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Monday, August 1, 2011

Using large population metrics to improve asthma outcomes

In this month’s issue, Schatz and Zeiger (J Allergy Clin Immunol 2011;128: 273-277) bring us validation results comparing administrative and clinical tools for assessing asthma outcomes from a Kaiser Permanente patient population. They describe their assessment experience in two primary areas: population management and quality of care.

The authors look at three elements of population management, beginning with the definition of persistent asthma. They use the modified, 2-year (current year and previous year) Health Effectiveness and Data Information Set (HEDIS) and compare it to a 2007 patient survey based on the EPR3 clinical definition. Schatz and Zeiger find that the majority of patients with HEDIS-defined persistent asthma in 2006 reported clinically defined persistent asthma in 2007, demonstrating that 2-year HEDIS definition correlates well with the EPR3 definition. Next they assessed impairment based on comparison of the administrative data on SABA use in the past 12 months and telephone-implemented Asthma Control Test (ACT), again finding useful convergent and predictive correlation between the two. Lastly, they assessed administratively defined risk with clinical risk, correlating healthcare utilization in the past 12 months and pharmacy data, then evaluated the predictive power of several different asthma control questionnaires. Of note, Schatz and Zeiger find that any one asthma questionnaire was a sensitive as the others for predicting exacerbation and suggest that using only one questionnaire is sufficient to detect risk.

Finally, the authors address quality of care metrics and evaluate an administrative data outcome called the medication ratio measure, which is defined from pharmacy data as ratio of controller medications to total asthma medications (controllers + relievers) dispensed in a 12-month period. Their results show that patients with a ratio of 0.5 or higher were significantly less likely to require emergent hospital care and were more likely to report higher quality of life than patients with a ratio of less than 0.5.

In conclusion, Schatz and Zeiger comment that administrative outcome data and survey data appropriately reflect asthma severity, impairment, risk and quality of care in a large patient population. They note that generalizability of their findings may require additional research in order to capture disparities among specific populations. Further, they suggest that individual or group practitioners would benefit from the application of any single outcome measure validated in their large population study.

Dr. Schatz will be talking about this article as part of our next podcast, “Reducing Asthma Burden.” Look for it on starting August 15.

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