Doug Hamaker NEDSS Coordinator Division for Prevention and Preparedness

1. Reengineering the BioSense Data Feed to Support State Notifiable Conditions Reporting Requirements in Texas Doug Hamaker NEDSS Coordinator Division for Prevention and Preparedness Texas Department of State Health Services May 28, 2008

2. Project Beginnings Would it be possible to tap into an existing BioSense data stream in order to leverage data originally supporting biosurveillance and re-purpose it to provide electronic laboratory reporting (ELR) of notifiable test results ? ? ? ? If so, could it provide a proof-of-concept pathway for other States to benefit from?

3. Project Partnership • Christus Health • CDC • BioSense • NEDSS • SAIC • Constella Group • Texas DSHS

4. Christus BioSense/ELRProject Overview • Dual Use of Data • Biosurveillance extended to promote Case Reporting • Data sources • Foundational, Clinical, Laboratory, Pharmacy, and Radiology • BioSense Integration engine • Converts heterogeneous messages from multiple facilities • Infrastructure – Christus BioSense • 11 Hospitals enrolled, 4 sending lab result data • Standards employed • HL7 v2.5 • PHINMS for message transport

5. Biosurveillance Secondary use of data already collected within a healthcare organization, such as diagnosis codes, free-text chief complaints, laboratory orders/results Assigned to one or more disease syndromes. Counts of records in the various syndrome groups are analyzed to determine when excess numbers are reported. Obvious patient identifiers excluded; data is anonymized prior to transmission Traditional Disease Case Surveillance Makes use of pre-specified definitions of notifiable conditions Includes data collection of positive laboratory and clinical findings. Reporting mandated by state law/regulation, Personally identifiable Health care providers, laboratories report to local HD (county or regional) County HD submits notifiable reports to State, State to CDC System Attributes of Biosurveillance and Traditional Case Surveillance

6. Project Purpose and Benefits • Extends existing infrastructure developed via BioSense • Builds/expands electronic laboratory reporting of lab results indicative of notifiable conditions • BioSense integration exists at a healthcare system level -- connects multiple facilities for ELR reporting

7. Message Creation Message Creation Message Creation Message Creation Message Transport Message Transport Message Transport Message Transport Message Consumption Message Consumption Message Consumption Message Consumption Message Consumption Message Consumption Message Consumption Message Consumption ELR Message Mechanics BioSense Integrator PHINMS Texas ELR System

8. Texas ELR Messaging Flow • ELR message is received from Laboratory • Native format is transformed to HL7 v2.3.1 • Vocabularies are validated and/or used to transform local codes to standard codes, which are dependent on • HL7 specification • ELR Implementation Guide • PHIN VADS • Program Area addendums

9. Texas ELR Routing • Message payload is interrogated and routed to appropriate systems according to matching criteria • HIV/STD test results to HIV/STD system • Core communicable disease results to NBS • Further transformation may occur immediately prior to final routing in order to meet individualized requirements of each system (STD*MIS, NBS, etc.), such as • Format (HL7 versus ASCII) • Content (Use of standard versus local codes)

10. Texas ELR Route

11. Preparation for BioSense Project “The MOU” • Describes the relationship between the healthcare system and the public health agency • Addresses HIPPA concerns • Clearly states the legal authority for the provision of data public health reporting

12. Comparison of Message Content • Gap analysis showed numerous (minor) differences in the HL7 content • Patient name/demographic is a very important component within ELR, and is missing in the standard BioSense message • Requires a circle-back for those messages fitting the BioSense ELR filter of results indicative of a notifiable condition • Beyond patient/demographics, differences can be handled within the mapping layer within ELR message processing system located at the State DOH office.

13. Defining What is Reportablefrom the BioSense Data Feed • State and local reporting rules extend beyond the list of nationally notifiable conditions • Determine the list of tests performed within the health care system indicative of a notifiable condition • Microbiology test results

14. Programmatic Tasks • Review Federal and State rules and regulations • MOU between Hospital and CDC • MOU between Hospital and State Health Department • Established list of required data fields and data content • NEDSS ELR Messaging Guide vs. BioSense Specification Guide

15. Technical Tasks • Determine data flow • Split data stream in the BioSense Integrator • Filtering Positive Microbiology Test Results • Re-Identifying de-identified data • Implement standards-based transmission of data from BioSense to State NEDSS • State consumption of ELR messages from the BioSense Integrator

16. Behold the Benefits of Standards! BioSense and NBS both use: • Industry Standards and Industry Tools • HL7 2.5 Message Standard • Orion Rhapsody integration broker toolset • Common Messaging Transport • PHINMS – send/receive • Message security is paramount • Standardized vocabulary

17. Status • BioSense data flowing to CDC • BioSense lab results reporting: • Message mapping for State consumption • Successful routing of “test” data through the mapping process and into the NEDSS data system • Initial development of evaluation process • Timeliness, completeness • Changes to the Business Process /Reporting Efficiency

18. Findings (thus far…) • Emphasizes the adoption and promotion of standards-based Electronic Laboratory Reporting • Fosters integration of public health case surveillance and health information systems • Facilitates a ready exchange of data • Opportunistic implementation of ELR for traditional case surveillance • Supports the development of a “Proof of Concept” that would be readily adoptable in other states with NEDSS-compliant data systems

19. One Final Note: A huge THANKS to Scott Danos Senior Advisor, Division of Integrated Surveillance Systems & ServicesNational Center for Public Health Informatics and congratulations on his retirement!