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The American Journal of Managed Care March 2010
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Ratio of Controller to Total Asthma Medications: Determinants of the Measure
Michael S. Broder, MD; Benjamin Gutierrez, PhD; Eunice Chang, PhD; David Meddis, PhD; and Michael Schatz, MD
Cost-Effectiveness of Pneumococcal Polysaccharide Vaccine Among Healthcare Workers During an Influenza Pandemic
Kenneth J. Smith, MD, MS; Mahlon Raymund, PhD; Mary Patricia Nowalk, PhD, RD;Mark S. Roberts, MD, MPP; and Richard K. Zimmerman, MD, MPH
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Alan C. O'Connor, MBA; Christine M. Layton, PhD, MPH; Todd J. Osbeck, MM; Therese M. Hoyle; and Bobby Rasulnia, PhD
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Melanie E. Mouzoon, MD; Flor M. Munoz, MD; Anthony J. Greisinger, PhD; Brenda J. Brehm, MA; Oscar A. Wehmanen, MS; Frances A. Smith, MD; Julie A. Markee, RN, MPH; and W. Paul Glezen, MD
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Pei-Jung Lin, PhD; Matthew L. Maciejewski, PhD; John E. Paul, PhD;and Andrea K. Biddle, PhD
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List of Peer Reviewers (2009)

Ratio of Controller to Total Asthma Medications: Determinants of the Measure

Michael S. Broder, MD; Benjamin Gutierrez, PhD; Eunice Chang, PhD; David Meddis, PhD; and Michael Schatz, MD
The ratio of controller to total asthma medications can be calculated using 1 or 2 quarters of data; high versus low ratios differentiate patient characteristics.
Objective: To investigate differences in demographics, physician specialty, and medication use between patients who achieve high versus low ratios of controller to total asthma medications.
 
Study Design: Cohort analysis.
 
Methods: We used a Health Insurance Portability and Accountability Act–compliant claims database to identify patients aged 5 to 56 years with persistent asthma during a premeasurement year and a measurement year. Based on values in the measurement year, the ratio of controller to total asthma medications ratio was defined using the following formula: (Units of Controllers) / (Units of Controllers + Relievers). Descriptive analysis and multivariate logistic regression models were used to examine patients with high and low ratios.
 
Results: The final study group comprised 38,538 patients with persistent asthma; 28,496 (73.9%) had high ratios. Specialty of usual-care physician differed (P <.001), with more high-ratio patients than low-ratio patients having an allergist or pulmonologist. Patients who received combination inhaled corticosteroid–long-acting β-agonist therapy (odds ratio [OR], 2.4) or leukotriene receptor antagonist therapy (OR, 3.5) were more likely to be in the high-ratio group compared with those dispensed a single inhaled corticosteroid. High-group and low-group assignment could be calculated by partial-year data: assignment based on 1 quarter of data was concordant with assignment based on full-year ratio in 91% of cases (Pearson product moment correlation coefficient, 0.864; κ statistic, 0.761), and assignment based on 2 quarters of data was concordant with full-year results in 94% of cases (Pearson product moment correlation coefficient, 0.928; κ statistic, 0.843).
 
Conclusions: A high ratio of controller to total asthma medications is associated with greater controller adherence and with more controller fills. The ratio can be calculated using 1 or 2 quarters of pharmacy claims data, at a time when intervention may reduce asthma-related exacerbations. Interventions that may improve the ratio include changing from single inhaled corticosteroid therapy and from asthma specialist care.
 
(Am J Manag Care. 2010;16(3):170-178)
The ratio of controller to total asthma medications may be a useful tool for improving quality of care.
 
  • Patients with greater adherence to controller therapy are more likely to have high ratios.
  • Higher ratios are seen in patients treated with medications other than single inhaled corticosteroids.
  • Ratios may be calculated using less than a full year of data.
The Healthcare Effectiveness Data and Information Set (HEDIS), developed by the National Committee for Quality Assurance,1 reports quality measures for various health conditions. The asthma measure assesses the proportion of patients who are prescribed a controller medication in a given year, and it has become a focus of quality improvement programs nationally.2 The current measure may not be ideal for directing improvement efforts because patients with “appropriate” care (those with >1 controller medication prescribed) may actually have an increased risk of requiring emergency hospital care.3

