Trends in Low-Value Cancer Care During the COVID-19 Pandemic

ABSTRACT

Objective: To assess the association between the onset of the COVID-19 pandemic and change in low-value cancer services.

Study Design: In this retrospective cohort study, we used administrative claims from the HealthCore Integrated Research Environment, a repository of medical and pharmacy data from US health plans representing more than 80 million members, between January 1, 2016, and March 31, 2021.

Methods: We used linear probability models to investigate the relation between the onset of the COVID-19 pandemic and 4 guideline-based metrics of low-value cancer care: (1) conventional fractionation radiotherapy instead of hypofractionated radiotherapy for early-stage breast cancer; (2) non–guideline-based antiemetic use for minimal-, low-, or moderate- to high-risk chemotherapies; (3) off-pathway systemic therapy; and (4) aggressive end-of-life care. We identified patients with new diagnoses of breast, colorectal, and/or lung cancer. We excluded members who did not have at least 6 months of continuous insurance coverage and members with prevalent cancers.

Results: Among 117,116 members (median [IQR] age, 60 [53-69] years; 72.4% women), 59,729 (51.0%) had breast cancer, 25,751 (22.0%) had colorectal cancer, and 31,862 (27.2%) had lung cancer. The payer mix was 18.7% Medicare Advantage or Medicare supplemental and 81.2% commercial non-Medicare. Rates of low-value cancer services exhibited minimal changes during the pandemic, as adjusted percentage-point differences were 3.93 (95% CI, 1.50-6.36) for conventional radiotherapy, 0.82 (95% CI, –0.62 to 2.25) for off-pathway systemic therapy, –3.62 (95% CI, –4.97 to –2.27) for non–guideline-based antiemetics, and 2.71 (95% CI, –0.59 to 6.02) for aggressive end-of-life care.

Conclusions: Low-value cancer care remained prevalent throughout the pandemic. Policy makers should consider changes to payment and incentive design to turn the tide against low-value cancer care.

Am J Manag Care. 2024;30(4):186-190. https://doi.org/10.37765/ajmc.2024.89530

Takeaway Points

Among adults with newly diagnosed cancer, rates of low-value cancer services persisted throughout the COVID-19 pandemic in areas ranging from peridiagnosis imaging to end-of-life care.

• Educational campaigns and payment reforms, including the Center for Medicare and Medicaid Innovation Oncology Care Model, have had limited success in curbing low-value cancer care.
• The COVID-19 pandemic caused a dramatic decrease in health care utilization, leading many to suspect that low-value cancer services would decrease.
• We found that low-value care in areas ranging from cancer treatment to supportive care to end-of-life care remained stubbornly high even during the height of stay-at-home orders in the US.
• Policy makers should consider more targeted changes to payment and incentive design to turn the tide against low-value cancer care.

Low-value health care services confer costs and risks to patients that exceed the services’ benefits.¹ The importance of low-value services in US health care has been demonstrated by several lines of research outside of cancer care, and low-value health care has been a frequent target of performance-based measures from alternative payment models.^2-4 Study findings have demonstrated how specific tests or treatments fail to produce health gains warranting their costs or adverse events; many such services have been highlighted by medical specialty societies through the Choosing Wisely initiative.⁵

Low-value services are prevalent in cancer care, with rates of certain metrics such as bone scans in low-risk prostate cancer and tumor markers in nonmetastatic breast cancer reaching over 50%.⁶ In 2020, the onset of the COVID-19 pandemic caused a dramatic shift in cancer care delivery in an effort to reduce the risks of exposing patients with cancer to health care settings.⁷ During this period of disruption, health systems and clinicians may have seized the opportunity to reduce the use of lower-value services because of the potential for increased visits and hospitalizations to spread the virus among vulnerable populations.⁸ Alternatively, clinicians may have preferred to use more low-value therapeutics—including off-pathway supportive care medications and systemic therapies—to avoid patients receiving clinic-based infusion therapy. However, prior evidence suggests considerable avoidance of cancer therapy during the pandemic with relatively minimal transition to oral chemotherapies, arguing against this hypothesis.^9,10

We investigated the relationship between the onset of the COVID-19 pandemic and changes in several metrics of low-value cancer care. We hypothesized that the COVID-19 pandemic resulted in decreased provision of low-value cancer care. We assumed that health systems and patients would have sought to minimize potential COVID-19 exposure for vulnerable patients with cancer and thus decreased utilization of services that may have been unnecessary during the pandemic. Furthermore, we would expect that any practice changes induced by the pandemic would be magnified among low-value practices, which may be marginal and thus more likely to change. We define low-value care using population-based metrics based on clinical guidelines, as per other studies outside of cancer care.^11,12

METHODS

Design

This retrospective cohort study examined trends in low-value care metrics for patients with cancer using a large database of commercial insurance claims. The study was exempt from the University of Pennsylvania’s institutional review board approval because it involved a limited study database with masked identifiers.

