Primary Care Innovations Can Deepen the Specialty

Megan Mahoney, MD, MBA, Professor and Chair, UCSF Department of Family and Community Medicine and Member, The Doctors Company Board of Governors

Like many primary care physicians, I wonder how my specialty will evolve through a period of physician shortage. In 10 years’ time, for every new physician who enters the primary care workforce, there will be two advanced practice clinicians (APCs).1

From my perspective, the more the merrier. We need all hands on deck to provide quality care. But the way we approach this evolution will determine whether primary care becomes a touch-and-pass specialty or whether it can remain a deep specialty, built on strong relationships with our patients. With team-focused innovations in care models and technology, I believe primary care can continue to offer the rewards of in-depth and longitudinal practice.

Preserve Depth of Care with Teamwork

Recently, colleagues and I designed what we call Primary Care 2.0, a new team-based care model.2 By focusing on role definition and authorization protocols, we have created the conditions for team members to perform at the top of their licenses:

Core care team: Each care team revolves around a primary care physician and an APC working together, supported by four medical assistants, who also provide in-room scribing.

Extended care team: Three care teams per clinic share access to two behavioral health specialists, a pharmacist, a case manager who is a nurse, a clinic manager, an assistant clinic manager, a nutritionist, and physical therapy services.

Resource-adjusted panels: Risk stratifying a patient panel means allocating the patients to the appropriate team member so that everybody practices at the top of their license. This approach could mean that the physician sees fewer, more medically complex patients.

eConsult: This delivery system is helpful for messaging specialist colleagues to ask how they would manage a condition or at least initiate a workup. When I used eConsult at Stanford Health Care or UCSF, specialists across our system were able to respond. Forty percent of issues addressed this way were resolved.

This Primary Care 2.0 model shows how innovations in care models and technologies can help us preserve depth within primary care, even as we face a physician shortage.

By contrast, if we are not mindful of how our specialty develops over the coming decade, we could find that we are sending patients to specialists the moment someone has diabetes, plantar fasciitis, hypothyroidism, or polymyalgia rheumatica—all of which are bread-and-butter primary care conditions. When we build in the capacity to manage more holistic care of the patient, I believe the care is better than when we carve it out. With thoughtful structuring of care teams, APCs can help preserve depth in our specialty.

Improve Access with Innovation

Meanwhile, with primary care at the forefront of transformations in healthcare in general, how can everyone benefit from what’s happening in the innovation space? Consider two interesting examples: Walmart Health and Babylon. Each has specific components I would like to highlight.

  • Walmart Health and transparency: In 2019, I visited the Walmart Health model clinic in Bentonville, Arkansas. This morning, I typed my zip code into Walmart Health’s website, and it was able to tell me exactly how much I would pay for an annual visit: $40; for a behavioral health consultation: $60; and for a lipid test: $10. As we think about the rising costs of out-of-pocket care for everyday households, we should remember that knowing how much to expect to pay matters to many patients. In fact, cost transparency can mean the difference between a patient’s seeking primary care and staying home—and then, perhaps, landing in the emergency department later.
  • Babylon and accessibility: When I visited East Africa in 2019, I found that Rwanda has great primary care. But it is spread out, so in-person patient access can be challenging. Babylon has filled a gap in Rwanda’s healthcare system by providing a chatbot and access to telehealth as a very first line of care. When I visited, Babylon had just facilitated a million consultations in Rwanda. More recently, Babylon’s AI-powered triage tool has aided call-center nurses in swifter decision making. Its record of combating lack of interoperability between healthcare systems makes it highly relevant to our concerns in the United States. Technology innovations can, instead of interfering in face-to-face care, help patients access the right care faster.

Diversify Data for Quality Care

As disruptive technologies emerge, we must remember that machine learning is only as good as our data sets. AI algorithms have often been trained on homogeneous data pools,3 and then they do not end up serving our healthcare population in the U.S.4

It is imperative for us as clinicians to be upstream when these training algorithms are made. If we intervene earlier in the development process, then AI algorithms can serve our needs and apply to the diverse population we serve. In primary care, as both a comprehensive and deep specialty, we can intervene at a population level while continuing to forge long-term patient relationships and foster continuity of care.

Resources

1. The complexities of physician supply and demand: projections from 2018 to 2033. Association of American Medical Colleges. Published June 2020. https://www.aamc.org/media/45976/download?attachment

2. Brown-Johnson CG, Chan GK, Winget M, et al. Primary Care 2.0: design of a transformational team-based practice model to meet the quadruple aim. Am J Med Qual. 2019;34(4):339-347. doi:10.1177/1062860618802365

3. Celi LA, Cellini J, Charpignon ML, et al. Sources of bias in artificial intelligence that perpetuate healthcare disparities—a global review. PLOS Digit Health. 1(3):e0000022. doi:10.1371/journal.pdig.0000022

4. Sklar J. Research: artificial intelligence can fuel racial bias in health care, but can mitigate it, too. The Journalist’s Resource. Published July 11, 2022. https://journalistsresource.org/home/research-artificial-intelligence-can-fuel-racial-bias-in-health-care-but-can-mitigate-it-too/