Setting performance benchmarks for stroke care delivery: Which quality indicators should be prioritized in quality improvement; an analysis in 500,331 stroke admissions.

BACKGROUND AND AIM: Benchmarking is a management approach for implementing best medical practices at the lowest cost. The objectives of this study were to set achievable performance benchmarks for individual quality indicators to determine the predicted quality achievement related to better adherence, and to select optimal quality indicators for improving the quality of acute ischemic stroke care. METHODS: We analyzed data on 500,331 patients diagnosed with acute ischemic stroke who were treated at 518 hospitals in China from January 2011 to May 2017. The primary outcome was independence (modified Rankin Scale score ≤2) at discharge. Data-driven achievable benchmarking used the "pared-mean" approach to set objective performance targets. Hierarchical logistic regression models were employed to evaluate the process-outcome association, as well as the predicted quality improvement if all hospitals were to operate at the benchmark level. RESULTS: Of the overall population, 64.01% were independent patients at discharge. The performance benchmarks were >90% for most of the quality indicators. After adjusting for patient-level and hospital-level characteristics and unifying hospital performance to the benchmark level, the quality indicators with high increase in both overall adherence rate and independence rate were thrombolytic therapy, anticoagulant therapy, venous thrombosis prophylaxis. CONCLUSIONS: Performance targets for three acute treatments, including thrombolytic therapy, anticoagulant therapy, venous thrombosis prophylaxis, could best motivate improvements in both overall adherence rate and independence rate at discharge. The finding suggests that the above three types of acute treatment should be given priority to improve the quality of acute ischemic stroke care.

Weekly variation in quality of care for acute ST-segment elevation myocardial infarction by day and time of admission: a retrospective observational study.

BACKGROUND: The admission time of patients with ST-segment elevation myocardial infarction (STEMI) may affect the quality of care they receive. This study aimed to explore the pattern and magnitude of variation in quality of care for patients with STEMI in both the process and outcome domains. METHODS: We performed a retrospective study based on STEMI data from China. We estimated the adjusted ORs of six process indicators and one outcome indicator of STEMI care quality by fitting multilevel multivariable regression models across 42 4hour time periods per week. RESULTS: The study cohort comprised 98 628 patients with STEMI. Care quality varied by time of arrival to the emergency department. We identified three main patterns of variation, which were consistent across days of the week. In the first pattern, which applied to electrocardiographic examination within 10 min of arrival and to aspirin or clopidogrel use within 10 min of arrival, quality was lowest for arrivals between 08:00 and 12:00, rose through the day and peaked for arrivals between 24:00 and 04:00. Percutaneous transluminal coronary intervention treatment within 90 min showed the same pattern but with maximal performance for those arriving 20:00-24:00. In the third pattern, applying to lipid function evaluation within 24 hours and beta blocker use within 24 hours, quality was best for arrivals between 04:00-08:00 and 16:00-19:00 and worst for arrivals between 24:00-04:00 and 12:00-16:00. CONCLUSIONS: The quality of care for STEMI shows three patterns of diurnal variation. Detecting the times at which quality is relatively low may lead to quality improvement in healthcare. Quality improvement should focus on reducing the weekend effect and off-hour effect and the diurnal temporal variation.

Predicted quality benefits of achievable performance benchmarks of chronic heart failure care in China: results from a nationwide observational study.

OBJECTIVES: This study aimed to set a data-driven achievable performance benchmark, explore the process-outcome association and speculate about the net gain in quality improvement with benchmarking. DESIGN: Observational study. SETTING: Patient survey conducted at 466 secondary and tertiary hospitals across 31 provinces, autonomous regions and municipalities in China. PARTICIPANTS: 183 334 patients diagnosed with chronic heart failure (CHF) who were treated at 466 Chinese hospitals from January 2011 through May 2017. PRIMARY INDEPENDENT VARIABLES: Hospital process composite performance (HPCP). SECONDARY INDEPENDENT VARIABLES: Patient-level and hospital-level characteristics. PRIMARY OUTCOME MEASURE: Patients getting better or recovered after treatment, in-hospital mortality, length of hospital stay (LOS) and medical cost. METHODS: HPCP was calculated using denominator-based weights. Mixed random-intercept models were used to evaluate the contributions of HPCP on patient outcomes and to speculate quality improvement after adjusting HPCP to benchmark level. RESULTS: When all hospitals were to operate at the benchmark level, the proportion of patients getting better or recovered after treatment would increase in most hospitals, particularly those with low baseline rates. However, there was no evidence for lowering in-hospital mortality, significant savings in cost or shortening LOS. CONCLUSIONS: Increasing the adherence rate of CHF care and closing the gap in HPCP between hospitals have important implications for improving patient condition.

