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The Future of Public Health: Defining Accountability, Integrating AI, and Building the Workforce
 

Author: Madeline Roberts, PhD, MPH

This month, Health Affairs devoted an entire issue to address the question “How might we reimagine what it takes to protect and promote the public’s health?” American public health is a sprawling cacophony of a system comprising over 3,300 state and local health departments, a fact in which lie both opportunity (troves of local data for tailoring interventions) and logistical minefields (to which any public health worker who experienced the pandemic can attest).

Jonathan Samet and Ross Brownson deem the public health system an “optimistic misnomer” and propose a post-pandemic-informed upgrade of Public Health 3.0, the framework developed by Karen DeSalvo and colleagues in 2017. They identify seven elements to move the ball forward for US public health: accountability; politicization and polarization; climate change; equity; data sciences; workforce; and communication.

As an epidemiologist, I have an inordinate appreciation for clearly defined terms. The term “accountability” is ubiquitous in post-pandemic discussions, and rightly so, however, it is not often accompanied by a description of optimal execution within the context of public health. Samet and Brownson offer this fantastic operational definition:

“Ideally, achieving public health accountability involves tracking a set of agreed-to measures across a continuum that begins with resources, moves to capacities, and extends to outcomes, and doing so at levels that reach from local to national, and even global.” This idea of accountability can take the form of data sharing and reporting public health program impacts.”

The backbone of public health is data-driven and perhaps data-driven accountability is one way to build back public trust. One salient example of this kind of accountability that comes to mind is the Office of National Drug Control Policy (ONDCP) Dashboard, which, among other things, provides publicly available data on non-fatal overdoses (a predictor of overdose fatalities) to guide community response to the opioid crisis. This dashboard was created to publicly demonstrate the progress of the ONDCP toward fulfilling federal opioid response plans.

One outsize external factor that continues to undermine public health efforts is misinformation and disinformation. Evidence points toward strategies such as audience segmentation for tailored messages, gain-framing messages, and data-based storytelling as effective communication tools for public health messaging.

Addressing misinformation through community members is also gaining traction. The iHeard STL tracking and response program for health information from Washington University in St. Louis asks over 200 adults on a weekly basis what they’ve heard that week, then tracks and disseminates the results of how health data is spreading within the community via a dashboard.  Similarly, the New York City Department of Health and Mental Hygiene created a Misinformation Response Unit to monitor for and respond to misinformation by collaborating with over 100 community partners who were able to couch accurate science in culturally appropriate messaging.

Perhaps the only thing more ubiquitous in public health discussions than accountability is artificial intelligence, and its role in reimagining public health cannot be overlooked. Monica Bharel and coauthors make the case that integrating novel technology into a field is most effective when it assists in executing daily tasks; they note, “Ultimately, AI, including generative AI, is just a tool, similar to a vaccine or genomic surveillance.” Three core public health capabilities for which AI is well-suited include public communication (i.e., quickly creating a range of public health messages in a number of languages and literacy levels), mitigating administrative burden and thereby optimizing workforce performance, and culling novel insights from data. EpiMonitor has previously reported on the epidemiological challenges of AI here, among them, inaccuracies, perpetuating inequity, and often a lack of a priori research questions.

In addition to external stressors such as disinformation and distrust, perhaps the biggest internal challenge to contend with in the effort to reimagine public health is workforce attrition and morale. EpiMonitor has previously written about the state of the public health workforce, which was dwindling prior to the pandemic and desperate in its aftermath. A study from 2017 to 2021 found that by 2021, 49% of all state and local public health workers staff had left their posts, and that turnover was highest among those with the shortest tenure (5 years or less). For younger workers, pay was the number one impetus for considering job separation. Other factors contributing to job separation included job-related stress, burnout, and hostility toward public health workers. 

The current moment necessitates innovative approaches to rebuild the public health workforce. The Rollins Epidemiology Fellowship is a two-year service-learning opportunity for recent MPH graduates, which has successfully contributed to reinvigorating Georgia’s public health workforce. Program leaders attribute the success of the program to:

♦         commitment from both the Rollins School of Public Health Dean and the Georgia Commissioner of Health,

♦         offloading the burden of program administration from the public health department to the academic institution,

♦         providing fellows with both an academic mentor and a site supervisor, and

♦         consistent funding (in this case largely from philanthropic foundations).

EpiMonitor has previously reported on similar programs partnering academic/research institutions with state and local health departments at both Yale University and UC Berkeley.

Another innovative approach to governmental public health workforce building comes from the Minnesota Public Health Corps, part of the newly established Public Health AmeriCorps. The initial year demonstrated the program is potentially scalable to ameliorate public health workforce burden and increase capacity, particularly attracting younger and more diverse workers to public health.

Ultimately, reimagining public health involves more than merely reconstructing existing frameworks; it demands dynamic, forward-thinking approaches that address current and emerging challenges. The issue of accountability, integrated with data-driven practices, holds potential to enhance public trust and program efficacy. Combating misinformation through tailored, culturally sensitive communication strategies delivered by trusted community messengers is essential. Innovative fellowships and programs offer promising solutions to rebuilding a robust public health work force, and utilizing artificial intelligence to streamline daily operations can optimize workers’ time and expertise. And as Samet and Brownson articulate, “By its name and what it does, public health is inherently political.” Its reimagining must not shy away from but rather embrace this reality to protect and promote the health of the public effectively.  

 

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