scholarly journals Issues for Medical Center Research

1998 ◽  
pp. 27-29
Author(s):  
A. L. Chapman
Keyword(s):  
Medical Center ◽  
Center Research

scholarly journals CardioNet: a manually curated database for artificial intelligence-based research on cardiovascular diseases

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Imjin Ahn ◽  
Wonjun Na ◽  
Osung Kwon ◽  
Dong Hyun Yang ◽  
Gyung-Min Park ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Cardiovascular Diseases ◽  
Language Processing ◽  
Medical Center ◽  
Unstructured Data ◽  
University Hospital ◽  
Common Data Model ◽  
Free Text ◽  
Medical Examinations ◽  
Center Research

Abstract Background Cardiovascular diseases (CVDs) are difficult to diagnose early and have risk factors that are easy to overlook. Early prediction and personalization of treatment through the use of artificial intelligence (AI) may help clinicians and patients manage CVDs more effectively. However, to apply AI approaches to CVDs data, it is necessary to establish and curate a specialized database based on electronic health records (EHRs) and include pre-processed unstructured data. Methods To build a suitable database (CardioNet) for CVDs that can utilize AI technology, contributing to the overall care of patients with CVDs. First, we collected the anonymized records of 748,474 patients who had visited the Asan Medical Center (AMC) or Ulsan University Hospital (UUH) because of CVDs. Second, we set clinically plausible criteria to remove errors and duplication. Third, we integrated unstructured data such as readings of medical examinations with structured data sourced from EHRs to create the CardioNet. We subsequently performed natural language processing to structuralize the significant variables associated with CVDs because most results of the principal CVD-related medical examinations are free-text readings. Additionally, to ensure interoperability for convergent multi-center research, we standardized the data using several codes that correspond to the common data model. Finally, we created the descriptive table (i.e., dictionary of the CardioNet) to simplify access and utilization of data for clinicians and engineers and continuously validated the data to ensure reliability. Results CardioNet is a comprehensive database that can serve as a training set for AI models and assist in all aspects of clinical management of CVDs. It comprises information extracted from EHRs and results of readings of CVD-related digital tests. It consists of 27 tables, a code-master table, and a descriptive table. Conclusions CardioNet database specialized in CVDs was established, with continuing data collection. We are actively supporting multi-center research, which may require further data processing, depending on the subject of the study. CardioNet will serve as the fundamental database for future CVD-related research projects.

Medicaid & Medicare: D.C. Appellate Court Denies Claim for Medicare Reimbursement of GME Cost

1999 ◽  
Vol 27 (2) ◽  
pp. 205-205
Author(s):  
choeffel Amy
Keyword(s):  
Medical Center ◽  
Federal District ◽  
Federal Court ◽  
University Of Pennsylvania ◽  
District Court ◽  
Appellate Court ◽  
Court Of Appeals ◽  
Department Of Health ◽  
Administrative Proceedings ◽  
Summary Judgment

The U.S. Court of Appeals for the District of Columbia upheld, in Presbyterian Medical Center of the University of Pennsylvania Health System v. Shalala, 170 F.3d 1146 (D.C. Cir. 1999), a federal district court ruling granting summary judgment to the Department of Health and Human Services (DHHS) in a case in which Presbyterian Medical Center (PMC) challenged Medicare's requirement of contemporaneous documentation of $828,000 in graduate medical education (GME) expenses prior to increasing reimbursement amounts. DHHS Secretary Donna Shalala denied PMC's request for reimbursement for increased GME costs. The appellants then brought suit in federal court challenging the legality of an interpretative rule that requires requested increases in reimbursement to be supported by contemporaneous documentation. PMC also alleged that an error was made in the administrative proceedings to prejudice its claims because Aetna, the hospital's fiscal intermediary, failed to provide the hospital with a written report explaining why it was denied the GME reimbursement.

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