Date of Award
Doctor of Philosophy (PhD)
Information Technology & Decision Sciences
Business Administration-Information Technology
Each year, huge investments into healthcare information systems (HIS) are being made all over the world. Despite the enormous cost for the hospitals, the overall benefits and costs of the healthcare information systems have not been deeply assessed. In recent years, much previous research has investigated the link between the implementation of Information Systems and the performance of organizations. Although the value of Healthcare Information System or Healthcare Information Technology (HIS/HIT) has been found in many studies, some questions remain unclear. Do HIS/HIT systems influence different hospitals the same way? How to understand and explain the mechanism that HIS/HIT improves the performance of hospitals? To address these questions, our research will: 1) Identify the bottlenecks of the current healthcare system which affects the operation efficiency (mismatch between demand and service provided); 2) Adopt the institutional theory to explain the process of implementing HIS/HIT and the possible outcomes; 3) Conduct an empirical study, to expose issues of current healthcare system and the value of the HIS/HIT, and to identify the factors that affect the performance of different hospitals; and 4) Design a decision support system for hospitals.
Based on institutional theory, we explain the empirical findings from 2014 HIMSS database. To solve the mismatch between the patient needs and doctor’s schedule, we will propose a business model for a new integrated information management system. It gives the physicians and patients a comprehensive picture needed to understand the type of different patients. A classification schema will be designed to provide recommendations for scheduling decision, and it is supported by the interactive system.
"The Value of Integrated Information Systems for U.S. General Hospitals"
(2015). Doctor of Philosophy (PhD), Dissertation, Information Technology & Decision Sciences, Old Dominion University, DOI: 10.25777/c35t-ye42