The Diffusion of Health Care Fraud: A Network Analysis

• Activity Number: 131 - Translating Health Outcome Data into Real-World Understanding and Policies
• Type: Topic Contributed
• Date/Time: Monday, August 8, 2022 : 10:30 AM to 12:20 PM
• Sponsor: Health Policy Statistics Section
• Author(s): James O'Malley* and Thomas Bubolz and Jonathan S Skinner
• Companies: Geisel School of Medicine at Dartmouth and Geisel School of Medicine at Dartmouth and Dartmouth College
• Keywords: Anti-fraud “strike force”; Beneficiary-sharing; Bipartite mixture network index; Bipartite degree; Diffusion; Home health care

Abstract

Many studies have examined the diffusion of health care innovations but less is known about the diffusion of health care fraud. We consider the diffusion of potentially fraudulent Medicare home health care billing in the United States during 2002-16. In response to an a priori hypothesis about mechanisms enabling rapid diffusion of fraudulent strategies, we develop a novel bipartite mixture (or BMIX) network index for patient-sharing in networks across home health care agencies. We show that the HRR-level BMIX was a strong predictor of above-average home care expenditures across health referral regions (HRRs), including in HRRs where expenditures have increased the most, and that it was much more predictive than any other network measure. Within HRRs analyses show that agencies sharing more patients with other agencies were associated with increased spending the following year, HRR-level analyses show that the BMIX index was also strongly associated with longer-term subsequent changes in home health billing, and additional analyses rule out reverse causation. These results highlight the importance of bipartite network structure in diffusion and in infection models more generally.