
Health Equity & Access Weekly Roundup: June 26, 2026
Key Takeaways
- Undercoding obesity in EHRs obscures counseling, impedes referrals, and compounds coverage instability, exemplified by Pennsylvania’s Medicaid GLP-1 rollback and insurer churn limiting ROI from treatment.
- SEER-based projections through 2032 show rising DLBCL and MCL incidence, with disproportionate growth in women and patients under 65, pressuring care delivery capacity and payer budgets.
Obesity coding gaps limit care; MCL rising in women; racial pain disparities in oncology; AML access expands; SDOH rivals genetics.
Coding, Coverage Gaps Hamper Multidisciplinary Obesity Care
Chronic undercoding of
Ajaykumar Rao, MD, chief of adult endocrinology at Temple University, described a cascade of downstream failures from the coding gap. Sharon Herring, MD, MPH, professor of medicine at Temple, pointed to Pennsylvania’s January 2026 rollback of Medicaid glucagon-like peptide-1 coverage as a sharp reversal after 3 years of access growth. Daniel Rubin, MD, MSc, FACE, attributed
More Women Will Be Diagnosed With MCL Through 2032, SEER Data Suggest
Incidence of both diffuse large B-cell lymphoma (DLBCL) and
Drawing on the National Cancer Institute’s SEER-21 data from 2017 to 2022 and SEER-Medicare claims from 2012 to 2021, the analysis projects DLBCL incidence rising 7%—from approximately 28,800 new cases in 2023 to 30,800 by 2032—with first-line treatment-eligible patients growing from 33,120 to 35,523. MCL incidence is projected to grow by 6% overall, with a 43% increase among women, from 920 to 1318 annual cases, and a 33% increase among patients aged younger than 65, signaling demographic shifts that will challenge existing care models and payer budgeting.
Data Reveal Racial Disparities in Oncology Pain Prescribing: Ila Struti, MPH
Real-world data from community oncology settings reveal significant
Among patients with
Rewriting the AML Treatment Playbook: Tina Bhatnagar, DO
As former director of hematology and medical oncology, Bhatnagar focused on elevating care standards in a rural, underserved community and expanding clinical trial access, countering widespread misconceptions that trial participation represents experimentation rather than a pathway to emerging therapies.
Social Factors May Match, Outpace Genetic Risk in Disease Prediction
Social, behavioral, and environmental factors can contribute as much as—or more than—polygenic risk scores to predicting common disease, according to a study from the
Investigators analyzed data from 413,457 All of Us Research Program participants, finding that adding social determinants of health (SDOH) embeddings—derived from more than 100 survey variables—improved disease risk model discrimination by 0.007 to 0.027 in the area under the curve across 6 conditions. For asthma, chronic kidney disease, congenital heart disease, and hypercholesterolemia, SDOH contributed as much as or more than polygenic scores, and the 2 risk types appeared largely additive, suggesting social interventions can reduce disease risk regardless of a patient’s genetic background.




