Atlantic Fellows for Health Equity (AFHE) brings together health professionals from around the world and across disciplines to build leaders, create solutions and grow community. As we celebrate our tenth anniversary, we are reflecting on what our community has learned and accomplished while looking ahead at the future of health equity.
Through The Future of Health Equity Blog Series, AFHE Senior Fellows share their perspectives on the challenges, opportunities, innovations and leadership that will shape health equity in the years ahead. We are proud to bring these reflections to the BMJ Leader Blog audience as part of our 10-year celebration. The opinions reflected here are the views of the authors.
The blog below was written by Thomas Merrill, a 2017 Atlantic Fellow for Health Equity.
Equity: The Final Frontier of Quality Improvement
The most important lessons I learned about health equity came from building dashboards that were not asked to measure it.
My introduction to health care was from the back office, as an economist in state planning when the Affordable Care Act was first passed, to reporting analytics for an integrated organization with both physical clinics and insurance plans, and later coding as a risk adjustment data scientist charged with deriving information from the disparate expanses of our health system.
I observed how actors within our health system respond when a priority is translated into something that can be defined, collected, monitored, regulated, financed and — most notably — gamed. What becomes measurable becomes visible — perceptible across disciplines if we communicate it right — but what remains outside those regulated and audited systems too often remains aspirational.
That was the professional context in which I joined the inaugural Leaders for Health Equity fellowship in 2017, now the Atlantic Fellows for Health Equity. The fellowship gave me something my technical work could not: a community from different disciplines who approached health equity as a shared leadership responsibility.
This growing community stayed with me through an unexpected decade. Organizational changes made it increasingly difficult to connect my day job to my purpose. Then COVID-19 left me working remotely from the woods of rural Maine as a data architect for a clinic I had never actually stepped foot in until the unlikely opportunity for a mid-career change, enrolling in an accelerated nursing program.
I am now a registered nurse and PhD student in nursing science, an inverted path of the many mentors and role models who inspired me after their grounding in clinical practice before moving toward informatics. I began with the data before clinical training, and this reversed path changed my understanding of quality.
For years I had worked in Quality Improvement (QI) as industry practices it: monitoring dashboards, meeting specifications, reporting performance and managing financial risk. Only later did I encounter QI Science as a discipline concerned with systematically learning how systems produce better outcomes. Donald Berwick described improvement as a science, not just compliance with performance targets. Avedis Donabedian’s enduring structure-process-outcome model likewise reminds us that outcomes emerge from the systems and processes preceding them.
That distinction matters for health equity.
Twenty-five years ago, Crossing the Quality Chasm placed equity alongside safety, effectiveness, patient-centeredness, timeliness and efficiency as a foundation of health care quality. We have learned how to construct systems around safety, utilization, preventive care and other priorities. We have not built equally mature systems for asking whether improvements are distributed fairly.
Why has equity lagged the others operationally?
Is this a measurement problem? Health disparities can disappear inside averages. A health system can improve an overall outcome while leaving the gap between more and less advantaged clients or community members unchanged. Equity-focused improvement therefore asks a different question: not “Did the average improve?” but “For whom did it improve, and who was left behind?”
Work on equity-focused quality improvement and a recent scoping review of equity-focused QI interventions reinforce the need to examine distribution rather than assuming population-level gains are equitable gains. Researchers studying the measurement of health equity similarly emphasize the importance of common definitions, appropriate measures, and data that can support action.
Is this a problem of incentives? Performance measurement can mobilize enormous organizational attention, but high-stakes targets can create incentives to optimize the measure rather than its underlying purpose. The literature on performance-measure gaming emphasizes why measurement needs to remain connected to meaningful outcomes. The lesson is that we need better measures—ones that keep client and community benefit, fairness, and lived experience connected to performance.
An early conversation in my PhD training with my friend and AFHE fellow Toyese Oyeyemi helped bring this into focus. Through his work with the Social Mission Alliance, he studies how health professions institutions can organize around social mission. The concept itself asks health professions institutions to contribute intentionally to health equity rather than treating it as peripheral to their work. Toyese challenged me to focus on the outcomes: How do we know where advancing social mission changes health?
That question led to the development of the Equity-Driven Quality Framework. We adapted Donabedian’s familiar model so that Structure becomes Structural Competence, Process becomes Social Mission, and Outcome becomes Health Equity. Structural competence asks whether health organizations understand the social, economic, environmental, and political structures shaping health. Social mission asks whether that understanding becomes action. Health equity asks whether disparities were avoided.
My hope for the next decade is that this becomes less exceptional, less elective.
Health equity does not need to remain a parallel initiative, a special office, or an optional lens applied after the regulated QI work is checked off. We can build it into the machinery of QI itself: more reliable socioeconomic data; measures designed to reveal disparities rather than average them away; meaningful community participation in deciding what improvement means; and organizational, payment, and policy systems that reward addressing avoidable gaps.
Equity-centered learning health systems already offer practical lessons for making participation and accountability part of improvement, not an afterthought.
We have made progress in QI implementation. We standardize definitions. We improve data infrastructure. We compare results over time. We align clinicians, payers, policymakers and communities around outcomes that matter.
My own next step is empirical: using epidemiology and predictive analytics to study acute exacerbations and hospitalizations among people living with chronic illness and examining how those outcomes relate to the biosocial and environmental conditions where they live. The framework now needs testing, refinement and challenge.
Ten years after joining this fellowship, what gives me hope is that we have better tools, stronger networks, and a growing capacity to translate moral commitments into measurable systems of accountability. Health equity can be more than an aspiration attached to quality—it can become how we decide whether quality has indeed been achieved.
Author
Thomas Merrill
Thomas Merrill is a registered nurse and currently in PhD training with a focus on integrating data science methods with equity and sustainability to promote health system quality improvement that emphasizes disparities reduction and addresses inequities.
Declarations of Interest
No interests to declare.