Shiva G. Sajjan, PhD

 Unintended consequences may result from changes in pharmacy benefit design. The objective was to determine the impact of increasing patient prescription copayments for guidelinerecommended, long-term asthma controller (LTC) medications on asthma-related medication use and healthcare services.

 We used 2005 MarketScan healthcare and pharmacy claims data to identify asthma (

International Classification of Diseases, 9th Revision, Clinical Modification [ICD-9-CM]

 diagnosis code 493.xx) patients aged 12 to 64 years who were continuously enrolled through 2006 with 

1 claim for an asthma medication in 2005. LTCs included: inhaled corticosteroid (ICS) (n = 10,251), ICS plus long-acting beta agonist (COMBO) (n = 27,407), and leukotriene receptor antagonist (LTRA) (n = 20,664).

Using multivariable models, we estimated the associations between changes in LTC copayments and LTC consumption and asthmarelated outpatient and emergency department (ED) visits.

$5 average increase in patient copayments per month of medication supplied (yes/no). The mean annual change (2005-2006) in copayments per month was $13.23 versus —$3.88 (ICS), $11.76 versus –$3.06 (COMBO), and $9.78 versus –$2.06 (LTRA). The 

$5 group experienced a significant decline in average annual days of medication supplied of —47.1 days of ICS (95% CI –43.5 to –50.8), –35.3 days of COMBO (–32.4 to –38.2), and –47.5 days of LTRA (–43.2 to –51.7). Among COMBO and LTRA medication users, the 

$5 copayment increase was associated with more asthma-related outpatient visits and ED visits compared with the <$5 group.

 The findings suggest that even small changes in average copayment for asthma medications can result in significant reductions in medication use and\ unintended increases in healthcare services.

$5 average increase in patient copayments per month of medication supplied (yes/no).

$5 increase in copayment was associated with more than 1 month’s supply less utilization of long-term controller medications over the course of 1 year.

		For certain classes of long-term controller medications, a 

$5 increase in copayment was associated with more subsequent oral corticosteroid bursts, increases in asthma outpatient visits, and increases in asthma emergency department visits.

		The study findings should be considered when designing drug benefit decisions that change formulary patient copayment structures.

	As the costs of healthcare rise, healthcare payers struggle to balance access and affordability for patients and plan sponsors. To mitigate overconsumption of pharmaceuticals, many US pharmacy benefits have built-in, out-of-pocket (OOP) payments for pharmaceuticals. Historically, the patient’s contribution to pharmaceutical purchases (copayments) has been quite low, on the order of 10% to 15% of the average market price. In recent years, however, payers have increased patient copayment substantially and have created tiered pharmacy benefits and step-edits to countermand increasing demand for expensive drugs.

 For example, a 3-tier pharmacy benefit may require a monthly patient (OOP) cost of $10 for less costly generic drugs, a $25 copayment for preferred branded drugs, and a $50 copayment for nonpreferred branded drugs. This type of system is intended to incentivize the patient to move toward less costly substitutes. Substitutes are not, however, always available at the lower copayment level.

	An unintended and possibly harmful consequence of changes in pharmacy benefit design is the impact that higher copayments have on clinically beneficial or optimal medication consumption.

 Several studies have shown that increasing OOP costs for prescription drugs reduces the rate of utilization of medications for patients with chronic diseases.

 However, the literature is limited on the impact that changes in health benefit design have on asthma controller medication utilization. Canadian researchers have found that increases in patient contributions to controller medications, such as inhaled corticosteroids (ICS), have reduced ICS utilization.

 In the United States, findings on the impact of changes in health benefit design have been mixed. Fung et al showed a reduction in ICS use with increased demand barriers on the Medicare population,

 whereas Crown et al suggested a limited change in patient-level treatment patterns due to higher patient contributions.

 The latter did, however, suggest that physician and practice prescribing preferences influenced patient treatment.

	An important unanswered question is to what extent changes in consumption resulting from alterations in pharmacy benefit design impact health outcomes. Our study objective fills a gap in the literature that relates changes in longterm asthma controller (LTC) medication patient copayment with LTC utilization and with asthma health outcomes. We tested whether or not an increase in patient-level average LTC prescription copayment per month would result in lower LTC utilization and higher rates of asthma-related health services, which are typically thought of as components of asthma exacerbations. Asthma is a convenient disease state to test these hypotheses using years 2005 and 2006 claims data because: (1) LTCs are guideline-recommended therapies; (2) LTCs prevent inflammation and reduce the risk of asthma exacerbations but many LTC users do not necessarily observe noticeable and immediate benefits from LTCs; (3) some consequences of LTC medication failure can be observed in health insurance claims data; and (4) during the study period, no known large changes occurred to the LTC market in terms of new LTCs or new generics.

	We performed a retrospective cohort analysis using the Thompson Healthcare MarketScan commercial database (29 million covered lives in all geographic regions of the United States). MarketScan captures medical (inpatient, outpatient, and emergency care) and pharmacy claims information including the claim-level patient copayment amount, as well as eligibility status, from employees of large corporations. MarketScan is known for its high standard of claims-based information that is representative of the privately insured US population.

