From
Dr. Alexander Chiu
Understanding Health Equity Research w/ Kevin Sykes, PhD, MPH | BackTable ENT Podcast Ep. 152
With Dr. Kevin Sykes · hosted by Dr. Gopi Shaw
Chapter 3 of 12 · Fundamentals
Data aggregation issues
Social Determinants, Health Disparities, and Data Aggregation Pitfalls
Cued at 15:17 · press play
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What the experts said
Sykes discloses that he is a cisgender white man and that his lived experience does not always reflect the experiences of the communities he works in, which may introduce bias into his work.
Life expectancy varies dramatically by zip code; in Sykes's current work area, mean life expectancy is 68 years in two zip codes, 76 years one zip code north, and 90 years two zip codes north.
Life expectancy differences across zip codes are linked to socioeconomics, race, ethnicity, education levels, healthcare access, historical redlining, and segregation.
The term 'social determinants of health' is falling out of favor because 'determinant' implies inflexibility; alternatives include 'social drivers of health' or 'social inhibitors to health.'
Health disparities are the metrics used to evaluate differences in health values; health equity refers to a consistent level of health and access to resources regardless of social determinants.
Aggregating racial categories into 'other' or 'everybody else' groups in research hinders the ability to see inequities, particularly in relatively rare cancers like head and neck cancer.
If diversity is absent from clinical trials, we cannot be confident that interventions are effective for all populations or that data are generalizable.
Large databases like the National Cancer Database or SEER may not be representative of safety-net community hospitals or areas where historically minoritized communities seek care.
Community health workers understand their populations better than researchers and can craft culturally appropriate messaging to encourage research participation.
Health equity research is more difficult and takes more time; budgets must include appropriate compensation for participants and recognize transportation barriers.
Community health workers should be included as key personnel with full-time equivalent roles in research teams, not just paid hourly for attendance, because they are essential to study design, recruitment, analysis, and dissemination.
Gender categories in research have evolved from four (man, woman, trans man, trans woman) to many more, requiring inclusive options and allowing participants to contribute their own definitions.
If a researcher does not intend to disaggregate data by race, they should not collect race data, as it may bias analysis or create confusion without adding value.
Researchers should ask whether they are using race as a proxy for socioeconomics, racism, or oppression; if so, they should measure those constructs directly rather than race.
Health equity research requires accepting lower statistical power to achieve realistic recruitment goals within budget and time constraints.
Researchers must avoid sacrificing diversity of the study population in order to meet recruitment targets.
Study materials must be available in multiple languages, appropriate for low literacy settings, and administered in private settings if questions address socially undesirable topics like drug use.
A validated instrument may not be valid in a population different from the one in which it was validated; researchers must re-validate instruments in their target population.
Qualitative research provides depth that quantitative surveys cannot; it allows researchers to understand the 'why' behind disparities and informs the design of quantitative studies.
Semi-structured interviews allow questions to flow conversationally rather than in a fixed order, which is important for exploring participants' lived experiences.
Data suggest that Black and African American individuals choose surgery less often than other populations in the context of head and neck cancer, a nuanced question requiring qualitative methods to understand.
The goal of qualitative research is exploration of a concept or phenomenon, not generalizability.
Qualitative analysis involves verbatim transcription, field notes documenting emotional moments, dual independent coding, thematic saturation, and member checking to validate themes with participants.
Research is about building relationships with participants; without proper relationships, researchers cannot be confident that participants' responses reflect their true experiences.
Physicians are well-positioned to advocate for marginalized populations with policymakers because policymakers will listen to them.
In Indiana, researchers used county-level life expectancy data to secure bipartisan investment in public health infrastructure by framing it in terms of economic benefit and family ties, which resonated with Republican policymakers.
Public health funding typically surges during crises (pandemics, bioterrorism) and then evaporates, creating gaps in infrastructure; sustainable funding is needed to maintain progress.
Medical students today are more sensitive to health disparities than previous generations due to greater media exposure and globalized society.
Medical education must include health equity researchers in grand rounds, add health equity components to morbidity and mortality conferences, and continuously expose trainees to disparities.
At the University of Kansas, Dr. Carrie Francis led the addition of a social determinants of health component to M&M presentations, asking 'what are the potential contributors to this circumstance?'
The inaugural GSK Health Equity grant aims to establish an expert consensus on a uniform data set for measuring health disparities in head and neck cancer, allowing tracking of improvements or expansions of disparities over time.
The second aim of the GSK grant is to apply the uniform data set in a prospective multi-center observational study to predict higher stage at presentation with head and neck cancer and assess barriers to timely radiotherapy after surgery.
The GSK grant project uses a pragmatic design to understand real-world barriers to care, not the controlled conditions of a clinical trial, in order to predict which patients face barriers to surveillance and downstream treatments.