Data Sources

We used administrative claims and health plan enrollment data from the HealthCore Integrated Research Environment for information on diagnoses, use of cancer treatment, costs, comorbidities, and rendering of clinician identifiers. The HealthCore Integrated Research Environment is a repository of medical and pharmacy claims data for approximately 80 million geographically diverse members enrolled in individual, employer-sponsored, and Medicare Advantage plans starting in 2006. In 2016, the HealthCore Integrated Research Environment covered 6.6% of adults 20 years or older in the US.

Study Sample

We identified enrollees in the health plans who were 18 years or older in fully insured or self-insured plans and who had received a new diagnosis of breast, colorectal, or lung cancer between January 1, 2016, and March 31, 2021. We identified new cancer cases using International Classification of Diseases, Ninth Revision or International Statistical Classification of Diseases, Tenth Revision diagnosis codes for breast, colorectal, or lung cancer (see eAppendix Table 1 [eAppendix available at ajmc.com] for all diagnostic and procedure codes). We required members to have at least 6 months of continuous insurance coverage prior to their initial cancer diagnosis date. We excluded individuals with cancers that had been previously diagnosed because it is difficult to ascertain the prevalence of low-value cancer care practices across a heterogeneous cohort that may have received previous lines of therapy and are at different points in their cancer course. To exclude prevalent cancers and isolate incident cases, we excluded individuals who had any diagnosis code for an eligible cancer in the 6 months prior to incident index cancer diagnosis between 2016 and 2021. We further identified eligible populations for each low-value care outcome analysis as per published guidelines (eAppendix Tables 1 and 2) such that each analysis for each low-value care outcome contained a different denominator of eligible patients. Baseline patient characteristics were measured during the 6-month period prior to diagnosis.

Low-Value Care Outcomes

The primary outcome for all analyses was receipt of low-value cancer care, defined as the percentage of eligible patients per period who received a low-value service. Although there are no consensus definitions of low-value care in oncology care, we included published metrics from guideline bodies or peer-reviewed literature. These measures spanned across the cancer care continuum, from diagnosis to treatment to survivorship and end of life. We intentionally did not include metrics of cancer screening because the pandemic’s impact on a decline in cancer screening has been well described.^13,14 Low-value care measures were identified from the American Society of Clinical Oncology and American Society for Radiation Oncology Choosing Wisely campaigns,^15,16 the Hutchinson Institute for Cancer Outcomes Research,¹⁷ Anthem’s Cancer Care Quality Program treatment pathways,¹⁸ National Comprehensive Cancer Network guidelines,¹⁹ and peer-reviewed literature on low-value antiemetic use.²⁰ We defined 4 measures of low-value cancer care spanning the cancer care continuum (eAppendix Table 2): (1) conventional fractionation radiotherapy instead of hypofractionated radiotherapy for early-stage breast cancer only¹⁵; (2) non–guideline-based antiemetic use for minimal-, low-, or moderate- to high-risk chemotherapies across breast, colorectal, and lung cancers^16,19,20; (3) off-pathway systemic therapy across breast, colorectal, and lung cancers¹⁸; and (4) aggressive end-of-life care (chemotherapy in the last 14 days of life, multiple emergency department visits in the last 30 days of life, intensive care unit utilization in the last 30 days of life, hospice initiation ≤ 3 days before death, and/or no hospice care receipt before death) across breast, colorectal, and lung cancers.¹⁷ We intentionally chose measures of low-value care that involved both additional health care encounters (eg, conventional radiotherapy, aggressive end-of-life care) and selection of lower-value diagnostics or treatment without increased encounters (eg, low-value antiemetics, off-pathway systemic therapy). We hypothesized that metrics reflecting increased encounters would disproportionately decrease, compared with other low-value metrics, during the pandemic.

