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EditorialEditorial

Addressing the Use of Teams in Primary Care

José E. Rodríguez and Therese Zink
The Annals of Family Medicine September 2021, 19 (5) 386-387; DOI: https://doi.org/10.1370/afm.2741
José E. Rodríguez
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  • For correspondence: jose.rodriguez@hsc.utah.edu
Therese Zink
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Key words:
  • primary health care
  • patient care team
  • ethnicity
  • ethnic groups
  • cultural diversity
  • artificial intelligence
  • reimbursement incentive

Teams have been important in primary care for almost 15 years,1 and the recent National Academies of Sciences, Engineering, and Medicine (NASEM) report, Implementing High-Quality Primary Care: Rebuilding the Foundation of Health Care, calls for the formation of diverse interprofessional teams that are well prepared and well supported to meet the primary care needs of their communities in the future.2 In addition, the report specifically recommends that teams be paid to care for people, that teams are trained where people live and work, and that teams are served by new information technology.2 In this issue of Annals of Family Medicine, we feature articles addressing these recommendations.

The mixed method study by Vilendrer et al3 examines financial incentives as an updated version of pay for performance (P4P) to engage medical assistants (MAs) in population health quality measure success. They point out that success with quality measures requires MA involvement. Medical assistants do much of the work, but seldom reap any reward, while quality bonuses are common for physicians.4 One MA in the study shared her frustration: “But if we’re doing all the work, and we already know they’re making all the money, [then] we’re peons.”3 Although the majority of the MA participants reported no ongoing or past experience with financial incentives, they responded overwhelmingly positively when presented with hypothetical monetary bonuses as a way to restore equity.3 This study speaks directly to the first recommendation above, that the teams be paid. The current model of rewarding only doctors to deliver services is challenged by the authors, and even before learning of the report, they had explored a potential model of paying the team.

Shaw et al5 evaluate burnout in several health systems that have implemented Primary Care 2.0–enhanced team-based primary care. They underline the importance of MA support and availability and recommend that all future evaluations of primary care redesign and burnout should explicitly consider levels and fluctuations in MA staffing. They show that cost-containment efforts should not decrease the MA-physician ratio, as this may negatively impact the team and increase turnover. In addition, institutional commitment is essential to maintain the effectiveness and wellness of the entire team and addressing burnout cannot be a one-time, or one-participant group (physicians vs MA) intervention. This article also addresses the importance of individual team members and highlights the costs of not taking care of the entire team. This is in harmony with the NASEM report’s recommendation that teams be paid for taking care of people.

Electronic health records are part of clinical care and with that comes decision-making support in the forms of information technology (IT) and artificial intelligence (AI). The NASEM report recommends that these products serve the care teams. Holdsworth et al6 explore how artificial intelligence (AI) might augment pre-visit planning (PVP) efforts through key informant interviews and literature review based on the 10 steps of PVP outlined by the American Medical Association (AMA).7 They conclude by calling for rigorous evaluation to ensure that any AI intervention is always supporting—not subverting—the patient-physician relationship.6 It is important to remember that while AI systems and algorithms can be helpful, they can also unintentionally make care worse. This can happen, for example, when costs, instead of illness severity, are used to predict which treatments to give.8 The authors are to be commended, however, for charting a way to think about how AI products can serve the team and preserve the patient-physician relationship.

The remaining recommendation to train teams where people live and work will be addressed in this editorial, and in subsequent issues of Annals. The authors of the NASEM report were careful to include a call to expand and diversify the primary care work force as part of this recommendation. Dismantling privileging systems9 and systemic anti-Black racism10 will be required. In addition, equitable and holistic admissions practices11 must be adopted with a goal of increasing race/ethnic/gender diversity in health care teams. Currently, physicians, physician assistants (PA), and nurse practitioners (NP) do not reflect the diversity of our patients; in fact, we may be going in the opposite direction, evidenced by non-Hispanic White matriculation increasing in the PA schools,12 the nursing profession remaining over 80% White,13 and decreasing matriculation of Black men and American Indian/Alaska Native students into medical school in the past 40 years.14 We can learn from our MA and community health worker (CHW) team members, as 55% of MAs and 45% of CHWs and health educators identify as Black, Latinx, American Indian/Alaska Native, Pacific Islander, or Asian.15,16

The NASEM report calls for more educational opportunities for interprofessional and diverse team members to work together early in their training.2 While these are noble goals, supported in adjacent research, the implementation of diverse teams requires further study. Future research questions could include: Does a diverse team impact patient care and outcomes to the same degree as physician-patient race concordance? Does the diversity of the team leadership matter more than the team composition? How do we better support and develop our diverse MA and CHW workforce? How do we decrease the turnover of these lower-paid staff? Does providing tuition benefits for furthering career goals to those in entry-level health care jobs decrease turnover? What can we do to ensure that diversity is not concentrated in the lowest-paying jobs in health care? What can be shifted to AI so all staff members can have meaningful work and the care of the patient is maximized?

