Predicting Patient-Reported Asthma Outcomes for Adults in Managed Care

stantial effects on individuals, the healthcare system, and society, accounting annually for 2 million emergency department (ED) visits, more than 400 000 hospitalizations, 4500 deaths, 2 million lost work days, and a cost of $6 billion. The enormous burden of asthma on patients and society in part reflects the undertreatment of patients at risk of poor outcomes. Therefore, there is a need for screening tools to identify patients needing closer scrutiny of their therapeutic regimen. Screening populations to identify higher-risk individuals for disease management programs can improve efficiency of resource use and lead to cost savings. In managed care, there are opportunities to improve asthma care, particularly with medication use. Programs that identify high-risk patients and direct them to certain interventions have achieved improved outcomes. Most risk models for asthma have focused on using physiologic and clinical data to predict clinical outcomes, including mortality, hospitalization, ED use, and relapse. Some recent work has focused on developing tools to predict patient-reported outcomes, including health-related quality of life, adherence, satisfaction, and work disability. This emphasis is important, as the perspectives of varied stakeholders, such as employers, patients, clinicians, disease management companies, and health plans, support the need for developing models that predict a broader range of outcomes. Managed care organizations (MCOs) have a financial incentive to intervene to prevent hospitalizations and ED use. Employers may find lost work days to be the most relevant outcome. Patients’ quality of life and satisfaction with care may be affected most by symptom reduction. The objective of this study was to develop a brief set of patient-reported questions that could be used to predict a broad array of outcomes, including severe symptoms, reduced activities, ED use, and hospitalization. We developed and assessed the performance of 5 asthma risk models, based on a common set of survey questions, to predict these outcomes in patients enrolled in managed care.