RT Journal Article
T1 Comparing Markov and non-Markov alternatives for cost-effectiveness analysis: insights from a cervical cancer case
A1 Del Campo Campos, Cristina
A1 Bai, Jiaru
A1 Keller, L. Robin
AB Markov model allows medical prognosis to be modeled with health state transitions over time and are particularly useful for decisions regarding diseases where uncertain events and outcomes may occur. To provide sufficient detail for operations researchers to carry out a Markov analysis, we present a detailed example of a Markov model with five health states with monthly transitions with stationary transition probabilities between states to model the cost and effectiveness of two treatments for advanced cervical cancer. A different approach uses survival curves to directly model the fraction of patients in each state at each time period without the Markov property. We use this alternative method to analyze the cervical cancer case and compare the Markov and non-Markov approaches. These models provide useful insights about both the effectiveness of treatments and the associated costs for healthcare decision makers.
PB Elsevier
SN 2211-6923
YR 2019
FD 2019-06
LK https://hdl.handle.net/20.500.14352/103478
UL https://hdl.handle.net/20.500.14352/103478
LA eng
NO del Campo, C., Bai, J., & Keller, L. R. (2019). Comparing Markov and non-Markov alternatives for cost-effectiveness analysis: Insights from a cervical cancer case. Operations Research for Health Care, 21, 32-43.
DS Docta Complutense
RD 13 abr 2025