	We used the 2005 and 2006 years of the MarketScan claims database to identify the study cohort and test our hypotheses. Inclusion criteria for the study (

) were: (1) a 2005 diagnosis of asthma defined by 1 of the following criteria: at least 2 outpatient claims with primary or secondary diagnoses of asthma (

 diagnosis code 493.xx) OR at least 1 emergency department (ED) or hospitalization claim with primary diagnosis of asthma (493.xx); (2) continuous enrollment during 2005 and 2006; (3) age 

12 and <64 years on January 1, 2005; and (4) at least 1 drug claim for an LTC medication (ICS, ICS combined with long-acting beta-2 agonist [LABA], leukotriene receptor antagonist [LTRA], mast cell stabilizers, or omalizumab) with 

30 days supply during 2005. Patients were excluded (Figure) if they had: (1) a diagnosis of chronic obstructive pulmonary disease (

491.2, 493.2, 496, 506.4), or at least 1 claim for an anticholinergic medication; (2) a diagnosis of emphysema (

 492.x, 506.4, 518.1, or 518.2); (3) a diagnosis of cystic fibrosis (

 277.0x); or (4) were enrolled in Medicare.

	We linked national drug codes in the Medstat data with classes as defined in the Healthcare Effectiveness Data and Information Set 2009 Final NDC table.

 Upon reviewing the LTC utilization patterns of the study cohort during the year 2005 (Figure), we included the following most common LTC classes for analysis: ICS, ICS plus long-acting beta agonist (COMBO), and LTRA. The primary exposure variable of interest was the average change in patients’ monthly prescription copayment from 2005 to 2006 for each LTC class.

	The average copayment per patient month for a given LTC class within a claim year was estimated by averaging all of the LTC claims filled for a patient and the patient OOP payment (copayment) divided by the number of months supplied (assuming 100% medication adherence). The months supplied were estimated using the days supplied field in the claims data. Patients who filled an LTC class in 2005 but not in 2006 were assigned the plan-level average monthly copayment for 2006. In this way, we assumed such patients would have faced this copayment had they filled the same LTC class in 2006. The change in copayment was calculated for each LTC class and patient by taking the average copayment per month supplied in 2006 and subtracting the average copayment per month supplied in 2005.

	The outcome measures captured from 2006 pharmacy and medical claims included the following for 2005 LTC users: LTC utilization (yes/no), LTC days supplied, LTC substitution and switching patterns, oral corticosteroid bursts, asthma-related outpatient visits (primary or secondary diagnosis of asthma with 

 493.xx), asthma related ED visits (primary asthma diagnosis with 

 493.xx) and asthma-related hospitalizations (primary asthma diagnosis with 

 493.xx). LTC utilization was characterized in terms of average days supplied and also adherence for those who had at least 30 days supplied. Adherence was defined as the medication possession ratio where the total days supplied in a year was divided by the number of days in 1 year.

	The distribution of patient copayment change (primary exposure measure) was split into those experiencing 

$5 average increase in monthly copayment versus <$5, based on an empiric analysis. We also had interest in evaluating an economically significant change of at least a $5 increase because previous evaluations suggested that this exposure variable is likely to not be linearly related to outcome measures.

 We used descriptive statistics to display the 2005 demographics and clinical characteristics and the 2005 versus 2006 LTC utilization by copayment change category for each LTC. Differences in continuous characteristics were tested using 

 tests and differences in the categorical characteristics and utilization proportions were tested using X

 test. For each LTC, we used linear regression to test for differences in the continuous outcome of 2006 days supplied and Poisson (negative binomial distribution for asthma-related hospitalizations) regression to test for differences in 2006 count outcomes, including oral corticosteroid bursts, asthma-related outpatient visits, asthma-related ED visits, and asthma-related hospitalizations.

	We adjusted all regression analyses for 2005 baseline and clinical characteristics including: age, gender, insurance plan type, comorbidities, LTC use in terms of 2005 annual days supplied, asthma-related outpatient visits, oral corticosteroid bursts, asthma-related ED visits, asthma-related hospitalizations, and total OOP patient expenditures. We applied a modified Charlson Index (Quan et al index) to generate scores on the level and burden of comorbidity for the study cohorts to adjust for the potential confounding of health status.

 The Quan et al index draws on diagnostic information from 

codes and procedure codes, resulting in conditions that are weighted based on the adjusted risk of 1-year mortality. The index score is the sum of the weights for all of a patient’s conditions, with higher numbers indicating increased levels of comorbidity.

	We conducted 2 sensitivity analyses on key exposure and outcome variables. First, we examined the 

$5 average increase in monthly copayment only in those who filled the same LTC in both 2005 and 2006 (a subgroup of the base case cohort). Second, we examined the effect of a 

$10 average increase in monthly copayment cutoff on the base case cohort.

	Of a possible 2,434,764 patients with claims in the 2005 MarketScan claims data set, our study cohort was a sample size of 40,784 (Figure). Of the overall study cohort, 10,251 (25.1%) patients filled at least 30 days supplied of ICS; 27,407 (67.2%) filled at least 30 days of COMBO; and 20,664 (50.7%) filled at least 30 days of LTRA. Note that the LTC categories are not mutually exclusive. A patient could be counted in more than 1 LTC category if he or she filled at least 30 days supplied in each category.

