Methods for the guideline-based development of quality indicators--a systematic review

<p>Abstract</p> <p>Background</p> <p>Quality indicators (QIs) are used in many healthcare settings to measure, compare, and improve quality of care. For the efficient development of high-quality QIs, rigorous, approved, and evidence-based development methods are needed. Clinical practice guidelines are a suitable source to derive QIs from, but no gold standard for guideline-based QI development exists. This review aims to identify, describe, and compare methodological approaches to guideline-based QI development.</p> <p>Methods</p> <p>We systematically searched medical literature databases (Medline, EMBASE, and CINAHL) and grey literature. Two researchers selected publications reporting methodological approaches to guideline-based QI development. In order to describe and compare methodological approaches used in these publications, we extracted detailed information on common steps of guideline-based QI development (topic selection, guideline selection, extraction of recommendations, QI selection, practice test, and implementation) to predesigned extraction tables.</p> <p>Results</p> <p>From 8,697 hits in the database search and several grey literature documents, we selected 48 relevant references. The studies were of heterogeneous type and quality. We found no randomized controlled trial or other studies comparing the ability of different methodological approaches to guideline-based development to generate high-quality QIs. The relevant publications featured a wide variety of methodological approaches to guideline-based QI development, especially regarding guideline selection and extraction of recommendations. Only a few studies reported patient involvement.</p> <p>Conclusions</p> <p>Further research is needed to determine which elements of the methodological approaches identified, described, and compared in this review are best suited to constitute a gold standard for guideline-based QI development. For this research, we provide a comprehensive groundwork.</p

Kreislauffuehrung von Prozessabwasser in der Teppichindustrie Abschlussbericht

SIGLEAvailable from TIB Hannover: F04B316 / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDeutsche Bundesstiftung Umwelt, Osnabrueck (Germany)DEGerman

The Potential of High‐Dimensional Propensity Scores in Health Services Research: An Exemplary Study on the Quality of Care for Elective Percutaneous Coronary Interventions

OBJECTIVE: Evaluating the potential of the high‐dimensional propensity score (HDPS) to control for residual confounding in studies analyzing quality of care based on administrative health insurance data. DATA SOURCE: Secondary data from 2004 to 2009 from three German statutory health insurance providers. STUDY DESIGN: We conducted a retrospective cohort study in patients with elective percutaneous coronary interventions (PCIs) and compared the mortality risk between the in‐ and outpatient setting using Cox regression. Adjustment for predefined confounders was performed using conventional propensity score (PS) techniques. Further, an HDPS was calculated based on predefined and empirically selected confounders from the database. PRINCIPAL FINDINGS: Conventional PS methods showed a decreased mortality risk for outpatient compared to inpatient PCIs, while trimming of patients with nonoverlap in the HDPS distribution and weighting resulted in a comparable risk. Most comorbidities were less prevalent in the HDPS‐trimmed population compared to the original one. CONCLUSION: The HDPS methodology may reduce residual confounding by rendering the studied cohort more comparable through restriction. However, results cannot be generalized for the entire study population. To provide unbiased results, full assessment of all unmeasured confounders from proxy information in the database would be necessary