A Markov Model for Estimating Medication Adherence Effect on Pediatric Asthma Healthcare Use and Cost

Abstract Background/Objective: Asthma medication adherence, measured by the asthma medication ratio (AMR), has been shown to be a reliable predictor of exacerbations among children with asthma. We estimated the effects of optimal vs suboptimal AMR on exacerbations resulting in an emergency department (ED) visit or inpatient (IP) admission. Methods: We constructed an asthma Markov model using claims for a cohort of Medicaid beneficiaries aged 2‐17 years (n = 214,452) using 2013‐2014 MarketScan® data who had at least one claim for an inhaled corticosteroid. We calculated 3‐month AMRs as the basis of transition estimates in the model. The AMRs data were transformed to reflect a one‐month Markov cycle length. Our model included five states: controlled, sub optimally controlled, inactive, IP admission, and ED. The Markov model used an overall 2‐year time horizon for 10,000 beneficiaries. Patients entered the model in one of the five states as observed in the Medicaid data. Costs were based on 2017 Medicaid claims adjusted to reflect 2019 costs. Asthma medication cost-weight were mean payments observed for controller or rescue drugs, and costs weights for an ED visit or inpatient admission used median payments. Utilities for each state were based on existing literature. Results: Monthly costs for children with asthma were $214 for controlled, $32 for suboptimally controlled (attributable to fewer medication fills), $565 for months with ED visit, and $5,883 with admission. Over a 2‐year period, we estimated the 2‐year direct medical costs of asthma among Medicaid insured children to average $4,552 per child. Children are on average 1.6 months more in controlled state at a cost of $0.71 more per child per month accounting for medication cost less the cost of ED visits and hospitalizations. In addition to the saved side effects of oral steroids and time hospitalized, there is one increased quality month per 13 months. Conclusions: This Markov model populated with Medicaid population exacerbation, ED, hospital and medication use and payment data provides a solid framework to examine the cost effectiveness of existing and novel targeted interventions aimed at improving medication adherence and decreasing acute care visits for Medicaid children with asthma.