Graduation Date

Spring 5-6-2017

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Programs

Health Services Research, Administration, and Policy

First Advisor

Dr. Preethy Nayar

Abstract

Population health management (PHM) is used to identify the needs of a population and to align strategies to improve the health of the population through care coordination. The Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009 emphasized the meaningful use (MU) of electronic health records (EHRs) to improve clinical and population health outcomes. The American Recovery and Reinvestment Act (ARRA) of 2009 approved the EHRs incentives program for eligible hospitals to demonstrate the MU of EHRs. Further, eligible hospitals which failed to demonstrate the MU of EHRs could face payment adjustments. Given a heightened focus on MU of EHRs for PHM and a reimbursement policy that incentivizes the MU of EHRs for PHM, EHRs can play an important role in PHM. Therefore, it is important to study the correlates of MU of EHRs for PHM in hospitals.

This study examined the organizational and environmental correlates of the implementation of PHM objectives of MU of EHRs for PHM and the level of MU of EHRs for PHM in acute care hospitals in the United States (U.S). Three of the four dependent variables examined in this study were based on the three PHM objectives of MU of EHRs: 1) submission of electronic data to immunization registries, 2) submission of electronic data on reportable laboratory results to public health agencies, and 3) submission of electronic syndromic surveillance data to public health agencies. The level of MU of EHRs for PHM was a composite measure created using the aforementioned three PHM objectives.

This study used resource dependency theory to derive the conceptual model based on its constructs of munificence, uncertainty, and interdependence. This study used an observational, retrospective, multiple correlational study design with a one-year lag for independent variables to address the research objectives. The data for this study were obtained from the American Hospital Association Annual Survey Database 2013, Area Health Resource Files 2015-2016, Centers of Medicare and Medicaid Stage 1 and Stage 2 MU datafiles for year 2014, and state health policy levers compendium 2011-2013. Due to the hierarchical nature of the data, mixed effects regression models were used for the analyses. The study found the munificence construct operationalized as the size of the hospital, uncertainty construct operationalized as market competition, and interdependence construct operationalized as system membership, ownership control, and the stage of MU implementation of EHRs to be significantly associated with the MU of EHRs for PHM.

Download

Share

COinS