	The 2005 mean copayment per month supplied was $18.51 with standard deviation (SD) of $15.10 for the ICS cohort, $19.16 for the COMBO cohort (SD = $13.10), and $16.46 for the LTRA cohort (SD = $10.60). The mean copayment per month supplied from 2005 to 2006 for all 3 LTC class cohorts changed less than $1.00 in absolute value. Patients in all 3 cohorts with <$5 change in copayment per month supplied had, on average, a reduction in monthly copayment from 2005 to 2006 (

). Conversely, patients in all 3 cohorts with 

$5 increase in copayment per month supplied had, on average, an increase in monthly copayment from 2005 to 2006 (Table 1).

$5 increase in patient copayment per month supplied, compared with patients with a <$5 increase, were younger (

 <.0001), had a different distribution of insurance plan type (

 <.0001), had lower baseline LTRA copayment (

 = .008), and lower annual patient OOP expenses (

). The 2005 demographic and clinical characteristics for the ICS and COMBO cohorts were not displayed. However, statistical differences between copayment groups followed the same trend as in the LTRA cohort.

 displays the proportion of patients who filled the same LTC in 2006, comparing those with <$5 increase in average monthly copayment with patients with 

$5 increase in average monthly copayment. Among the ICS cohort, 66.7% (<$5 increase) versus 37.3% (

 <.0001) filled an ICS prescription in 2006. Among the COMBO cohort, 70.8% (<$5 increase) versus 58.3% (

 <.0001) filled a COMBO prescription in 2006. Among the LTRA cohort, 77.3% (<$5 increase) versus 59.8% (

 <.0001) filled an LTRA prescription in 2006. Further, patients in the ICS cohort with a 

$5 increase in copayment per month supplied were more likely to fill a prescription for a COMBO in 2006 (28.7%) compared with patients with a <$5 increase (21.7%). The proportions of patients with a 2006 LTRA prescription fill were similar between the copayment groups in the ICS cohort (36.3% and 37.9% for 

$5 increase and <$5 increase, respectively). COMBO patients with a 

$5 increase in copayment per month supplied were slightly more likely to fill a prescription for an ICS in 2006 (13.5%) compared with patients with a <$5 increase (11.0%), but not as likely to fill a prescription for an LTRA (39.7% and 41.5% for 

$5 increase and <$5 increase, respectively). Patients in the LTRA cohort with a 

$5 increase in copayment per month supplied were less likely to fill a prescription for an ICS or a COMBO in 2006 compared with patients with a <$5 increase in copayment (ICS 18.3% and 20.6%; COMBO 59.8% and 77.3%, respectively).

$5 average increase in 2006 copayment resulted in declines in adjusted average annual days supplied for: ICS of —47.1 days (95% confidence interval [CI], –43.5 to –50.8), ICOMBO of –35.3 days (–32.4 to –38.2), and LTRA of –47.5 days (–43.2 to –51.7). 

 displays the adjusted rate ratios of asthma-related health services for those with a 

$5 increase in copayment per month supplied compared with those without a $5 increase. Among all 3 LTC classes, the 

$5 copayment increase was associated with more asthma-related outpatient visits. Among LTRA and COMBO, the 

$5 copayment increase was associated with more asthma-related ED visits. Among the COMBO cohort, the 

$5 copayment increase was associated with more oral corticosteroid bursts.

Sensitivity Analysis Requiring Same LTC Use for Both 2005 and 2006.

$5 average increase in 2006 copayment resulted in declines in adjusted average annual days supplied for: ICS of —35.3 days (95% CI –29.5 to –41.1), COMBO of –26.7 days (–23.0 to –30.3), and LTRA of –27.7 days (–22.9 to –32.5). We found similar results as compared with our base case analysis when estimating the adjusted rate ratios of asthma health services. The only statistical change from base case results was that the ICS oral corticosteroids comparison became statistically significant for oral corticosteroids (adjusted rate ratio: 1.12 [95% CI 1.02-1.23]).

$10 Cut-off for Average Increase in 2006 Copayment.

$10 average increase in 2006 copayment resulted in declines in adjusted average annual days supplied for: ICS of —53.2 days (95% CI –48.5 to –57.8), COMBO of -41.1 days (–36.8 to –45.4), and LTRA of –72.2 days (–65.5 to –78.9). We found similar results as compared with our base case analysis when estimating the adjusted rate ratios of asthma health services. The only statistical change as compared with the base case was that the LTRA outpatient visit rate ratio (RR) became not statistically significant (adjusted RR: 0.99 [95% CI 0.95-1.03]).

30-day supply), we found that LTC average adherence was low regardless of copayment (medication possession ratio across the 3 LTC classes ranged from 0.54 for LTRA to 0.26 for ICS). Asthma LTC medications such as ICS, ICS LABA, and LTRA are prescribed to achieve control of asthma symptoms, maintain pulmonary function, and prevent exacerbations. Even without additional financial barriers such as patient copayment, previous research suggests that optimal asthma LTC consumption falls short for many patients.

 Bahadori et al reported in their burden of illness study that large variation of asthma control can partly be explained by variation in guideline adherence to medication use and deficits of patients’ management.

 Suboptimal LTC adherence is linked with suboptimal asthma control.

 No matter the definition of asthma control, those with poorer control have vastly greater burden in terms of the propensity to reach asthma control in the future, direct and indirect costs, and health-related quality of life.

