Strategies to Prioritize Clinical Options in Primary Care

Patrick J. O'Connor, MD, MA, MPH; JoAnn M. Sperl-Hillen, MD; Karen L. Margolis, MD, MPH; Thomas E. Kottke, MD, MSPH


Ann Fam Med. 2017;15(1):10-13. 

In This Article

How to Apply Prioritization in Practice

The potential of electronic health records (EHRs) to improve care has long been recognized but rarely been realized. Prototype EHR-linked, Web-based clinical decision support systems that identify and prioritize clinical options, however, save time, satisfy clinicians, empower patients, have high use rates, and improve care are now up and running in several large health care systems.[15,16] Web services that include risk prediction equations can receive patient-specific data that are automatically sent from an EHR, perform the multiple computations needed to estimate the relative benefits of alternative treatment options, and display patient-specific prioritized treatment options on the EHR screen within 1 second.

Presenting clinical options to the patient facilitates patient-centered care and shared decision making by informing the patient of clinical options with the most potential benefit and then empowering the patient to select their preferred option(s). Many patients will continue to decline clinical options of high benefit, such as smoking cessation, colorectal cancer screening, or statin treatment. Then we must respect our patient's preferences and remember that patient treatment preferences and readiness to change typically vary with time.[23] Clinical decision support systems update and reprioritize evidence-based treatment options at each subsequent encounter, enabling patients to see progress in some areas and reconsider previous preferences in other areas.

Results of randomized trials show that systems improve blood pressure levels and glucose control in diabetes patients, smoking cessation in dental offices, identification of high blood pressure levels in adolescents, and screening for hepatitis B in high-risk populations, as well as reduce cardiovascular risk in adults at high risk but without a diagnosis of heart disease or diabetes.[16] There is also evidence that such systems are cost-effective and may be cost saving to payers when used on a routine basis in large care delivery systems.[24] These clinical decision support systems are used at 70% to 80% of targeted visits, have 94% primary care clinician satisfaction, and are now in use every day at 3 large health care delivery systems that provide care to 1.5 million patients.