Objectives: A systematic review of the effectiveness and costs of different guideline development, dissemination, and implementation strategies wasundertaken. The resource implications of these strategies was estimated, and a framework for deciding when it is efficient to develop and introduce clinical guidelines was developed.
BackgroundDeterminants of practice are factors that might prevent or enable improvements. Several checklists, frameworks, taxonomies, and classifications of determinants of healthcare professional practice have been published. In this paper, we describe the development of a comprehensive, integrated checklist of determinants of practice (the TICD checklist).MethodsWe performed a systematic review of frameworks of determinants of practice followed by a consensus process. We searched electronic databases and screened the reference lists of key background documents. Two authors independently assessed titles and abstracts, and potentially relevant full text articles. We compiled a list of attributes that a checklist should have: comprehensiveness, relevance, applicability, simplicity, logic, clarity, usability, suitability, and usefulness. We assessed included articles using these criteria and collected information about the theory, model, or logic underlying how the factors (determinants) were selected, described, and grouped, the strengths and weaknesses of the checklist, and the determinants and the domains in each checklist. We drafted a preliminary checklist based on an aggregated list of determinants from the included checklists, and finalized the checklist by a consensus process among implementation researchers.ResultsWe screened 5,778 titles and abstracts and retrieved 87 potentially relevant papers in full text. Several of these papers had references to papers that we also retrieved in full text. We also checked potentially relevant papers we had on file that were not retrieved by the searches. We included 12 checklists. None of these were completely comprehensive when compared to the aggregated list of determinants and domains. We developed a checklist with 57 potential determinants of practice grouped in seven domains: guideline factors, individual health professional factors, patient factors, professional interactions, incentives and resources, capacity for organisational change, and social, political, and legal factors. We also developed five worksheets to facilitate the use of the checklist.ConclusionsBased on a systematic review and a consensus process we developed a checklist that aims to be comprehensive and to build on the strengths of each of the 12 included checklists. The checklist is accompanied with five worksheets to facilitate its use in implementation research and quality improvement projects.
A consistent finding in articles on quality improvement in health care is that change is difficult to achieve. According to the research literature, the majority of interventions are targeted at health care professionals. But success in achieving change may be influenced by factors other than those relating to individual professionals, and theories may help explain whether change is possible. This article argues for a more systematic use of theories in planning and evaluating quality-improvement interventions in clinical practice. It demonstrates how different theories can be used to generate testable hypotheses regarding factors that influence the implementation of change, and it shows how different theoretical assumptions lead to different quality-improvement strategies.Keywords: Theories, quality improvement, health care. S ometimes new scientific findings, best practices, or clinical guidelines are easily implemented in practice. Most of the time, however, improving patient care is not easy, particularly if an innovation requires complex changes in clinical routines, better collaboration among disciplines, changes in patients' behavior, or changes in the organization of care. To date, the majority of health care improvements have been targeted at factors related to individual professionals, particularly their knowledge, routines, or attitudes (Grimshaw et al.Address correspondence to: Richard Grol, Centre for Quality of Care Research (WOK), Radboud University Nijmegen Medical Centre (UMCN), KWAZO 117, PO Box 9101, 6500 HB Nijmegen, the Netherlands (email: R.Grol@kwazo.umcn.nl). The Milbank Quarterly, Vol. 85, No. 1, 2007 (pp. 93-138) 94R. Grol, M. Bosch, M. Hulscher, M. Eccles, and M. Wensing 2004), although improvement may be impeded by a much broader range of economic, administrative, and organizational factors or those relating to patients' beliefs or behavior.Because the interaction of factors at multiple levels may influence the success or failure of quality-improvement interventions (Ferlie and Shortell 2001;Grol 1997;Shortell et al. 2000), an understanding of these factors (the obstacles and incentives for change) is crucial to an effective intervention (Grol and Grimshaw 2003;Grol and Wensing 2004;van Bokhoven, Kok, and van der Weijden 2003). An understanding of the theoretical assumptions and hypotheses behind these factors is necessary as well, as it enables the consideration of theory-based interventions for quality improvement. Currently, however, the specific model or approach is usually based on implicit (and potentially biased) personal beliefs about human behavior and change (Grol 1997).In this article we summarize and recommend a set of theories regarding change in health care and argue for a more systematic use of theories in planning and evaluating changes in clinical practice, by following and extending previous overviews of theories (e.g., Ashford 1998;Greenhalgh et al. 2004;Kitson, Harvey, and McCormack 1998;Michie et al. 2005;Robertson, Baker, and Hearnshaw 1996). The Complexity ...
