Analyzing Electronic Health Records Can Impact Quality Improvement Processes

USDA photo by Bob Nichols

Electronic health records (EHRs) are a digital version of a patient’s medical history and contain key administrative clinical data from that patient’s care from a particular provider. The data, which can include demographics, progress notes, medications, vital signs, medical history, and laboratory data, can also be analyzed to help improve health care delivery.

Using data and statistical models to analyze EHRs can help identify the root cause of problems in health care and have a positive impact on quality improvement processes, according to a new study by Farrokh Alemi, professor in the Department of Health Administration and Policy, in the July-September issue of Quality Management in Health Care.

“Current methods of root cause analysis rely on an analyst’s judgement,” Alemi said. “Through analysis of EHRs, root causes of adverse outcomes can be determined more rigorously and eliminate potential subjective bias.

In this study, Alemi and other colleagues at the DC VA Medical Center analyzed EHR data to identify excessive emergency department stays in one hospital setting. Excessive emergency department stays, a common issue in the United States, are defined as a patient spending more than six hours from arrival to leaving, whether the patient is admitted or discharged.

The analysis found that 23 different causes resulted in excessive emergency department stays for the 70,049 emergency department visits from March 2011 to April 2014. A majority of those causes were related to hospital operations outside of the emergency department, such as availability of hospital beds for admitted patients and delays in laboratory results.

“Improving emergency departments is not easy as there are multiple causes for delay,” Alemi said. “We set out to discover root causes, so the problem could be solved for good. To our surprise, we found that the root cause of emergency department delay had little to do with the emergency department. We found that the root cause had to do with hospital occupancy. Our analysis demonstrates that implementing interventions, like better discharge processes and an increase in the number of beds, could help improve patient care.”