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BACKGROUND: Hospitals have implemented diverse quality improvement (QI) interventions to reduce rates of catheter-associated urinary tract infections (CAUTIs). The economic value of these QI interventions is uncertain. OBJECTIVE: To systematically review economic evaluations of QI interventions designed to prevent CAUTI in acute care hospitals. METHODS: A search of Ovid MEDLINE, Econlit, Centre for Reviews & Dissemination, New York Academy of Medicines Grey Literature Report, WorldCat, IDWeek conference abstracts and prior systematic reviews was conducted from January 2000 to October 2020.We included English-language studies of any design that evaluated organisational or structural changes to prevent CAUTI in acute care hospitals, and reported programme and infection-related costs.Dual reviewers assessed study design, effectiveness, costs and study quality. For each eligible study, we performed a cost-consequences analysis from the hospital perspective, estimating the incidence rate ratio (IRR) and incremental net cost/savings per hospital over 3 years. Unadjusted weighted regression analyses tested predictors of these measures, weighted by catheter days per study. RESULTS: Fifteen unique economic evaluations were eligible, encompassing 74 hospitals. Across 12 studies amenable to standardisation, QI interventions were associated with a 43% decline in infections (mean IRR 0.57, 95% CI 0.44 to 0.70) and wide ranges of net costs (mean US$52 000, 95% CI -$288 000 to $392 000), relative to usual care. CONCLUSIONS: QI interventions were associated with large declines in infection rates and net costs to hospitals that varied greatly but that, on average, were not significantly different from zero over 3 years. Future research should examine specific practices associated with cost-savings and clinical effectiveness, and examine whether or not more comprehensive interventions offer hospitals and patients the best value.

ObjectiveQuality improvement (QI) interventions can improve glycemic control, but little is known about their value. We systematically reviewed economic evaluations of QI interventions for glycemic control among adults with type 1 or type 2 diabetes.Research design and methodsWe used English-language studies from high-income countries that evaluated organizational changes and reported program and utilization-related costs, chosen from PubMed, EconLit, Centre for Reviews and Dissemination, New York Academy of Medicine's Grey Literature Report, and WorldCat (January 2004 to August 2016). We extracted data regarding intervention, study design, change in HbA1c, time horizon, perspective, incremental net cost (studies lasting ≤3 years), incremental cost-effectiveness ratio (ICER) (studies lasting ≥20 years), and study quality. Weighted least-squares regression analysis was used to estimate mean changes in HbA1c and incremental net cost.ResultsOf 3,646 records, 46 unique studies were eligible. Across 19 randomized controlled trials (RCTs), HbA1c declined by 0.26% (95% CI 0.17-0.35) or 3 mmol/mol (2 to 4) relative to usual care. In 8 RCTs lasting ≤3 years, incremental net costs were $116 (95% CI -$612 to $843) per patient annually. Long-term ICERs were $100,000-$115,000/quality-adjusted life year (QALY) in 3 RCTs, $50,000-$99,999/QALY in 1 RCT, $0-$49,999/QALY in 4 RCTs, and dominant in 1 RCT. Results were more favorable in non-RCTs. Our limitations include the fact that the studies had diverse designs and involved moderate risk of bias.ConclusionsDiverse multifaceted QI interventions that lower HbA1c appear to be a fair-to-good value relative to usual care, depending on society's willingness to pay for improvements in health.

CONTEXT: Influenza vaccination rates remain below Healthy People 2020 goals. This project sought to systematically review economic evaluations of healthcare-based quality improvement interventions for improving influenza vaccination uptake among general populations and healthcare workers. EVIDENCE ACQUISITION: The databases MEDLINE, Econlit, Centre for Reviews & Dissemination, Greylit, and Worldcat were searched in July 2016 for papers published from January 2004 to July 2016. Eligible studies evaluated efforts by bodies within the healthcare system to encourage influenza vaccination by means of an organizational or structural change. For each study, program costs per enrollee and per additional enrollee vaccinated were derived (excluding vaccine costs, standardized to 2017 U.S. dollars). Complete economic evaluations were examined when available. EVIDENCE SYNTHESIS: Of 2,350 records, 18 articles were eligible and described 29 unique interventions. Most interventions improved vaccine uptake. Among 23 interventions in general populations, the median program cost was $3.27 (interquartile range, $0.82-$11.53) per enrollee and $50.78 (interquartile range, $27.85-$124.84) per additional enrollee vaccinated. Among ten complete economic evaluations in general populations, three studies reported net cost savings, four reported costs

Criteria for evaluating faculty are traditionally based on a triad of scholarship, teaching, and service. Research scholarship is often measured by first or senior authorship on peer-reviewed scientific publications and being principal investigator on extramural grants. Yet scientific innovation increasingly requires collective rather than individual creativity, which traditional measures of achievement were not designed to capture and, thus, devalue. The authors propose a simple, flexible framework for evaluating team scientists that includes both quantitative and qualitative assessments. An approach for documenting contributions of team scientists in team-based scholarship, nontraditional education, and specialized service activities is also outlined. Although biostatisticians are used for illustration, the approach is generalizable to team scientists in other disciplines.The authors offer three key recommendations to members of institutional promotion committees, department chairs, and others evaluating team scientists. First, contributions to team-based scholarship and specialized contributions to education and service need to be assessed and given appropriate and substantial weight. Second, evaluations must be founded on well-articulated criteria for assessing the stature and accomplishments of team scientists. Finally, mechanisms for collecting evaluative data must be developed and implemented at the institutional level. Without these three essentials, contributions of team scientists will continue to be undervalued in the academic environment.