Covariates

We collected covariates for statistical adjustment including sex (male vs female), age in years, Deyo-Charlson Comorbidity Index score, insurance type (Medicare Advantage, Medicare supplemental, commercial), geographic region (Northeast, Midwest, South, West), urban vs rural domicile, and area-level socioeconomic status. Area-level socioeconomic status was specified as first quartile (lowest) to fourth quartile (highest) based on validated socioeconomic indicators such as median home value, median family income, the ratio of population below poverty, ratios of the population with less than high school education and at least 4 years of college, and unemployment rates, as developed by the Agency for Healthcare Research and Quality and applied to American Community Survey data.²¹ For the conventional radiotherapy outcome, additional covariates (based on a prior study²²) included service-site facility (office vs outpatient facility), county-level radiation oncologist density, and a post-2018 indicator because the American Society for Radiation Oncology released guidance recommending hypofractionated radiotherapy for all patients with early-stage breast cancer at that time.

Statistical Analysis

To verify the disruption in cancer care induced by the pandemic in this sample, we first described trends in cancer diagnosis rates. Linear probability models applied to patient-month–level data were then used to evaluate the association of the COVID-19 period with each of the 4 low-value outcomes. The COVID-19 period was defined as March 2020 to December 2020 due to the initiation of many state stay-at-home orders in March 2020. All analyses included a month fixed effect to account for seasonality and a linear time trend to account for secular changes in the outcome over time and were adjusted for the above covariates. Linear time trends were defined as the month entering the regressions (eg, month 1, 2, 3, etc), and we controlled for differential trends in the pre–COVID-19 and COVID-19 periods. The key regression terms of interest were an indicator for the COVID-19 period and an interaction between that indicator and a linear time trend. After conducting each linear regression model, we used the Stata margins command to calculate the marginal effect of the COVID-19 period; these calculated marginal effects provide adjusted estimates that incorporate both changes in the outcome level and changes in the linear temporal trend in the outcome during the COVID-19 period. All analyses were conducted using Stata 16.1 (StataCorp LLC). Statistical significance was set at .05, and all tests were 2-sided.

RESULTS

Among 117,116 members (median [IQR] age, 60 [53-69] years; 72.4% women), 59,729 (51.0%) had breast cancer, 25,751 (22.0%) had colorectal cancer, and 31,862 (27.2%) had lung cancer (Table 1). The payer mix was 18.7% Medicare Advantage or Medicare supplemental and 81.2% commercial non-Medicare. We observed an initial steep decline in overall cancer diagnosis rates at the start of the COVID-19 pandemic for all cancers that returned to baseline (eAppendix Figure). In unadjusted analyses, rates of low-value cancer care in the pre–COVID-19 vs COVID-19 periods were 22.1% vs 9.4% for conventional fractionation radiotherapy (n = 12,213), 61.2% vs 58.1% for non–guideline-based antiemetics (n = 81,315), 36.7% vs 43.2% for off-pathway systemic therapy (n = 41,487), and 75.7% vs 73.3% for aggressive end-of-life care (n = 21,662) (Figure). In adjusted analyses, the COVID-19 period, relative to the pre–COVID-19 period, was not associated with significant changes in off-pathway systemic therapy (adjusted percentage-point difference, 0.82; 95% CI, –0.62 to 2.25; P = .262) and aggressive end-of-life care (adjusted percentage-point difference, 2.71; 95% CI, –0.59 to 6.02; P = .108) (Table 2). The COVID-19 period was associated with an increase in conventional radiotherapy (adjusted percentage-point difference, 3.93; 95% CI, 1.50-6.36; P = .002) and a decrease in non–guideline-based antiemetics (adjusted percentage-point difference, –3.62; 95% CI, –4.97 to –2.27; P < .001).

DISCUSSION

Among adults with breast, colorectal, or lung cancer, the onset of the COVID-19 pandemic was not associated with consistent changes in low-value cancer care. Rates of low-value cancer services persisted throughout the pandemic. Importantly, utilization-related metrics (conventional radiation, aggressive end-of-life care) did not show declines compared with metrics other than utilization that reflected discretionary care decisions (eg, non–guideline-based antiemetics). Indeed, conventional radiation had a strong declining secular trend prior to the pandemic that appeared to plateau during the pandemic.

