Optimizing healthcare network design under reference pricing and parameter uncertainty

Healthcare payers are exploring cost-containing policies to steer patients, through qualified information and financial incentives, towards providers offering the best value proposition. With Reference Pricing (RP), a payer or insurer determines a maximum amount paid for a procedure, and patients who select a provider charging more pay the difference. In a Tiered Network (TN), providers are stratified according to a set of criteria (such as quality, cost and sometimes location) and patients pay a different out-of-pocket price depending on the tier of their chosen provider. Motivated by a recent CalPERS program, we design two original MIP optimization models for payers that combine both RP and TN, filling the gap of quantitative research on these novel payment policies. Carefully designed constraints provide the decision maker with levers for a trade-off between cost reduction and patients' satisfaction. Numerical experiments provide valuable insights in that respect, displaying also how the tiers are scattered on a cost/quality plane. We argue that this system has strong potential in terms of costs reduction for public or private payers, quality increase for patients and visibility for high-value providers.

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Technical Report, Lehigh University, Department of Industrial and Systems Engineering, Bethlehem PA, USA. (2015).

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