BackgroundThe Health Information Technology for Economic and Clinical Health (HITECH) Act subsidizes implementation by hospitals of electronic health records with computerized provider order entry (CPOE), which may reduce patient injuries caused by medication errors (preventable adverse drug events, pADEs). Effects on pADEs have not been rigorously quantified, and effects on medication errors have been variable. The objectives of this analysis were to assess the effectiveness of CPOE at reducing pADEs in hospital-related settings, and examine reasons for heterogeneous effects on medication errors.MethodsArticles were identified using MEDLINE, Cochrane Library, Econlit, web-based databases, and bibliographies of previous systematic reviews (September 2013). Eligible studies compared CPOE with paper-order entry in acute care hospitals, and examined diverse pADEs or medication errors. Studies on children or with limited event-detection methods were excluded. Two investigators extracted data on events and factors potentially associated with effectiveness. We used random effects models to pool data.ResultsSixteen studies addressing medication errors met pooling criteria; six also addressed pADEs. Thirteen studies used pre-post designs. Compared with paper-order entry, CPOE was associated with half as many pADEs (pooled risk ratio (RR) = 0.47, 95% CI 0.31 to 0.71) and medication errors (RR = 0.46, 95% CI 0.35 to 0.60). Regarding reasons for heterogeneous effects on medication errors, five intervention factors and two contextual factors were sufficiently reported to support subgroup analyses or meta-regression. Differences between commercial versus homegrown systems, presence and sophistication of clinical decision support, hospital-wide versus limited implementation, and US versus non-US studies were not significant, nor was timing of publication. Higher baseline rates of medication errors predicted greater reductions (P

BackgroundThere are both theoretical and empirical reasons to believe that design and execution factors are associated with bias in controlled trials. Statistically significant moderator effects, such as the effect of trial quality on treatment effect sizes, are rarely detected in individual meta-analyses, and evidence from meta-epidemiological datasets is inconsistent. The reasons for the disconnect between theory and empirical observation are unclear. The study objective was to explore the power to detect study level moderator effects in meta-analyses.MethodsWe generated meta-analyses using Monte-Carlo simulations and investigated the effect of number of trials, trial sample size, moderator effect size, heterogeneity, and moderator distribution on power to detect moderator effects. The simulations provide a reference guide for investigators to estimate power when planning meta-regressions.ResultsThe power to detect moderator effects in meta-analyses, for example, effects of study quality on effect sizes, is largely determined by the degree of residual heterogeneity present in the dataset (noise not explained by the moderator). Larger trial sample sizes increase power only when residual heterogeneity is low. A large number of trials or low residual heterogeneity are necessary to detect effects. When the proportion of the moderator is not equal (for example, 25% 'high quality', 75% 'low quality' trials), power of 80% was rarely achieved in investigated scenarios. Application to an empirical meta-epidemiological dataset with substantial heterogeneity (I(2) = 92%, τ(2) = 0.285) estimated >200 trials are needed for a power of 80% to show a statistically significant result, even for a substantial moderator effect (0.2), and the number of trials with the less common feature (for example, few 'high quality' studies) affects power extensively.ConclusionsAlthough study characteristics, such as trial quality, may explain some proportion of heterogeneity across study results in meta-analyses, residual heterogeneity is a crucial factor in determining when associations between moderator variables and effect sizes can be statistically detected. Detecting moderator effects requires more powerful analyses than are employed in most published investigations; hence negative findings should not be considered evidence of a lack of effect, and investigations are not hypothesis-proving unless power calculations show sufficient ability to detect effects.

ObjectiveTo use empirical data from previously published literature to address 2 research questions: (1) Do interventions that incorporate at least 1 element of the Chronic Care Model (CCM) result in improved outcomes for specific chronic illnesses? (2) Are any elements essential for improved outcomes?Study designMeta-analysis.MethodsArticles were identified from narrative literature reviews and quantitative meta-analyses, each of which covered multiple bibliographic databases from inception to March 2003. We supplemented this strategy by searching the MEDLINE database (1998-2003) and by consulting experts. We included randomized and nonrandomized controlled trials of interventions that contained 1 or more elements of the CCM for asthma, congestive heart failure (CHF), depression, and diabetes. We extracted data on clinical outcomes, quality of life, and processes of care. We then used random-effects modeling to compute pooled standardized effect sizes and risk ratios.ResultsOf 1345 abstracts screened, 112 studies contributed data to the meta-analysis: asthma, 27 studies; CHF, 21 studies; depression, 33 studies; and diabetes, 31 studies. Interventions with at least 1 CCM element had consistently beneficial effects on clinical outcomes and processes of care across all conditions studied. The effects on quality of life were mixed, with only the CHF and depression studies showing benefit. Publication bias was noted for the CHF studies and a subset of the asthma studies.ConclusionsInterventions that contain at least 1 CCM element improve clinical outcomes and processes of care--and to a lesser extent, quality of life--for patients with chronic illnesses.