The American Journal of Managed Care June 2011
Costs of Asthma Among US Working Adults
Objectives: To evaluate the effect of asthma on direct and indirect costs among US working adults.
Study Design: A case-control retrospective analysis was conducted. Data between January 1, 2003, and December 31, 2006, among patients aged 18 to 64 years with vs without asthma were extracted from MarketScan Research Databases. Patients with chronic obstructive pulmonary disease or emphysema were excluded, and all patients were required to have 12-month continuous enrollment before and after the index date. Outcomes included direct medical costs, the number of absence days, the number of short-term disability days, and associated indirect costs.
Methods: Patients with asthma were propensity score–matched to patients without asthma using nearest neighbor 1:1 with caliper. Subsequent multivariate analysis was conducted on matched samples to examine the marginal effect of asthma on direct and indirect costs.
Results: A total of 13,379 patients with asthma were propensity score–matched to 13,379 patients without asthma; in each cohort, 3453 patients had absence eligibility, and 8497 patients had shortterm disability eligibility. Direct costs for patients with asthma were $3762, and indirect costs were $4572. Compared with the matched cohort without asthma, patients with asthma had $1785 higher direct medical expenditures (P <.001). Incremental indirect costs were $191 for absenteeism (P = .007) and $172 for short-term disability (P <.001).
Conclusions: Compared with patients without asthma, patients with asthma experience significantly higher direct medical costs and, although modest, significantly higher work loss. Treatments or interventions that prevent or reduce asthma symptoms may have a beneficial effect on medical costs and work absenteeism.
(Am J Manag Care. 2011;17(6):409-416)
Asthma has profound effects on medical costs and work productivity.
- Patients with asthma experienced significantly higher direct medical costs and modestly higher work loss than patients without asthma.
- Treatments or interventions that prevent or reduce asthma symptoms can potentially have a beneficial effect on medical costs and work absenteeism.
The annual cost of asthma is estimated to be almost $18 billion, of which $10 billion is owing to direct costs and $8 billion is owing to indirect costs.3 In 2002, 11.8 million workdays and 14.7 million school days were missed because of asthma.2 Previous studies have shown that asthma significantly increases direct and indirect costs. Cisternas et al4 estimated costs using a cross-sectional survey of 401 adult patients in northern California and found that total annual costs for patients with\ asthma averaged $4912, with 65% in direct costs and 35% in indirect costs. For indirect costs, total cessation of work accounted for 61% of costs, and loss of entire workdays among those who remained employed accounted for 28%. In another study that assessed costs of asthma to an employer between 1996 and 1998, Birnbaum et al5 found that for employees with asthma having disability claims total medical costs were approximately 3 times higher than those for employees without asthma. Furthermore, among employees with asthma, wage replacement costs for workdays lost as a result of disability and sporadic absenteeism (40%) accounted for almost as much as medical costs (43%). Both of these studies lacked generalizability, as the study by Cisternas et al focused on a specific geographic region and the study by Birnbaum et al was based on a single employer assessing workers with asthma who had filed disability claims. In addition, Cisternas and colleagues used self-reported measures to estimate costs instead of claims, which can be a more reliable measure. Colice et al6 studied patients with persistent asthma among 17 large self-insured companies in the United States using a claims database; the study period was 2001 to 2003, and indirect costs were drawn from only 9 companies. Their study found that patients with persistent asthma had $4412 more in annual total medical costs and $924 more in work loss compared with patients without asthma. The objective of the present study was to evaluate the incremental direct and indirect costs incurred by patients with asthma compared with patients without asthma using more recent data that are representative of typical US working adults.
Two Thomson Reuters MarketScan Research Databases (http://thomsonreuters.com/), the Commercial Database and the Health and Productivity Management Database, were used in this study. These are large national databases constructed from paid medical and prescription drug claims of privately insured enrollees working for self-insured employers and their spouses and dependents. The data cover all US census regions and are representative of the US population with insurance provided by large employers. The Commercial Database contains inpatient, outpatient, and outpatient prescription drug experiences of 31.9 million enrollees and their dependents in 2006, covered under various fee-for-service and capitated health plans, including exclusive provider organizations, preferred provider organizations, point-of-service plans, indemnity plans, health maintenance organizations, and consumer-driven health plans. The Health and Productivity Management Database contains workplace absence, short-term disability, and workers’ compensation data, which can be linked to medical and pharmacy data in the Commercial Database. The databases are unique because they allow examination of direct and indirect costs of patients by linking employees’ medical and pharmacy claims to productivity data. Between 1997 and 2006, 41 employers covering more than 2.2 million employees have contributed to the Health and Productivity Management Database. Both the Commercial Database and the Health and Productivity Management Database were deidentified in compliance with regulations of the Health Insurance Portability and Accountability Act of 1996.
