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The American Journal of Managed Care June 2018
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Initial Results of a Lung Cancer Screening Demonstration Project: A Local Program Evaluation
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A Longitudinal Examination of the Asthma Medication Ratio in Children
Annie Lintzenich Andrews, MD, MSCR; Daniel Brinton, MHA, MAR; Kit N. Simpson, DrPH; and Annie N. Simpson, PhD
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Sarah L. Martin, PhD; Nancy Connelly, MBA; Cassandra Parsons, PharmD; and Katlyn Blackstone, MS, LSW
Placement of Selected New FDA-Approved Drugs in Medicare Part D Formularies, 2009-2013
Bruce C. Stuart, PhD; Sarah E. Tom, PhD; Michelle Choi, PharmD; Abree Johnson, MS; Kai Sun, MS; Danya Qato, PhD; Engels N. Obi, PhD; Christopher Zacker, PhD; Yujin Park, PharmD; and Steve Arcona, PhD
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Jonathan Hatoun, MD, MPH, MS; Emily K. Trudell, MPH; and Louis Vernacchio, MD, MS
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Klaus W. Lemke, PhD; Kimberly A. Gudzune, MD, MPH; Hadi Kharrazi, MD, PhD, MHI; and Jonathan P. Weiner, DrPH
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Adam L. Sharp, MD, MS; Ernest Shen, PhD; Yi-Lin Wu, MS; Adeline Wong, MPH; Michael Menchine, MD, MS; Michael H. Kanter, MD; and Michael K. Gould, MD, MS
Cost Sharing for Antiepileptic Drugs: Medication Utilization and Health Plan Costs
Nina R. Joyce, PhD; Jesse Fishman, PharmD; Sarah Green, BA; David M. Labiner, MD; Imane Wild, PhD, MBA; and David C. Grabowski, PhD

A Longitudinal Examination of the Asthma Medication Ratio in Children

Annie Lintzenich Andrews, MD, MSCR; Daniel Brinton, MHA, MAR; Kit N. Simpson, DrPH; and Annie N. Simpson, PhD
This longitudinal examination of the asthma medication ratio in a national sample of children has determined the predictive accuracy of a rolling 3-month ratio.
ABSTRACT

Objectives: The asthma medication ratio (AMR) (number of controller medications / [number of controller medications + number of rescue medications]) can be calculated using claims data. This measure has not previously been studied longitudinally. Our objective is to conduct a longitudinal examination of the AMR in a large national cohort of children with asthma.

Study Design: Retrospective analysis of pharmacy and medical claims data.

Methods: Using 2013-2014 TruvenHealth MarketScan data, we identified children with asthma. Beginning with the month of first controller claim, we calculated an AMR for each rolling 3-month period and each rolling 6-month period and examined the proportion who had AMRs classified as low-risk (≥0.5), high-risk (<0.5), and missing for each period. Using logistic regression, we tested how a rolling AMR predicted a child’s hospitalization or emergency department (ED) visit for asthma.

Results: We identified 197,316 patients aged 2 to 17 years with a claim for a controller. AMRs were relatively stable over time, with the majority of patients remaining in the same AMR category through a 12-month period. Using both the rolling 3-month and 6-month AMRs, a higher proportion of patients with high-risk AMRs (9.6% and 9.5%, respectively) had an ED visit or hospitalization compared with patients with low-risk (5.0% and 5.7%) and missing (3.5% and 3.2%) AMRs (P <.0001). Using logistic regression, the 3-month AMR is more strongly associated with subsequent ED visit or hospitalization than the 6-month AMR.

Conclusions: AMR-based risk assignment is relatively stable over time. Three-month AMR calculation periods appear to provide the most accurate assessment of risk. Children with missing AMRs likely have inactive asthma and are at the lowest risk for emergent asthma visits.