	Acknowledging that the baseline LTC consumption is not optimal in the real world (more patients likely underconsume than overconsume), our study sought to test the impact of potential financial barriers to LTC consumption in terms of an increased patient LTC copayment on LTC utilization and asthma- related healthcare utilization. A 

$5 increase in copayment was associated with greater than 1 month’s supply less utilization of LTCs over the course of 1 year for ICS, COMBO, and LTRA. Our primary objective for the study was to determine if a 

$5 increase in copayment was not only associated with lower LTC utilization but also impacted meaningful asthmarelated health services. The multivariable models suggest that when adjusting for 2005 demographics, insurance plan type, comorbidities, LTC use, healthcare resource use, and total patient OOP expenses, a 

$5 increase in copayment was associated with more subsequent oral corticosteroid bursts (7% increase for COMBO), a 3% to 6% increase in asthma outpatient visits (ICS, COMBO, and LTRA), and a 48% and a 19% increase in asthma ED visits for COMBO and LTRA, respectively. The adjusted asthma-related health services findings from our sensitivity analyses were similar to those of the base case analysis.

	Our study findings may be of use to value-based insurance design. Value-based insurance design is growing in the United States. It attempts to address the underuse of essential therapies by linking cost-sharing and value.

 Evidence suggests that suboptimal adherence to LTCs is linked with suboptimal asthma control which, in turn, is linked with suboptimal value. However, value may have different definitions based on the stakeholders and perspective.

	Bae et al modeled the health outcomes and cost shifts associated with an increase in monthly Medicaid copayment from $0.50 to $2.00 for ICS medication in adults.

 They projected that this small increase (but large relative increase) in patient copayment for a financially vulnerable population in Massachusetts would increase the annual number of acute asthma events by 646 due to lower adherence of ICS. In the Bae et al paper, the Medicaid plan was better off by $2.10 million by increasing the copayment because of savings due to decreased medication utilization and lower pharmacy reimbursement rates as compared with the additional costs of the acute events. The Bae et al model brings into question the perspective of the analysis. In this case, the average Medicaid asthma patient was worse off because they paid more OOP and experienced more acute events. Decreased adherence may also have affected other patient outcomes such as asthma symptoms and health-related quality of life. The payer, on the other hand, was financially better off, as was the pharmacy benefit manager. In certain instances, shifting costs to the patient may be fiscally beneficial to the pharmacy benefit manager and/or payer in the short run, but such actions may have clinical- (eg, asthma exacerbations) and humanistic- (eg, patient health-related quality of life) relevant consequences as well as potential long-term economic consequences that were not modeled in the Bae et al study.

Articles

Even small changes in average copayment for long-term controller asthma medications can result in significant reductions in medication use and increases in healthcare services.

Increasing Pharmaceutical Copayments: Impact on Asthma Medication Utilization and Outcomes

To describe the relationships between persistent asthma defined by administrative versus survey data and their stability over time.

 Longitudinal survey and retrospective administrative database.

 Administrative data were used to identify patients meeting the Healthcare Effectiveness Data and Information Set (HEDIS) criteria for persistent asthma in year 1 (2006). At the end of year 2 and on 3 occasions during year 3, patients were mailed a survey to define persistent asthma based on symptoms and medication use in the prior month and exacerbations in the prior 12 months. Administrative data were also used to define medical utilization for asthma in year 3.

 Of 13,833 eligible patients, 2895 (20.9%) returned the survey; 2751 of these respondents reported physician-diagnosed asthma, of whom 2517 (91.5%) had survey-defined persistent asthma. Patients having survey-defined persistent asthma (68.0%) were more likely to requalify as having HEDIS-defined persistent asthma in year 2 than patients not having survey-defined persistent asthma (22.2%). However, 81.6% of survey respondents who did not requalify as having HEDIS-defined persistent asthma in year 2 had survey-defined persistent asthma. Patients with survey-defined persistent asthma in year 2 had significantly more medical utilization for asthma in year 3 than patients without survey-defined persistent asthma. Approximately 82% of the 799 patients completing all 4 surveys had persistent asthma on all surveys.

 HEDIS-defined persistent asthma is generally consistent with survey-defined persistent asthma. Persistent asthma usually remains persistent over a 3-year period, indicating that it is a stable characteristic of asthma for most patients. The low survey response rate suggests that further population-based studies will be necessary to confirm the validity and generalizability of our study findings regarding persistent asthma.

	Healthcare Effectiveness Data and Information Set (HEDIS)-defined persistent asthma seems to reflect clinical persistent asthma.

		The 2-year HEDIS definition is more specific for persistent asthma than the 1-year definition.

		Persistent asthma is associated with increased medical utilization compared with nonpersistent asthma.

		Persistent asthma seems to be persistent over a 3-year period and is an appropriate target for intervention.

	Persistent asthma is clinically defined based on the frequency and severity of asthma symptoms and on pulmonary function test results when available.

 It is important to  differentiate persistent from intermittent asthma because persistent asthma requires daily controller therapy, while intermittent asthma can be treated with rescue therapy as needed.

	The National Committee for Quality Assurance

 has developed an administrative data—based definition of persistent asthma as part of the Healthcare Effectiveness Data and Information Set (HEDIS) quality measurement program. This definition relies on asthma-coded medical visits and asthma-related pharmacy utilization and is meant to define a population for whom asthma controller therapy is indicated. However, studies

 have shown that only a modest relationship exists between this administrative data—based definition of persistent asthma and a definition based on patient report of symptoms. Moreover, findings from other studies

 suggest that 24% to 45% of patients who qualify as having persistent asthma in one year based on the HEDIS definition do not qualify again the next year. This raises the question of how persistent is persistent asthma. In other words, is persistent asthma a sufficiently stable characteristic of asthma to warrant the recommendation for long-term controller therapy? We are unaware of studies that have specifically addressed this question.