Research is necessary to understand how to support diverse interprofessional teams. Funding models must be modified to ensure that team leaders and team members are diverse. The call for change has been issued—it is now our job to implement change and study it to ensure we are improving patient outcomes with these changes. We look forward seeing the science that supports team-based care as a mechanism to improve patient outcomes and reduce costs.

Footnotes

  • Conflicts of interest: authors report none.

  • To read or post commentaries in response to this article, go to https://www.AnnFamMed.org/content/19/5/386/tab-e-letters.

  • Received for publication July 30, 2021.
  • Revision received July 30, 2021.
  • Accepted for publication July 30, 2021.
  • © 2021 Annals of Family Medicine, Inc.

References

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    OpenUrlPubMed
  2. 2.↵
    1. National Academies of Sciences Engineering, and Medicine, Health and Medicine Division, Board on Health Care Services, Committee on Implementing High Quality Primary Care
    . Implementing high-quality primary care: rebuilding the foundation of health care. Published 2021. https://www.nationalacademies.org/our-work/implementing-high-quality-primary-care
  3. 3.↵
    1. Vilendrer S,
    2. Brown-Johnson C,
    3. Kling SMR, et al.
    Financial incentives for medical assistants: a mixed-methods exploration of bonus structures, motivation, and population health quality measures. Ann Fam Med. 2021; 19(5): 427-436.
    OpenUrlAbstract/FREE Full Text
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    1. Shaw JG,
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    Primary Care 2.0: a prospective evaluation of a novel model of advanced team care with expanded medical assistant support. Ann Fam Med. 2021; 19(5): 411-418.
    OpenUrlAbstract/FREE Full Text
  6. 6.↵
    1. Holdsworth LM,
    2. Park C,
    3. Asch SM,
    4. Lin S
    . Technology-Enabled and artificial intelligence support for pre-visit planning in ambulatory care: findings from an environmental scan. Ann Fam Med. 2021; 19(5): 419-426.
    OpenUrlAbstract/FREE Full Text
  7. 7.↵
    1. American Medical Association
    . 10 steps to pre-visit planning that can produce big savings. Published Sep 4, 2015. Accessed Jul 29, 2021. https://www.ama-assn.org/practice-management/sustainability/10-steps-pre-visit-planning-can-produce-big-savings
  8. 8.↵
    1. Obermeyer Z,
    2. Powers B,
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    4. Mullainathan S
    . Dissecting racial bias in an algorithm used to manage the health of populations. Science. 2019; 366(6464): 447-453. doi:10.1126/science.aax2342
    OpenUrlAbstract/FREE Full Text
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    1. Rodríguez JE,
    2. Tumin D,
    3. Campbell KM
    . Sharing the power of white privilege to catalyze positive change in academic medicine. J Racial Ethn Health Disparities. 2021; 8(3): 539-542. doi:10.1007/s40615-020-00947-9
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    1. Foster KE,
    2. Johnson CN,
    3. Carvajal DN, et al.
    Dear white people. Ann Fam Med. 2021; 19(1): 66-69. doi:10.1370/afm.2634
    OpenUrlAbstract/FREE Full Text
  11. 11.↵
    1. Sklar DP
    . Diversity, fairness, and excellence: three pillars of holistic admissions. Acad Med. 2019; 94(4): 453-455. doi:10.1097/ACM.0000000000002588
    OpenUrlCrossRef
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    1. Ryujin D,
    2. Spackman J,
    3. Honda TJ, et al.
    Increasing racial and ethnic diversity at the University of Utah physician assistant program. Fam Med. 2021; 53(5): 372-375. doi:10.22454/FamMed.2021.923340
    OpenUrlCrossRef
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    1. Rosseter R
    . Enhancing diversity in the workforce. American Association of Colleges of Nursing. Updated Apr 1, 2019. Accessed Jul 29, 2021. https://www.aacnnursing.org/news-information/fact-sheets/enhancing-diversity
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    1. Morris DB,
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    4. Murillo AL,
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    . Diversity of the national medical student body – four decades of inequities. N Engl J Med. 2021; 384(17): 1661-1668. doi:10.1056/NEJMsr2028487
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    1. DATA USA
    . Medical assistants. Accessed Jul 29, 2021. https://datausa.io/profile/soc/medical-assistants
  16. 16.↵
    1. DATA USA
    . Miscellaneous community & social service specialists, including health educators & community health workers. Accessed Jul 29, 2021. https://datausa.io/profile/soc/miscellaneous-community-social-service-specialists-including-health-educators-community-health-workers
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The Annals of Family Medicine: 19 (5)
The Annals of Family Medicine: 19 (5)
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1 Sep 2021
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Addressing the Use of Teams in Primary Care
José E. Rodríguez, Therese Zink
The Annals of Family Medicine Sep 2021, 19 (5) 386-387; DOI: 10.1370/afm.2741

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José E. Rodríguez, Therese Zink
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