Dataset Information

Rating Hospital Performance in China: Review of Publicly Available Measures and Development of a Ranking System.

ABSTRACT:

Background

In China, significant emphasis and investment in health care reform since 2009 has brought with it increasing scrutiny of its public hospitals. Calls for greater accountability in the quality of hospital care have led to increasing attention toward performance measurement and the development of hospital ratings. Despite such interest, there has yet to be a comprehensive analysis of what performance information is publicly available to understand the performance of hospitals in China.

Objective

This study aims to review the publicly available performance information about hospitals in China to assess options for ranking hospital performance.

Methods

A review was undertaken to identify performance measures based on publicly available data. Following several rounds of expert consultation regarding the utility of these measures, we clustered the available options into three key areas: research and development, academic reputation, and quality and safety. Following the identification and clustering of the available performance measures, we set out to translate these into a practical performance ranking system to assess variation in hospital performance.

Results

A new hospital ranking system termed the China Hospital Development Index (CHDI) is thus presented. Furthermore, we used CHDI for ranking well-known tertiary hospitals in China.

Conclusions

Despite notable limitations, our assessment of available measures and the development of a new ranking system break new ground in understanding hospital performance in China. In doing so, CHDI has the potential to contribute to wider discussions and debates about assessing hospital performance across global health care systems.

SUBMITTER: Dong S

PROVIDER: S-EPMC8277410 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundChIPx (i.e., ChIP-seq and ChIP-chip) is increasingly used to map genome-wide transcription factor (TF) binding sites. A single ChIPx experiment can identify thousands of TF bound genes, but typically only a fraction of these genes are functional targets that respond transcriptionally to perturbations of TF expression. To identify promising functional target genes for follow-up studies, researchers usually collect gene expression data from TF perturbation experiments to determine which of the TF targets respond transcriptionally to binding. Unfortunately, approximately 40% of ChIPx studies do not have accompanying gene expression data from TF perturbation experiments. For these studies, genes are often prioritized solely based on the binding strengths of ChIPx signals in order to choose follow-up candidates. ChIPXpress is a novel method that improves upon this ChIPx-only ranking approach by integrating ChIPx data with large amounts of Publicly available gene Expression Data (PED).ResultsWe demonstrate that PED does contain useful information to identify functional TF target genes despite its inherent heterogeneity. A truncated absolute correlation measure is developed to better capture the regulatory relationships between TFs and their target genes in PED. By integrating the information from ChIPx and PED, ChIPXpress can significantly increase the chance of finding functional target genes responsive to TF perturbation among the top ranked genes. ChIPXpress is implemented as an easy-to-use R/Bioconductor package. We evaluate ChIPXpress using 10 different ChIPx datasets in mouse and human and find that ChIPXpress rankings are more accurate than rankings based solely on ChIPx data and may result in substantial improvement in prediction accuracy, irrespective of which peak calling algorithm is used to analyze the ChIPx data.ConclusionsChIPXpress provides a new tool to better prioritize TF bound genes from ChIPx experiments for follow-up studies when investigators do not have their own gene expression data. It demonstrates that the regulatory information from PED can be used to boost ChIPx data analyses. It also represents an important step towards more fully utilizing the valuable, but highly heterogeneous data contained in public gene expression databases.

Project description:IntroductionA Cloud-ORiented Engine for advanced MRI simulations (coreMRI) is presented in this study. The aim was to develop the first advanced MR simulation platform delivered as a web service through an on-demand, scalable cloud-based and GPU-based infrastructure. We hypothesized that such an online MR simulation platform could be utilized as a virtual MRI scanner but also as a cloud-based, high-performance engine for advanced MR simulations in simulation-based quantitative MR (qMR) methods.Methods and resultsThe simulation framework of coreMRI was based on the solution of the Bloch equations and utilized a ground-up-approach design based on the principles already published in the literature. The development of a front-end environment allowed the connection of the end-users to the GPU-equipped instances on the cloud. The coreMRI simulation platform was based on a modular design where individual modules (such as the Gadgetron reconstruction framework and a newly developed Pulse Sequence Designer) could be inserted in the main simulation framework. Different types and sources of pulse sequences and anatomical models were utilized in this study revealing the flexibility that the coreMRI simulation platform offers to the users. The performance and scalability of coreMRI were also examined on multi-GPU configurations on the cloud, showing that a multi-GPU computer on the cloud equipped with a newer generation of GPU cards could significantly mitigate the prolonged execution times that accompany more realistic MRI and qMR simulations.ConclusionscoreMRI is available to the entire MR community, whereas its high performance and scalability allow its users to configure advanced MRI experiments without the constraints imposed by experimentation in a true MRI scanner (such as time constraint and limited availability of MR scanners), without upfront investment for purchasing advanced computer systems and without any user expertise on computer programming or MR physics. coreMRI is available to the users through the webpage https://www.coreMRI.org.

