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OBJECTIVE: The aim of this article is to evaluate the burden of direct and indirect costs borne by recalled patients after a false positive screening mammogram. METHODS: Women aged 40-75 years undergoing screening mammography were identified from a U. S. commercial claims database. Women were required to have 12 months pre- and 6 months post-index enrollment to identify utilization and exclude patients with subsequent cancer diagnoses. Recall was defined as the use of diagnostic mammography or breast ultrasound during 6 months post-index. Descriptive statistics were presented for recalled and non-recalled patients; differences were compared using the chi square test. Out-of-pocket costs were totaled by utilization type and in aggregate for all recall utilization. RESULTS: Of 1, 723, 139 patients with a mammography screening that were not diagnosed with breast cancer, 259, 028 (15. 0%) were recalled. Significant demographic differences were observed between recalled and non-recalled patients. The strongest drivers of patient costs were image-guided biopsy (mean 351 among 11. 8% utilizing), diagnostic mammography (50; 80. 1%), and ultrasound (58; 65. 7%), which accounted for 29. 9%, 29. 0%, and 27. 5% of total recall costs, respectively. For many patients the entire cost of recall utilization was covered by the health plan. Total costs were substantially greater among patients with biopsy; one-third of all patients experienced multiple days of recall utilization. CONCLUSION: After a false positive screening mammography, recalled women incurred both direct medical costs and indirect time costs. The cost burden for women with employer-based insurance was dependent upon the type of utilization and extent of health plan coverage. Additional research and technologies are needed to address the entirety of the recall burden in diverse populations of women.
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Matthew Alcusky
Harvard University
Liane E. Philpotts
Yale University
Machaon Bonafede
Diagnostics for the Real World (United States)
The Medicine Forum
Journal of Women s Health
Yale University
Jefferson College
Truven Health Analytics (United States)
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Alcusky et al. (Mon,) studied this question.
synapsesocial.com/papers/6a12cd65b761793c20c093b8 — DOI: https://doi.org/10.1089/jwh.2014.1511