Pancreas fistula risk prediction: implications for hospital costs and payments

Abstract Background As payment models evolve, disease-specific risk stratification may impact patient selection and financial outcomes. This study sought to determine whether a validated clinical risk score for post-operative pancreatic fistula (POPF) could predict hospital costs, payments, and prof...

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Veröffentlicht in:HPB (Oxford, England) England), 2017-02, Vol.19 (2), p.140-146
Hauptverfasser: Abbott, Daniel E, Tzeng, Ching Wei D, McMillan, Matthew T, Callery, Mark P, Kent, Tara S, Christein, John D, Behrman, Stephen W, Schauer, Daniel P, Hanseman, Dennis J, Eckman, Mark H, Vollmer, Charles M
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Sprache:eng
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Zusammenfassung:Abstract Background As payment models evolve, disease-specific risk stratification may impact patient selection and financial outcomes. This study sought to determine whether a validated clinical risk score for post-operative pancreatic fistula (POPF) could predict hospital costs, payments, and profit margins. Methods A multi-institutional cohort of 1193 patients undergoing pancreaticoduodenectomy (PD) were matched to an independent hospital where cost, in US$, and payment data existed. An analytic model detailed POPF risk and post-operative sequelae, and their relationship with hospital cost and payment. Results Per-patient hospital cost for negligible-risk patients was $37,855. Low-, moderate-, and high- risk patients had incrementally higher hospital costs of $38,125 ($270; 0.7% above negligible-risk), $41,128 ($3273; +8.6%), and $41,983 ($3858; +10.9%), respectively. Similarly, hospital payment for negligible-risk patients was $42,685/patient, with incrementally higher payments for low-risk ($43,265; +1.4%), moderate-risk ($45,439; +6.5%) and high-risk ($46,564; +9.1%) patients. The lowest 30-day readmission rates – with highest net profit – were found for negligible/low-risk patients (10.5%/11.1%), respectively, compared with readmission rates of moderate/high-risk patients (15%/15.7%). Conclusion Financial outcomes following PD can be predicted using the FRS. Such prediction may help hospitals and payers plan for resource allocation and payment matched to patient risk, while providing a benchmark for quality improvement initiatives.
ISSN:1365-182X
1477-2574
DOI:10.1016/j.hpb.2016.10.016