The Relationship between Inpatient HIV/AIDS Characteristics and Hospital Charges: Use of Big Data

Abstract

With the adoption of Electronic Health Records (EHR) by acute care hospitals, research in biomedical field has become increasingly data-intensive as investigators are rapidly using large, complex, and diverse datasets. Big data to knowledge (BD2K) focus is to enhance the advances in data acquisition, analytics, policy, and training which are critically needed for the effective use of big data. Current information shows that minorities are more likely to be diagnosed with HIV infection compared to their white counterparts. There are few research studies on the association between hospital charges and inpatient HIV/AIDS characteristics. The goal of this study was to conduct an investigation on the association and the factors that affect hospital charges of inpatient HIV/AIDS adults with mental illness and behavioral disorders. An estimation of inpatients HIV/AIDS hospital charges was conducted by data extraction and analytics from the Nationwide Inpatient Sample (NIS) Healthcare Costs and Utilization Program (HCUP) for 2007 and 2010. Regression analysis was used to test the study hypotheses. The critical ranking effects of variables were seen in the specific hierarchical association between the hospital charges and total number of procedures, hospital staff, total number of comorbidities, bipolar, and drug abuse. The outcome of our research could be used to support the advances in clinical data analytics, big data to knowledge (BD2K) and data science.