The effect of budgetary restrictions on breast cancer diagnostic decisions

Mehmet U.S. Ayvaci*, Oguzhan Alagoz, Elizabeth S. Burnside

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

22 Scopus citations


We develop a finite-horizon discrete-time constrained Markov decision process (MDP) to model diagnostic decisions after mammography where we maximize the total expected quality-adjusted life years (QALYs) of a patient under resource constraints. We use clinical data to estimate the parameters of the MDP model and solve it as a mixed-integer program. By repeating optimization for a sequence of budget levels, we calculate incremental cost-effectiveness ratios attributable to consecutive levels of funding and compare actual clinical practice with optimal decisions. We prove that the optimal value function is concave in the allocated budget. Comparing to actual clinical practice, using optimal thresholds for decision making may result in approximately 22% cost savings without sacrificing QALYs. Our analysis indicates short-term follow-ups are the immediate target for elimination when budget becomes a concern. Policy change is more drastic in the older age group with the increasing budget, yet the gains in total expected QALYs related to larger budgets are predominantly seen in younger women along with modest gains for older women.

Original languageEnglish (US)
Pages (from-to)600-617
Number of pages18
JournalManufacturing and Service Operations Management
Issue number4
StatePublished - Sep 2012
Externally publishedYes


  • Breast cancer
  • Constrained MDPs
  • Cost-effectiveness
  • Diagnostic decisions
  • Linear programming
  • Mammography
  • Markov decision processes
  • Medical decision making
  • Mixed-integer programming
  • Service operations

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research

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