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The American Journal of Managed Care January 2013
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Predicting Asthma Outcomes in Commercially Insured and Medicaid Populations
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Predicting Asthma Outcomes in Commercially Insured and Medicaid Populations

Richard H. Stanford, PharmD, MS; Manan B. Shah, PharmD, PhD; Anna O. D’Souza, BPharm, PhD; and Michael Schatz, MD, MS
The controller-to-total asthma medication ratio was a significant predictor of exacerbations in pediatric and adult commercially insured and Medicaid patients.
Objectives: To assess the predictive ability of the ratio of controller-to-total asthma medication in commercially insured and Medicaid patients.

Study Design: Retrospective cohort.

Methods: Medical and pharmacy claims were used to identify asthma patients between 2004 and 2006. Ratios were computed during 3-, 6-, and 12-month assessment periods and asthma exacerbations were assessed during a subsequent 12-month follow-up period. Receiver operating characteristic curve analyses and logistic regression were used to select optimal ratio number, assessment time period, and incremental ratio analysis.

Results: The ratio significantly predicted future asthma exacerbations. An optimal value of >0.7 was identified in pediatric and adult Medicaid patients with a shorter assessment period in adults (3 months) than in children (6 months). In commercially insured patients, an optimal value of >0.5 during a 6-month assessment period was identified for children and adults. In commercially insured patients, a 0.1-unit increase in the ratio below the 0.5 value resulted in a 72% (odds ratio [OR] 0.28; 95% confidence interval [CI] 0.13-0.57) and 80% (OR 0.20; 95% CI 0.12-0.33) risk reduction among pediatric and adult patients, respectively. Similarly, a 0.1-unit increase in the ratio below the 0.7 optimal value in the Medicaid population resulted in significant risk reduction in the pediatric (OR 0.65; 95% CI 0.43-0.97) but not the adult cohort.

Conclusions: The ratio is a significant predictive risk marker in commercially insured and Medicaid asthma populations. Incremental risk reductions can be realized by unit increases in the ratio up to the identified optimal value.

(Am J Manag Care. 2013;19(1):60-67)
This study examined the predictive ability of the controller-to-total asthma medication ratio in pediatric and adult commercially insured and Medicaid patients.

  •  The ratio significantly predicted future asthma exacerbations in both populations.

  • Incremental risk reductions could be realized by unit increases in the ratio up to the identified optimal value.
Asthma represents a significant burden to the healthcare system. In 2008, almost half of the total current asthma population in the United States (12.7 of 23.3 million) experienced an asthma exacerbation, adversely affecting patients’ quality of life and increasing the likelihood of hospitalizations and emergency department (ED) visits.1 Consequently, efforts have been made to determine quality-of-care markers that can predict future exacerbations, particularly those requiring hospital or ED visits, in order to improve asthma management and reduce this burden.

One such measure, the Healthcare Effectiveness Data and Information Set (HEDIS), is based on the proportion of health plan members with persistent asthma who are appropriately prescribed long-term control medication at least once during a given year.2 Although adherence to the HEDIS measure has been associated with a lower risk of hospital and ED visits,3,4 it has shown to be an inconsistent predictor of asthma outcomes.5,6

Therefore, alternate measures have been proposed that more effectively assess asthma quality of care and that can more reliably predict the occurrence of exacerbations. One measure in particular, the ratio of controller-to-total asthma medication (ratio), has been shown to be a strong predictor of patient outcomes, asthma-related hospitalizations, and ED utilization,5,7-11 and a better quality-of-care marker than the HEDIS measure.10 Studies examining the predictive ability of this marker incorporate a 1-year measurement period that is consistent with the HEDIS performance measure. This period is valid given that the ratio might not be appropriate for patients who do not have persistent asthma. However, a 1-year measurement period prevents rapid interventional adjustments. It is not known whether a shorter measurement period would affect the predictive ability of the ratio. Because of the restrictive nature of the persistent asthma measure and the need for defining a population in a study with shorter observation times, an asthma population at risk for uncontrolled asthma or asthma exacerbations was defined for this study. At-risk patients were defined as those that meet the treatment and symptom (albuterol use as the proxy) criterion of having at least mild persistent asthma according to National Asthma Education and Prevention Program guidelines.2

Most of the studies on the ratio have been performed in persistent asthma patients from commercially insured databases across age groups. Studies in children and those from the Medicaid population are limited. It is important to study these populations because Medicaid patients are representative of a population that is more likely to have asthma and asthmarelated adverse events, specifically individuals who are younger, are female, and have lower socioeconomic status.12-14 Among those insured by Medicaid, a higher percentage of patients have asthma and poorer asthma control compared with those who have private insurance or are uninsured.15,16 Medicaid coverage was found to be independently associated with poor asthma control in children, and controller medication underuse among Medicaid- covered children is widespread.17-20 Studies have shown that children in Medicaid were more likely to be admitted to the ED or hospital for asthma compared with privately insured children.17,21

In this study we examined the predictive ability of the ratio in pediatric and adult populations at risk for asthma exacerbations using both commercially insured and Medicaid databases. The primary goal was to determine an optimal value for the ratio that is associated with a significant difference in predicting future exacerbations. We also examined the correlation between incremental unit changes in the ratio and the risk of having an exacerbation. Lastly, we identified an optimal time frame for measuring the ratio to accurately predict the risk of future exacerbations.