	Because data suggest that patients who qualify for administrative data—based persistent asthma for 2 consecutive years have increased markers of asthma morbidity and are more likely to receive controller therapy,

 the HEDIS definition of persistent asthma for the purposes of assessing appropriate controller use has been modified to require qualification in each of 2 successive years.2 However, no studies to date have investigated the relationship of this 2-year administrative data—based definition of persistent asthma to persistent asthma as defined by patient report of symptom frequency, severity, and treatment. The objectives of this study were (1) to investigate the relationship of the 2-year HEDIS definition of persistent asthma to persistent asthma as defined by patient report, (2) to compare medical utilization for patients with versus without persistent asthma, and (3) to determine the persistence of persistent asthma over time.

	This study was approved by the Kaiser Permanente SouthernCalifornia Institutional Review Board. Using computerized Kaiser Permanente Southern California inpatient, outpatient, pharmacy, and membership records, we identified patients aged 18 to 56 years with persistent asthma in 2006 (study year 1) based on their meeting 1 or more of the following HEDIS criteria: (1) 4 or more asthma medication dispensings, (2) 1 or more emergency department visits or hospitalizations with a principal diagnosis of asthma, or (3) 4 or more asthma outpatient visits with 2 or more asthma medication dispensings. Patients with continuous membership in 2007 who also met 1 or more of these HEDIS criteria in 2007 (study year 2) were considered to requalify for 2-year HEDIS-defined persistent asthma (

). Only patients with continuous membership in Kaiser Permanente Southern California from 2006 to 2008 were included in the study.

	The following additional information was captured from the Kaiser Permanente Southern California records: (1) sex, (2) age, (3) smoking status, (4) Medicare or Medi-Cal insurance, (5) hospitalization with asthma coded (

International Classification of Diseases, Ninth Revision, Clinical Modification

] code 493.xx) as the primary diagnosis or as the

	second diagnosis with another respiratory primary diagnosis, (6) emergency department visit with asthma coded (

 code 493.xx) as the primary diagnosis or as the second diagnosis with another respiratory primary diagnosis, (7) outpatient visit with asthma coded (

 code 493.xx) as a diagnosis, (8) any oral corticosteroid dispensing, (9) dispensings of more than 6 short-acting b-agonist canisters in a 12-month period, (10) any asthma controller dispensing, and (11) address. We successfully linked more than 95% of the addresses of our enrollees to census block groups and assigned block group—level income and education estimates in 2006 to patients by using the proprietary  demographic estimates supplied by Nielsen Claritas (http://www.claritas.com). Census-based income and education variables have been widely used as proxies for the socioeconomic status of individuals in many health-related investigations.

 Using this method, we determined (1) the proportion of the population older than 25 years in the patient’s census block having more than a high school education and (2) the median household income in the patient’s census block. Medical utilization for asthma was assessed during 2006 (study year 1) and during 2008 (study year 3) (Table 1).

	In November 2007, all eligible patients were mailed a survey to define persistent asthma based on symptoms and medication use in the prior month and exacerbations in the prior 12 months. The survey used the Expert Panel Report 3 definition of persistent asthma, which includes impairment and risk domains.

 The impairment domain includes the frequency and intensity of symptoms and functional limitations that the patient is currently experiencing. The risk domain includes the likelihood of asthma exacerbations based on the number of exacerbations in the prior 12 months. Four yes or no questions asked whether the patient in the past 30 days had (1) “experienced asthma symptoms at least 3 times per week,” (2) “used your rescue inhaler for symptoms at least 3 times per week,” (3) “been awakened by asthma symptoms at least 3 times,” and (4) had asthma that “interfered with your normal activity.” One question asked “In the past 12 months, how many times have you been given oral corticosteroids (such as prednisone, methylprednisolone, medrol) for a flare up of your asthma?” The final question regarding persistent asthma asked “Over the past 30 days, have you taken any of the following medications every day for your asthma?” and was followed by a list of controller medications with a yes or no option for each. A comparison of the HEDIS and survey definitions of persistent asthma is given in 

	Patients who completed the baseline surveys were sent follow-up surveys in April, July, and October 2008 (Table 1). Only survey respondents who reported physician-diagnosed asthma on the baseline survey were included in the study.

	The main analyses were directed at (1) identifying the relationships between HEDIS-defined persistent asthma (hereafter HEDIS persistent asthma) and survey-defined persistent asthma (hereafter survey persistent asthma) among patients completing the survey, (2) comparing medical utilization for asthma among patients with versus without persistent asthma, and (3) determining the persistence of persistent asthma over time. Hypothesis testing for comparisons of characteristics among survey responders versus  nonresponders was by means of 

Survey Persistent Asthma Versus HEDIS Persistent Asthma. 

The presence or absence of survey persistent asthma on the baseline survey administered at the end of 2007 was assessed relative to requalification or nonrequalification for HEDIS persistent asthma in 2007 using 

 Persistent Asthma Versus Medical Utilization.

