U.S. hospital performance methodologies: a scoping review to identify opportunities for crossing the quality chasm.

BACKGROUND: Hospital performance quality assessments inform patients, providers, payers, and purchasers in making healthcare decisions. These assessments have been developed by government, private and non-profit organizations, and academic institutions. Given the number and variability in available assessments, a knowledge gap exists regarding what assessments are available and how each assessment measures quality to identify top performing hospitals. This study aims to: (a) comprehensively identify current hospital performance assessments, (b) compare quality measures from each methodology in the context of the Institute of Medicine's (IOM) six domains of STEEEP (safety, timeliness, effectiveness, efficiency, equitable, and patient-centeredness), and (c) formulate policy recommendations that improve value-based, patient-centered care to address identified gaps. METHODS: A scoping review was conducted using a systematic search of MEDLINE and the grey literature along with handsearching to identify studies that provide assessments of US-based hospital performance whereby the study cohort examined a minimum of 250 hospitals in the last two years (2017-2019). RESULTS: From 3058 unique records screened, 19 hospital performance assessments met inclusion criteria. Methodologies were analyzed across each assessment and measures were mapped to STEEEP. While safety and effectiveness were commonly identified measures across assessments, efficiency, and patient-centeredness were less frequently represented. Equity measures were also limited to risk- and severity-adjustment methods to balance patient characteristics across populations, rather than stand-alone indicators to evaluate health disparities that may contribute to community-level inequities. CONCLUSIONS: To further improve health and healthcare value-based decision-making, there remains a need for methodological transparency across assessments and the standardization of consensus-based measures that reflect the IOM's quality framework. Additionally, a large opportunity exists to improve the assessment of health equity in the communities that hospitals serve.

A new grid-scale model simulating the spatiotemporal distribution of PM2.5-PAHs for exposure assessment.

Exposure to polycyclic aromatic hydrocarbons (PAHs) associated with ambient air particulate matter (PM) poses significant health concerns. Several modeling approaches have been developed for simulating ambient PAHs, but no hourly intra-urban spatial data are currently available. The aim of this study is to develop a new modeling strategy in simulating, on an hourly basis, grid-scale PM2.5-PAH levels. PM and PAHs were collected over a one-year time frame through an established air quality monitoring network within a metropolitan area of Taiwan. Multivariate linear regression models, in combination with correlation analysis and PAH source identification by principal component analysis (PCA), were performed to simulate hourly grid-scale PM2.5-PAH concentrations, taking criteria pollutants and meteorological variables selected as possible predictors. The simulated levels of 72-h personal exposure were found to be significantly (R=0.729**, p<0.01) correlated with those analyzed from portable personal monitors. A geographic information system (GIS) was used to visualize spatially distributed PM2.5-PAH concentrations of the modeling results. This new grid-scale modeling strategy, incorporating the output of simulated data by GIS, provides a useful and versatile tool in personal exposure analysis and in the health risk assessment of air pollution.

ROCK1 in AgRP neurons regulates energy expenditure and locomotor activity in male mice.

Normal leptin signaling is essential for the maintenance of body weight homeostasis. Proopiomelanocortin- and agouti-related peptide (AgRP)-producing neurons play critical roles in regulating energy metabolism. Our recent work demonstrates that deletion of Rho-kinase 1 (ROCK1) in the AgRP neurons of mice increased body weight and adiposity. Here, we report that selective loss of ROCK1 in AgRP neurons caused a significant decrease in energy expenditure and locomotor activity of mice. These effects were independent of any change in food intake. Furthermore, AgRP neuron-specific ROCK1-deficient mice displayed central leptin resistance, as evidenced by impaired Signal Transducer and Activator of Transcription 3 activation in response to leptin administration. Leptin's ability to hyperpolarize and decrease firing rate of AgRP neurons was also abolished in the absence of ROCK1. Moreover, diet-induced and genetic forms of obesity resulted in reduced ROCK1 activity in murine arcuate nucleus. Of note, high-fat diet also impaired leptin-stimulated ROCK1 activity in arcuate nucleus, suggesting that a defect in hypothalamic ROCK1 activity may contribute to the pathogenesis of central leptin resistance in obesity. Together, these data demonstrate that ROCK1 activation in hypothalamic AgRP neurons is required for the homeostatic regulation of energy expenditure and adiposity. These results further support previous work identifying ROCK1 as a key regulator of energy balance and suggest that targeting ROCK1 in the hypothalamus may lead to development of antiobesity therapeutics.