Project description:Public reporting of quality is considered a key strategy for stimulating improvement efforts at US hospitals; however, little is known about the attitudes of hospital leaders toward existing quality measures.To describe US hospital leaders' attitudes toward hospital quality measures found on the Centers for Medicare & Medicaid Services' Hospital Compare website, assess use of these measures for quality improvement, and examine the association between leaders' attitudes and hospital quality performance.We mailed a 21-item questionnaire from January 1 through September 31, 2012, to senior hospital leaders from a stratified random sample of 630 US hospitals, including equal numbers with better-than-expected, as-expected, and worse-than-expected performance on mortality and readmission measures.We assessed levels of agreement with statements concerning quality measures, examined use of measures for improvement activities, and analyzed the association between leaders' attitudes and hospital performance.Of 630 hospitals surveyed, 380 (60.3%) responded. For each of the mortality, readmission, process, and patient experience measures, more than 70% of hospitals agreed with the statement that "public reporting stimulates quality improvement activity at my institution"; agreement for measures of cost and volume was 65.2% and 53.3%, respectively. A similar pattern was observed for the statement that "our hospital is able to influence performance on this measure"; agreement for processes of care and patient experience measures was 96.4% and 94.2%, respectively. A total of 89.7% of hospitals agreed that the hospital's reputation was influenced by patient experience measures; agreement was 77.4% for mortality, 69.9% for readmission, 76.3% for process measures, 66.1% for cost measures, and 54.0% for volume measures. A total of 87.1% of hospitals reported incorporating performance on publicly reported measures into their hospital's annual goals, whereas 90.2% reported regularly reviewing the results with the hospital's board of trustees and 94.3% with senior clinical and administrative leaders. When compared with chief executive officers and chief medical officers, respondents who identified themselves as chief quality officers or vice presidents of quality were less likely to agree that public reporting stimulates quality improvement and that measured differences are large enough to differentiate among hospitals.Hospital leaders indicated that the measures reported on the Hospital Compare website exert strong influence over local planning and improvement efforts. However, they expressed concerns about the clinical meaningfulness, unintended consequences, and methods of public reporting.

Project description:ObjectiveTo determine if increases in hospital discharge prices are associated with improvements in clinical quality or patient experience.Data sourcesThis study used Medicare cost report data and publicly available Medicare.gov Care Compare quality measures for approximately 3000 short-term care general hospitals between 2011 and 2018.Study designWe separately regressed quality measure scores on a lag of case mix adjusted discharge price, hospital fixed effects, and year indicators. Clinical quality measures included 30-day readmission rates for acute myocardial infarction, chronic obstructive pulmonary disease, heart failure, hip and knee replacement, and pneumonia; risk-adjusted 30-day mortality rates for acute myocardial infarction, chronic obstructive pulmonary disease, heart failure, and stroke; and 90-day complication rate for hip and knee replacement. Patient experience measures included the summary star rating and 10 domain measures reported through the Hospital Consumer Assessment of Healthcare Providers and Systems survey. We tested for heterogeneous effects by hospital ownership, number of beds, the commercial share of overall discharges, and market concentration.Data collection/extraction methodsWe linked hospitals identified in Medicare cost reports to Medicare.gov Care Compare quality measures. We excluded hospitals for which we could not identify a discharge price or that had an unrealistic price.Principal findingsThere was no positive association between lagged discharge price and any clinical quality measure. For patient experience measures, a 2% increase in discharge price was not associated with overall patient satisfaction but was associated with small, statistically significant increases ranging from 0.01% to 0.02% (relative to mean scores) for seven of ten domain measures. There was a positive association for five of ten patient experience measures in competitive markets and one measure in both moderately concentrated and heavily concentrated markets.ConclusionsWe found no evidence that hospitals use higher prices to make investments in clinical quality; patient experience improved, but only negligibly.