Objective: To determine the relationship between hospital membership in systems and the treatments, expenditures, and outcomes of patients.
Data Sources: The Medicare Provider Analysis and Review dataset, for data on Medicare patients admitted to general medical-surgical hospitals between 1985 and 1998 with a diagnosis of acute myocardial infarction (AMI); the American Hospital Association Annual Survey, for data on hospitals.
Study Design: A multivariate regression analysis. An observation is a fee-for-service Medicare AMI patient admitted to a study hospital. Dependent variables include patient transfers, catheterizations, angioplasties or bypass surgeries, 90-day mortality, and Medicare expenditures. Independent variables include system participation, other admission hospital and patient traits, and hospital and year fixed effects. The five-part system definition incorporates the size and location of the index admission hospital and the size and distance of its partners.
Principal Findings: While the effects of multihospital system membership on patients are in general limited, patients initially admitted to small rural system hospitals that have big partners within 100 miles experience lower mortality rates than patients initially admitted to independent hospitals. Regression results show that to the extent system hospital patients experience differences in treatments and outcomes relative to patients of independent hospitals, these differences remain even after controlling for the admission hospital's capacity to provide cardiac services.
Conclusions: Multihospital system participation may affect AMI patient treatment and outcomes through factors other than cardiac service offerings. Additional investigation into the nature of these factors is warranted.
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http://dx.doi.org/10.1111/j.1475-6773.2004.00256.x | DOI Listing |
J Imaging Inform Med
January 2025
University Hospitals Cleveland Medical Center, Case Western Reserve University, 11100 Euclid Avenue, BSH 5056, Cleveland, OH, 44106, USA.
The objective of this study is to implement an actionable incidental findings (AIFs) communication workflow integrated into the electronic health record (EHR) using dictation macros to improve the quality of radiology reports and facilitate delivery of findings to clinicians. The workflow was implemented across an academic multi-hospital health system and used by over 100 radiologists from 12 divisions. Standardized macros were created for different organ systems including the thyroid, lungs, liver, pancreas, spleen, kidney, female reproductive, and others, designed based on the ACR Novel Quality Measure Set.
View Article and Find Full Text PDFInt J Clin Oncol
January 2025
Translational Research Support Section, National Cancer Center Hospital East, Chiba, Japan.
Early cancer detection substantially improves the rate of patient survival; however, conventional screening methods are directed at single anatomical sites and focus primarily on a limited number of cancers, such as gastric, colorectal, lung, breast, and cervical cancer. Additionally, several cancers are inadequately screened, hindering early detection of 45.5% cases.
View Article and Find Full Text PDFDiagnostics (Basel)
December 2024
Department of Information Technology, Aylol University College, Yarim 547, Yemen.
Background And Objectives: Brain tumors are complex diseases that require careful diagnosis and treatment. A minor error in the diagnosis may easily lead to significant consequences. Thus, one must place a premium on accurately identifying brain tumors.
View Article and Find Full Text PDFJ Biomed Inform
January 2025
Harvard Medical School, Boston, MA, USA; VA Boston Healthcare System, Boston, MA, USA; Harvard T.H. Chan School of Public Health, Boston, MA, USA. Electronic address:
Motivation: The increasing availability of Electronic Health Record (EHR) systems has created enormous potential for translational research. Recent developments in representation learning techniques have led to effective large-scale representations of EHR concepts along with knowledge graphs that empower downstream EHR studies. However, most existing methods require training with patient-level data, limiting their abilities to expand the training with multi-institutional EHR data.
View Article and Find Full Text PDFSurg Obes Relat Dis
December 2024
Northwestern Quality Improvement, Research and Education in Surgery, Northwestern University, Feinberg School of Medicine, Chicago, Illinois; Department of Surgery, Northwestern University, Feinberg School of Medicine, Chicago, Illinois.
Background: The impact of referral type and socioeconomic status on completion of the bariatric surgery process is not well understood.
Objectives: This study aims to 1) describe how sociodemographic characteristics influence referral type and 2) identify predictors of completion of surgery.
Setting: Large multihospital health care system, including a large academic medical center.
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