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Data from the American Hospital Association’s Annual Survey of Hospitals, which are used to produce the AHA Guide, Hospital Statistics, and other data products, are widely used by hospital administrators, academic researchers, and healthcare marketers. Although they are widely used, many who use data from the survey are unaware of their limitations and problems. Such problems include: inaccuracies and inconsistencies in reporting; low response rates to certain data items; biases in reporting; and a lack of publicly available technical documentation concerning the statistical methodology of the survey, particularly its estimation and imputation procedures for missing data. Failure to be sophisticated consumers of data products can misdirect the outcome of important planning and marketing efforts.

Background – Reliable and valid hospital nurse staffing measures are a major requirement for health services research. As the use of these measures increases, discussion is growing as to whether current nurse staffing measures adequately meet the needs of health services researchers.

Objective – This study assesses whether the measures, sampling frameworks, and data sources meet the needs of health services research in areas such as staffing assessment; patient, nurse, and financial outcomes; and prediction of staffing.

Methods – We performed a systematic review of articles from 1990 through 2007, which use hospital nurse staffing measures in original research, or which address the validity, reliability, and availability of the measures. Taxonomies of measures, sampling frameworks, and sources were developed. Articles were analyzed to assess what measures, sampling strategies, and sources of data were used and to ascertain whether the measures, samples, and sources meet the needs of researchers.

Results – The review identified 107 articles that use hospital nurse staffing measures for original research. Multiple types of measures, some of which are used more often than others and some of which are more valid than others, exist in each of the following categories: staffing counts, staffing/patient load ratios, and skill mix. Sampling frameworks range from hospital units to all hospitals nationally, with all hospitals in a state being the most common. Data sources range from small-scale surveys to national databases. The American Hospital Association Annual Survey is the most frequently used data source, but there are limitations with its nurse staffing measures. Arguably, the multiplicity of measures and differences in sampling and data sources are due, in part, to data availability. The limitations noted by other researchers and by this review indicate that staffing measures need improvements in conceptualization, content, scope, and availability.

Discussion – Recommendations are made for improvements to research and administrative practice and to data.

The purpose of this paper is to examine the feasibility of collecting standardized, patient reported race and ethnicity (RE) data in hospitals, and to assess the impact on data quality and utility.

Part of a larger evaluation that included a comprehensive assessment. Sites documented RE data collection procedures before and after program implementation. Primary data collected through qualitative interviewing with key respondents in ten hospitals to assess implementation. Nine hospitals provided RE data on the same patients before and after implementation new data collection procedures were implemented to assess impact.

Implementation went smoothly in nine of ten hospitals and had substantial effects on the hospital staff awareness on the potential for disparities within their hospitals. New procedures had minimal impact on characterization of readmitted patients.

This study demonstrated that it is feasible for staff in a diverse group of hospitals to implement systematic, internally standardized methods to collect self-reported RE data from patients.

Although this study found little impact patients’ demographic characterizations, other benefits included greater awareness of and attention to disparities, uncovering small pockets of minorities, and dramatically increased RE data use in quality improvement efforts.

The purpose of this paper is to understand the concerns and factors that impact on hospital quality and safety, particularly related to use of performance data, within a setting of devolved governance.

This qualitative study used thematic analysis of interviews with public hospital medical directors. For additional context, findings were framed by themes from a review of hospital safety and quality in the same jurisdiction.

Varying approaches and levels of complexity were described about what and how performance data are reviewed, prioritised, and quality improvements implemented. Although no consistent narrative emerged, facilitators of improvement were suggested relating to organisational culture, governance, resources, education, and technologies. These hospital-level perspectives articulate with and expand on the system-level themes in a state-wide review of hospital safety and quality.

The findings are not generalisable, but point to an underlying absence of system-wide agreement on how to perceive, retrieve, analyse, prioritise and action hospital performance data.

Lack of electronic medical records and an inefficient incident reporting system limits the extent to which performance and incident data can be analysed, linked and shared, thus limiting hospital performance improvement, oversight and learning.

Variable approaches to quality and safety, standards of care, and hospital record keeping and reporting, mean that healthcare consumers might expect inconsistency across Victorian hospitals.

The views of medical directors have been little researched. This work uses their voice to better understand contextual factors that situate and impact on hospital quality and safety towards understanding the mixed effectiveness of hospital quality improvement strategies.

This study investigates the stability of the “hospital effect” on performance over time by administrative health data as a source of evidence. Using 78,907 heart failure adult records from 117 hospitals in the Lombardy Region (Northern Italy) over three years (2010–2012), we analyzed hospital performance in terms of 30-day mortality and 30-day unplanned readmissions to gather evidence about the stability of the “hospital effect.” Best/worst performers were identified through multi-level models that combine both patient and hospital covariates. Our results confirm that managerial choices affect hospital performance, and that the “hospital effect” is not, contrary to expectations, stable over the short term. Performance improvement/worsening over the three years has been also analyzed.

Delay in the clinical information system (CIS) restoration overseeing critical health-care operations after an unexpected data loss can be fatal for patients under care. Investment in information technology (IT) capabilities and synergy between various computerized systems has been argued as the resilient information system's enablers. The purpose of this study is to empirically quantify the influence of IT investment, integration and interoperability in recovering the CIS from a data disaster.