Prepandemic evidence suggests substantial physician variation in low-value practice patterns among both primary care and oncology clinicians.^11,23,24 Our study results suggest that pandemic-related guidance to avoid unnecessary health care visits did not change low-value practice patterns of oncology clinicians. This is in line with prior evidence from smaller, limited-institution studies not focusing on cancer, which suggests that pandemic-related disruptions did not meaningfully change metrics of hospice utilization near patients’ end of life.²⁵ Of note, findings from a national study among Medicare beneficiaries in 2020 showed some decreases in low-value cancer screening but increases in low-value opioid use—thus representing an inconsistent effect.²⁶ Another national study of several low-value care practices outside of oncology care found a sharp decline in April 2020 that normalized by the end of 2020, in line with the findings of this study.²⁷ Our study’s results run counter to prevailing notions that the utilization shock induced by the pandemic would disproportionately decrease low-value services.^7,8 Indeed, both low-value and non–low-value cancer services may have decreased proportionately during the pandemic. Additionally, we have previously demonstrated that, despite clinical guidelines suggesting avoidance of discretionary infusion-based therapies during the pandemic, the prevalence of transitions from infusion or injection therapies to oral therapies was minimal.¹⁰ It is possible that utilization declines were countered by practices intentionally increasing low-value services to mitigate revenue losses during the pandemic; future studies should investigate this troubling possibility. Of note, although the pandemic was associated with statistically significant changes in 2 low-value metrics (conventional radiotherapy, non–guideline-based antiemetics), the changes were less than 5 percentage points in absolute value and were relatively low compared with the underlying prevalence of low-value care for each of these metrics; furthermore, these do not represent consistent effects, and thus we interpret these findings as not clinically impactful.

Oncology is a particular target of insurers’ efforts to curb expensive and potentially unnecessary health care services.²⁸ By definition, low-value cancer care may pose additional costs and harms—including high out-of-pocket spending, medication adverse events, and care inconsistent with patient goals—to patients and the health care system, without meaningful benefits in patient outcomes. Thus, curbing low-value care represents an important policy priority given efforts to limit the costs of cancer care.Our study has implications for future strategies to curb low-value cancer care in oncology and beyond. Educational efforts, such as the American Board of Internal Medicine Choosing Wisely campaign, and broad-based payment reform, including the Center for Medicare and Medicaid Innovation Oncology Care Model, have had limited success in substantially curbing low-value cancer care.^29-31 Given that rates of low-value cancer care were persistently high through a massive health care disruption such as the COVID-19 pandemic, it is clear that low-value care is a persistent and difficult problem.

Limitations

There are several limitations to our analysis. Claims-based analyses are unable to account for unmeasured patient-, provider-, practice-, or system-related factors that, if associated with the COVID-19 pandemic, may have influenced our results. Thus, other factors may have affected rates of low-value cancer care during the study period, although our analytic approach accounted for observed confounders, temporal trends, and unobserved confounders that were stable over time. Additionally, there is no consensus definition of low-value cancer care metrics after the point of cancer screening. Although we chose several metrics that spanned the cancer care continuum, our selected metrics were not exhaustive. Greater efforts to define low-value cancer care practices are necessary. Finally, it is possible that certain low-value metrics such as low-value antiemetic use may be prone to measurement error because claims lack information on chemotherapy dosing. However, we assume that any measurement error would be constant across time and not affected by COVID-19 such that comparing rates post COVID-19 with those before COVID-19 would still be valid.

CONCLUSIONS

Low-value cancer care remained prevalent throughout the pandemic. Policy makers should consider changes to payment and incentive design to turn the tide against low-value cancer care.

Acknowledgments

The authors acknowledge Jay Fein, BA, for assistance in preparing this manuscript for publication.

Author Affiliations: Departments of Medicine and Medical Ethics and Health Policy (RBP, JEB, ALS) and Penn Center for Cancer Care Innovation (RBP, JEB), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA; HealthCore Inc (YC, PO, GS), Wilmington, DE; Elevance Health (DD), Indianapolis, IN; AIM Specialty Health (MJF), Chicago, IL.

Source of Funding: National Cancer Institute grant K08CA263541 to RBP. The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Author Disclosures: Dr Civelek and Dr Ozluk are employed by HealthCore. Dr Debono is employed by Elevance Health. Dr Fisch is employed by AIM Specialty Health. Ms Sylwestrzak is employed by Humana. The remaining authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Authorship Information: Concept and design (RBP, YC, JEB, ALS); acquisition of data (RBP, YC, PO, GS, JEB, ALS); analysis and interpretation of data (RBP, YC, PO, GS, JEB, ALS); drafting of the manuscript (RBP, YC, GS, JEB, ALS); critical revision of the manuscript for important intellectual content (YC, PO, DD, MJF); statistical analysis (RBP, YC, PO, GS, JEB, ALS); provision of patients or study materials (RBP, YC, PO, DD, MJF, GS, JEB, ALS); obtaining funding (RBP, YC, JEB, ALS); and administrative, technical, or logistic support (RBP, YC, PO, DD, MJF, JEB, ALS).

