Does hospital ownership influence hospital referral region health rankings in the United States

Single-Vendor Electronic Health Record Use Is Associated With Greater Opportunities for Organizational and Clinical Care Improvements

Objective

To compare how hospitals that use single-vendor vs best-of-breed electronic health record (EHR) vendors utilize clinical and organizational evaluation capabilities.

Methods

Data from the 2018 (June 1, 2016, to December 31, 2017) American Hospital Association Information Technology Supplement Survey and Medicare Final Rule Standardizing File were used. Multinomial logistic regression analysis of hospitals (n=1902) was conducted to identify hospital characteristics associated with the use of EHRs for (1) clinical care evaluation capabilities and (2) organizational evaluation capabilities.

Results

Single-vendor EHR hospitals were more likely (relative risk ratio, 3.37; 95% confidence interval, 1.97-5.76) to use EHRs for clinical care and organizational evaluation capabilities. Not-for-profit hospitals were more likely to use EHRs for all organizational evaluation capabilities than government nonfederal hospitals. For-profit hospitals were less likely to use EHRs for organizational or clinical evaluation capabilities than government nonfederal hospitals.

Conclusion

Hospitals using the single-vendor EHR system were more likely to engage in clinical care and organizational evaluation than hospitals using best-of-breed EHR systems.

Hospital-Acquired Conditions Reduction Program, Patient Safety, and Magnet Designation in the United States

OBJECTIVE

The aim of the study was to investigate the association between hospitals' nursing excellence accreditation and patient safety performance-measured by the Hospital-Acquired Conditions Reduction Program (HACRP).

METHODS

We linked data from the American Nursing Credentialing Center Magnet Recognition Program, Centers for Medicare and Medicaid Services HACRP, and the American Hospital Association annual survey from 2014 to 2016. We constrained the analysis to hospitals participating in Centers for Medicare and Medicaid Services' HACRP and deployed propensity score matching models to calculate the coefficients for our HACRP patient safety measures. These measures consisted of (a) patient safety indicator 90, (b) hospital-associated infection measures, and (c) total HAC scores. In addition, we used propensity score matching to assess HACRP scores between hospitals achieving Magnet recognition in the past 2 versus longer and within the past 5 years versus longer.

RESULTS

Our primary findings indicate that Magnet hospitals have an increased likelihood of experiencing lower patient safety indicator 90 scores, higher catheter-associated urinary tract infection and surgical site infection scores, and no different total HAC scores. Finally, when examining the impact of Magnet tenure, our analysis revealed that there were no differences in Magnet tenure.

CONCLUSIONS

Results indicate that the processes, procedures, and educational aspects associated with Magnet recognition seem to provide important improvements associated with care that is controlled by nursing practice. However, because these improvements do not differ when comparing total HAC scores nor Magnet hospitals with different tenure, there are likely opportunities for Magnet hospitals to continue process improvements focused on HACRP scores.

The Effects of Home Health Value-Based Purchasing on Home Health Care Quality in For-Profit and Nonprofit Agencies: A Comparative Interrupted Time-Series Analysis, 2012-2018

Beginning in 2016, the Home Health Value-Based Purchasing (HHVBP) model incentivized U.S. Medicare-certified home health agencies (HHAs) in nine states to improve quality of patient care and patient experience. Here, we quantified HHVBP effects upon quality over time (2012-2018) by HHA ownership (i.e., for-profit vs. nonprofit) using a comparative interrupted time-series design. Our outcome measures were Care Quality and Patient Experience indices composed of 10 quality of patient care measures and five patient experience measures, respectively. Overall, 17.7% of HHAs participated in the HHVBP model of which 81.4% were for-profit ownership. Each year after implementation, HHVBP was associated with a 1.59 (p < .001) percentage point increase in the Care Quality index among for-profit HHAs and a 0.71 (p = .024) percentage point increase in the Patient Experience index among nonprofits. The differences of quality improvement under the HHVBP model by ownership indicate variations in HHA leadership responses to HHVBP.

The influence of community health on hospitals attainment of Magnet designation: Implications for policy and practice

AIMS

To determine if there is an association between better County Health Rankings and the increased odds of a hospital gaining Magnet designation in subsequent years (2014-2019) compared with counties with lower rankings.

BACKGROUND

The Magnet hospital model is recognized to have a great effect on nurses, patients and organizational outcomes. Although Magnet hospital designation is a well-established structural marker for nursing excellence, the effect of County Health Rankings and subsequent hospital achievement of Magnet status is unknown.

DESIGN

A descriptive, cross-sectional quantitative approach was adopted for this study.

METHODS

Data were derived from 2010 to 2019 U.S. County Health Rankings, American Hospital Association, and American Nursing Credentialing Center databases. Logistic regression models were utilized to determine associations between county rankings for health behaviours, clinical care, social and economic factors, physical environment and counties with a new Magnet hospital after 2014.

RESULTS

Counties with the worst rankings for clinical care and socio-economic status had reduced odds of obtaining a Magnet hospital designation compared with best-ranking counties. While middle-ranking counties for the physical environment ranking had increased odds of having Magnet designation compared with best-ranking counties. Additionally, having an increased percent of government non-federal hospital or a higher percentage of critical access hospitals in the county reduced the odds of having a Magnet-designated facility after 2014.