This study used a case-control design with retrospective claims analysis to compare direct and indirect costs between patients with asthma and their controls. To ensure that the difference between patients with vs without asthma represented the incremental direct and indirect costs, the groups were matched on patients’ demographic and clinical characteristics using propensity score–matching techniques. This assured that the groups were composed of patients with similar factors likely to affect the outcomes; therefore, differences in costs between these 2 groups were attributable to the presence of asthma.
All patients aged 18 to 64 years were identified as having asthma if they met 1 of the following criteria: (1) at least 1 inpatient stay or emergency department visit with asthma (International Classification of Diseases, Ninth Revision, Clinical Modification code 493.xx, excluding 493.2) listed as the principal diagnosis, (2) at least 2 outpatient visits on 2 unique dates with asthma listed in any diagnosis field, or (3) at least 1 outpatient visit with asthma listed in any diagnosis field and at least 1 asthma medication prescription between January 1, 2003, and December 31, 2005. Patients with any claim for chronic obstructive pulmonary disease (COPD) or emphysema at any time between January 1, 2002, and December 31, 2006, were excluded from the study because COPD and emphysema are also chronic lung diseases that affect patients’ airways. Some of the medications used for asthma are also used for COPD and emphysema. Including patients with COPD or emphysema would have made it challenging to single out the effect of asthma on drug costs and total costs. The index date was the first asthma diagnosis or treatment claim date. All patients were required to be continuously enrolled with medical and pharmacy benefits for 12 months before (baseline period) and 12 months after (follow-up period) the index date.
The control group comprised patients aged 18 to 64 years without asthma diagnosis or treatment as already defined and without COPD or emphysema from January 1, 2002, to December 31, 2006. Patients in the control group also had 12-month continuous enrollment before and after the index date. The index date for patients without asthma was assigned based on the distribution of index dates among patients with asthma. The number of days between January 1, 2003, and the index date for patients with asthma was calculated for each patient with asthma, giving a range in the number of days (this range of days was referred to as the interval pool). The index date for patients without asthma was January 1, 2003, plus a random number drawn from the interval pool. After this assignment, patients with vs without asthma had similar distributions in the number of days between January 1, 2003, and the index date. Patients with vs without asthma were required to have productivity (Health and Productivity Management Database) data.
The primary outcome measures in this study were direct medical costs and indirect costs associated with absence or short-term disability. Analysis of direct costs was performed for patients with complete medical and pharmacy claims. Direct costs were measured as total reimbursed amount, including patient copayment and deductibles. Total cost and its components (inpatient admissions, emergency department, outpatient, and pharmacy) were calculated from medical and pharmacy claims. All direct costs were inflated to 2006 US dollars using the medical service component of the Consumer Price Index from the Bureau of Labor Statistics (http://www.bls.go /cpi/). Healthcare utilization was also summed for the 12-month follow-up period for all services.
Outcome measures for the analysis of indirect costs included the number of absence days from work, the number of short-term disability days, and associated indirect costs. Indirect costs were calculated for a subset of patients with full-time employment and absence or short-term disability eligibility during the 1-year follow-up period. Part-time workers were excluded from the analysis of indirect costs because absenteeism benefits offered to part-time workers may differ from those offered to full-time workers, and this would affect the absenteeism pattern. In addition, part-time workers are usually not eligible for short-term disability, and calculation of short-term disability days and costs would not have been possible. For absence and short-term disability data fields, the start and end dates and the number of hours are reported in the Health and Productivity Management Database. The number of absence days and the number of short-term disability days were estimated as the number of hours absent or under short-term disability divided by 8 hours (equivalent to a typical working day). Indirect costs associated with absence were estimated as the number of absence days multiplied by age-, sex-, and region-specific wage rates from a 2006 population survey conducted by the US Census Bureau for the Bureau of Labor Statistics.7 Because there is wide variation in short-term disability benefits depending on the size of a company and an employee’s length of employment and no universal benefit rule, indirect costs associated with short-term disability were estimated using 75% of the wage rates in the base scenario. Sensitivity analysis was performed using 50% and 100% of the wage rates to examine the effect of short-term disability benefit on indirect costs.
Propensity score matching of patients with vs without asthma was conducted using demographic characteristics (eg, age, sex, geographic region, and plan type) and clinical characteristics (Charlson Comorbidity Index and diagnoses of cancer, hypertension, heart disease, osteoarthritis, osteoporosis, stroke, depression, anxiety, diabetes, and pregnancy), as well as index year and type of industry. Although matching of patients with vs without disease is a different application of propensity score matching, it has been used in other published studies.8-10 Matching was performed using nearest neighbor 1:1 with caliper, which was defined as one-fourth
of the estimated standard errors of propensity scores. Three sets of propensity score matching were conducted as follows: (1) for all patients with medical, pharmacy, and productivity data to examine their direct costs; (2) for a subset of patients with absence eligibility to examine absence days and associated cost; and (3) for a subset of patients with short-term disability eligibility to examine short-term disability days and associated cost.