{"doi":"10.21037/jhmhp.2020.01.02","title":"Estimating hospitals’ all-payer volume of cancer surgeries from Fee-for-Service Medicare claims","abstract":"Background: Despite prior research establishing a relationship between volume and outcomes in certain surgical procedures for cancer, there is still no comprehensive national resource reporting hospital cancer surgical volume publicly. We evaluated whether Fee-for-service (FFS) Medicare claims data is representative of hospital all-payer cancer surgery volume and whether we could leverage the data to accurately predict hospital all-payer volume. Methods: We utilized FFS Medicare claims data matched to state inpatient discharge data by hospital for six states and identified cancer-directed surgeries between 2011 and 2013. We first evaluated the representativeness of FFS Medicare of all-payer volume by inspecting scatterplots and calculating correlations. We additionally assessed the change in quartile rank when classifying hospitals by FFS Medicare as compared to all-payer volume. Second, we developed a model to predict all-payer volume from FFS Medicare volume and other possible predictors. Results: There is a positive correlation between FFS Medicare and all-payer volume for cancer-directed surgeries (r=0.92). When considering hospitals FFS Medicare and all-payer volume quartile ranks, most did not change quartiles (71.2%) or moved only one quartile (27%). In using our model to predict hospital volume, the correlation was high between the predicted and observed all-payer volume (r=0.92). However, the average difference between predicted and observed volume was 42.0 (standard deviation 67.0) and was less accurate for low-volume hospitals. Conclusions: Our study found support that FFS Medicare volume is representative of all-payer volume. However, estimates of all-payer volume using FFS Medicare data may be less accurate for low volume hospitals.","journal":"Journal of Hospital Management and Health Policy","year":2020,"id":116610,"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":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.8606,"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":268585,"name":"Jessica A. Lavery","orcid":"0000-0002-2746-5647","position":1,"is_corresponding":false},{"id":316498,"name":"Katherine S. Panageas","orcid":"0000-0002-6591-604X","position":2,"is_corresponding":false},{"id":484813,"name":"Peter B. Bach","orcid":"0000-0001-5175-402X","position":3,"is_corresponding":false},{"id":454514,"name":"Allison Lipitz‐Snyderman","orcid":"0000-0003-2423-2220","position":4,"is_corresponding":false},{"id":533604,"name":"Diane G. Li","orcid":"0000-0001-8050-0918","position":0,"is_corresponding":true}],"reference_count":11,"raw_metadata":null,"created_at":"2026-07-18T23:13:44.286758Z","pmid":null,"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":[]}