How do teams in quality improvement collaboratives interact?

BACKGROUND: The multi-organizational collaborative is a popular model for quality improvement (QI) initiatives. It assumes organizations will share information and social support. However, there is no comprehensive documentation of the extent to which teams do interact. Considering QI collaboratives as networks, interactions among reams were documented, and the associations between network roles and performance were examined. METHODS: A telephone survey of official team contact persons for 94 site teams in three QI collaborarives was conducted in 2002 and 2003. Four performance measures were used to assess the usefulness of ties to other teams and being considered a leader by peers. RESULTS: Eighty percent of the teams said they would contact another team again if they felt the need. Teams made a change as a direct result of interaction in 86% of reported relationships. Teams typically exchanged tools such as software and interacted outside of planned activities. Having a large number of ties to other teams is strongly related to the number of mentions as a leader. Both of these variables are related to faculty-assessed performance, number of changes the ream made to improve care, and depth of those changes. DISCUSSION: The Findings suggest that collaborative teams do indeed exchange important information, and the social dynamics of the collaborarives contribute to individual and collaborative success.

The role of perceived team effectiveness in improving chronic illness care.

BACKGROUND/OBJECTIVES: The importance of teams for improving quality of care has received increased attention. We examine both the correlates of self-assessed or perceived team effectiveness and its consequences for actually making changes to improve care for people with chronic illness. STUDY SETTING AND METHODS: Data were obtained from 40 teams participating in the national evaluation of the Improving Chronic Illness Care Program. Based on current theory and literature, measures were derived of organizational culture, a focus on patient satisfaction, presence of a team champion, team composition, perceived team effectiveness, and the actual number and depth of changes made to improve chronic illness care. RESULTS: A focus on patient satisfaction, the presence of a team champion, and the involvement of the physicians on the team were each consistently and positively associated with greater perceived team effectiveness. Maintaining a balance among culture values of participation, achievement, openness to innovation, and adherence to rules and accountability also appeared to be important. Perceived team effectiveness, in turn, was consistently associated with both a greater number and depth of changes made to improve chronic illness care. The variables examined explain between 24 and 40% of the variance in different dimensions of perceived team effectiveness; between 13% and 26% in number of changes made; and between 20% and 42% in depth of changes made. CONCLUSIONS: The data suggest the importance of developing effective teams for improving the quality of care for patients with chronic illness.

An evaluation of collaborative interventions to improve chronic illness care. Framework and study design.

The author's dual-purpose evaluation assesses the effectiveness of formal collaboratives in stimulating organizational changes to improve chronic illness care (the chronic care model or CCM). Intervention and comparison sites are compared before and after introduction of the CCM. Multiple data sources are used to measure the degree of implementation, patient-level processes and outcomes, and organizational and team factors associated with success. Despite challenges in timely recruitment of sites and patients, data collection on 37 participating organizations, 22 control sites, and more than 4,000 patients with diabetes, congestive heart failure, asthma, or depression is nearing completion. When analyzed, these data will shed new light on the effectiveness of collaborative improvement methods and the CCM.

A conceptual framework for evaluating outpatient electronic prescribing systems based on their functional capabilities.

OBJECTIVE: Electronic prescribing (e-prescribing) may substantially improve health care quality and efficiency, but the available systems are complex and their heterogeneity makes comparing and evaluating them a challenge. The authors aimed to develop a conceptual framework for anticipating the effects of alternative designs for outpatient e-prescribing systems. DESIGN: Based on a literature review and on telephone interviews with e-prescribing vendors, the authors identified distinct e-prescribing functional capabilities and developed a conceptual framework for evaluating e-prescribing systems' potential effects based on their capabilities. Analyses of two commercial e-prescribing systems are presented as examples of applying the conceptual framework. MEASUREMENTS: Major e-prescribing functional capabilities identified and the availability of evidence to support their specific effects. RESULTS: The proposed framework for evaluating e-prescribing systems is organized using a process model of medication management. Fourteen e-prescribing functional capabilities are identified within the model. Evidence is identified to support eight specific effects for six of the functional capabilities. The evidence also shows that a functional capability with generally positive effects can be implemented in a way that creates unintended hazards. Applying the framework involves identifying an e-prescribing system's functional capabilities within the process model and then assessing the effects that could be expected from each capability in the proposed clinical environment. CONCLUSION: The proposed conceptual framework supports the integration of available evidence in considering the full range of effects from e-prescribing design alternatives. More research is needed into the effects of specific e-prescribing functional alternatives. Until more is known, e-prescribing initiatives should include provisions to monitor for unintended hazards.

How to evaluate and improve the quality and credibility of an outcomes database: validation and feedback study on the UK Cardiac Surgery Experience.

OBJECTIVES: To assess the quality and completeness of a database of clinical outcomes after cardiac surgery and to determine whether a process of validation, monitoring, and feedback could improve the quality of the database. DESIGN: Stratified sampling of retrospective data followed by prospective re-sampling of database after intervention of monitoring, validation, and feedback. SETTING: Ten tertiary care cardiac surgery centres in the United Kingdom. INTERVENTION: Validation of data derived from a stratified sample of case notes (recording of deaths cross checked with mortuary records), monitoring of completeness and accuracy of data entry, feedback to local data managers and lead surgeons. MAIN OUTCOME MEASURES: Average percentage missing data, average kappa coefficient, and reliability score by centre for 17 variables required for assignment of risk scores. Actual minus risk adjusted mortality in each centre. RESULTS: The database was incomplete, with a mean (SE) of 24.96% (0.09%) of essential data elements missing, whereas only 1.18% (0.06%) were missing in the patient records (P<0.0001). Intervention was associated with (a) significantly less missing data (9.33% (0.08%) P<0.0001); (b) marginal improvement in reliability of data and mean (SE) overall centre reliability score (0.53 (0.15) v 0.44 (0.17)); and (c) improved accuracy of assigned Parsonnet risk scores (kappa 0.84 v 0.70). Mortality scores (actual minus risk adjusted mortality) for all participating centres fell within two standard deviations of the mean score. CONCLUSION: A short period of independent validation, monitoring, and feedback improved the quality of an outcomes database and improved the process of risk adjustment, but with substantial room for further improvement. Wider application of this approach should increase the credibility of similar databases before their public release.

Do patient consent procedures affect participation rates in health services research?

BACKGROUND: Few studies have examined the effects of Institutional Review Board (IRB) requirements to contact potential research participants. OBJECTIVE: To examine the association between requirements to contact potential research subjects and participation rates in a multisite health services research study. RESEARCH DESIGN, SUBJECTS: Prospective observational study of survey participation by 2673 individuals with diabetes and 1974 individuals with congestive heart failure treated at 15 clinical sites in the United States that had implemented a quality improvement intervention. MAIN OUTCOME MEASURES: Telephone survey response rates. RESULTS: Of 15 IRBs, seven required sites to obtain authorization from participants to release contact information to the study team. Five required oral and two required written advance permission. The response rate was 58% (913/1571) at sites where no advance permission was required, 39% (989/2530) from sites that required oral advance permission and 27% (145/546, P <0.001) at sites requiring written advance permission. Although 85% of eligible participants contacted directly by the study team consented to complete the survey, only 43% of individuals at sites requiring written advance permission allowed the release of contact information to the study team. CONCLUSIONS: Many potential participants did not grant advance permission to be contacted by the study team. Requiring advance permission reduced participation rates, especially at sites requiring written authorization.