Factors influencing success in quality-improvement collaboratives: development and psychometric testing of an instrument

Contains fulltext : 88630.pdf (publisher's version ) (Open Access)ABSTRACT: BACKGROUND: To increase the effectiveness of quality-improvement collaboratives (QICs), it is important to explore factors that potentially influence their outcomes. For this purpose, we have developed and tested the psychometric properties of an instrument that aims to identify the features that may enhance the quality and impact of collaborative quality-improvement approaches. The instrument can be used as a measurement instrument to retrospectively collect information about perceived determinants of success. In addition, it can be prospectively applied as a checklist to guide initiators, facilitators, and participants of QICs, with information about how to perform or participate in a collaborative with theoretically optimal chances of success. Such information can be used to improve collaboratives. METHODS: We developed an instrument with content validity based on literature and the opinions of QIC experts. We collected data from 144 healthcare professionals in 44 multidisciplinary improvement teams participating in two QICs and used exploratory factor analysis to assess the construct validity. We used Cronbach's alpha to ascertain the internal consistency. RESULTS: The 50-item instrument we developed reflected expert-opinion-based determinants of success in a QIC. We deleted nine items after item reduction. On the basis of the factor analysis results, one item was dropped, which resulted in a 40-item questionnaire. Exploratory factor analysis showed that a three-factor model provided the best fit. The components were labeled 'sufficient expert team support', 'effective multidisciplinary teamwork', and 'helpful collaborative processes'. Internal consistency reliability was excellent (alphas between .85 and .89). CONCLUSIONS: This newly developed instrument seems a promising tool for providing healthcare workers and policy makers with useful information about determinants of success in QICs. The psychometric properties of the instrument are satisfactory and warrant application either as an objective measure or as a checklist

The health disparities cancer collaborative: a case study of practice registry measurement in a quality improvement collaborative

<p>Abstract</p> <p>Background</p> <p>Practice registry measurement provides a foundation for quality improvement, but experiences in practice are not widely reported. One setting where practice registry measurement has been implemented is the Health Resources and Services Administration's Health Disparities Cancer Collaborative (HDCC).</p> <p>Methods</p> <p>Using practice registry data from 16 community health centers participating in the HDCC, we determined the completeness of data for screening, follow-up, and treatment measures. We determined the size of the change in cancer care processes that an aggregation of practices has adequate power to detect. We modeled different ways of presenting before/after changes in cancer screening, including count and proportion data at both the individual health center and aggregate collaborative level.</p> <p>Results</p> <p>All participating health centers reported data for cancer screening, but less than a third reported data regarding timely follow-up. For individual cancers, the aggregate HDCC had adequate power to detect a 2 to 3% change in cancer screening, but only had the power to detect a change of 40% or more in the initiation of treatment. Almost every health center (98%) improved cancer screening based upon count data, while fewer (77%) improved cancer screening based upon proportion data. The aggregate collaborative appeared to increase breast, cervical, and colorectal cancer screening rates by 12%, 15%, and 4%, respectively (p < 0.001 for all before/after comparisons). In subgroup analyses, significant changes were detectable among individual health centers less than one-half of the time because of small numbers of events.</p> <p>Conclusions</p> <p>The aggregate HDCC registries had both adequate reporting rates and power to detect significant changes in cancer screening, but not follow-up care. Different measures provided different answers about improvements in cancer screening; more definitive evaluation would require validation of the registries. Limits to the implementation and interpretation of practice registry measurement in the HDCC highlight challenges and opportunities for local and aggregate quality improvement activities.</p

The implementation of a translational study involving a primary care based behavioral program to improve blood pressure control: The HTN-IMPROVE study protocol (01295)

<p>Abstract</p> <p>Background</p> <p>Despite the impact of hypertension and widely accepted target values for blood pressure (BP), interventions to improve BP control have had limited success.</p> <p>Objectives</p> <p>We describe the design of a 'translational' study that examines the implementation, impact, sustainability, and cost of an evidence-based nurse-delivered tailored behavioral self-management intervention to improve BP control as it moves from a research context to healthcare delivery. The study addresses four specific aims: assess the implementation of an evidence-based behavioral self-management intervention to improve BP levels; evaluate the clinical impact of the intervention as it is implemented; assess organizational factors associated with the sustainability of the intervention; and assess the cost of implementing and sustaining the intervention.</p> <p>Methods</p> <p>The project involves three geographically diverse VA intervention facilities and nine control sites. We first conduct an evaluation of barriers and facilitators for implementing the intervention at intervention sites. We examine the impact of the intervention by comparing 12-month pre/post changes in BP control between patients in intervention sites versus patients in the matched control sites. Next, we examine the sustainability of the intervention and organizational factors facilitating or hindering the sustained implementation. Finally, we examine the costs of intervention implementation. Key outcomes are acceptability and costs of the program, as well as changes in BP. Outcomes will be assessed using mixed methods (<it>e.g</it>., qualitative analyses--pattern matching; quantitative methods--linear mixed models).</p> <p>Discussion</p> <p>The study results will provide information about the challenges and costs to implement and sustain the intervention, and what clinical impact can be expected.</p

How collaborative are quality improvement collaboratives:A qualitative study in stroke care

BACKGROUND: Quality improvement collaboratives (QICs) continue to be widely used, yet evidence for their effectiveness is equivocal. We sought to explain what happened in Stroke 90:10, a QIC designed to improve stroke care in 24 hospitals in the North West of England. Our study drew in part on the literature on collective action and inter-organizational collaboration. This literature has been relatively neglected in evaluations of QICs, even though they are founded on principles of co-operation and sharing. METHODS: We interviewed 32 professionals in hospitals that participated in Stroke 90:10, conducted a focus group with the QIC faculty team, and reviewed purposively sampled documents including reports and newsletters. Analysis was based on a modified form of Framework Analysis, combining sensitizing constructs derived from the literature and new, empirically derived thematic categories. RESULTS: Improvements in stroke care were attributed to QIC participation by many professionals. They described how the QIC fostered a sense of community and increased attention to stroke care within their organizations. However, participants’ experiences of the QIC varied. Starting positions were different; some organizations were achieving higher levels of performance than others before the QIC began, and some had more pre-existing experience of quality improvement methods. Some participants had more to learn, others more to teach. Some evidence of free-riding was found. Benchmarking improvement was variously experienced as friendly rivalry or as time-consuming and stressful. Participants’ competitive desire to demonstrate success sometimes conflicted with collaborative aims; some experienced competing organizational pressures or saw the QIC as duplication of effort. Experiences of inter-organizational collaboration were influenced by variations in intra-organizational support. CONCLUSIONS: Collaboration is not the only mode of behavior likely to occur within a QIC. Our study revealed a mixed picture of collaboration, free-riding and competition. QICs should learn from work on the challenges of collective action; set realistic goals; account for context; ensure sufficient time and resources are made available; and carefully manage the collaborative to mitigate the risks of collaborative inertia and unhelpful competitive or anti-cooperative behaviors. Individual organizations should assess the costs and benefits of collaboration as a means of attaining quality improvement