Health

An Expert’s Perspective on ‘Precision Population Health’

It is a well-established fact that multiple factors (e.g., family history/genetics, clinical care, socioeconomics, lifestyle) contribute to the prevalence and outcomes of cardiovascular disease. Today, accruing evidence suggests that a strong relationship also exists between economic indicators (e.g., wealth, prosperity, employment) and cardiovascular disease outcomes.

Large-scale population studies indicate that improvements in local economic prosperity are associated with relative decreases in cardiovascular mortality rates, ischemic heart disease mortality rates, and all-cause mortality rates regardless of race, ethnicity, or gender. Moreover, the evidence suggests that living in more prosperous areas is associated with generally higher quality of healthcare (including greater receipt of recommended services), lower hospital admission and mortality rates, and lower per-capita healthcare expenditures (including end-of-life care costs).

For vulnerable populations living in less prosperous areas, the data show conditions that are the polar opposite — and the economic hardship created by COVID-19 has exacerbated the issues. There couldn’t be a more opportune time for researchers to ramp up their efforts to better understand the importance of socioeconomic variables (e.g., income supplements, local economic opportunity, housing availability, nutrition) and other social determinants of health for defined demographic areas.

This brought to mind an editorial that caught my attention a few months ago. After discussing the issues noted above in greater detail, the authors postulated that in the future “precision population health” strategies and tactics will leverage data “to reduce inefficiencies and waste in the distribution of social and support services, better meet the needs of the population, and improve population health by identifying which interventions work for which population subgroups in which areas.”

Curious to learn more about precision population health, I contacted one of the authors, James Weinstein, DO, MS. Weinstein sees his clinical specialty (spine surgery) as being a primary motivator of his involvement in population health. “When you have 30% of people in the world suffering from back pain, you have a population health problem! Back pain impacts health and quality of life in interesting ways. The symptoms are painful and debilitating, and the condition occurs in all demographic segments — every race, gender, economic stratum, and education level.”

In addition to conducting research for the National Institutes of Health (basic science in pain/function, and foundational clinical trials work in how to advance population health), Weinstein served as president and CEO of Dartmouth-Hitchcock and as director of the Dartmouth Institute for Health Policy and Clinical Practice (home of the Dartmouth Atlas of Health Care, the go-to resource for understanding the ongoing variations in the quality and cost of healthcare delivery across the U. S.)

How does he think about precision healthcare in the context of population health? Precision medicine has made great strides in individual patient treatment; however, as medicine advances, Weinstein believes the N=1 approach can become reality. The ability to aggregate metadata into the cloud and apply sophisticated artificial intelligence (AI) models will lead to more patient-specific treatments with better outcomes within and across populations. Using a precision population health approach will allow us to design and organize cohorts of “people like me” to home in on subpopulations for improved population studies and more predictable N=1 outcomes, within and across populations.

As Microsoft Healthcare’s Senior Vice President of Equity and Innovation, Weinstein now heads up the Precision Population Health Team. With an explicit focus on equity, the team seeks to improve population health and healthcare delivery by leveraging the potential of Big Data, advanced machine learning and causal inferences techniques. Key areas of concentration are:

  • Health equity: Use information and tools to assess whether health care is delivered equitably. Support treatment decision tools that are based in equitable trial design. Recognize that social determinants of health contribute to ~60% of an individual’s health. Aim to understand if, when, and for whom diagnostic and treatment interventions would be useful.
  • Quality in Care: Use methods to adjust for patient demographics, geography, and socioeconomic factors to help avoid suboptimal outcomes associated with over- or under-treatment. Work with providers, payers, pharmacies, policymakers, and patients to assess quality of care and identify where improvements can be made.
  • Consumer-Focused Decision Tools: Create and transform AI models into easily understood visuals to help patients and providers better understand patient preferences and the most appropriate diagnostic and treatment options. Decision aids fully inform patients of risks versus benefits of options based on the best available evidence, while fully incorporating a patient’s own values/utilities towards selection of one treatment versus another.

Weinstein is quick to acknowledge the pivotal role of Microsoft and its focus on healthcare. Its platform has enormous potential for monitoring, artificial intelligence, machine learning, diagnostics, and education with a chief interest in finding community-based solutions to promote health equity. The “Microsoft Teams” technology has already demonstrated value in healthcare delivery (especially since the emergence of the COVID-19 pandemic), and the company’s pending acquisition of Nuance Communications (with critical expertise in voice AI) will be useful for medical applications with Microsoft cloud capabilities. “I hope that with a better understanding of technology, we as a society will continue to develop tools that create better opportunities for equity,” he said.

As cities around the world come to the table around broadband and platforms for health, perhaps we can move the curve. With one-quarter of its citizens living in poverty, the challenges of delivering precision population health in a city like Philadelphia will be huge. But in spite of this, I share Weinstein’s genuine optimism about the future.

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