Assessing Medicaid Claims Data as an Additional Data Source for Surveillance

1. Assessing Medicaid Claims Data as an Additional Data Source for Surveillance Rachel Wiseman, MPH Texas Department of state health services Andy mauney; Jeff Taylor, MPH; Kristen kellogg; Katelyn hammond

2. Project Objectives • Identify previously unreported cases of select notifiable conditions • Determine if Medicaid data can be used as additional surveillance source • Volume of unreported patients by condition • Effort required to evaluate unreported Medicaid claims • Percent change in disease counts by adding Medicaid data

3. Methods Request all Medicaid inpatient claims data for six month period Identify Medicaid patients with ICD-9 codes for selected notifiable conditions Search NBS for patients identified in Medicaid Request medical records for all unreported Medicaid patients Determine if patient meets CSTE case definition Add patients that meet case definition to NBS Educate facilities on reporting requirements

4. January-June 2012 Results *Applied to case count for same time period. ^Applied to case count for cases <1 year old.

5. Analysis of Objectives

6. Lessons Learned • Medicaid claims data has potential for disease surveillance • Billing data prone to errors • Vaccine administration miscoded as disease • Patients/dates of service not found by facilities • Programming ICD-9 codes correctly is CRITICAL • Gaps in providers reporting varicella patients

7. Project Validation and Expansion Measure same objectives Use same methods Expand the number of notifiable conditions evaluated Validate chickenpox findings, expand age group Use different six month period

8. July-December 2012 Results *compared to same six month period in same age group

9. Varicella Comparison *Compared to Jan-Jun 2012 for cases <1 year old ^Compared to July-Dec 2012 for cases <19 years old • Seasonality, vaccine may explain difference in Medicaid claim volume • Shingles diagnoses miscoded as chickenpox may explain difference in percent meeting case definition • These factors do not explain difference in percent increase to case count

10. Analysis of Objectives

11. Lessons Learned, Again • Medicaid claims data has potential for disease surveillance • Perhaps only for specific diseases: varicella, tetanus • Billing data still prone to errors • Coding is VERY loose • Example: No distinction between acute disease (paralytic polio) and chronic disease (sequelae from polio 30 years ago) • Still gaps in providers reporting varicella patients

12. Conclusions • Medicaid claims data can identify previously unreported cases of select notifiable conditions • Varicella, tetanus • Medicaid data can be used as additional surveillance source • Volume of unreported patients by condition is variable • Does not necessarily reflect burden of disease • Effort required to evaluate unreported Medicaid claims is low for most conditions • Percent change in disease counts by adding Medicaid data is variable

13. Next Steps Done: Implemented monthly investigation into Medicaid claims for varicella (<19 years old) and tetanus To Do: Pilot pertussis project to feed “real time” claims data directly into NBS for investigation by health departments Create plan for addressing deficiency in chickenpox reporting in a systematic fashion Explore claims for vaccines to enhance vaccine history capture Explore hepatitis B claims with prenatal visit claims

14. Special Thanks To Texas Medicaid & Healthcare Partnership for providing us with access to Medicaid data To the University of Texas Public Health Internship program, specifically to Dr. Leann Field and Andy Tang.