ACA Medicaid expansion association with racial disparity reductions in timely cancer treatment

Adamson, Blythe; Cohen, Aaron B.; Gross, Cary P.; Estévez, Melissa; Magee, Kelly; Williams, Erin R.; Davidoff, Amy J.

doi:10.37765/ajmc.2021.88700

Cited by 19 publications

(6 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“… 13 , 28 While many factors may mediate this disparity, formerly incarcerated individuals are often uninsured, due in part to suspension or cancelation of Medicaid enrollment upon incarceration, barriers to re‐enrollment upon release, and strict eligibility criteria, particularly in states that have not expanded Medicaid. 30 , 31 As studies have demonstrated that improved access to Medicaid reduces cancer mortality and reduces racial disparities in time to treatment in the community, 32 , 33 research is needed to determine how state polices on Medicaid enrollment and post‐release healthcare transitions may influence disparities in cancer mortality for formerly incarcerated individuals compared to incarcerated and never‐incarcerated individuals.…”

Section: Discussionmentioning

confidence: 99%

Disparities in cancer prevalence, incidence, and mortality for incarcerated and formerly incarcerated patients: A scoping review

2021

View full text Add to dashboard Cite

Background Racial and ethnic minority status, structural racism, low educational attainment, and poverty are consistently associated with cancer disparities and with higher rates of incarceration. The objective of this scoping review is to conduct a qualitative synthesis of the literature on cancer prevalence, incidence, mortality, and disparities in these outcomes for incarcerated and formerly incarcerated patients, as this literature is fragmented and heterogenous. Methods This scoping review included Bureau of Justice Statistics reports and searched PubMed in May 2021 for all English language studies published between 1990 and 30 April 2021, that reported on cancer prevalence, incidence, or mortality for incarcerated or formerly incarcerated individuals in the United States. Results Twenty studies were selected. Data on cancer prevalence and incidence were scarce but suggested that incarcerated and formerly incarcerated patients have a similar overall risk of cancer diagnosis as the general population, but elevated risk of certain cancers such as cervical, lung, colorectal, and hepatocellular carcinoma for which effective prevention and screening interventions exist. Cancer mortality data in state and local jails as well as prisons were robust and suggests that both incarcerated and formerly incarcerated patients have higher cancer mortality than the general population. Conclusions Incarcerated and formerly incarcerated patients likely have a higher risk of dying from cancer than the general population, but important gaps in our knowledge about the extent and drivers of disparities for this population remain. Additional research is needed to guide interventions to reduce cancer disparities for patients experiencing incarceration.

show abstract

Section: Discussionmentioning

confidence: 99%

Disparities in cancer prevalence, incidence, and mortality for incarcerated and formerly incarcerated patients: A scoping review

2021

View full text Add to dashboard Cite

show abstract

“…Reflecting the importance of timely cancer treatment and its contribution to health disparities, certain accrediting organizations now consider it a quality metric, [12][13][14] and investigators have also used it as an outcome to evaluate policy interventions. 9,15 Accurately determining which patients are at risk for treatment delays may facilitate timely and effective interventions. While care coordination and patient navigation services may improve the timeliness of cancer treatment, 7,16,17 these interventions are resource intensive.…”

Section: Introductionmentioning

confidence: 99%

“…Thus, the factors contributing to delays are nuanced, multilevel, and often influenced not only by clinical factors, but social determinants of health (SDOH). Reflecting the importance of timely cancer treatment and its contribution to health disparities, certain accrediting organizations now consider it a quality metric, and investigators have also used it as an outcome to evaluate policy interventions …”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Development of a Multilevel Model to Identify Patients at Risk for Delay in Starting Cancer Treatment

