Graduation Year


Document Type




Degree Granting Department


Major Professor

Jay Wolfson, Dr.Ph., J.D.

Co-Major Professor

Shivendu Shivendu, Ph.D.

Committee Member

Anol Bhattacherjee, Ph.D.

Committee Member

Kaushik Dutta, Ph.D.


electronic medical record, EMR, EHR, Hospital re-admissions


Health information technology (HIT), which includes electronic health record (EHR) systems and clinical data analytics, has become a major component of all health care delivery and care management. The adoption of HIT by physicians, hospitals, post-acute care organizations, pharmacies and other health care providers has been accepted as a necessary (and recently, a government required) step toward improved quality, care coordination and reduced costs: “Better coordination of care provides a path to improving communication, improving quality of care, and reducing unnecessary emergency room use and hospital readmissions. LTPAC providers play a critical role in achieving these goals” (, 2013).

Though some of the impacts of evolving HIT and EHRs have been studied in acute care hospitals and physician office settings, a dearth of information exists about the deployment and effectiveness of HIT and EHRs in long-term and post-acute care facilities, places where they are becoming more essential. This dissertation examines how and to what extent health information technology and electronic health record implementation and use affects certain measurable outcomes in long term and post-acute care facilities. Monthly data were obtained for the period beginning January 1, 2016 through June 30, 2017, a total of 18 months. The level of EHR adoption was found to positively impact hospital readmission rates, employee engagement, complaint deficiencies, failed revisit surveys, staff overtime (partial EHR), staff turnover rate (full EHR) and United States Centers for Medicare and Medicaid Services (CMS) Five Star Quality score. The level of EHR adoption was found to negatively impact CMS Five Star Total score, staff retention rate (full EHR) and staff overtime (full EHR group higher than partial EHR).