A View of Health Inequities Through the Lens of Health System Science: Population Health and Hotspotting 

As models for health care reimbursement shift to merit-based incentive payment systems, the impetus for optimizing care for our patients intensifies. While the approach to medical error has historically been to blame the provider, the approach to failing to reach optimal outcomes has historically been placed on the patient: the elderly deciding between insulin and electricity, the mother opting for something familiar from their culture rather than an unknown medication, or the child eating only canned or packaged foods because they live in a food desert.  

Twenty years ago, population health was defined in literature.1 Since then, the Centers for Disease Control (CDC)2 and Institute for Health Improvement (IHI)3 have noted population health as pivotal for correcting health inequities. The major tenets of population health include chronic care management, quality and safety, public health, and health policy. These intersections have been in the spotlight with our own PAEA book read of Political Determinants of Health just last year.  

While population health is both small enough to consider the individual health care user and large enough to consider the entire community of users, it still may not identify all needs. Other population health-like initiatives include “hotspotting.” Hotspotting uses data from health care systems to identify “superutilizers” of resources with the goal of an interprofessional approach to care coordination that both improves patient outcomes and reduces expenditures. 

A recent article in NEJM⁴ described a randomized control trial of hotspotting in one hospital in the US that did not show improvement in hospital readmission as expected. However, upon further review of the study design, the data collected included a lack of literacy, exclusion of patients with mental health admissions, housing instability that made connecting with resources after admission difficult, and a note that despite temporary housing being available many did not utilize it.  

While the study seems to indicate hotspotting may not be all it was hoped, it highlights the need for more population health—with both a broad and more individualized approach to address long term spending needs and goals such as investment in education, mental health reform, and trust building in communities. Introducing learners to population health early prepares them to be part of the change and to advocate for patients to improve health equity.  

Looking for evidence-based activities related to population health for your program? Consider a few of these options which are also shared in the Digital Learning Hub.  

• Use a poverty simulation5 to allow students to simulate the experiences of several families traversing the healthcare system and navigating “life” from multiple lenses. Take it from the “cultural competence” to population health level by following the activity with next-step activities to explore the complexities and intersections of identity and resources.  
•  Virtual or in-person “community tours”6 or “windshield tours”7 followed with thorough debriefing and reflection to explore the needs of communities. Take it to the next step by connecting learners with community agencies and/or local leaders where they can advocate for the needs of the community.  
• CLARION Case Competition or create a smaller scale competition at your own institution. Take it to the next level by using real data—collaborate with a local health system or network to answer a “real data” problem 

References 

1. Kindig D, Stoddart G. What Is Population Health? Am J Public Health. 2003;93(3):380-383. 

2. What is Population Health? | Population Health Training in Place Program (PH-TIPP) | CDC. Accessed June 19, 2023. https://www.cdc.gov/pophealthtraining/whatis.html 

3. Resources | IHI – Institute for Healthcare Improvement. Accessed June 19, 2023. https://www.ihi.org/Topics/Population-Health/Pages/Resources.aspx 

4.  Finkelstein A, Zhou A, Taubman S, Doyle J. Healthcare Hotspotting – A Randomized Controlled Trial. N Engl J Med. 2020;382(2):152-162. doi:10.1056/NEJMsa1906848  

5. Keeney AJ, Hohman M, Bergman E. Interprofessional Education: A Poverty Simulation with Elementary Teachers and Social Work Students. J Teach in Soc Work. 2019;39(2):148-162. doi:10.1080/08841233.2019.1586808 

6. Irby MB, Moore KR, Hamlin D, et al. Building bridges between a community and an academic medical center via community tours. J Clin Trans Sci. 2020;4(4):294-300. doi:10.1017/cts.2020.7 

7. Lazow MA, Real FJ, Ollberding NJ, Davis D, Cruse B, Klein MD. Modernizing Training on Social Determinants of Health: A Virtual Neighborhood Tour is Noninferior to an in-Person Experience. Acad Pediatr. 2018;18(6):720-722. doi:10.1016/j.acap.2018.04.007 

8. Ketcherside M, Puett E, Banez C, Maher M. Interprofessional clinical education case study competition from the public health perspective. Health, Interprofessional Practice and Education. 2015;2(3). DOI: 10.7772/2159-1253.1090  

The other stories in this series can be found on the PAEA website. The first story is here, the second story is here, the third story is here, the fifth story is here, and the sixth story is here.