Title

The Effect Of Information Technology On Hospital Performance

Keywords

AID; DEA; Efficiency; Health information technology; Hospital; Quality

Abstract

While healthcare entities have integrated various forms of health information technology (HIT) into their systems due to claims of increased quality and decreased costs, as well as various incentives, there is little available information about which applications of HIT are actually the most beneficial and efficient. In this study, we aim to assist administrators in understanding the characteristics of top performing hospitals. We utilized data from the Health Information and Management Systems Society and the Center for Medicare and Medicaid to assess 1039 hospitals. Inputs considered were full time equivalents, hospital size, and technology inputs. Technology inputs included personal health records (PHR), electronic medical records (EMRs), computerized physician order entry systems (CPOEs), and electronic access to diagnostic results. Output variables were measures of quality, hospital readmission and mortality rate. The analysis was conducted in a two-stage methodology: Data Envelopment Analysis (DEA) and Automatic Interaction Detector Analysis (AID), decision tree regression (DTreg). Overall, we found that electronic access to diagnostic results systems was the most influential technological characteristics; however organizational characteristics were more important than technological inputs. Hospitals that had the highest levels of quality indicated no excess in the use of technology input, averaging one use of a technology component. This study indicates that prudent consideration of organizational characteristics and technology is needed before investing in innovative programs.

Publication Date

12-1-2016

Publication Title

Health Care Management Science

Volume

19

Issue

4

Number of Pages

338-346

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1007/s10729-015-9329-z

Socpus ID

84930157572 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84930157572

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