A comparison of a Bayesian vs. a frequentist method for profiling hospital performance

BackgroundRisk-adjusted rates of hospital readmission are a common indicator of hospital performance. There are concerns that current risk-adjustment methods do not account for the many factors outside the hospital setting that can affect readmission rates. Not accounting for these external factors could result in hospitals being unfairly penalized when they discharge patients to communities that are less able to support care transitions and disease management. While incorporating adjustments for the myriad of social and economic factors outside of the hospital setting could improve the accuracy of readmission rates as a performance measure, doing so has limited feasibility due to the number of potential variables and the paucity of data to measure them. This paper assesses a practical approach to addressing this problem: using mixed-effect regression models to estimate case-mix adjusted risk of readmission by community of patients’ residence (community risk of readmission) as a complementary performance indicator to hospital readmission rates.MethodsUsing hospital discharge data and mixed-effect regression models with a random intercept for community, we assess if case-mix adjusted community risk of readmission can be useful as a quality indicator for community-based care. Our outcome of interest was an unplanned repeat hospitalisation. Our primary exposure was community of residence.ResultsCommunity of residence is associated with case-mix adjusted risk of unplanned repeat hospitalisation. Community risk of readmission can be estimated and mapped as indicators of the ability of communities to support both care transitions and long-term disease management.ConclusionContextualising readmission rates through a community lens has the potential to help hospitals and policymakers improve discharge planning, reduce penalties to hospitals, and most importantly, provide higher quality care to the people that they serve.

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Attributes of turnaround rural hospitals: Case study findings and research opportunities

Journal of Hospital Administration ◽

10.5430/jha.v6n6p8 ◽

2017 ◽

Vol 6 (6) ◽

pp. 8

Author(s):

Asa B. Wilson

Keyword(s):

Theory Of The Firm ◽

Access Point ◽

Hospital Performance ◽

Rural Hospitals ◽

Rural Hospital ◽

Classical Economics ◽

The Status ◽

History Of ◽

Closure Conversion ◽

The Impact

Background: Rural and Critical Access Hospitals (CAHs) have a history of operating challenges and closure-conversion threats. The history is reviewed including the supportive public policy provisions and administrative tactics designed to maintain a community’s hospital as the hub and access point for health services. Limited research indicates that rural facilities are not strategic in their responses to challenges. A question emerges regarding the enduring nature of operating difficulties for these facilities, i.e., no understanding with explanatory value.Objective: The author, as the CEO in six rural hospitals designated as turnaround facilities, used inductive participant-observer involvement to identify operating attributes characteristic of these organizations. An objective description of each facility is provided. While implementing a turnaround intervention, fifteen behaviors or outcomes were found to be consistent across all six entities. This information is used to posit factors associated with or accounting for identified performance weaknesses.Conclusions: It is conceptualization that observed organizational behaviors can be explained as remnants of an agrarian ideology. Such a mindset is focused on preserving the status quo despite challenges that would require strategic positioning of the organization. In addition, emerging studies on community types indicates that follow-up research is needed that assesses the impact of community attributes on rural hospital performance. Also, this study shows that a theory of the rural hospital firm based on neo-classical economics has no explanatory value. Thus, a theory of the firm can be developed that includes behavioral economic principles.

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A Massive Pulmonary Embolism Treatment Protocol: How Trauma Performance Improvement Affects Outcome Throughout the Hospital System

The American Surgeon ◽

10.1177/000313481007600204 ◽

2010 ◽

Vol 76 (2) ◽

pp. 145-148

Author(s):

Catherine Garrison Velopulos ◽

Mark Zumberg ◽

Priscilla Mcauliffe ◽

Lawrence Lottenberg ◽

A. Joseph Layon

Keyword(s):

Pulmonary Embolism ◽

Sudden Death ◽

Performance Improvement ◽

Pulmonary Embolus ◽

Treatment Protocol ◽

Right Heart Failure ◽

Hospital Performance ◽

Massive Pulmonary Embolism ◽

Hospital System ◽

Submassive Pulmonary Embolism

Trauma performance improvement is the hallmark of a mature trauma center. If loop closure is to be complete, preventable deaths must result in significant change in management and the establishment of protocol-driven improvements so such an instance does not recur. The trauma performance improvement committee reviewed a case of a massive pulmonary embolus and determined that this was a preventable death. The hospital performance improvement committee then initiated a root cause analysis, which led to creation of a treatment protocol for patients with massive or submassive pulmonary embolism. A focused review of the first 6 months of the implementation of the protocol was undertaken. Four patients over a 6-month period had massive or submassive pulmonary embolus. All four had sudden death or near sudden death and were appropriately resuscitated. All four sustained right heart failure. Two patients were treated by catheter-directed fibrinolysis, one with catheter-directed suction embolectomy, and one by surgical pulmonary embolectomy. All survived with full neurologic function. Trauma performance improvement is the model by which all hospital performance improvement should be done. Preventable deaths can result in change, which can have a future impact on survival in potentially lethal scenarios.