 Hypothesis testing was conducted for the relationship between the presence of survey persistent asthma on the baseline survey at the end of 2007 (year 2) or HEDIS requalification in 2007 and medical utilization for asthma in 2008 (year 3). This was performed by means of 

 Concordance between survey persistent asthma at baseline and on follow-up surveys was evaluated. Among patients who completed all 4 surveys, the proportions of patients with persistent asthma on 0, 1, 2, 3, or 4 surveys were determined.

	Nominal 2-tailed statistical significance for all analyses was set at 

 <.05. All analyses were conducted using SAS version 9.13 for Windows (SAS Institute Inc, Cary, North Carolina).

	A total of 13,833 patients aged 18 to 56 years met the HEDIS criteria for persistent asthma in 2006 and were continuously enrolled in Kaiser Permanente Southern California from 2006 to 2008. Of these, 2895 (20.9%) returned the November 2007 baseline survey; 144 denied a history of physician-diagnosed asthma, leaving a sample of 2751 survey respondents.

	Compared with nonrespondents, respondents were more likely to be female, were older, lived in neighborhoods (census blocks) with higher education and household income, and were less likely to be smokers (

). Respondents experienced fewer exacerbations requiring emergency department visits or oral corticosteroid dispensings and were less likelyto receive more than 6 canisters of short-acting ß-agonists in 2006. In contrast, respondents were more likely to have asthma outpatient visits, to receive asthma controllers,  and to requalify for HEDIS persistent asthma in 2007.

	Of 2751 respondents to the baseline survey, 799 (29.0%) completed all 4 surveys. A total of 455 (16.5%) completed 3 surveys, 422 (15.3%) completed 2 surveys, and 1075 (39.1%) completed only the baseline survey.

Survey Persistent Asthma Versus HEDIS Persistent Asthma

	A total of 2517 among 2751 respondents (91.5%) had survey persistent asthma on the baseline survey. These 2517 patients met the following persistent asthma criteria: (1) symptoms with or without other criteria (74.7%), (2) medications without qualifying symptoms (24.5%), or (3) exacerbations without symptom or medication criteria (0.8%).

	A total of 1764 among 2751 respondents (64.1%) requalified for HEDIS persistent asthma in 2007. Of those who requalified, 97.1% reported survey persistent asthma 

). Patients with survey persistent asthma were significantly more likely to requalify for HEDIS persistent asthma in 2007 than patients without survey persistent asthma (68.0% vs 22.2%, 

 <.001). However, 805 of 987 patients (81.6%) who did not requalify as having HEDIS persistent asthma in 2007 (but who had qualified in 2006) reported survey persistent asthma in 2007.

 Persistent Asthma Versus Medical Utilization

	Compared with patients without survey persistent asthma, patients with survey persistent asthma in year 2 (2007) had significantly more year 3 (2008) asthma hospitalizations or emergency department visits, oral corticosteroid dispensings, and shortacting ß-agonist canisters (

). Similarly, among patients with survey persistent asthma, those who requalified for HEDIS persistent asthma in year 2 had significantly more year 3 medical utilization for asthma (asthma emergency department visits or hospitalizations, oral corticosteroid dispensings, and short-acting ß-agonist canisters) than patients who did not requalify.

	The relationships between survey persistent asthma at baseline and at the first follow-up survey 5 months later are summarized in 

. For this analysis, persistent asthma was based only on impairment and not on risk (exacerbations) because the interval between surveys (5 months) was too short to identify persistent asthma based on exacerbations over the interval (12 months) recommended in the Expert Panel Report 3 guidelines to assess risk.

 Ninety-four percent of 1199 patients who reported persistent asthma at baseline

	also reported persistent asthma on the first follow-up survey.Of 91 patients who did not report persistent asthma on the baseline survey, more than half (51.6%) reported persistent

	asthma on the first follow-up survey (Table 6).

HEDIS-defined persistent asthma is generally consistent with survey-defined persistent asthma over a 3-year period.

Persistent Asthma Defined Using HEDIS Versus Survey Criteria

 To compare the relationship of surrogate markers of asthma control to subsequent asthma exacerbations.

 Administrative data were used to identify patients who met the Healthcare Effectiveness Data and Information Set (HEDIS) criteria for persistent asthma in 2006 and 2007. The following potential surrogate markers of asthma control assessed in 2007 were compared for their ability to predict asthma exacerbations in 2008 (defined as oral corticosteroid dispensing or an asthma hospitalization or emergency department visit): dispensing of any controller, unweighted medication ratio (the ratio of controller to total medication), weighted medication ratio, and the number of short-acting Î²-agonist (SABA) canisters dispensed. Weighted medication ratios were weighted for controller potency and for doses per container.

Meeting the HEDIS criteria for persistent asthma were 8634 patients (60.5% female) aged 18 to 56 years (mean age, 42.7 years), of whom 6.5% experienced emergency hospital care and 27.3% received oral corticosteroids in 2008. The largest effect size for predicting reduced emergency hospital care was for the number of SABA canisters dispensed (odds ratio [OR], 0.49; 95% confidence interval [CI], 0.40-0.60), followed by the unweighted medication ratio (OR, 0.54; 95% CI, 0.40-0.72), and then the weighted medication ratio (OR, 0.57; 95% CI, 0.45-0.73). Dispensing of any controller was associated with a nonsignificant increased risk of emergency hospital care (OR, 1.41; 95% CI, 0.95-2.09).

