A Qualitative Study of How Employees Perceive Job Satisfaction Through the Adoption of Electronic Health Records and Innovative Technologies
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| Publicado en: | ProQuest Dissertations and Theses (2025) |
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| Acceso en línea: | Citation/Abstract Full Text - PDF |
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| 045 | 2 | |b d20250101 |b d20251231 | |
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| 100 | 1 | |a Ferrer-Bethencourt, Anthony | |
| 245 | 1 | |a A Qualitative Study of How Employees Perceive Job Satisfaction Through the Adoption of Electronic Health Records and Innovative Technologies | |
| 260 | |b ProQuest Dissertations & Theses |c 2025 | ||
| 513 | |a Dissertation/Thesis | ||
| 520 | 3 | |a The introduction of technology in the medical industry and health care has changed how business is conducted. The health care system continues to advance in computer technology, which allows it to record and analyze data faster and better than ever. However, dissatisfaction with electronic health records (EHR) adoption and utilization among health care communities has recently increased, adding to frustrations and distrust of the electronic application, which leads to end-user burnout, increased risk for high user turnover rates, and decreased user satisfaction across the United States. This study applies a qualitative methodology approach with the primary objective of conducting a comprehensive analysis of the impact of the implementation and utilization of EHRs and the degree of user contentment with their functionalities, efficiency, and advantages. The research used a customer-centric approach, requiring interviewing EHR end-users across the United States. Qualitative data were collected and analyzed using a basic qualitative methodology to maintain uniformity and simplicity in the study. First, EHR end-user information was gathered through interview questions via Zoom or phone calls, and the data was uploaded into the qualitative data analysis application. Second, the researcher reviewed secondary data from past studies with similar values to compare results. | |
| 653 | |a Health care management | ||
| 653 | |a Computer engineering | ||
| 653 | |a Artificial intelligence | ||
| 773 | 0 | |t ProQuest Dissertations and Theses |g (2025) | |
| 786 | 0 | |d ProQuest |t ProQuest Dissertations & Theses Global | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3218904458/abstract/embedded/75I98GEZK8WCJMPQ?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3218904458/fulltextPDF/embedded/75I98GEZK8WCJMPQ?source=fedsrch |