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More research is needed to understand the relationship between management costs and hospital performance

Evidence-based Healthcare ◽

10.1054/ebhc.1999.0275 ◽

1999 ◽

Vol 3 (4) ◽

pp. 97

Author(s):

Ewan Ferlı́e

Keyword(s):

Hospital Performance ◽

The Relationship

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An Empirical Study on Post-Adoption Behavior of Information Technologies for Health Care Management: A View of Big Five Personality

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.631-632.1106 ◽

2014 ◽

Vol 631-632 ◽

pp. 1106-1114

Author(s):

Wen Xing Lu ◽

Yu Yong Wu ◽

Chang Yong Liang ◽

Zuo Zuo Gu ◽

Yu Zhao ◽

...

Keyword(s):

Health Care ◽

Empirical Study ◽

Big Five ◽

Information Technologies ◽

Care Management ◽

Health Care Management ◽

Hospital Performance ◽

Ease Of Use ◽

Perceived Usefulness ◽

Big Five Personality

Nowadays, health care management is driven by informationization and information technologies are widely used in various types of hospitals. Doctors and nurses are the direct users of information technologies for health care management (ITHCM), as well as the most critical prerequisites in ITHCM implementation. Their acceptance and use of ITHCM can significantly promote hospital performance and enhance core competitiveness. However, different people have different attitude, values and motivation on ITHCM. These factors not only affect employee’s behavior in ITHCM adoption, but also their continued use behavior of ITHCM. Based on the Big Five personality as well as real-world healthcare situation in China, we investigated the impacting factors of ITHCM continuing use, and built ITHCM Continuing Use Model based on personality. We conducted an empirical study to verify the related hypothesis. The results show that Big Five personality affect the willingness of ITHCM continuing use through perceived ease of use and perceived usefulness.

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828. Evaluation of Home Time as a Patient-Centered Metric for Pneumonia Hospitalizations: A Retrospective Cohort Study of Medicare Fee-For-Service Beneficiaries

Open Forum Infectious Diseases ◽

10.1093/ofid/ofaa439.1017 ◽

2020 ◽

Vol 7 (Supplement_1) ◽

pp. S455-S456

Author(s):

Rajeshwari Nair ◽

Yubo Gao ◽

Mary Vaughan-Sarrazin ◽

Eli N Perencevich ◽

Saket Girotra ◽

...

Keyword(s):

Performance Metrics ◽

Care Delivery ◽

Care Facility ◽

Hospital Performance ◽

Policy Implications ◽

Fee For Service ◽

Multilevel Regression ◽

Hospital Level ◽

Post Discharge ◽

Patient Centered

Abstract Background The Centers for Medicare & Medicaid Services (CMS) uses hospital readmission to incentivize hospital care delivery for acute conditions including pneumonia. However, current CMS performance metrics do not account for the competing risk of mortality in the post-discharge period or during the hospital stay. Our objective was to assess home time within 30 days after discharge among pneumonia hospitalizations, as a patient-centered metric. Methods A retrospective observational study was conducted in a cohort of Medicare fee-for-service beneficiaries admitted between 01/01/2015 and 11/30/2017. Home time was the number of days spent alive, out of an acute care setting, skilled nursing facility, or a rehabilitation facility within 30 days of discharge. If a patient spends any part of a day in a care facility or died after discharge, then that day was not included in the calculation for home time. Hospital-level rates of risk-adjusted home time were calculated using multilevel regression models. We compared hospital performance on 30-day risk-standardized home time with its performance on 30-day risk standardized readmission rate (RSRR) and mortality rate (RSMR). Characteristics of hospitals with high and low risk-adjusted home-time were compared. Results Among 1.7 million pneumonia admissions admitted to 3,116 hospitals, the median 30-day risk-standardized home time was 20.5 days (interquartile range: 18.9-21.9 days). Hospital-level characteristics such as case volume, bed size, for-profit ownership, rural location of hospital, teaching status, and participation in the bundle payment program were significantly associated with home-time. RSRR (rho: -0.233, p< 0.0001) and RSMR (rho: -0.223, p< 0.0001) had weak, inverse correlations with home time. Using the home time metric, 35.5% of hospitals were reclassified as high performers compared with their average or poor performance on the RSRR or RSMR metric. Conclusion Home time is a novel, patient-centered, hospital-level metric that can be easily calculated using claims data, accounts for differences in post-discharge mortality and can be intuitively interpreted. Utilization of this metric could potentially have policy implications in assessing hospital performance on delivery of healthcare to pneumonia patients. Disclosures Rajeshwari Nair, PhD, Merck and Company, Inc. (Research Grant or Support)

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