The number of SABA canisters dispensed is most strongly related to improved asthma outcomes, followed by the unweighted medication ratio; dispensing of any controller is least related. Health plans can use the number of SABA canisters dispensed and the unweighted medication ratio for asthma population management or for provider quality-of-care assessment to reduce asthma exacerbations, which exact a high economic and humanistic cost.

	The following relationships of asthma control to subsequent asthma exacerbations were observed:

		The number of short-acting β-agonist canisters dispensed is most useful to identify at-risk patients for targeted intervention in population management.

		The ratio of controller to total medication can be used as an asthma quality-of-care marker.

		Dispensing of any controller does not seem to be a good marker for population management or for quality of care.

Asthma is a common chronic medical condition that is associated with substantial individual morbidity and cost to society. 

The traditional approach to improving disease outcomes has been by one-on-one physician—patient interactions. Computerization of medical utilization and claims data (“administrative data”) has allowed 2 more recent approaches for asthma control. The first is the use of administrative data to define asthma quality-of-care or performance measures. These measures are used by managed care organizations and others to improve the performance of their providers, with the expectation that improved performance on the measures will lead to improved asthma outcomes and lower costs.

 The most widely used asthma quality-of-care measure is the one developed by the National Committee for Quality Assurance

 to evaluate the performance of health plans, the Healthcare Effectiveness Data and Information Set (HEDIS) measure (“HEDIS measure”). This measure identifies patients with “persistent asthma” based on administrative data criteria and then determines the proportion of these patients who receive at least 1 controller medication dispensing the following year. Although used for approximately a decade, few studies have attempted to validate the HEDIS measure as being associated with improved subsequent outcomes. A study

 in children demonstrated such a relationship, but 3 studies

 in children and adults failed to show that improved performance on this measure is associated with improved asthma outcomes. After a study by Mosen et al

 demonstrated a relationship between the number of consecutive years of HEDIS qualification and markers of persistent asthma, the National Committee for Quality Assurance

modified the definition of HEDIS persistent asthma to require that the administrative data criteria for persistent asthma be met for both the measurement year (the year the measure is being assessed) and the premeasurement year (“2-year HEDIS population”). To date, the HEDIS measure has not been systematically evaluated in this new 2-year HEDIS population.

The second use of computerized administrative data has been for population management. Patients with inadequately controlled asthma are identified based on administrative data criteria, and targeted intervention by mail, telephone, or in-person visits are instituted. In addition to the HEDIS measure of any controller use, 2 other measures have been suggested for use as quality-of-care measures or as measures to identify patients with uncontrolled asthma in need of intervention. The first is the medication ratio, which is the ratio of units of controllers dispensed to the total units of controllers and units of short-acting β-agonists (SABAs) dispensed. A higher medication ratio has been associated with reduced subsequent exacerbations and with better patient- reported outcomes.

This ratio has been used in a weighted form (weighted for doses per container and drug potency) 

 although these 2 ways of using the ratio measure have not been directly compared to date. The second is the number of SABA canisters dispensed per year (“SABA measure”), which has been shown to be a long-term measure of asthma control.

To our knowledge, this SABA measure has not been compared with the HEDIS measure or the medication ratio measure as a predictor of improved asthma outcomes.

The objective of this study was to compare the ability of the HEDIS measure, the medication ratio measure (weighted and unweighted), and a SABA measure to predict asthma exacerbations (defined in 2 different ways) in the 2-year HEDIS population. Asthma exacerbations are particularly appropriate outcomes to use in validating surrogate markers of asthma control because of their large contribution to the cost of asthma care

 and their substantial effect on quality of life. Identifying valid asthma control measures based on administrative data that are associated with reduced asthma exacerbations should allow health plans to use these measures to provide outreach to patients in need of intervention and to offer “inreach” to providers whose patients may be at increased risk for poor asthma outcomes.

This study was approved by the Kaiser Permanente Southern California (KPSC) Institutional Review Board. Using computerized KPSC inpatient, outpatient, pharmacy, and membership records, we identified patients aged 18 to 56 years with continuous enrollment (

1 gap of <45 days’ coverage) in 2006 and with persistent asthma in 2006 based on meeting 1 or more of the following HEDIS criteria: 4 or more asthma medication dispensings, 1 or more emergency department visits or hospitalizations with a principal diagnosis of asthma, or 4 or more asthma outpatient visits with 2 or more asthma medication dispensings. Patients with continuous enrollment in 2007 who requalified in 2007 as having HEDISdefined persistent asthma (ie, met 

1 of these criteria in 2007) who also remained continuously enrolled KPSC members in 2008 are the subjects of this study.

The outcome of interest was asthma exacerbations in 2008. These were identified in the following 2 ways: (1) emergency hospital care for asthma, defined as having at least 1 hospitalization or emergency department visit for which asthma (

] code 493.xx) is the primary diagnosis or is a secondary diagnosis with another respiratory diagnosis coded as the primary diagnosis, or (2) a filled prescription of an oral corticosteroid prescribed within 7 days after an outpatient encounter for asthma (

Nebulized medications were excluded as potential markers of asthma control because dispensed quantities could not be reliably translated into medication units. The following candidate markers of quality asthma care or uncontrolled asthma in 2007 were evaluated as predictors of asthma exacerbations in 2008:

HEDIS Measure (Dispensing at Any Time and in Any Amount of Any Asthma Controller, as Defined by HEDIS,4 Which Is the Current HEDIS Asthma Quality-of-Care Measure). 

