European Union, available data seem to indicate that less than 50% of the citizens are involved in regular aerobic leisure-time and/or occupational physical activity, and that the observed increasing prevalence of obesity is associated with a sedentary lifestyle. It seems reasonable therefore to provide institutions, health services, and individuals with information able to implement effective strategies for the adoption of a physically active lifestyle and for helping people to effectively incorporate physical activity into their daily life both in the primary and the secondary prevention settings. This paper summarizes the available scientific evidence dealing with the relationship between physical activity and cardiovascular health in primary and secondary prevention, and focuses on the preventive effects of aerobic physical activity, whose health benefits have been extensively documented. Eur J Cardiovasc Prevention Rehab 10:319-327

Effect of guideline based computerised decision support on decision making of multidisciplinary teams: cluster randomised trial in cardiac rehabilitation

Objective To determine the extent to which computerised decision support can improve concordance of multidisciplinary teams with therapeutic decisions recommended by guidelines. Design Multicentre cluster randomised trial. Participants Multidisciplinary cardiac rehabilitation teams in Dutch centres and their cardiac rehabilitation patients. Interventions Teams received an electronic patient record system with or without additional guideline based decision support. Main outcome measures Concordance with guideline recommendations assessed for two standard rehabilitation treatments—exercise and education therapy—and for two new but evidence based rehabilitation treatments—relaxation and lifestyle change therapy; generalised estimating equations were used to account for intra-cluster correlation and were adjusted for patient’s age, sex, and indication for cardiac rehabilitation and for type and volume of centre. Results Data from 21 centres, including 2787 patients, were analysed. Computerised decision support increased concordance with guideline recommended therapeutic decisions for exercise therapy by 7.9% (control 84.7%; adjusted difference 3.5%, 95% confidence 0.1% to 5.2%), for education therapy by 25.7% (control 63.9%; adjusted difference 23.7%, 15.5% to 29.4%), and for relaxation therapy by 25.5% (control 34.1%; adjusted difference 41.6%, 25.2% to 51.3%). The concordance for lifestyle change therapy increased by 3.2% (control 54.1%; adjusted difference 7.1%, −2.9% to 18.3%). Computerised decision support reduced cases of both overtreatment and undertreatment. Conclusions In a multidisciplinary team motivated to adopt a computerised decision support aid that assists in formulating guideline based care plans, computerised decision support can be effective in improving the team’s concordance with guidelines. Therefore, computerised decision support may also be considered to improve implementation of guidelines in such settings. Trial registration Current Controlled Trials ISRCTN36656997.

The effect of computerized decision support on barriers to guideline implementation: A qualitative study in outpatient cardiac rehabilitation

CONTEXTnComputerized decision support systems (CDSSs) can be used to improve the implementation of clinical practice guidelines by changing the behaviour of care professionals. While the influence of system characteristics on the effectiveness of CDSSs is studied, little is known about the relation between cognitive, organizational and environmental factors, and CDSSs effectiveness.nnnOBJECTIVEnTo assess the effect of CDSSs on cognitive, organizational, and environmental factors that hamper guideline implementation.nnnDESIGNnIn-depth, semi-structured interviews with care professionals, on reasons for improved adherence or persistent non-adherence to the prevailing guideline after successful adoption of a CDSS. All remarks regarding guideline implementation were extracted and classified using the conceptual framework from Cabana et al.nnnSETTINGnOutpatient cardiac rehabilitation clinics.nnnPARTICIPANTSnCare professionals that used the CARDSS decision support system for therapeutic decision making in cardiac rehabilitation.nnnRESULTSnTwenty-nine rehabilitation nurses and physiotherapists from 21 Dutch clinics were interviewed. CARDSS improved guideline adherence by increasing its users familiarity with the guidelines recommendations and decision logic, by overcoming users inertia to previous practice, and by reducing guideline complexity for example by facilitating calculation and interpretation of data. If the systems recommendations were shared with patients, refusal to participate in therapies reduced. CARDSS never incited users to target barriers related to organizational or environmental constraints.nnnCONCLUSIONnOur results suggest that computerized decision support can improve guideline implementation by increasing the knowledge of preferred practice, by reducing inertia to previous practice, and by reducing guideline complexity. However, computerized decision support is not effective when organizational or procedural changes are required that users consider to be beyond their tasks and responsibilities.

