Robert Wachter, MD, professor and chair of the department of medicine at San Francisco-based UCSF School of Medicine, and Jeff Goldsmith, PhD, associate professor of public health sciences at Charlottesville-based University of Virginia, outlined three ways to improve EHRs in an op-ed published in Harvard Business Review.
EHRs are "rightly seen as a major cause of professional burnout among physicians and nurses," the authors wrote. Issues with the technology stem from a variety of areas, including antiquated user interfaces "out of the mid-1990s" and documentation burdens that require clinicians use the EHR for charting, clinical ordering, billing and quality improvement, among other functions.
"Clinicians are spending almost half their professional time typing, clicking and checking boxes on electronic records," the authors wrote. "While some of these efforts actually have improved quality and patient safety, many others served merely to 'buff up the note' to make the clinician look good on 'process' measures and simply maximize billing."
Here are Drs. Wachter and Goldsmith's three foundational steps to improve EHR usability.
1. Trade out typing, clicking and checking boxes in the EHR with voice command and data visualization to streamline clinicians' work when documenting and reviewing a patient encounter. "Typing and point and click must go," the authors wrote. "Both documenting the clinical encounter and ordering should be done by voice command, confirmed by screen touch."
2. Focus on patient care, including recent diagnoses and clinical risks, rather than the current "mashing up" of billing, compliance and quality functions. This "patient portrait" should "have a discrete character limit like those imposed by Twitter" to decrease clutter, and, "while one individual [such as a hospitalist or primary care physician] should take the lead, this assessment should be curated collaboratively, a la Wikipedia," the authors wrote.
3. Apply artificial intelligence to help EHRs organize and prioritize greater amounts of patient data, for example, patient-generated information related to family history or medication usage. "AI algorithms must also be used to scrape from the EHR the information needed to assign acuity scores and suggest diagnoses that accurately reflect the patient’s current state," the authors wrote.
"Today, one can see a path to turning the EHR into a well-designed and useful partner to clinicians and patients in the care process," the authors wrote. "When this has been accomplished, we believe that clinicians will be converted from surly prisoners of poorly realized technology to advocates of the systems themselves and enthusiastic leaders of efforts to further improve them."
To access Drs. Wachter and Goldsmith's op-ed, click here.