Am J Manag Care. 2018;24(6):294-300
Takeaway Points

The asthma medication ratio (AMR) can be calculated using pharmacy claims data and used to identify patients with asthma who are at highest risk for exacerbation in the coming months.
  • AMR-based risk assignment is relatively stable over time.
  • In any given time period, 5% to 8% of children with asthma will be at high risk.
  • Children with no pharmacy claims for either rescue or controller medications are at lowest risk for exacerbation.
Asthma remains a frequent cause of emergency department (ED) visits and hospitalizations among children.1 Controller medications, particularly inhaled corticosteroids (ICSs), are effective at reducing the incidence of these acute care visits for asthma.2-4 However, these medications continue to be underutilized.5-8 Using pharmacy claims data to identify patterns of poor controller medication adherence is a potential way to target medication adherence interventions to high-risk children. With this in mind, the asthma medication ratio (AMR; number of controller medication claims / [number of controller medication claims + number of rescue medication claims]) has been developed to measure adherence and assign risk for exacerbation.9-16 Findings from previous studies have shown that the AMR predicts risk for future exacerbation on the patient level.10-12,17 The AMR has the potential to risk stratify large populations of children with asthma in real time, thereby accurately identifying the patients at highest risk for exacerbation and allowing for intervention before exacerbation occurs. This could ultimately prevent costly ED visits and hospitalizations, driving down healthcare costs and improving quality of life attributed to this common pediatric chronic disease.

Despite its potential for risk assessment and risk communication to prevent exacerbations, the AMR has not yet been translated to a point-of-care, real-time monitoring tool. All previous AMR studies have utilized a fixed cross-sectional AMR assessment period, capturing adherence behaviors for 1 specific moment. Before designing and testing an AMR-based intervention, we must better understand the longitudinal behavior of the AMR using rolling periods. This represents the most practical way to calculate the AMR in real time and will allow risk assessment using the most recent claims data available.

Traditionally, studies have relied on the Healthcare Effectiveness Data and Information Set (HEDIS) criteria for persistent asthma to determine who is eligible for AMR measurement. HEDIS is a quality tool and was designed to measure systems, not individuals. HEDIS criteria work well for reporting on the performance of health systems through tools such as the Quality Compass. Previous studies' results have shown that patients often do not meet HEDIS criteria for persistent asthma in consecutive years and that the number of consecutive years of HEDIS qualification was strongly associated with ICS use.18 HEDIS requires up to 1 year of claims monitoring in order to classify a patient as persistent asthmatic. This would lead to missed opportunities for intervention during the measurement year and potential inappropriate interventions the following year. Instead, we propose that the AMR can be measured in all children with a pharmacy claim for an ICS. According to the National Heart, Lung, and Blood Institute (NHLBI) Guidelines for the Diagnosis and Management of Asthma, ICSs are recommended only for children with persistent asthma.19 Therefore, it is unlikely that children with intermittent asthma would be identified using this criterion.

The objective of this study was to examine the longitudinal behavior of the AMR among a large national cohort of privately insured children with asthma, including a comparison of the predictive accuracy of a 3-month rolling AMR with that of a 6-month rolling AMR, as well as determining the proportion of patients in each risk category at any given time.

METHODS

Study Cohort

In order to identify all children for whom the AMR would be a potentially valid risk assessment tool, we first identified all asthma medication claims from the Truven Health MarketScan pharmacy claims databases for 2013 and 2014 using National Drug Code numbers. Medications were then categorized as rescue medications or controller medications. Patients aged 2 to 17 years with any claim for an ICS-containing medication were eligible for inclusion in our study cohort. Because we took an alternative approach to identifying the cohort of children eligible for AMR measurement, we assessed the proportion of our cohort that met HEDIS persistent asthma criteria and determined in any given AMR measurement period how many patients would qualify as at high risk for exacerbation but not as persistent asthmatic according to HEDIS criteria.

We defined each patient’s study index date as the date of his or her first ICS-containing medication claim in the study period. Patients with fewer than 360 (12 × 30) days of continuous insurance enrollment after their index date and patients with a diagnosis of cystic fibrosis (International Classification of Diseases, Ninth Revision [ICD-9] code 277.XX) at any time during the study period were excluded. We then identified all inpatient and ED visit claims with a primary diagnosis of asthma (ICD-9 code 493.XX) for each patient in the cohort. Only those claims representing visits that occurred after the patient’s index date were retained in the final analytical data set. Covariates used in this analysis include patient age (defined as age at index date, operationalized continuously and in age categories), sex, geographic region, and season of index date (winter, January-March; spring, April-June; summer, July-September; fall, October-December). MarketScan does not include a race variable.


 
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