Introduction: Markov Modeling is a clinical research technique that allows competing medical strategies to be mathematically assessed in order to identify the optimal allocation of health care resources. We present a brief analysis of publication trends using Markov Modeling within the neurosurgical literature.
Methods: The PubMed online database was searched from January 2010 to December 2017 to identify recently published neurosurgical literature that utilized Markov Modeling for neurosurgical cost-effectiveness studies. Included articles were then assessed with regards to year of publication, sub-specialty of neurosurgery, decision analytic techniques utilized, and source information for model inputs.
Results: A total of 55 manuscripts utilizing Markov Models were identified across a broad range of neurosurgical sub-specialties. 65% of the manuscripts were published within the past three years alone. The majority of models derived health transition probabilities, health utilities, and cost information from prior published studies or publicly available information. Only 61% of manuscripts incorporated indirect costs. 91% of models performed a 1-way or 2-way sensitivity analysis and 67% performed a probabilistic sensitivity analysis.
Conclusions: As neurosurgeons continue to innovate and identify novel treatment strategies for patients, Markov Modeling allows for the better characterization of the impact of these interventions on a patient and societal level. The aim of this work is to identify commonly utilized modeling techniques and understand the broad application cost-effectiveness research offers to neurological surgeons. Moreover, through examining the published literature, this work hopes to empower neurosurgeons to better critique and apply findings from cost-effectiveness research.
Patient Care: This research will impact patient care through educating neurosurgeons and health care administrators to better understand the strengths, limits, and clinical application of cost-effectiveness research as it pertains to neurosurgery.
Learning Objectives: By the conclusion of this session, participants should be able to: 1) Describe the increasing importance of cost-effectiveness research in neurosurgery 2) Discuss, in small groups the utility of cost-effectiveness research in guiding clinical management of patients 3) Identify limitations and strengths of performing Markov Modeling with respect to one’s chosen field.