A revision to the measure that would address this issue has been proposed.4,5 This proposed measure, the ratio of controller to total (controller plus rescue) asthma medications, has been shown to be a better indicator of the need for emergency hospital care than the HEDIS measure.5,6 A higher ratio also is significantly related to improved asthmarelated quality of life, better disease control, and reduced symptoms.5 In addition to validating its association with relevant outcomes, studies6,7 of the ratio have demonstrated its performance among various plans and regions, tested different inclusion criteria, and examined the ideal cutoff point for high versus low ratios. However, little information is available regarding which patient populations perform well on this measure or what individual patient characteristics indicate poor performance. The type and number of controller and reliever medications that comprise the ratio have not been studied extensively. Having a better understanding of this ratio measure would improve plans’ (and physicians’) ability to identify patients at risk of having poorly controlled asthma and might help plans, through targeted intervention, improve their compliance with the measure.

The primary objectives of this study were to investigate differences between patients who achieve high versus low ratios of controller to total asthma medications, to identify patient characteristics that are associated with high ratios, and to compare the type and number of controller and reliever medications used by patients with high versus low ratios.

METHODS

We conducted a cohort study to examine the characteristics of patients with high and low ratios of controller to total asthma medications. We used the PharMetrics database, a Health Insurance Portability and Accountability Act–compliant administrative claims database (www.imshealth.com). This database contains adjudicated pharmacy and medical claims submitted by providers, healthcare facilities, and pharmacies. The study was exempt from human subjects review.

Study Population

We included patients who had persistent asthma as defined by the current HEDIS measure during a premeasurement year (October 1, 2005, to September 30, 2006) and a measurement year (October 1, 2006, to September 30, 2007) who were aged 5 to 56 years during the measurement year and who were continuously enrolled during those 2 years. Patients with emphysema or chronic obstructive pulmonary disease (COPD) (International Classification of Diseases, Ninth Revision, Clinical Modification [ICD-9-CM] codes 492, 518.2, 491.2, 493.2, 496, and 506.4) were excluded.

Outcome Measure

The main outcome measure was the ratio of controller to total asthma medications, as described by Schatz et al.5 Patients with a ratio of at least 0.5 were classified as high-ratio patients, and those with a ratio of less than 0.5 were classified as low-ratio patients. Based on values in the measurement year, the ratio was defined using the following formula: (Units of Controllers)/(Units of Controllers + Relievers). Controller medications included cromolyn sodium, leukotriene modifiers, nedocromil, inhaled corticosteroids (including combination inhaled corticosteroid–long-acting β-agonists), methylxanthines, and omalizumab. Reliever medications included inhaled short-acting β-agonists. Long-acting β-agonists as individual drugs or as part of combination therapy were not counted in the numerator or the denominator for the ratio calculation.

To count medication units for oral medications, 1 U was considered equivalent to 1 dispensing event (for a 30-day supply). If a patient received a 90-day supply, it was considered 3 U. For inhalers, 1 U was 1 canister. For injected medications, 1 U was 1 claim, but if a subsequent claim had a service date within 21 days, it was ignored (eg, claims on days 1 and 15 counted as 1 U).5 We used HEDIS definitions to count dispensing events.1 For injected medications (omalizumab), each claim was counted as a dispensing event. The number of canisters dispensed in each claim was determined by a ratio of quantity to package size. For example, a claim of triamcinolone acetonide inhalation aerosol, 75 mcg/actuation (20-g package size), with a quantity of 20 was interpreted as 1 canister dispensed. Any claim with a ratio of quantity to package size of less than 1 was counted as 1 canister. For claims with a ratio of quantity to package size of at least 1, we rounded the number to a whole number of canisters. For example, claims of aerosol solution, 75 mcg/actuation (20-g package size), with quantities of 35 and 25 were counted as 2 canisters (35/20 = 1.75 [rounded to 2]) and 1 canister (25/20 = 1.25 [rounded to 1]), respectively. If a claim was for more than 12 canisters, it was truncated to 12 canisters.

