Prioritizing the social drivers of health
The COVID-19 pandemic has exposed gaps in most healthcare systems. The typical hospital or doctor’s office is built with the assumption that those in need of care can and will seek out professional healthcare when needed. Clinicians also assume that once someone receives care, the discharged patient has the means to prioritize a healthy recovery.
That leaves many healthcare systems overloaded and unable to care for those members of society least able to access basic drivers of health, such as food, shelter, and safety, particularly during times of crisis. And that also means that the data used to determine the best approaches to diagnosis, care—even hospital admissions—exclude the social needs and health experiences of marginalized community members until they are in dire need of help.
The details of what contributes to community members’ care and well-being are typically siloed, fragmented, or even lost among multiple organizations and technical systems that serve public health. The lack of complete health histories and gaps in the evidence base can exacerbate health inequities. At the same time, systems designed to track the health needs of individuals often lack critical context, such as access to jobs, stable housing and community support. These data are critical to understanding the needs of community members that experience systemic discrimination and chronic marginalization. Learning how to fill these gaps requires connecting health outcomes to the social realities that shape them.
The role of community health workers
Community health workers (CHWs) and the community-based organizations that coordinate their expertise, building effective, culturally resonant bridges between healthcare systems and marginalized community members. These frontline healthcare workers keep people at the center of a holistic approach to direct care while collaborating with community partners, funders, and clinicians to strengthen the capacity and sustainability of an equitable sociotechnical approach to public health.
“You go to the hospital to keep you alive…but what does it tell them about you if your labs look fine and you’re ready to lose your house?”
–Longtime community health worker
Project goal
Project Resolve is a multistakeholder collaboration that brings Microsoft Research’s social science, engineering, and computer science expertise to the service of community-based organizations to advance health equity for all.
The goal of the research is to study current community practices and create publicly available, interoperable systems attuned to the social dynamics and contexts that shape how people make use of technologies in their everyday lives. Resolve’s partnerships test out a model of working with a coalition of independent, resource-constrained organizations to co-design a shared secure home for open-source software tools and sensitive community health data. Resolve aims to support relationships among individuals in need of help, health workers, partners, organizations and funders and to ease their collective administrative burden so that more time and energy can be spent on direct care.
The Project Resolve research team will continue to develop frameworks and methodologies for co-creating sociotechnical systems—starting with community health technologies—that better understand and incorporate local expertise and organizational needs to build a more inclusive and equitable approach to healthcare’s digital transformation.
Project principles
Project Resolve is built upon three core principles:
Accelerate societal resilience by building with organizations that reflect and serve society’s most marginalized members
Project Resolve aims to co-develop sociotechnical systems that support individual relationships and align allyships among community members.
One example of this principle in action was creating open-source software and data management systems that understand, reflect, and incorporate healthcare workers’ unique relationships and ways of working across different communities. While traditional customer relationship management (CRM) systems are organized around individual users and sales or billing accounts, CHWs organize around two entirely different types of relationships: case-centric care and service-centric care.
Case-centric care focuses on meeting the immediate needs of individuals, often one-to-one, in a moment of acute adversity. Service-centric care offers broader intervention, often delivered to many people at once, with cultural sensitivity and an awareness of the chronic challenges ahead. Case-centric care can take the form of assisting a specific client with issues related to housing instability, while service-centric care may take the form of a vaccine clinic to serve the needs of multilingual communities with unreliable access to translators or basic information in their first language.
Adopt multidisciplinary approaches
Because healthcare is by its nature highly dependent on many factors critical to understanding individual and population health, it is key to account for the myriad environmental, economic, and organizational issues, such as access to fresh food, insurance, transportation, stable housing and other conditions that affect people’s ability to afford medications, adhere to interventions, or gain access to healthcare resources in the first place.
Understanding how social and cultural dynamics drive individual health outcomes requires expertise from research disciplines trained to identify and analyze the conditions that prime or forestall collective wellbeing. This includes a complement of humanist disciplinary perspectives, such as anthropology, communication, critical race and gender studies, and science and technology studies working with medical professionals, security and privacy experts, computer scientists, data scientists, and engineers. It also means foregrounding the expertise of community organizers and members who deeply understand the underlying capacity and potential for sustainable efforts critical to a positive outcome.
Prioritize iterating between large-scale observations and rich data analysis
One of the biggest challenges in healthcare innovation is that some of the most important data are typically lost, overlooked, scattered across multiple, disconnected spreadsheets, or never collected. In many cases, key insights come not from sensors or telemetry but ephemeral moments of connection among community members that cannot be logged and captured as discrete data points.
This quantitatively ‘sparse’ but qualitatively rich data can take the form of health histories scattered among disparate community health centers and urgent care clinics, pharmacies, emergency rooms and care sought out through other locations, like houses of worship, that aren’t recognized as healthcare settings at all. Taken together, qualitative data are critical to reflecting the relationships and needs of people who otherwise might not be represented in the large-scale datasets needed to innovate.
New privacy-preserving methodologies for securely and responsibly collecting, storing and learning from both qualitative and large-scale data are critical to building a more inclusive and robust evidence base, and may also be useful for other applications both within and outside of healthcare.