et al. 2023

View full text Add to dashboard Cite

ImportanceDelays in starting cancer treatment disproportionately affect vulnerable populations and can influence patients’ experience and outcomes. Machine learning algorithms incorporating electronic health record (EHR) data and neighborhood-level social determinants of health (SDOH) measures may identify at-risk patients.ObjectiveTo develop and validate a machine learning model for estimating the probability of a treatment delay using multilevel data sources.Design, Setting, and ParticipantsThis cohort study evaluated 4 different machine learning approaches for estimating the likelihood of a treatment delay greater than 60 days (group least absolute shrinkage and selection operator [LASSO], bayesian additive regression tree, gradient boosting, and random forest). Criteria for selecting between approaches were discrimination, calibration, and interpretability/simplicity. The multilevel data set included clinical, demographic, and neighborhood-level census data derived from the EHR, cancer registry, and American Community Survey. Patients with invasive breast, lung, colorectal, bladder, or kidney cancer diagnosed from 2013 to 2019 and treated at a comprehensive cancer center were included. Data analysis was performed from January 2022 to June 2023.ExposuresVariables included demographics, cancer characteristics, comorbidities, laboratory values, imaging orders, and neighborhood variables.Main Outcomes and MeasuresThe outcome estimated by machine learning models was likelihood of a delay greater than 60 days between cancer diagnosis and treatment initiation. The primary metric used to evaluate model performance was area under the receiver operating characteristic curve (AUC-ROC).ResultsA total of 6409 patients were included (mean [SD] age, 62.8 [12.5] years; 4321 [67.4%] female; 2576 [40.2%] with breast cancer, 1738 [27.1%] with lung cancer, and 1059 [16.5%] with kidney cancer). A total of 1621 (25.3%) experienced a delay greater than 60 days. The selected group LASSO model had an AUC-ROC of 0.713 (95% CI, 0.679-0.745). Lower likelihood of delay was seen with diagnosis at the treating institution; first malignant neoplasm; Asian or Pacific Islander or White race; private insurance; and lacking comorbidities. Greater likelihood of delay was seen at the extremes of neighborhood deprivation. Model performance (AUC-ROC) was lower in Black patients, patients with race and ethnicity other than non-Hispanic White, and those living in the most disadvantaged neighborhoods. Though the model selected neighborhood SDOH variables as contributing variables, performance was similar when fit with and without these variables.Conclusions and RelevanceIn this cohort study, a machine learning model incorporating EHR and SDOH data was able to estimate the likelihood of delays in starting cancer therapy. Future work should focus on additional ways to incorporate SDOH data to improve model performance, particularly in vulnerable populations.

show abstract

“… 16 , 17 In the metastatic setting, Medicaid expansion under the ACA was associated with decreased racial disparities for timely initiation of systemic therapy. 18 One theory is that the ACA would disproportionately benefit non‐White patients who were uninsured, increasing their access to care through Medicaid. However, the impact of the ACA on timely access to prostate cancer care is unclear, particularly as patients with Medicaid more frequently encounter providers who refuse to accept their insurance.…”

Section: Introductionmentioning

confidence: 99%

Disparities in time to prostate cancer treatment initiation before and after the Affordable Care Act

et al. 2023

View full text Add to dashboard Cite

BackgroundDelayed access to care may contribute to disparities in prostate cancer (PCa). The Affordable Care Act (ACA) aimed at increasing access and reducing healthcare disparities, but its impact on timely treatment initiation for PCa men is unknown.MethodsMen with intermediate‐ and high‐risk PCa diagnosed 2010–2016 and treated with curative surgery or radiotherapy were identified in the National Cancer Database. Multivariable logistic regression modeled the effect of race and insurance type on treatment delay >180 days after diagnosis. Cochran–Armitage test measured annual trends in delays, and joinpoint regression assessed if 2014, the year the ACA became fully operationalized, was significant for inflection in crude rates of major delays.ResultsOf 422,506 eligible men, 18,720 (4.4%) experienced >180‐day delay in treatment initiation. Compared to White patients, Black (OR 1.79, 95% CI 1.72–1.87, p < 0.001) and Hispanic (OR 1.37, 95% CI 1.28–1.48, p < 0.001) patients had higher odds of delay. Compared to uninsured, those with Medicaid had no difference in odds of delay (OR 0.94, 95% CI 0.84–1.06, p = 0.31), while those with private insurance (OR 0.57, 95% CI 0.52–0.63, p < 0.001) or Medicare (OR 0.64, 95% CI 0.58–0.70, p < 0.001) had lower odds of delay. Mean time to treatment significantly increased from 2010 to 2016 across all racial/ethnic groups (trend p < 0.001); 2014 was associated with a significant inflection for increase in rates of major delays.ConclusionsNon‐White and Medicaid‐insured men with localized PCa are at risk of treatment delays in the United States. Treatment delays have been consistently rising, particularly after implementation of the ACA.

show abstract

ACA Medicaid expansion association with racial disparity reductions in timely cancer treatment

Cited by 19 publications

References 0 publications

Disparities in cancer prevalence, incidence, and mortality for incarcerated and formerly incarcerated patients: A scoping review

Disparities in cancer prevalence, incidence, and mortality for incarcerated and formerly incarcerated patients: A scoping review

Development of a Multilevel Model to Identify Patients at Risk for Delay in Starting Cancer Treatment

Disparities in time to prostate cancer treatment initiation before and after the Affordable Care Act

Contact Info

Product

Resources

About