Identifying Performance Outliers for Stroke Care Based on Composite Score of Process Indicators: an Observational Study in China.

BACKGROUND: Variability in the quality of stroke care is widespread. Identifying performance-based outlier hospitals based on quality indicators (QIs) has become a common practice. OBJECTIVES: To develop a tool for identifying performance-based outlier hospitals based on risk-adjusted adherence rates of process indicators. DESIGN: Hospitals were classified into five-level outliers based on the observed-to-expected ratio and P value. The composite quality score was derived by summation of the points for each indicator for each hospital, and associations between outlier status and outcomes were determined. PARTICIPANTS: Patients diagnosed with acute ischemic stroke, January 1, 2011-May 31, 2017. INTERVENTION: N/A MAIN OUTCOME MEASURES: Independence at discharge (the modified Rankin Scale = 0-2). KEY RESULTS: A total of 501,132 patients from 519 hospitals were identified. From 0.39 to 19.65% of hospitals were identified as high outliers according to various QIs. Composite quality scores ranged from - 20 to 16. Providers that were high outliers based on QI2, QI8, QI9, and QI11 had higher independent rates. For composite quality score, each point increase corresponded to an 8% increase in the odds of independent rate. CONCLUSION: Nationwide variation in the quality of acute stroke care exists at the hospital level. Variability in the quality of stroke care can be captured by our proposed quality score. Applying this quality score as a benchmarking tool could provide audit-level feedback to policymakers and hospitals to aid quality improvement.

Factors analysis on the use of key quality indicators for narrowing the gap of quality of care of breast cancer.

BACKGROUND: There are differences in the quality of care among breast cancer patients. Narrowing the quality differences could be achieved by increasing the utilization rate of indicators. Here we explored key indicators that can improve the quality of care and factors that may affect the use of these indicators. METHODS: A total of 3669 breast cancer patients were included in our retrospective study. We calculated patient quality-of-care composite score based on patient average method. Patients were divided into high- and low-quality groups according to the mean score. We obtained the indicators with large difference in utilization between the two groups. Multilevel logistic regression model was used to analyze the factors influencing quality of care and use of indicators. RESULTS: The mean composite score was 0.802, and the number of patients in the high- and low-quality groups were 1898 and 1771, respectively. Four indicators showed a difference in utilization between the two groups of over 40%. Histological grade, pathological stage, tumor size and insurance type were the factors affecting the quality of care. In single indicator evaluation, besides the above factors, age, patient income and number of comorbidities may also affect the use of these four indicators. Number of comorbidities may have opposite effects on the use of different indicators, as does pathological stage. CONCLUSIONS: Identifying key indicators for enhancing the quality-of-care of breast cancer patients and factors that affect the indicator adherence may provide guides for enhancing the utilization rate of these indicators in clinical practice.

Regulation of proinflammatory monocyte activation by the kynurenine-AhR axis underlies immunometabolic control of depressive behavior in mice.

Elevated kynurenine (Kyn) production from tryptophan (Trp) metabolism is a biomarker of immune dysregulation in depression, but its mechanistic contributions to the behavioral symptoms are poorly defined. In this study, Kyn was shown to be a metabolic regulator of proinflammatory monocytes that orchestrated peripheral immune activation and neuroinflammation in depressive mice. Kyn-induced depressive behavior was paralleled by brain infiltration of proinflammatory monocytes and astrocytic activation. Kyn enhanced chemokine (C-C motif) ligand-2-mediated chemotaxis of monocytes and their proinflammatory capability on cocultured astrocytes in vitro, which involved the activation of aryl hydrocarbon receptor (AhR) signaling. Kyn augmented, whereas pharmacological AhR blockade rescued, systemic inflammation-induced monocyte trafficking, neuroimmune disturbance, and depressive-like behavior in mice. The behavior-exacerbating effects of the Kyn-AhR axis were dampened with prior depletion of functional monocytes in the periphery. The findings in our study extend understanding of an immunologic effect of Kyn that links Trp metabolism and inflammatory signaling in depression pathology, with potential therapeutic implications for depressive disorders.-Zang, X., Zheng, X., Hou, Y., Hu, M., Wang, H., Bao, X., Zhou, F., Wang, G., Hao, H. Regulation of proinflammatory monocyte activation by the kynurenine-AhR axis underlies immunometabolic control of depressive behavior in mice.