An archival dataset sourced from a European Commission-sponsored survey of 773 hospitals across 30 countries in Europe is utilized to study the relationships. The study adopts a quasi-experimental research design approach where sample observations are weighted based on their propensity to be selected in treatment groups. The artificial weighing allows attaining a pseudo-random sample to counter the effects of selection bias.

The study finds that hospitals with more than 5% of the budget dedicated to IT have 100% higher odds of recovering immediately from a critical data loss in comparison to those that have less than 1% investment in IT. The greater extent of IT integration significantly reduces the time to recover the CIS, while interoperability problems at the organizational level lessen the odds of immediate recovery by 19%. Interoperability problems at the technical and semantic levels do not significantly impact recovery times of the CIS.

The study proposes several empirically quantified and scientifically tested recommendations for health-care providers for faster restoration of critical CIS operations post data loss. The differential impact of the interoperability problems at the technical, semantic and organizational levels has also been highlighted.

Researchers recommend a reorganization of the medical profession into larger groups with a multispecialty mix. We analyze whether there is evidence for the superiority of these models and if this organizational transformation is underway.

We summarize the evidence on scale and scope economies in physician group practice, and then review the trends in physician group size and specialty mix to conduct survivorship tests of the most efficient models.

The distribution of physician groups exhibits two interesting tails. In the lower tail, a large percentage of physicians continue to practice in small, physician-owned practices. In the upper tail, there is a small but rapidly growing percentage of large groups that have been organized primarily by non-physician owners.

While our analysis includes no original data, it does collate all known surveys of physician practice characteristics and group practice formation to provide a consistent picture of physician organization.

Our review suggests that scale and scope economies in physician practice are limited. This may explain why most physicians have retained their small practices.

Larger, multispecialty groups have been primarily organized by non-physician owners in vertically integrated arrangements. There is little evidence supporting the efficiencies of such models and some concern they may pose anticompetitive threats.

This is the first comprehensive review of the scale and scope economies of physician practice in nearly two decades. The research results do not appear to have changed much; nor has much changed in physician practice organization.

The purpose of this paper is to examine the relationship between patient safety culture and hospital performance using objective performance measures and secondary data on patient safety culture.

Patient safety culture is measured using data from the Agency for Healthcare Research and Quality’s Hospital Survey on Patient Safety Culture. Hospital performance is measured using objective patient safety and operational performance metrics collected by the Centers for Medicare and Medicaid Services (CMS). Control variables were obtained from the CMS Provider of Service database. The merged data included 154 US hospitals, with an average of 848 respondents per hospital providing culture data. Hierarchical linear regression analysis is used to test the proposed relationships.

The findings indicate that patient safety culture is positively associated with patient safety, process quality and patient satisfaction.

Hospital managers should focus on building a stronger patient safety culture due to its positive relationship with hospital performance.

This is the first study to test these relationships using several objective performance measures and a comprehensive patient safety culture data set that includes a substantial number of respondents per hospital. The study contributes to the literature by explicitly mapping high-reliability organization (HRO) theory to patient safety culture, thereby illustrating how HRO theory can be applied to safety culture in the hospital operations context.

Since Jan. 1, 2019, the Centers for Medicare and Medicaid Services' (CMS) rule requiring hospitals publish their “standard charges” (also called “charge description masters” or “chargemasters”) in a public, machine-readable format has been in effect. The research at hand assesses hospital compliance with the federal regulation. In addition, a sentiment analysis of the chargemaster webpages compared to hospital homepages is performed to assess the consumer friendliness of the content in terms of language usage. A stratified sample of 212 hospitals was used to conduct observations. Strata were based on patient satisfaction scores drawn from the Hospital Consumer Assessment of health care Providers and Systems survey, and controls for hospital bed size and geographic US census region were utilized from the American Hospital Association Annual Survey. Descriptive statistics are presented, and chi-square testing is used to test for statistically significant differences. Key results are presented for compliance and sentiment. Most hospitals' websites are not presenting chargemaster data in a way that is readily collectable or comparable to other facilities. In addition, the tone of language used on chargemaster transparency webpages is generally more negative than that of hospitals' homepages. In particular, the messaging on transparency pages routinely suggests consumers to not use the data for decision-making purposes.

The goal of this contribution is to shed light on the benefits for research in health care coming from the use of administrative data, especially in terms of measuring hospitals’ outcomes. The main approaches to health outcome evaluation are reviewed and the possible improvements deriving from the use of administrative data are highlighted. Administrative data may be an essential element in the process of gathering to the public true rankings of health care organizations, reducing the degree of asymmetric information that typically arises in health care. Patients will be more aware of the best institutions, which will induce most of them to demand to be admitted in them, taking into account the costs associated with distance and with the severity of the illness. This in turn may ask for a reorganization of the sector, closing some organizations and expanding others, having as final goal to improve the health status of the population, without income barriers. This is one of the first attempts to provide an overview of the advantages that administrative data may gather in health care.