Cochrane Database of Systematic Reviews Data collection and analysisTwo review authors independently assessed quality and extracted data. We undertook qualitative and quantitative analyses, the quantitative analysis including two elements: we carried out 1) meta-regression analyses to compare interventions tailored to address identified determinants with either no interventions or an intervention(s) not tailored to the determinants, and 2) heterogeneity analyses to investigate sources of di erences in the e ectiveness of interventions. These included the e ects of: risk of bias, use of a theory when developing the intervention, whether adjustment was made for local factors, and number of domains addressed with the determinants identified. Main resultsWe added nine studies to this review to bring the total number of included studies to 32 comparing an intervention tailored to address identified determinants of practice to no intervention or an intervention(s) not tailored to the determinants. The outcome was implementation of recommended practice, e.g. clinical practice guideline recommendations. Fi een studies provided enough data to be included in the quantitative analysis. The pooled odds ratio was 1.56 (95% confidence interval (CI) 1.27 to 1.93, P value < 0.001). The 17 studies not included in the meta-analysis had findings showing variable e ectiveness consistent with the findings of the meta-regression. Authors' conclusionsDespite the increase in the number of new studies identified, our overall finding is similar to that of the previous review. Tailored implementation can be e ective, but the e ect is variable and tends to be small to moderate. The number of studies remains small and more research is needed, including trials comparing tailored interventions to no or other interventions, but also studies to develop and investigate the components of tailoring (identification of the most important determinants, selecting interventions to address the determinants). Currently available studies have used di erent methods to identify determinants of practice and di erent approaches to selecting interventions to address the determinants. It is not yet clear how best to tailor interventions and therefore not clear what the e ect of an optimally tailored intervention would be.
Background: A systematic review has shown that no measures of the extent to which healthcare professionals involve patients in decisions within clinical consultations exist, despite the increasing interest in the benefits or otherwise of patient participation in these decisions. Aims: To describe the development of a new instrument designed to assess the extent to which practitioners involve patients in decision making processes. Design: The OPTION (observing patient involvement) scale was developed and used by two independent raters to assess primary care consultations in order to evaluate its psychometric qualities, validity, and reliability. Study sample: 186 audiotaped consultations collected from the routine clinics of 21 general practitioners in the UK. Method: Item response rates, Cronbach's alpha, and summed and scaled OPTION scores were calculated. Inter-item and item-total correlations were calculated and inter-rater agreements were calculated using Cohen's kappa. Classical inter-rater intraclass correlation coefficients and generalisability theory statistics were used to calculate inter-rater reliability coefficients. Basing the tool development on literature reviews, qualitative studies and consultations with practitioner and patients ensured content validity. Construct validity hypothesis testing was conducted by assessing score variation with respect to patient age, clinical topic "equipoise", sex of practitioner, and success of practitioners at a professional examination. Results: The OPTION scale provided reliable scores for detecting differences between groups of consultations in the extent to which patients are involved in decision making processes in consultations. The results justify the use of the scale in further empirical studies. The inter-rater intraclass correlation coefficient (0.62), kappa scores for inter-rater agreement (0.71), and Cronbach's alpha (0.79) were all above acceptable thresholds. Based on a balanced design of five consultations per clinician, the interrater reliability generalisability coefficient was 0.68 (two raters) and the intra-rater reliability generalisability coefficient was 0.66. On average, mean practitioner scores were very similar (and low on the overall scale of possible involvement); some practitioner scores had more variation around the mean, indicating that they varied their communication styles to a greater extent than others. Conclusions: Involvement in decision making is a key facet of patient participation in health care and the OPTION scale provides a validated outcome measure for future empirical studies.
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