BackgroundThis paper has two goals. First, we explore the feasibility of conducting online expert panels to facilitate consensus finding among a large number of geographically distributed stakeholders. Second, we test the replicability of panel findings across four panels of different size.MethodWe engaged 119 panelists in an iterative process to identify definitional features of Continuous Quality Improvement (CQI). We conducted four parallel online panels of different size through three one-week phases by using the RAND's ExpertLens process. In Phase I, participants rated potentially definitional CQI features. In Phase II, they discussed rating results online, using asynchronous, anonymous discussion boards. In Phase III, panelists re-rated Phase I features and reported on their experiences as participants.Results66% of invited experts participated in all three phases. 62% of Phase I participants contributed to Phase II discussions and 87% of them completed Phase III. Panel disagreement, measured by the mean absolute deviation from the median (MAD-M), decreased after group feedback and discussion in 36 out of 43 judgments about CQI features. Agreement between the four panels after Phase III was fair (four-way kappa = 0.36); they agreed on the status of five out of eleven CQI features. Results of the post-completion survey suggest that participants were generally satisfied with the online process. Compared to participants in smaller panels, those in larger panels were more likely to agree that they had debated each others' view points.ConclusionIt is feasible to conduct online expert panels intended to facilitate consensus finding among geographically distributed participants. The online approach may be practical for engaging large and diverse groups of stakeholders around a range of health services research topics and can help conduct multiple parallel panels to test for the reproducibility of panel conclusions.
ObjectiveContinuous quality improvement (CQI) methods are foundational approaches to improving healthcare delivery. Publications using the term CQI, however, are methodologically heterogeneous, and labels other than CQI are used to signify relevant approaches. Standards for identifying the use of CQI based on its key methodological features could enable more effective learning across quality improvement (QI) efforts. The objective was to identify essential methodological features for recognizing CQI.DesignPrevious work with a 12-member international expert panel identified reliably abstracted CQI methodological features. We tested which features met rigorous a priori standards as essential features of CQI using a three-phase online modified-Delphi process.SettingPrimarily United States and Canada.Participants119 QI experts randomly assigned into four on-line panels.Intervention(s)Participants rated CQI features and discussed their answers using online, anonymous and asynchronous discussion boards. We analyzed ratings quantitatively and discussion threads qualitatively.Main outcome measure(s)Panel consensus on definitional CQI features.ResultsSeventy-nine (66%) panelists completed the process. Thirty-three completers self-identified as QI researchers, 18 as QI practitioners and 28 as both equally. The features ‘systematic data guided activities,’ ‘designing with local conditions in mind’ and ‘iterative development and testing’ met a priori standards as essential CQI features. Qualitative analyses showed cross-cutting themes focused on differences between QI and CQI.ConclusionsWe found consensus among a broad group of CQI researchers and practitioners on three features as essential for identifying QI work more specifically as ‘CQI.’ All three features are needed as a minimum standard for recognizing CQI methods.
BackgroundThe evidence base for quality improvement (QI) interventions is expanding rapidly. The diversity of the initiatives and the inconsistency in labeling these as QI interventions makes it challenging for researchers, policymakers, and QI practitioners to access the literature systematically and to identify relevant publications.MethodsWe evaluated search strategies developed for MEDLINE (Ovid) and PubMed based on free text words, Medical subject headings (MeSH), QI intervention components, continuous quality improvement (CQI) methods, and combinations of the strategies. Three sets of pertinent QI intervention publications were used for validation. Two independent expert reviewers screened publications for relevance. We compared the yield, recall rate, and precision of the search strategies for the identification of QI publications and for a subset of empirical studies on effects of QI interventions.ResultsThe search yields ranged from 2,221 to 216,167 publications. Mean recall rates for reference publications ranged from 5% to 53% for strategies with yields of 50,000 publications or fewer. The 'best case' strategy, a simple text word search with high face validity ('quality' AND 'improv*' AND 'intervention*') identified 44%, 24%, and 62% of influential intervention articles selected by Agency for Healthcare Research and Quality (AHRQ) experts, a set of exemplar articles provided by members of the Standards for Quality Improvement Reporting Excellence (SQUIRE) group, and a sample from the Cochrane Effective Practice and Organization of Care Group (EPOC) register of studies, respectively. We applied the search strategy to a PubMed search for articles published in 10 pertinent journals in a three-year period which retrieved 183 publications. Among these, 67% were deemed relevant to QI by at least one of two independent raters. Forty percent were classified as empirical studies reporting on a QI intervention.ConclusionsThe presented search terms and operating characteristics can be used to guide the identification of QI intervention publications. Even with extensive iterative development, we achieved only moderate recall rates of reference publications. Consensus development on QI reporting and initiatives to develop QI-relevant MeSH terms are urgently needed.
BackgroundThe term continuous quality improvement (CQI) is often used to refer to a method for improving care, but no consensus statement exists on the definition of CQI. Evidence reviews are critical for advancing science, and depend on reliable definitions for article selection.MethodsAs a preliminary step towards improving CQI evidence reviews, this study aimed to use expert panel methods to identify key CQI definitional features and develop and test a screening instrument for reliably identifying articles with the key features. We used a previously published method to identify 106 articles meeting the general definition of a quality improvement intervention (QII) from 9427 electronically identified articles from PubMed. Two raters then applied a six-item CQI screen to the 106 articles.ResultsPer cent agreement ranged from 55.7% to 75.5% for the six items, and reviewer-adjusted intra-class correlation ranged from 0.43 to 0.62. ‘Feedback of systematically collected data’ was the most common feature (64%), followed by being at least ‘somewhat’ adapted to local conditions (61%), feedback at meetings involving participant leaders (46%), using an iterative development process (40%), being at least ‘somewhat’ data driven (34%), and using a recognised change method (28%). All six features were present in 14.2% of QII articles.ConclusionsWe conclude that CQI features can be extracted from QII articles with reasonable reliability, but only a small proportion of QII articles include all features. Further consensus development is needed to support meaningful use of the term CQI for scientific communication.
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