Patient Characteristics

We evaluated patient characteristics in the premeasurement year and in the measurement year. Characteristics evaluated in the measurement year included demographics (age, sex, and geographic region of care), specialty of usual-care physician, and controller or reliever use. To determine the specialties of the patients’ usual physicians, we reviewed office visit claims for evidence of evaluation and management services (defined as those with Current Procedural Terminology codes for office or other outpatient services, office consultations, and preventive medicine services). We identified the specialty of the physician with whom each patient had the most evaluation and management visits during the measurement year and considered that the patient’s usual-care physician.8 We reported extent of controller and reliever use in the measurement year and calculated controller medication possession ratios (MPRs), defined as the sum of the “days of supply” divided by the total number of days in the measurement year (365 days). If the days of supply exceeded 365, the total number of covered days was truncated to 365 days.

We assessed asthma control in the premeasurement year with variables that reflect impairment and risk using 2 key concepts described by the National Asthma Education and Prevention Program.9 To assess impairment, we measured whether patients had 6 or more short-acting β-agonist canisters dispensed in the premeasurement year. Such use has been shown to be a marker of impairment in previous investigations.10, 11 To assess risk, we measured whether patients had the following: (1) at least 2 oral corticosteroid dispensing events, (2) any asthma-related (with primary diagnosis of asthma [ICD-9-CM code 493]) hospitalization, or (3) any asthma-related emergency department (ED) visits.12 We assessed impairment and risk in the premeasurement year rather than in the measurement year to understand the effect of baseline control on the ratio.

To describe patient clinical characteristics and chronic disease burden, we used claims in the premeasurement year and in the measurement year to capture more completely any relevant diagnoses. We evaluated clinical characteristics using individual and grouped diagnoses. We used Clinical Classifications Software, developed by the Agency for Healthcare Research and Quality (http://www.hcup-us.ahrq.gov/toolssoftware/ccs/ccs.jsp), to identify patients with mental disorders and disorders of the gastrointestinal system, conditions that may affect medication adherence and asthma severity.13 Individual diagnoses included reflux (ICD-9-CM codes 530.11 and 530.81), sinusitis (codes 461.x and 473.x), rhinitis (codes 477.0, 477.8, 477.9, and 472.0), acute upper respiratory tract infection (code 465.x), and nasal polyposis (code 471.x). To account for the burden of chronic health conditions, we applied the method by Hwang et al14 to assess the number of chronic health conditions each patient had.

Statistical Analysis

We conducted a descriptive analysis to compare demographic and clinical characteristics, specialty of usual-care physician, and medication use between the high-ratio and low-ratio groups. In addition to high-ratio and low-ratio groups, we further divided patients into 4 groups based on their actual ratios (<0.25, 0.25 to <0.5, 0.5 to <0.75, and >0.75) and compared their characteristics. We studied quartiles for a more precise evaluation. We conducted bivariate analyses comparing selected characteristics between the high-ratio and low-ratio groups. Characteristics that were significantly associated with the ratio were included in the multivariate models as independent variables. We compared ratios calculated using the first quarter, the first 2 quarters, and the first 3 quarters of data with full-year ratios using Pearson product moment correlation coefficient and κ statistic.

We used 2 multivariate logistic regression models to estimate the association between certain characteristics and a high ratio. The first model excluded patients with a zero ratio (no controller use). It also excluded patients treated with only theophylline or cromolyn sodium, as these drugs are not commonly used as single agents in current practice (<1% of patients in the study). The second model included patients with no controller use. We reported adjusted odds ratios (ORs) and their 95% confidence intervals (CIs). All tests were 2-sided with a significance level of .05. All data transformations and statistical analyses were performed using SAS version 9.1

(SAS Institute, Inc, Cary, NC).

RESULTS

We identified 150,903 patients with persistent asthma in the premeasurement year and 156,649 in the measurement year. After excluding those who did not meet the age criteria, those who were not continuously enrolled, those who had evidence of emphysema or COPD, and those who did not use controllers or relievers in the measurement year, 38,538 patients remained (eAppendix available at www.ajmc.com).

Of the final study cohort, 28,496 (73.9%) were classified as having high (>0.5) ratios. The mean age did not differ between the groups with high versus low ratios. Age group, sex, and geographic region of care differed (P <.001), with a higher proportion of high-ratio patients aged 5 to 9 years (14.1% vs 8.7%), female (55.2% vs 50.5%), and from the South (18.3% vs 13.6%). Specialty of usual-care physician in the measurement year differed (P <.001), with a higher proportion of high-ratio than low-ratio patients having an allergist (7.6% vs 3.9%) or a pulmonologist (2.9% vs 2.2%) (Table 1).

 
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