CONCLUSION

The findings underscore the important associations between Magnet-designated facilities' location and the health of its surrounding counties. This study is the first to examine the relationship between County Health Rankings and a hospital's likelihood of obtaining Magnet status and points to the need for future research to explore outcomes of care previously identified as improved in Magnet-designated hospitals.

IMPLICATIONS

Recognizing the benefits of Magnet facilities, it is important for health care leaders and policy makers to seek opportunities to promote centres of excellence in higher need communities through policy and financial intervention.

Race to the Top of the Hospital Value-Based Purchasing Program

EXECUTIVE SUMMARY

Medicare's Hospital Valued-Based Purchasing (HVBP) program measures hospitals' total performance score (TPS); its measurement strategies have changed regularly since its rollout in 2013. Because the program influences care delivery, it is important to examine how the policy has changed hospitals' behavior and how it may inform future policies. The purpose of this study was to assess the relationship between hospitals' performance on TPS annually from 2013 to 2018 and organizational characteristics. Using the HVBP TPS from 2013 to 2018 and associated hospital characteristics-hospital size, teaching hospital status, system membership, ownership type, urban/rural location, average percentages of patients from Medicare and Medicaid, operating margins, percentages of inpatient revenue as a proportion of total revenue, and case mix index-we conducted a retrospective cohort study of all U.S. hospitals participating in the HVBP program. Regression and panel analyses found that organizations that were expected to have robust and rigid resources were unable to score in the superior category consistently. In addition, organizations were unable to consistently perform positively over time because of changes in the HVBP program measurement and the required organizational responses. Policymakers should consider the ability of organizations to respond to changes to the HVBP program. Likewise, healthcare managers, particularly those in larger organizations, should seek to remove bureaucracy or allow for greater resource slack to meet these changes.

Smoke-Free Policies and 30-Day Readmission Rates for Chronic Obstructive Pulmonary Disease

INTRODUCTION

Previous evidence has shown that smoke-free policies reduce hospital admissions due to respiratory causes, but the impact on 30-day readmission has not been determined. As 25 states in the U.S. have not adopted comprehensive smoke-free legislation, it is likely that patients return to an environment that increases risk of a secondary event. The aim of this study is to investigate the impact of smoke-free policies on 30-day readmission rates for adults aged ≥65 years following hospitalization for chronic obstructive pulmonary disease in the U.S.

METHODS

Data from the U.S. Tobacco Control Laws Database, Centers for Medicare and Medicaid Services Hospital Readmissions Reduction Program, American Hospital Association, Area Health Resource File, and U.S. Census Bureau Current Population Survey were merged at the county level for years 2013-2016 and analyzed in 2018. Hierarchical Poisson regression models were utilized to calculate incidence rate ratios to determine the impact of full, partial, and no smoke-free policies on 30-day readmission rates after chronic obstructive pulmonary disease hospitalization.

RESULTS

Multivariable analysis adjusting for both county and hospital characteristics revealed that the presence of full (incidence rate ratio=0.81, 95% CI=0.76, 0.88) and partial (incidence rate ratio=0.87, 95% CI=0.81, 0.92) smoke-free policies were associated with fewer 30-day readmissions for chronic obstructive pulmonary disease-related hospitalizations when compared with counties with no smoke-free policy.

CONCLUSIONS

The implementation of smoke-free policies is an effective measure for reducing 30-day readmissions following hospitalization due to chronic obstructive pulmonary disease, with stronger policies resulting in decreased risk. Efforts to reduce chronic obstructive pulmonary disease-related 30-day readmissions should include the implementation of smoke-free policies.

Impact of hospitals' Referral Region racial and ethnic diversity on 30-day readmission rates of older adults

Background: The Hospital Readmissions Reduction Program (HRRP) began decreasing Medicare payments to hospitals reporting high readmission rates for individuals over 65. Thus, financially incentivizing hospitals to improve quality performance on preventable readmissions. Well-established research indicates that minorities are more frequently readmitted to hospitals, but it is unknown if community diversity is associated with 30-day readmission rates. Objectives: To investigate the association between racial/ethnic diversity and hospitals' 30-day readmission rates. Methods: We linked the 2017 HRRP, American Hospital Association (AHA) database, Area Health Resource File, US Census Bureau Current Population Survey, and the Dartmouth Atlas HRR dataset to examine 30-day readmission rate for heart failure (HF), pneumonia (PN), acute myocardial infarction (AMI), and hip replacement (HR) surgery of 4,299 hospitals across 306 HRRs. Results: Our findings indicate a statistically significant negative relationship between diversity and 30-day readmission rates for HF, PN, AMI, and HR with a hospital referral region (HRR). Thus, hospitals located in HRRs with diverse populations are more likely to have higher 30-day readmission rates for all conditions under Medicare's HRRP Conclusion: Better discharge follow-up, interventions, and use of support staff aimed at meeting needs associated with differences in communities and cultures are likely to prove more fruitful than traditional one-size fits all approaches to care.