Study Population and Design

This study was a retrospective analysis of 2 databases, the Ingenix Impact National Managed Care Database (commercially insured) and the MarketScan Medicaid Database. The data used were from January 1, 2003, to either June 30, 2007 (Medicaid), or June 30, 2008 (commercially insured). The commercially insured database utilized the integrated medical and pharmacy administrative claims of more than 98 million lives spanning 9 census regions. The Medicaid database utilized nearly 22 million enrollees across 6 states. The initial study population identified included patients with at least 1 pharmacy claim for any type of asthma medication excluding oral corticosteroids (OCSs) during the enrollment period from January 1, 2004, to either June 30, 2005 (Medicaid), or June 30, 2006 (commercially insured). The 1-year period before the enrollment period (preindex period) was used for baseline assessment and to ensure the presence of asthma. The postindex period had 2 parts: 1 to calculate the ratio (the optimal assessment period) and a subsequent 12-month follow-up period. The optimal assessment period was varied using 3-, 6-, and 12-month periods to allow for sufficient time to accurately calculate the ratio.

All patients identified as the initial study population were also required to meet the following study criteria: have at least 1 medical claim with an asthma diagnosis (International Classification of Diseases, Ninth Revision, Clinical Modification [ICD-9-CM] code 493.xx) in any diagnosis field during the preindex period or 30 days after the index date; be continuously eligible to receive medical and pharmacy services in the 1-year preindex period and 24-month postindex period; be at least 4 years of age at the index date; and have no diagnosis of chronic obstructive pulmonary disease (codes 491.xx, 492.xx, 496.xx) anytime during the preindex and postindex periods. Patients at risk for asthma exacerbation constituted a subset of this initial study population meeting all study criteria. The definition of “at risk for asthma exacerbation” for this study was based on medication use and differed based on the length of the assessment period. Accordingly, the number of patients identified as being at risk for asthma exacerbation differed for each assessment period. Patients were considered to be at risk for asthma exacerbation if they had >1 dispensing event for an asthma controller medication or >2 short-acting beta-agonist (SABA) canisters for the 3-month period; >1 dispensing event for an asthma controller medication or >4 SABA canisters for the 6-month period; or >1 dispensing event for an asthma controller medication or >5 SABA canisters for the 12-month period. By requiring patients to have at least 1 controller medication or SABA use during the assessment periods, we reduced the likelihood of having missing ratio values (ie, no controller or SABA use) or many zero values (ie, no controller but only SABA use). Including patients with missing ratio values or many zero values would have increased the likelihood of including patients with intermittent asthma. Since the ratio is only reliable in patients with persistent asthma, inclusion of patients with intermittent asthma would affect the overall reliability of the marker.

Study Variables

The controller-to-total asthma medication ratio was calculated as the ratio of the units of controller medications used divided by the sum of the units of the controller medications, plus the units of inhaled SABAs. Controller medications included inhaled corticosteroids (ICSs), ICS and long-acting beta-agonist (LABA) combination products, leukotriene modifiers, cromolyn sodium, nedocromil, methylxanthines, and omalizumab. The ratio ranged from 0 (no controller + SABA) to 1 (controller + no SABA). Patients using no medications or using only LABAs during the assessment periods would have had missing ratio values and were excluded. As previously described,22 1 unit of medication was defined as (1) 1 canister of an inhaler, (2) a 30-day supply of an oral medication, or (3) 1 dispensing of a nebulized or injected medication.

Study Outcomes

The primary outcome was an asthma exacerbation requiring an inpatient hospitalization or ED visit with a primary discharge diagnosis of asthma (ICD-9-CM code 493.xx) during the 12-month follow-up period. We selected the optimal ratio value, the assessment period, and the incremental risk-change analysis using this primary outcome. We evaluated the impact of the optimal ratio value and assessment period on exacerbations, individual components of the exacerbations (ie, inpatient hospitalization, ED visits), and OCS-dispensing events.

Statistical Analysis

The final study sample was split into pediatric (4-17 years) and adult (>18 years) cohorts. The same analysis was conducted on both cohorts. A receiver operating characteristic (ROC) curve analysis was done to select the optimal cutoff of the ratio. The ROC analysis was done only with the primary outcome of exacerbations during a 12-month follow-up period. The cutoff values for the ratio ranged from >0.1 to >0.9 at 0.1 intervals. The ROC analysis compared the areas under the curve (AU Cs) obtained from the C statistic of the logistic regression model that was run for each cutoff value. All logistic regression models controlled for baseline characteristics during the preindex period (age, sex, Charlson Comorbidity Index,23 number of unique diagnosis codes, number of unique prescription drug categories, number of unique prescriptions filled) and asthma severity (presence of asthma-related hospitalizations or ED visits, number of OCS-dispensing events) during the assessment period. To select the optimal cutoff value within an assessment period, we considered the model that had the highest AU C and that showed a statistically significant effect of the ratio on the outcome. After selecting the optimal cutoff within each assessment period, the choice of an assessment period was based on a statistical comparison of the AU Cs of the models selected for each of the 3 assessment periods. The following steps were used for this comparison. The highest AU C was compared with the lowest. If the difference was not statistically significant, then the shorter assessment period was chosen with its respective cutoff value. If, however, the difference was statistically significant, then the comparison was repeated with the next-lowest AU C.

For the incremental risk-change analysis, the presence of a linear relationship was first demonstrated with a significant linear trend statistical test result and a graphical analysis showing an increasing or decreasing odds ratio (OR) with an increase in the ratio values.24,25 If a linear relationship was found, the ratio was entered into a logistic regression model as a continuous variable, adjusting for baseline characteristics and asthma severity as described above. The OR was then interpreted as the percent decrease or increase in risk of the outcome with each unit increase in the ratio value.

After selection of the optimal cutoff value and assessment period, multivariate logistic regression models were developed to predict the likelihood of the other outcomes during the follow-up period as a function of the optimal cutoff of the ratio, while controlling for baseline characteristics during the preindex period and asthma severity during the assessment period as described above. Adjusted ORs with corresponding 95% confidence intervals (CIs) are presented.

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