Browsing by Subject "Data analytics"

Now showing 1 - 2 of 2
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    A decade post-HITECH: Critical access hospitals have electronic health records but struggle to keep up with other advanced functions
    (Oxford University Press, 2021) Apathy, Nate C.; Holmgren, A. Jay; Adler-Milstein, Julia; Health Policy and Management, Richard M. Fairbanks School of Public Health
    Objective: Despite broad electronic health record (EHR) adoption in U.S. hospitals, there is concern that an "advanced use" digital divide exists between critical access hospitals (CAHs) and non-CAHs. We measured EHR adoption and advanced use over time to analyzed changes in the divide. Materials and methods: We used 2008 to 2018 American Hospital Association Information Technology survey data to update national EHR adoption statistics. We stratified EHR adoption by CAH status and measured advanced use for both patient engagement (PE) and clinical data analytics (CDA) domains. We used a linear probability regression for each domain with year-CAH interactions to measure temporal changes in the relationship between CAH status and advanced use. Results: In 2018, 98.3% of hospitals had adopted EHRs; there were no differences by CAH status. A total of 58.7% and 55.6% of hospitals adopted advanced PE and CDA functions, respectively. In both domains, CAHs were less likely to be advanced users: 46.6% demonstrated advanced use for PE and 32.0% for CDA. Since 2015, the advanced use divide has persisted for PE and widened for CDA. Discussion: EHR adoption among hospitals is essentially ubiquitous; however, CAHs still lag behind in advanced use functions critical to improving care quality. This may be rooted in different advanced use needs among CAH patients and lack of access to technical expertise. Conclusions: The advanced use divide prevents CAH patients from benefitting from a fully digitized healthcare system. To close the widening gap in CDA, policymakers should consider partnering with vendors to develop implementation guides and standards for functions like dashboards and high-risk patient identification algorithms to better support CAH adoption.
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    Healthcare Data Analytics for Parkinson’s Disease Patients: A Study of Hospital Cost and Utilization in the United States
    (American Medical Informatics Association, 2017-02-10) Mukherjee, Sunanda; Wu, Huanmei; Jones, Josette; Department of Biohealth Informatics, School of Informatics and Computing
    Parkinson's Disease (PD), a prevalent problem, especially for the aged populations, is a progressive but non-fatal nervous system disorder. PD patients have special motor as well as non-motor symptoms over time. There are several limitations in the study of PD such as unavailability of data, proper diagnosis and treatment methods. These limitations significantly reduce the quality of PD patient life quality, either directly or indirectly. PD also imposes great financial burdens to PD patients and their family. This project aims to analyze the most common reasons for PD patient hospitalization, review complications that occur during inpatient stays, and measure the costs associated with PD patient characteristics. Using the HCUP NIS data, comprehensive data analysis has been performed. The results are customized visualized using Tableau and other software systems. The preliminary findings sheds light into how to improve the life quality of PD patients.