Study: Optimal use of EHRs result in faster hospital discharges

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Hospitals with the highest use of electronic health records discharge their patients quicker.

That’s the finding of a new study from Case Western Reserve University in Cleveland.

According to researchers, hospitals that meet federal standards for Meaningful Use of EHRs discharge patients about four hours earlier— which equates to a 3 percent reduction in the average five-day hospital stay.

Further, patients with complex conditions have an additional 0.5 percent reduction in their stay, while the overall reduction in stays does not result in increased re-admissions.

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As a result, use of EHRs can better contain growing healthcare costs in an era of reduced reimbursement for treatment, says Manoj Malhotra, dean of the Weatherhead School of Management at Case Western and co-author of the study.

“Electronic health records when meaningfully implemented help patients go home sooner, reducing their exposure to germs in the hospital and likelihood of coming back,” Malhotra adds.

The study, available in the Journal of Operations Management, also found that hospitals not fully engaged in Meaningful Use had no significant reductions in the length of patient stays.

“Any efficiencies, even small improvements, can produce significant savings when adopted in a large healthcare system and are certainly preferable to the alternative,” Malhotra contends.

Researchers placed hospitals into three catagories: partial adoption of EHRs, full adoption, and “meaningful assimilation” of EHRs.

What they found was that while partial or full adoption of EHRs showed no benefit for reducing stays, “meaningful assimilation” of EHRs—the highest standard of Meaningful Use—reduced length of stay without impact on readmissions, Malhotra says.

To support the study, researchers used four years of detailed patient-level data from all acute care hospitals in California, as well as data from Meaningful Use hospitals.

The research was co-conducted with Deepa Wani, an assistant professor of management science and statistics at the University of Texas at San Antonio.

The study is available here.

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