{"doi":"10.1111/1475-6773.13622","title":"Identifying outlier patterns of inconsistent ambulance billing in Medicare","abstract":"OBJECTIVE: To illustrate a method that accounts for sampling variation in identifying suppliers and counties with outlying rates of a particular pattern of inconsistent billing for ambulance services to Medicare. DATA SOURCES: US Medicare claims for a 20% simple random sample of 2010-2014 fee-for-service beneficiaries. STUDY DESIGN: We identified instances in which ambulance suppliers billed Medicare for transporting a patient to a hospital, but no corresponding hospital visit appeared in billing claims. We estimated the distributions of outlier supplier and county rates of such \"ghost rides\" by fitting a nonparametric empirical Bayes model with flexible distributional assumptions to account for sampling variation. DATA COLLECTION: We included Basic and advanced life support ground emergency ambulance claims with a hospital destination. PRINCIPAL FINDINGS: \"Ghost ride\" rates varied considerably across both ambulance suppliers and counties. We estimated 6.1% of suppliers and 5.0% of counties had rates that exceeded 3.6%, which was twice the national average of \"ghost rides\" (1.8% of all ambulance transports). CONCLUSIONS: Health care fraud and abuse are frequently asserted but can be difficult to detect. Our data-driven approach may be a useful starting point for further investigation.","journal":"Health Services Research","year":2021,"id":202073,"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":6,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.772,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":281055,"name":"Anupam B. Jena","orcid":"0000-0002-9734-5122","position":1,"is_corresponding":false},{"id":390981,"name":"Joseph P. Newhouse","orcid":"0000-0001-5837-3203","position":2,"is_corresponding":false},{"id":415944,"name":"Alan M. Zaslavsky","orcid":"0000-0003-1072-6043","position":3,"is_corresponding":false},{"id":781575,"name":"Prachi Sanghavi","orcid":"0000-0002-0738-3193","position":0,"is_corresponding":true}],"reference_count":7,"raw_metadata":null,"created_at":"2026-07-18T23:51:05.955461Z","pmid":"33492665","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":[]}