Is the MacNew quality of life questionnaire a useful diagnostic and evaluation instrument for cardiac rehabilitation

Purpose The MacNew health-related quality of life questionnaire is internationally used as a standard for psychosocial assessment in many cardiac rehabilitation centres. This study investigates its discriminating capacity between diagnostic disease categories, sex and age at entry (T1) and at the end (T2) of cardiac rehabilitation as well as the responsiveness of the MacNew during this period. Method Data were used from 6749 cardiac rehabilitation patients at T1 and 1654 at T2. Results Results show that the global MacNew as well as the three (physical, emotional, social) subscales have high internal consistencies, and differentiate well and in the expected direction at T1 between diagnostic groups (heart surgery, myocardial infarction with and without percutaneous coronary intervention, stable angina with and without percutaneous coronary intervention, implantable cardioverter defibrillator, and heart failure patients), sex and age. The MacNew also proves to be an adequate evaluation instrument for cardiac rehabilitation, as all scales are responsive enough to capture changes from T1 to T2. At T2, however, the MacNew seems to lose some of its discriminating power, partly because of ceiling effects. Conclusion It is suggested to complement the use of the MacNew both at T1 and T2 with a brief anxiety and depression measure, which is valid and responsive for different groups of cardiac rehabilitation patients.

Improving guideline adherence for cardiac rehabilitation in the Netherlands

BackgroundIn 2004, the Netherlands Society of Cardiology released the current guideline on cardiac rehabilitation. Given its complexity and the involvement of various healthcare disciplines, it was supplemented with a clinical algorithm, serving to facilitate its implementation in daily practice. Although the algorithm was shown to be effective for improving guideline adherence, several shortcomings and deficiencies were revealed. Based on these findings, the clinical algorithm has now been updated. This article describes the process and the changes that were made.MethodsThe revision consisted of three phases. First, the reliability of the measurement instruments included in the 2004 Clinical Algorithm was investigated by evaluating between-centre variations of the baseline assessment data. Second, based on the available evidence, a multidisciplinary expert advisory panel selected items needing revision and provided specific recommendations. Third, a guideline development group decided which revisions were finally included, also taking practical considerations into account.ResultsA total of nine items were revised: three because of new scientific insights and six because of the need for more objective measurement instruments. In all revised items, subjective assessment methods were replaced by more objective assessment tools (e.g. symptom-limited exercise instead of clinical judgement). In addition, four new key items were added: screening for anxiety/depression, stress, cardiovascular risk profile and alcohol consumption.ConclusionBased on previously determined shortcomings, the Clinical Algorithm for Cardiac Rehabilitation was thoroughly revised mainly by incorporating more objective assessment methods and by adding several new key areas.

Revision of the Dutch clinical algorithm for assessing patient needs in cardiac rehabilitation based on identified implementation problems

Background: Despite all available evidence of its effectiveness, cardiac rehabilitation and secondary prevention (CRSP) is still insufficiently implemented in current clinical practice. Based on an analysis of implementation problems, recently the Dutch clinical algorithm for the assessment of patient’s CRSP needs was revised. The purpose of this paper is to describe the revision process and its results to improve CRSP guideline implementation. Methods: The National Institute for Health and Clinical Excellence (NICE) guidelines manual for conducting guideline revisions was followed. Information on the use of the algorithm in practice was collected from electronic medical records and by conducting semi-structured interviews. Next, an expert advisory group identified the problems for use in daily practice and defined the scope for the revision. A multidisciplinary guideline development group subsequently wrote the revised algorithm. Results: A large variation in assessed patient needs was observed between CRSP clinics. Assessment based on clinical judgement was found to be a source of practice variation and is therefore avoided in the revised algorithm. It was decided to add assessment instruments for anxiety and depression, cardiovascular risk factors, stress, attitude of partner and lifestyle parameters. Conclusion: The Dutch clinical algorithm for assessing patient needs for CRSP was revised using a combination of patient data from routine practice, knowledge from academic experts and experience from field experts. The revised algorithm is a practical tool consisting of assessment instruments to improve CRSP guideline adherence in the Netherlands. This algorithm may also be useful for other Western countries to organize their CRSP needs assessment procedure.