Evidence map›Paper›PMID 41879763›Full record

ArticleJAMA2026

The Oncology Care Model and Medicare Payments, Utilization, and Quality.

Gabriel A Brooks, Matthew Trombley, Sean McClellan, Qing Zheng, Mary Beth Landrum, Van Doren Hsu, Colleen M Kummet, Pang-Hsiang Liu, Derek Hoodin, Colin Doyle and 2 more

Abstract read
In one paragraph

Article in JAMA, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Gabriel A BrooksDepartment of Medicine, Geisel School of Medicine, Lebanon, New Hampshire.
Matthew TrombleyAbt Global, Cambridge, Massachusetts.
Sean McClellanAbt Global, Cambridge, Massachusetts.
Qing ZhengAbt Global, Cambridge, Massachusetts.
Mary Beth LandrumDepartment of Health Care Policy, Harvard Medical School, Boston, Massachusetts.
Van Doren HsuGeneral Dynamics Information Technology, Falls Church, Virginia.
Colleen M KummetGeneral Dynamics Information Technology, Falls Church, Virginia.
Pang-Hsiang LiuDepartment of Health Care Policy, Harvard Medical School, Boston, Massachusetts.
Derek HoodinAbt Global, Cambridge, Massachusetts.
Colin DoyleThe Lewin Group, Falls Church, Virginia.
Carol SimonThe Lewin Group, Falls Church, Virginia.
Nancy L KeatingDepartment of Health Care Policy, Harvard Medical School, Boston, Massachusetts.

Funding

Translational Engineering in Cancer (TEC)P30CA023108 · NCI · DARTMOUTH COLLEGE · PI Fred W Kolling IV · 1985 to 2026
$91.3M
NCI NIH HHS P30 CA023108
6 · The paper itself

Abstract

Importance: The Oncology Care Model (OCM) was the Centers for Medicare & Medicaid Services' first cancer-focused alternative payment model, running from 2016 to 2022. The OCM aimed to reduce Medicare spending and improve quality of care for patients receiving chemotherapy. Objective: To evaluate the association of the OCM with changes in Medicare spending, utilization, and quality of care. Design, Setting, and Participants: Difference-in-differences (DID) regression analysis of 6-month chemotherapy episodes attributed to practices voluntarily participating in the OCM or propensity-matched comparison practices, adjusted for beneficiary, episode, practice, and regional characteristics. Episodes for fee-for-service Medicare beneficiaries were grouped into baseline (initiated January 2014-January 2016) and intervention (initiated July 2016-June 2022) periods. Main Outcomes and Measures: Total episode payments (Medicare spending for Parts A, B, and D, excluding OCM Monthly Enhanced Oncology Services [MEOS] payments); episode payments for Medicare Parts A, B, and D, hospitalizations, emergency department visits, and measures of quality. Results: The study population included 739 735 Medicare beneficiaries (mean age, 73.2 [SD, 8.6] years; 59.4% female; 1 746 368 episodes) undergoing chemotherapy (ie, traditional cytotoxic therapy, targeted therapy, immunotherapy, and hormonal therapy) at 202 OCM practices and 830 165 beneficiaries (mean age, 73.1 [SD, 8.8] years; 56.6% female; 1 919 516 episodes) at 534 comparison practices. Total episode payments increased from $29 206 (baseline period) to $36 190 (intervention period) for OCM episodes and from $28 788 to $36 388 for comparison episodes, for an OCM-associated spending change of -$616 [90% CI, -$912 to -$321]). Reductions in total episode payments increased over time (-$1282 in the final 6-month performance period). Statistically significant spending reductions were observed for Part A (DID, -$176 [90% CI, -$288 to -$63]) and Part B (DID, -$340 [90% CI, -$529 to -$149]) but not for Part D (DID, -$53 [90% CI, -$216 to $111]). The OCM was not associated with significant differences in hospitalizations, emergency department visits, or quality. Accounting for MEOS payments and performance-based incentive payments, the OCM resulted in an estimated net loss to Medicare of $639 million over 6 years. Conclusions and Relevance: The OCM was associated with modest reductions in Medicare payments during cancer treatment episodes without significant changes in care quality; payment reductions increased during the program's last 3 years. However, the OCM incurred a net loss because these estimated savings were exceeded by enhanced services payments and performance-based payments to practices.

Indexed as

Health ExpendituresMedical OncologyMedicareNeoplasmsQuality of Health CareReimbursement MechanismsAgedAged, 80 and overAntineoplastic AgentsCenters for Medicare and Medicaid Services, U.S.Drug CostsEmergency Service, HospitalFee-for-Service PlansFemaleHospitalizationHumansAntineoplastic Agents

Identifiers

PMID41879763
PMCPMC13019339

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.