Expert Point of View: Johnie Rose, MD, PhD

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Johnie Rose, MD, PhD

Johnie Rose, MD, PhD

Invited study discussant, Johnie Rose, MD, PhD, called the correlation between Medicaid expansion and changes in 30-day mortality a critical research question. Dr. Rose is Assistant Professor in the Center for Community Health Integration at Case Western Reserve University School of Medicine and Preventive Medicine Residency Program Director at the University Hospitals Cleveland Medical Center.

“Obviously, if our patients don’t survive the first 30 days after surgery, they’re never going to make it to longer-term survivorship,” said Dr. Rose. “If we can mitigate disparities here, we will have gone a very long way.”

Study Strengths

According to Dr. Rose, the strengths of the study include the importance of the topic and the utilization of the National Cancer Database, which captures more than 70% of patients with cancer in the United States. With this comprehensive database, researchers were able to achieve a sample size of nearly 12,000 patients, and they were able to include 10 years of data, he noted.

With a large database analysis, however, there is also the potential for selection bias that comes from the “changing composition of the Medicaid population post-expansion,” Dr. Rose explained.

“Patients in the 90% to 138% of the federal poverty level group who become newly insured in Medicaid-expanding states tend to be largely working, nondisabled adults who have slightly higher income than the original Medicaid population,” said Dr. Rose. “Income matters as an independent risk factor when it comes to 30-day mortality after lung cancer resection.”

Next Step: Stratify by Neighborhood Income Level?

According to Dr. Rose, the relationship between zip code median income and 30-day post-resection mortality was demonstrated in a prior study of patients in the National Cancer Database.1

“A good expansion of this study might be to stratify patients by neighborhood income level,” said Dr. Rose. He added that researchers should consider the probability-weighting method of Kim et al for future work.2

“Large databases are key to understanding disparities in delivery and outcomes, but avoiding selection bias can be an ongoing challenge,” Dr. Rose concluded. “In studies like this, looking at a policy change that impacts people based on socioeconomic status, we need to find better ways to obtain or approximate information about the socioeconomic status of individuals.” 

DISCLOSURE: Dr. Rose reported financial relationships with Vinya Intelligence.


1. Melvan JN, Sancheti MS, Gillespie T, et al: Nonclinical factors associated with 30-day mortality after lung cancer resection: An analysis of 215,000 patients using the National Cancer Data Base. J Am Coll Surg 221:550-563, 2015.

2. Kim U, Koroukian S, Statler A, et al: The effect of Medicaid expansion among adults from low-income communities on stage at diagnosis in those with screening-amenable cancers. Cancer 126:4209-4219, 2020.

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