These controllers include inhaled corticosteroids, inhaled corticosteroid/long-acting β-agonist combinations,leukotriene modifiers, theophylline, and cromolyn sodium. They do not include SABAs, long-acting β-agonists alone, or oral corticosteroids.

Unweighted Medication Ratio (Unweighted Ratio of Controller to Total Asthma Medication).

 The ratio was calculated for each patient as the number of controller units dispensed during 2007 divided by the sum of the controller units and SABA inhaler canisters dispensed during 2007. For inhalers, 1 controller unit was 1 canister. For oral medications, 1 controller unit was 1 prescription of an amount lasting 30 days or less. Medication ratios range from 0 (no controllers) to 1.0 (no SABAs).

Weighted Medication Ratio (Weighted Ratio of Controller to Total Asthma Medication). 

This ratio was calculated as for the unweighted medication ratio except that controllers were weighted for medication potency and for the number of doses per container to account for potentially important differences in these characteristics between products. The specific weighting algorithm for individual products is available from the authors by request. Examples of weights for common controllers among our patients are 1.0 (montelukast sodium), 1.7 (beclomethasone dipropionate hydrofluoroalkane 80), 2.0 (budesonide 180), and 4.0 (fluticasone propionate 220 and mometasone furoate 220).

SABA Measure (Number of SABA Canisters Dispensed in 2007). 

The total number of inhalational SABA canisters dispensed in 2007 was used for this marker.

Optimal cutoffs for the medication ratio and SABA measures to predict emergency hospital care and asthma exacerbations as defined by oral corticosteroid dispensing were determined. For the medication ratios, cutoffs between 0.3 and 0.9 (at 0.1 intervals) were examined; for the SABA measure, levels of 4 to 12 canisters per 12 months were examined. These levels were chosen to include likely optimal cutoffs based on results of prior studies.

 For each level of the predictor, odds ratios (ORs) and 95% confidence intervals (CIs) were calculated by means of simple logistic regression analysis. The optimal cutoff was determined based on (1) a significant association with a reduced risk of the outcome (upper 95% CI <1) and (2) the lowest OR associated with a significant reduction.

Optimal cutoffs for the unweighted medication ratio, weighted medication ratio, and SABA measure were then compared with the results for the HEDIS measure (dispensing of any controller) and with each other based on the magnitude of the significant effect sizes (calculated as 1 minus the OR for significant relationships). Predictor status of all patients was defined and was used in the analyses of each measure. All analyses were performed using commercially available statistical software (SAS version 9.13 for Windows; SAS Institute, Cary, NC).

Of 2,365,947 KPSC members 18 years and older in 2006, a total of 14,856 (age range, 18-56 years) met the HEDIS criteria for having persistent asthma in 2006 and were conntinuously enrolled in 2007 and 2008. Of these patients, 8634 (58.1%) requalified as having persistent asthma in 2007 (mean [SD] age, 42.7 [10.9] years; 60.5% female). Of these 8634 patients, 558 (6.5%) experienced an exacerbation as defined by emergency hospital care for asthma in 2008, and 2361 (27.3%) experienced at least 1 asthma exacerbation as defined by oral corticosteroid dispensing linked to an asthma encounter.

 Odds ratios for emergency hospital care decreased with increasing unweighted and weighted medication ratio cutoffs (

). Odds ratios for emergency hospital care for any given ratio cutoff were lower (effect size larger) for the unweighted ratio compared with the weighted ratio. The optimal cutoff for the unweighted and weighted ratios was 0.9 or higher, with an OR of 0.54 (95% CI, 0.40- 0.72) for the unweighted ratio and an OR of 0.57 (95% CI, 0.45-0.73) for the weighted ratio.

Oral Corticosteroid Dispensing—Defined Asthma Exacerbations.

 Odds ratios for oral corticosteroid dispensing— defined asthma exacerbations also decreased with increasing unweighted and weighted medication ratio cutoffs and for any given ratio cutoff were lower (effect size larger) for the unweighted ratio compared with the weighted ratio (

). However, unweighted ratio cutoffs of 0.3 or higher and 0.4 or higher were associated with increased risk of asthma exacerbations, and only an unweighted ratio cutoff of 0.9 or higher was associated with significantly reduced risk of oral corticosteroid dispensing (OR, 0.78; 95% CI, 0.68-0.90). In contrast, weighted ratio cutoffs between 0.3 and 0.8 were associated with increased risk of asthma exacerbations as defined by oral corticosteroid dispensing, and a weighted ratio cutoff of 0.9 or higher neither significantly increased nor decreased the risk.

All levels of SABA dispensing cutoffs were associated with reduced risk of emergency hospital care and oral corticosteroid dispensing—defined asthma exacerbations, although ORs were lower for emergency hospital care than for asthma exacerbations as defined by oral corticosteroid dispensing (

). The optimal cutoff for emergency hospital care was less than 11, with an OR of 0.49 (95% CI, 0.40-0.60) and for oral corticosteroid dispensing was less than 12, with an OR of 0.64 (95% CI, 0.56-0.73).

Fewer short-acting agonist canisters dispensed (but not dispensing of any controller) and higher ratio of controller to total medication are associated with reduced asthma exacerbations.

Shiva G. Sajjan, PhD

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