Non-participants can have a considerable influence on the external validity of a study. Therefore, we assessed the socio-demographic, health-related, and lifestyle behavioral differences between ...participants and non-participants in a comprehensive CVD lifestyle intervention trial, and explored the motives and barriers underlying the decision to participate or not.
We collected data on participants (n = 50) and non-participants (n = 50) who were eligible for inclusion in a comprehensive CVD lifestyle interventional trial. Questionnaires and a hospital patient records database were used to assess socio-demographic, health-related and lifestyle behavioral variables. Univariate and multivariate logistic regression was used to describe the relationship between explanatory variables and study participation. Furthermore, motives and barriers that underlie study participation were investigated by means of questionnaires.
Participants were younger, single, had a higher level of education and were employed. No statistically significant differences were found in health measures and behavioral variables. The motives for participation that were most frequently reported were: the perception of being unhealthy and willingness to change their lifestyle. The main barriers reported by non-participants were financial arguments and time investment.
The differences between participants and non-participants in a lifestyle intervention trial are in mainly demographic factors. The participants consent in order to alter their lifestyle, and/or because they want to improve their health. To minimize non-participation, it is recommended that access to a lifestyle intervention program should be easy and cause no financial restraints.
ISRCTN69776211.
Abstract Context Computerized 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. Objective To assess the effect of CDSSs on cognitive, organizational, and environmental factors that hamper guideline implementation. Design In-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. 5. Setting Outpatient cardiac rehabilitation clinics. Participants Care professionals that used the CARDSS decision support system for therapeutic decision making in cardiac rehabilitation. Results Twenty-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 system's recommendations were shared with patients, refusal to participate in therapies reduced. CARDSS never incited users to target barriers related to organizational or environmental constraints. Conclusion Our 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.
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.
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.
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.
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.
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.
Non-thrombotic PE does not represent a distinct clinical syndrome. It may be due to a variety of embolic materials and result in a wide spectrum of clinical presentations, making the diagnosis ...difficult. With the exception of severe air and fat embolism, the haemodynamic consequences of non-thrombotic emboli are usually mild. Treatment is mostly supportive but may differ according to the type of embolic material and clinical severity.
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