Using Information Technology to Improve Asthma Adherence
Using Information Technology to Improve Asthma Adherence
The purpose of this study is to determine whether providing patient medication adherence
 information on inhaled corticosteroid use to clinicians will result in improved patient
 adherence and asthma control.
In 2001 an estimated 31.1 million people in the United States reported ever having had an
 asthma diagnosis. Asthma is a leading cause of preventable hospitalizations, and it accounts
 for an estimated 14 million days of missed school and 100 million days of restricted activity
 yearly.

 The routine use of anti-inflammatory medications, particularly inhaled corticosteroids (ICS),
 in the treatment of asthma can markedly improve symptoms and reduce complications. Yet,
 evidence suggests that these medications are under-prescribed by physicians and poorly taken
 by patients. For example, in one study of asthma patients enrolled in a large, California HMO
 only 71.7% of patients with severe symptoms reported having a steroid inhaler, and only 53.6%
 of those reported using it daily in the preceding month. Using electronic monitoring devices
 to record inhaler use, researchers have estimated that patients use their ICS as directed 20
 to 73% of the time. Using claims-based measures of adherence we have shown that adherence to
 inhaled steroids is inversely correlated with the frequency of oral steroid use and
 asthma-related emergency room visits. In addition, these measures suggest that non-adherence
 to ICS is an independent predictor of asthma-related hospitalizations. In our study
 population, we estimated that 60% of asthma-related hospitalizations were attributable to
 poor adherence to ICS. Together these findings suggest that increasing ICS use may improve
 asthma outcomes.

 Studies employing health-behavioral models of adherence suggest that medication adherence is
 associated with treatment-related concerns regarding complications, efficacy, and benefits.
 Unfortunately, the results of behavioral and educational interventions to improve adherence
 have been disappointing. Despite, in some cases, considerable time spent with patients, these
 interventions have at best resulted in modest adherence improvements. Given the time,
 training, and resources required to implement these interventions, they are unlikely to be
 widely adopted in the clinical setting. Some recent studies, however, suggest that providing
 adherence data to clinicians may improve patient adherence. In one, clinicians gave repeated
 feedback to patients regarding ICS adherence; this resulted in sustained improvements over
 the study period. Unfortunately, this small study did not find differences in asthma
 outcomes.

 In this proposal we seek to test an asthma adherence intervention specifically designed for
 use in the clinical setting. Adherence measures will be generated by linking currently
 available electronic data. In this cluster-randomized trial, primary care physician-practice
 groups will be randomized to receive asthma medication adherence information electronically
 for patients with asthma associated with these practices. In addition to ICS adherence
 information, clinicians in intervention practices will have data on patient beta-agonist use
 to better tailor ICS therapy to disease severity.

 Eligible patients with asthma will be identified prior to randomizing practices and will be
 invited to participate. Patient surveys will be sent in the pre-intervention survey and in
 the post-intervention period. Patient-level outcomes will be assessed through the medical
 record, patient surveys, and claims data.

 We will perform an intention-to-treat analysis with all eligible patients identified
 pre-randomization included in the analysis (the primary analysis). This study is powered to
 allow for only 60% of the eligible patient population being seen within the first 6-months
 (i.e., no effect in 40% of the patient population). As a secondary analysis, we will perform
 a modified intention-to-treat (or per protocol) analysis, whereby we will analyze the results
 of only those patients in both study arms seen within the first 6-months of the intervention.
Inclusion Criteria (patient-level):

 -  Age 5-56 years

 -  Physician diagnosis of asthma

 -  Continuous HMO enrollment with prescription drug rider

 -  Electronic prescription of an inhaled corticosteroid

 Exclusion Criteria (patient-level):

 -  Diagnosis of chronic obstructive pulmonary disease

 -  Diagnosis of congestive heart failure

 Inclusion Criteria (practice-level):

 -  Primary care practice (i.e., pediatrics, family practice, or internal medicine) within
 the health system. A practice is defined as a group of physicians who by virtue of
 speciality or geography care for a relatively contained population of patients and who
 cross-cover the care of these patients.

 Exclusion Criteria (practice-level):

 -  None