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Understanding optimization processes of electronic health records (EHR) in select leading hospitals: a qualitative study.
Journal of Innovation in Health Informatics 2018 June 31
BACKGROUND: Little is known about optimization of electronic health records (EHR) systems in the hospital setting while adoption of EHR systems continues in the United States.
OBJECTIVE: To understand optimization processes of EHR systems undertaken in leading healthcare organizations in the United States.
METHODS: Informed by grounded theory approach, a qualitative study was undertaken that involved 11 in-depth interviews and a focus group with the EHR experts from the high performing healthcare organizations across the United States.
RESULTS: The study describes EHR optimization processes characterized by prioritizing exponentially increasing requests with predominant focus on improving efficiency of EHR, building optimization teams or advisory groups, and standardization. The study discusses 16 types of optimization that interdependently produced 16 results along with identifying 11 barriers and 20 facilitators to optimization.
CONCLUSION: The study describes overall experiences of optimizing electronic health records in select high performing healthcare organizations in the US. The findings highlight the importance of optimizing the EHR after, and even before, go-live and dedicating resources exclusively for optimization.
OBJECTIVE: To understand optimization processes of EHR systems undertaken in leading healthcare organizations in the United States.
METHODS: Informed by grounded theory approach, a qualitative study was undertaken that involved 11 in-depth interviews and a focus group with the EHR experts from the high performing healthcare organizations across the United States.
RESULTS: The study describes EHR optimization processes characterized by prioritizing exponentially increasing requests with predominant focus on improving efficiency of EHR, building optimization teams or advisory groups, and standardization. The study discusses 16 types of optimization that interdependently produced 16 results along with identifying 11 barriers and 20 facilitators to optimization.
CONCLUSION: The study describes overall experiences of optimizing electronic health records in select high performing healthcare organizations in the US. The findings highlight the importance of optimizing the EHR after, and even before, go-live and dedicating resources exclusively for optimization.
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