Administrative claims data provides tremendous utility in analyzing specific real world questions; however, as noted by the ISPOR Task Force for Retrospective Database Analysis, many research questions require information beyond the scope of claims-based databases. The CHIEF Study was designed to capture complementary survey data to supplement an existing claims database for evaluating how household cases of influenza impact employee productivity. Leveraging existing relationships with three large employers, the CHIEF Study links monthly web-based surveys collected during the 2007-2008 influenza season with administrative claims from the MarketScan Databases. Three employers, which include a national retail chain, a transportation company, and a durable goods manufacturing company, participate in CHIEF. Participant eligibility was based on having at least one child aged £17 years with employer-sponsored health insurance that lives in household ³4 days per week. A total of 3686 employees completed the web-based screening questionnaire; 2295 (62%) of employees were eligible for study participation. Each month between October 2007 and May 2008, participants receive an email with an electronic link to the survey. The baseline surveys include questions about demographic, health status and health behaviors of all household members as well as the employee's workplace characteristics, absenteeism and presenteeism. The average household includes 2.08 adults and 1.85 children. Employees are approximately 40.77 years old and are predominately full-time workers (81.91%). Monthly surveys include questions about the presence of influenza in the household, the impact of influenza on employee productivity and influenza-related health care use. The completion rate for the first and second monthly surveys was 97.2% (n=2230) and 96.5% (n=2213) respectively. Prospective examination of household illness, absenteeism and presenteeism linked with administrative claims data is feasible and provides an opportunity to understand the impact of disease on indirect costs. This information can provide more credibility to future economic analyses and decision making.