Address Correspondence to: Ravi B. Parikh, MD, MPP, University of Pennsylvania, 423 Guardian Dr, Blockley 1102, Philadelphia, PA 19104. Email: ravi.parikh@pennmedicine.upenn.edu.

REFERENCES

1. Korenstein D, Falk R, Howell EA, Bishop T, Keyhani S. Overuse of health care services in the United States: an understudied problem. Arch Intern Med. 2012;172(2):171-178. doi:10.1001/archinternmed.2011.772

2. Song Z, Ji Y, Safran DG, Chernew ME. Health care spending, utilization, and quality 8 years into global payment. N Engl J Med. 2019;381(3):252-263. doi:10.1056/NEJMsa1813621

3. Newhouse JP; Insurance Experiment Group. Free for All? Lessons From the RAND Health Insurance Experiment. Harvard University Press; 1993. Accessed December 22, 2022. https://www.rand.org/pubs/commercial_books/CB199.html

4. Skinner J. Causes and consequences of regional variations in health care. In: Pauly MV, Mcguire TG, Barros PP, eds. Handbook of Health Economics. Vol 2. Elsevier; 2011:45-93. Accessed December 22, 2022. https://www.sciencedirect.com/science/article/pii/B9780444535924000025

5. Choosing Wisely: five things physicians and patients should question. News release. Choosing Wisely. April 4, 2012. Accessed December 22, 2022. https://web.archive.org/web/20221006083425/https:/www.choosingwisely.org/choosing-wisely-five-things-physicians-and-patients-should-question-press-release-april-4-2012/

6. Baxi SS, Kale M, Keyhani S, et al. Overuse of health care services in the management of cancer: a systematic review. Med Care. 2017;55(7):723-733. doi:10.1097/MLR.0000000000000734

7. Gyawali B, Poudyal BS, Eisenhauer EA. Covid-19 pandemic—an opportunity to reduce and eliminate low-value practices in oncology? JAMA Oncol. 2020;6(11):1693-1694. doi:10.1001/jamaoncol.2020.2404

8. Oakes AH, Segal JB. The COVID-19 pandemic can help us understand low-value health care. Health Affairs Forefront. October 27, 2020. Accessed March 1, 2022. https://www.healthaffairs.org/do/10.1377/forefront.20201023.522078/full/

9. Lang JJ, Narendrula A, Iyer S, et al. Patient-reported disruptions to cancer care during the COVID-19 pandemic: a national cross-sectional study. Cancer Med. 2023;12(4):4773-4785. doi:10.1002/cam4.5270

10. Parikh RB, Takvorian SU, Vader D, et al; PRACTICE Investigators. Impact of the COVID-19 pandemic on treatment patterns for patients with metastatic solid cancer in the United States. J Natl Cancer Inst. 2022;114(4):571-578. doi:10.1093/jnci/djab225

11. Schwartz AL, Jena AB, Zaslavsky AM, McWilliams JM. Analysis of physician variation in provision of low-value services. JAMA Intern Med. 2019;179(1):16-25. doi:10.1001/jamainternmed.2018.5086

12. Schwartz AL, Chernew ME, Landon BE, McWilliams JM. Changes in low-value services in year 1 of the Medicare Pioneer Accountable Care Organization program. JAMA Intern Med. 2015;175(11):1815-1825. doi:10.1001/jamainternmed.2015.4525

13. Croswell JM, Corley DA, Lafata JE, et al; National Cancer Institute Population-based Research to Optimize the Screening Process (PROSPR) II Consortium. Cancer screening in the U.S. through the COVID-19 pandemic, recovery, and beyond. Prev Med. 2021;151:106595. doi:10.1016/j.ypmed.2021.106595

14. Patt D, Gordan L, Diaz M, et al. Impact of COVID-19 on cancer care: how the pandemic is delaying cancer diagnosis and treatment for American seniors. JCO Clin Cancer Inform. 2020;4:1059-1071. doi:10.1200/CCI.20.00134

