Since the enactment of the HITECH Act in 2009, the US has invested billions in building a robust health information technology (HIT) infrastructure that is secure, capable of the electronic transfer of data and allows for real-time access of patient medical data, among others. This empirical study explored the driving forces (coercive, mimetic, and normative) in the adoption of HIT (i.e. EHRs and HIEs) by local health departments (LHDs) and how it has impacted the population health of counties in the US. The researcher conducted a cross-sectional, quantitative study using secondary data sources. The study included data on 505 local health departments and 433 counties' population health data. Institutional theory guided this research and generalized estimating equations, logistic regression, and multiple linear regression were utilized to analyze health IT adoption by LHDs and its impact on county-level health outcomes. Results showed that normative forces, measured by the employment of IS specialists was most impactful in the adoption of both EHRs and HIEs. Mimetic forces, measured by the completion of a CHA and coercive forces measured by the implementation of the HITECH Act were not found to be statistically significant in the adoption of EHRs or HIEs. Finally, EHR adoption was statistically significant at improving population health at the county level. This research study has contributed in three areas: 1) to fill a knowledge gap on the impact of health IT adoption by LHDs on health outcomes; 2) to formulate a theoretically grounded framework to study population health and its variability; and 3) to identify target areas for public health interventions. In conclusion, a substantial amount of resources dedicated in creating a robust health IT infrastructure requires close analysis of the impact health IT has on the population health of our nation.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-6586 |
| Date | 01 January 2017 |
| Creators | Yeung, Tina |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations |
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