Filter Results:
(2)
Show Results For
- All HBS Web
(2)
- Research (2)
- Faculty Publications (2)
Show Results For
- All HBS Web
(2)
- Research (2)
- Faculty Publications (2)
Page 1 of 2
Results
- May–June 2018
- Article
Data Uncertainty in Markov Chains: Application to Cost-Effectiveness Analyses of Medical Innovations
By: Joel Goh, Mohsen Bayati, Stefanos A. Zenios, Sundeep Singh and David Moore
Cost-effectiveness studies of medical innovations often suffer from data inadequacy. When Markov chains are used as a modeling framework for such studies, this data inadequacy can manifest itself as imprecision in the elements of the transition matrix. In this paper,... View Details
Keywords: Markov Chains; Cost Effectiveness; Medical Innovations; Colorectal Cancer; Health Care and Treatment; Cost vs Benefits; Innovation and Invention; Mathematical Methods; Health Industry
Goh, Joel, Mohsen Bayati, Stefanos A. Zenios, Sundeep Singh, and David Moore. "Data Uncertainty in Markov Chains: Application to Cost-Effectiveness Analyses of Medical Innovations." Operations Research 66, no. 3 (May–June 2018): 697–715. (Winner, 2014 INFORMS Health Applications Society Pierskalla Award & Finalist, 2014 INFORMS George E. Nicholson student paper competition.)
- Research Summary
Health-care Applications
Active postmarketing drug surveillance. There is substantial interest within the U.S. health community and among health policymakers in developing a surveillance system that scans public health databases in order to proactively detect potential drug safety... View Details