Enhanced patient outcomes and improved budget impact from increased PFO diagnostic testing in cryptogenic stroke workup: a US hospital perspective

Limited research exists on the hospital-level costs and reimbursement associated with PFO diagnostic testing. This study estimates the impact of fully implementing guideline-driven PFO diagnostic evaluation in patients with a history of cryptogenic stroke, from the perspective of an US hospital, focusing on costs, hospital reimbursement, and clinical outcomes. A budget impact analysis (BIA) was conducted from the perspective of a typical US hospital managing an average of 186 new cryptogenic stroke patients annually. Two scenarios were compared: the Current Diagnostic scenario, with a 54% testing rate, versus an Increased Testing scenario with a 100% testing rate. A hybrid decision tree combined with a Markov health state transition model was used to simulate costs and clinical outcomes over a one-year time horizon. Clinical and diagnostic input parameters were derived from the literature, while cost data were obtained from the Centers for Medicare and Medicaid Services (CMS) and other published sources. Among a cohort of 186 cryptogenic stroke patients, testing 100% of eligible patients (compared to 54%) was expected to result in diagnosing an additional 21 PFO-related strokes (46 vs. 25), and with 8 more PFO closures (17 vs. 9) over a period of one year. This translated to a total expected reimbursement increase of $378,359 ($719,738 vs $1,098,097) over a one-year period. Most reimbursement increases came from PFO closure ($275,546), with contributions from diagnostics ($96,880) and adverse event management ($13,919). The total increase in contribution margin was $191,655 from improving PFO diagnostics. Increased diagnostic testing for PFO-associated stroke is expected to improve patient health outcomes and increase contribution margin from an US hospital perspective. This evidence supports improving PFO testing in US hospitals to reduce recurrent strokes and improve hospital efficiency.