{"doi":"10.1002/cncr.33137","title":"Quality of care at safety‐net hospitals and the impact on pay‐for‐performance reimbursement","abstract":"BACKGROUND: Pay-for-performance reimbursement ties hospital payments to standardized quality-of-care metrics. To the authors' knowledge, the impact of pay-for-performance reimbursement models on hospitals caring primarily for uninsured or underinsured patients remains poorly defined. The objective of the current study was to evaluate how standardized quality-of-care metrics vary by a hospital's propensity to care for uninsured or underinsured patients and demonstrate the potential impact that pay-for-performance reimbursement could have on hospitals caring for the underserved. METHODS: The authors identified 1,703,865 patients with cancer who were diagnosed between 2004 and 2015 and treated at 1344 hospitals. Hospital safety-net burden was defined as the percentage of uninsured or Medicaid patients cared for by that hospital, categorizing hospitals into low-burden, medium-burden, and high-burden hospitals. The authors evaluated the impact of safety-net burden on concordance with 20 standardized quality-of-care measures, adjusting for differences in patient age, sex, stage of disease at diagnosis, and comorbidity. RESULTS: Patients who were treated at high-burden hospitals were more likely to be young, male, Black and/or Hispanic, and to reside in a low-income and low-educated region. High-burden hospitals had lower adherence to 13 of 20 quality measures compared with low-burden hospitals (all P < .05). Among the 350 high-burden hospitals, concordance with quality measures was found to be lowest for those caring for the highest percentage of uninsured or Medicaid patients, minority patients, and less educated patients (all P < .001). CONCLUSIONS: Hospitals caring for uninsured or underinsured individuals have decreased quality-of-care measures. Under pay-for-performance reimbursement models, these lower quality-of-care scores could decrease hospital payments, potentially increasing health disparities for at-risk patients with cancer.","journal":"Cancer","year":2020,"id":69898,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":20,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9537,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":369812,"name":"P.T. Courtney","orcid":"0000-0001-7625-3678","position":1,"is_corresponding":false},{"id":370575,"name":"Katie Bachand","orcid":null,"position":2,"is_corresponding":false},{"id":369813,"name":"Paige Sheridan","orcid":"0000-0002-2099-6760","position":3,"is_corresponding":false},{"id":263864,"name":"Paul Riviere","orcid":"0000-0001-7966-3090","position":4,"is_corresponding":false},{"id":370576,"name":"Zachary D. Guss","orcid":null,"position":5,"is_corresponding":false},{"id":370577,"name":"Christian R. Lopez","orcid":null,"position":6,"is_corresponding":false},{"id":369814,"name":"Michael G. Brandel","orcid":"0000-0001-7422-390X","position":7,"is_corresponding":false},{"id":369815,"name":"Matthew P. Banegas","orcid":"0000-0002-6158-7162","position":8,"is_corresponding":false},{"id":263870,"name":"James D. Murphy","orcid":"0000-0002-0523-9091","position":9,"is_corresponding":false},{"id":265416,"name":"Reith Sarkar","orcid":null,"position":0,"is_corresponding":true}],"reference_count":32,"raw_metadata":null,"created_at":"2026-07-18T21:42:48.813846Z","pmid":"32780469","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}