Assessing asthma severity based on claims data: a systematic review.

Area of Science:

• Health economics
• Epidemiology
• Health services research

Background:

• Asthma is a prevalent chronic condition in Germany, necessitating accurate cost evaluations.
• Economic assessments of asthma require data on disease severity, often absent in standard health insurance claims.
• Developing algorithms is crucial for utilizing claims data to determine asthma severity.

Purpose of the Study:

• To systematically review international literature for algorithms stratifying asthma patients by severity using claims data.
• To identify existing methods for assessing asthma severity within health insurance claims databases.

Main Methods:

• A comprehensive systematic literature review was performed in September 2015.
• DIMDI SmartSearch, encompassing multiple databases (BIOSIS, MEDLINE, EMBASE), was utilized.
• Studies categorizing asthma patients by severity using claims data were identified.

Main Results:

• 54 publications were identified that assessed asthma severity using claims data.
• 39 studies employed standardized algorithms like HEDIS, Leidy, GINA, or CACQ.
• 16 studies utilized varied criteria, including diagnoses, prescriptions, and hospitalizations.

Conclusions:

• No definitive best practice exists for asthma severity categorization using claims data.
• A combined algorithmic approach appears pragmatic for severity assessment.
• Direct transfer to the German context requires consideration of specific claims data characteristics.