Researchers offer vision for next generation of clinical decision support
More robust decision support within electronic health records systems to “maximally support teams may be one of biomedical informatics best opportunities to decrease healthcare costs, improve quality and increase clinical capacity.”
The next generation of electronic health records systems should include far more robust clinical decision support designed for use by diverse primary care teams.
That’s the conclusion of two informaticians at the Regenstrief Institute in Indianapolis, a think-tank where one of the first electronic health records systems was developed 50 years ago.
“A clinical decision support system that maximally supports teams may be one of biomedical informatics’ best opportunities to decrease healthcare costs, improve quality and increase clinical capacity,” the researchers say in their recently published paper.
“To make computer support happen, we need to invest in understanding how teams work.”
“A team-based approach to care allows physicians to spend most of their time overseeing care rather than personally delivering the majority of care,” says Paul Dexter, MD, a research scientist at Regenstrief and an associate professor of clinical medicine at Indiana University School of Medicine. This approach could help improve the quality of care while enabling physicians to treat more patients and avoid “burn out,” he says in an interview with Health Data Management.
But this new approach to care delivery requires far better decision support than what’s available in today’s EHR systems, says Titus Schleyer, DMD, program director for learning health informatics at Regenstrief and professor of biomedical informatics at IU School of Medicine. “To make computer support happen, we need to invest in understanding how teams work,” he says. “Unless we understand that, we cannot reengineer their workflow.”
Today’s EHR systems offer basic clinical decision support designed for use by one clinician – not a clinical team that collaborates on all aspects of care, including diagnosis, treatment and followup, the researchers say.
The next generation of decision support must be customizable so it can work well for widely varying teams, such as, for example, a physician working with nurses, pharmacists, social workers, health educators and therapists. “This is not a cookie-cutter business,” he says.
Artificial intelligence “plug ins” to a more robust clinical decision support system within an EHR could be designed to handle certain tasks, Dexter says. For example, AI could alert a doctor that they should consider referring a particular patient to a social worker who can help enroll the patient in a program for the homeless, he points out.
Schleyer believes there’s “unarticulated demand” for the type of decision support the research paper describes.
“The tough work” of implementing EHRs at virtually all clinical locations has been accomplished...the “nuances that maximize the value” of these systems is still lacking.
“EHR companies ultimately respond to their customers,” Dexter adds. “If the customers recognize this opportunity exists, the EHR vendors can be pushed.” Eventually, the government also could demand its EHR suppliers provide new capabilities, he adds.
“History is full of examples of coming up with things the market needs but the market doesn’t recognize the need yet,” Schleyer adds. He calls on “early adopters” to experiment with robust decision support for teams. “And we need some courageous vendors to try it.”
Dexter says “the tough work” of implementing EHRs at virtually all clinical locations has been accomplished. But, he argues, the “nuances that maximize the value” of these systems is still lacking. "Now, we have to make it really worthwhile.”
The two researchers call on vendors to work with provider organizations to create test beds for the innovative approach. And they call for “congregating behind a common vision,” such as by holding national meetings on the subject to help start a movement.
Sizing up the potential
The researchers’ paper summarizes their conclusions: “In team-based care models, CDS (clinical decision support) software has the potential to be invaluable, transforming potentially fragmented team efforts into highly effective integrated healthcare delivery,” the paper notes.
“Despite risks of fragmented care, the clinical advantages of multidisciplinary medical care will likely drive wide adoption of team-based practice,” the researchers state.
The goal of using a robust decision support system paired with a team-based approach, the paper says, is to support care coordination by ensuring that "regardless of how work is dynamically allocated or delegated within a practice, or regardless of the sequence by which tasks are completed, there would be software verification that all aspects of healthcare are addressed by the end of the visit.”
“Team-based approaches have been associated with increased physician satisfaction and decreased burnout.”
The paper offers numerous examples of how enhanced clinical decision support could play a role in various scenarios, including helping nurse practitioners or physician assistants treat patients with low-acuity episodic illnesses; assisting with diagnostic workups of new onset symptoms; capturing medical histories for chronic care patients; and directly coordinating much more preventive care than is now common.
According to the paper, other activities that occur frequently in primary care that could benefit from team-based decision support software include:
- Establishing the patient’s agenda and priorities for an upcoming physician visit
- Completing medication reconciliation
- Reviewing potential side effects of newly prescribed medications with a patient
- Following up of hospitalizations and emergency department visits by using standardized questionnaires, and then forwarding summaries to the physician
- Renewing certain medications using electronic standing order protocols
- Completing triage of returning test results, incoming emails and phone calls and requests for insurance clarifications
- Tracking of referrals from the original order to returning recommendations from a specialist
- Following up on missed clinic appointments or diagnostic testing.
“Team-based approaches have been associated with increased physician satisfaction and decreased burnout,” the paper concludes. “Too may PCPs (primary care physicians) practice within a ‘frantic bubble,’ experiencing workdays as a nonstop stream of patients. Almost all aspects of a primary care physician’s busy day could benefit from team-based assistance. CDS software can make that possible.”