15. Hahn C, Kavanagh B, Bhatnagar A, et al. Choosing wisely: the American Society for Radiation Oncology’s top 5 list. Pract Radiat Oncol. 2014;4(6):349-355. doi:10.1016/j.prro.2014.06.003

16. American Society of Clinical Oncology. Ten things physicians and patients should question. Choosing Wisely. Updated July 26, 2021. Accessed July 15, 2022. https://web.archive.org/web/20220704145358/https:/www.choosingwisely.org/societies/american-society-of-clinical-oncology/

17. Hutchinson Institute for Cancer Outcomes Research. Community Cancer Care in Washington State: Quality and Cost Report 2021. Fred Hutchinson Cancer Research Center; 2021. Accessed January 17, 2022. https://www.fredhutch.org/content/dam/www/research/institute-networks-ircs/hicor/HICOR-Community-Cancer-Care-Report-2021.pdf

18. Bekelman JE, Gupta A, Fishman E, et al. Association between a national insurer’s pay-for-performance program for oncology and changes in prescribing of evidence-based cancer drugs and spending. J Clin Oncol. 2020;38(34):4055-4063. doi:10.1200/JCO.20.00890

19. Berger MJ, Ettinger DS, Aston J, et al. NCCN Guidelines insights: antiemesis, version 2.2017. J Natl Compr Canc Netw. 2017;15(7):883-893. doi:10.6004/jnccn.2017.0117

20. Encinosa W, Davidoff AJ. Changes in antiemetic overuse in response to Choosing Wisely recommendations. JAMA Oncol. 2017;3(3):320-326. doi:10.1001/jamaoncol.2016.2530

21. Agency for Healthcare Research and Quality. Creation of New Race-Ethnicity Codes and Socioeconomic Status (SES) Indicators for Medicare Beneficiaries: Final Report. CreateSpace Independent Publishing Platform; 2017.

22. Parikh RB, Fishman E, Chi W, et al. Association of utilization management policy with uptake of hypofractionated radiotherapy among patients with early-stage breast cancer. JAMA Oncol. 2020;6(6):839-846. doi:10.1001/jamaoncol.2020.0449

23. Obermeyer Z, Powers BW, Makar M, Keating NL, Cutler DM. Physician characteristics strongly predict patient enrollment in hospice. Health Aff (Millwood). 2015;34(6):993-1000. doi:10.1377/hlthaff.2014.1055

24. Lipitz-Snyderman A, Sima CS, Atoria CL, et al. Physician-driven variation in nonrecommended services among older adults diagnosed with cancer. JAMA Intern Med. 2016;176(10):1541-1548. doi:10.1001/jamainternmed.2016.4426

25. Sarkar A, Parulekar M, Sanders A. Impact of COVID-19 pandemic on utilization of the inpatient hospice services (general inpatient hospice). Am J Hosp Palliat Care. 2022;39(8):996-1000. doi:10.1177/10499091211064833

26. Levine DM, Samal L, Neville BA, et al. The association of the first surge of the COVID-19 pandemic with the high- and low-value outpatient care delivered to adults in the USA. J Gen Intern Med. 2022;37(15):3979-3988. doi:10.1007/s11606-022-07757-1

27. Shahzad M, Song Z, Chernew ME, Fendrick AM. Changes in use of low-value services during the COVID-19 pandemic. Am J Manag Care. 2022;28(11):600-604. doi:10.37765/ajmc.2022.89031

28. Schwartz AL, Brennan TA, Verbrugge DJ, Newhouse JP. Measuring the scope of prior authorization policies: applying private insurer rules to Medicare Part B. JAMA Health Forum. 2021;2(5):e210859. doi:10.1001/jamahealthforum.2021.0859

29. Keating NL, Jhatakia S, Brooks GA, et al; Oncology Care Model Evaluation Team. Association of participation in the Oncology Care Model with Medicare payments, utilization, care delivery, and quality outcomes. JAMA. 2021;326(18):1829-1839. doi:10.1001/jama.2021.17642

30. Kapadia NS, Brooks GA, Landrum MB, et al. Association of the Oncology Care Model with value-based changes in use of radiation therapy. Int J Radiat Oncol Biol Phys. 2022;114(1):39-46. doi:10.1016/j.ijrobp.2022.01.044

31. Brooks GA, Landrum MB, Kapadia NS, et al. Impact of the Oncology Care Model on use of supportive care medications during cancer treatment. J Clin Oncol. 2022;40(16):1763-1771. doi:10.1200/JCO.21.02342