Evolution of Integrated Surveillance in the United States

1. Evolution of Integrated Surveillance in the United States Scott J.N. McNabb, Ph.D., M.S. Ruth Ann Jajosky, D.M.D., M.P.H. Robert Fagan Scott Danos, M.P.H. Program Briefing April 29, 2008 Division of Integrated Surveillance Systems and Services National Center for Public Health Informatics Coordinating Center for Health Information and Service Centers for Disease Control and Prevention The findings and conclusions in this presentation are those of the authors and do not necessarily represent the views of the Centers for Disease Control and Prevention.

2. McNabb, S.J.N., D. Koo, R.W. Pinner, and J.D. Seligman. Informatics and Public Health at CDC. MMWR. Dec. 22, 2006. 55(Sup02);25 – 8.

3. Fundamental Theorem of Medical Informatics (Charles Friedman) Informatics is as much about people as it is technology In practice, people and technology are in an interactive partnership 3

4. Perspectives & Points-of-View

5. What is case reporting? Actions taken by providers* to recognize and report a condition of public health significance** to a local, county, or state public health agency * physicians, infection-control, laboratories ** required by law or not

6. What is case notification? • Actions taken by a U.S. State or Territorial Health Department to recognize a case of public health significance at the federal level and notify the federal public health system (e.g., through the National Notifiable Diseases Surveillance System [NNDSS]) • Actions taken by a local, state, and national agency to recognize a public health emergency of international concern (PHEIC) and notify the World Health Organization

7. Case Report Reusable data elements can be mapped Case Notification Jajosky RA and Groseclose SL. Evaluation of reporting timeliness of public health surveillance systems for infectious diseases, BMC Public Health. 2004 Jul 26;4:29.

8. Clinical Information Subject Information Reporter/Health Care Provider Information Clinical Information

9. Diagnostic Information Reporter/Health Care Provider Information Subject Information Clinical Information Clinical Information

10. Epidemiologic Information

11. Epidemiologic Information

12. What does Integrated BioSurveillance Mean? In the process sense of the word, the term integrating BioSurveillance means achieving N – 1 systems through which CDC is notified of outcomes of national public health significance.

13. Integrating BioSurveillance(by interoperating the silos) reporting E A B C D

14. What does Integrated BioSurveillance Mean? In the process sense of the word, integrating BioSurveillance means working to achieve efficient and effective public health work practices that are supported by interoperable information systems to detect, register, confirm, report, and analyze health outcome data while visualizing and reporting out messages that guide [and are guided by] acute and planned responses.

15. What does Integrated BioSurveillance Mean? In the end-state sense of the word, integrated BioSurveillance means a person-based, longitudinal registry of public health data built from case reports vis-à-vis an event-based one.

16. What does Integrated BioSurveillance Mean? In the end-state sense of the word, integrated biosurveillance means one set of standards for "bringing together" or interoperating existing or new data streams; one sign-on, data-entry once, and one system that allows individual access from any computer; one source and set of individualized public health tools for customized data views, command sets, and public health management; one set of guidelines for establishing and managing databases; one-stop shopping for information in public health informatics and one source about integration of public health information for all users; one grid with one access to all information, but all information is not stored in one place; one medicine (i.e., health without regard to species differences); yet one size does NOT fit all.

17. National Notifiable Diseases Surveillance System (NNDSS) Ruth Ann Jajosky, D.M.D., M.P.H.

18. What is the NNDSS? (1) • State-based public health surveillance system • Based upon a list of Nationally Notifiable Infectious Diseases (NNID) • There are approximately 77 NNID • Unifying principle: regular, frequent, and timely information is necessary for prevention and control of NNID • Council of State and Territorial Epidemiologists (CSTE) • Collaborates with CDC in the administration of the NNDSS • Represents collective voice of epidemiologists in the States and Territories on issues involving public health practice • Through CSTE position statement process, they document policy decisions • Annually approve changes to NNID list and national surveillance case definitions

19. What is the NNDSS? (2) • 57 reporting jurisdictions report data to CDC each week • All U.S. states, NYC, Washington DC, 5 U.S. territories • No personal identifiers sent • States report data voluntarily to CDC • The list of NNID can change each year • Disease reporting is mandated only at the local or state level • The list of reportable diseases is different in each state • U.S. Constitution gives the State Health Officer the authority for public health • CDC assumed responsibility for collection and reporting of NNID in 1961

20. NNDSS Background • At the federal level, the data are used to: • Monitoring trends • Monitoring the effectiveness of prevention and control activities • Program planning and evaluation • Policy development • Research • At the state level, the data are also used as indicated above but also to implement immediate public health action (disease prevention and control activities) • Some NNID are reported to the World Health Organization (WHO) • Public Health Emergencies of International Concern (PHEIC), under the revised International Health Regulations

21. Major NNDSS Products • MMWR Tables I and II • MMWR Table IV (HIV/AIDS, TB data) • MMWR Figure I • MMWR Summary of Notifiable Diseases, U.S. • NNDSS Link (AVR tool) • Annual reporting requirements assessment • Policies and procedures • Data-stewardship agreements, standardized case definitions, residency rules, publication criteria, etc. • NNDSS case definitions web site

23. NNDSS Data • Summary data in National Electronic Telecommunications System for Surveillance (NETSS) format (beginning 1951) • Case-specific data in NETSS format (1992 to 2008) • Two data conversion processes • National Electronic Disease Surveillance System (NEDSS)- to-NETSS conversion • NEDSS-base system (NBS) data from 16 states (core and disease-specific data) • Supports current publication and analytical needs • NETSS-to-NEDSS conversion • Supports analyses of data in Data Marts • Complex transition converting systems and data • Quality control and quality assurance • Resource intensive • Steep learning curve for data analysts

24. Terms • NNDSS • State-based public health surveillance system • National Center for Public Health Informatics compiles the data which becomes the official U.S. statistics for this system • NETSS • Legacy message format for data reported to CDC for selected NNDSS conditions • CDC-developed surveillance information system • NEDSS • New message format for data reported to CDC for the NNDSS and other systems • CDC-developed a surveillance information system (NBS) • There are other dimensions (NEDSS discussion later in presentation)

25. What’s the difference between NNDSS, NETSS, NEDSS, and NNDSS Link?

26. Products Weekly Tables NNDSS technology neutral Policies Procedures Data Annual Summary Data Release NNDSS Link NETSS HARS STD*MIS Information Systems TIMS NBS ArboNET SARS NEDSS compatible systems Influenza-associated pediatric mortality

27. Overlap among the NNDSS, NETSS, NEDSS, and the Surveillance World NNDSS: 77 Nationally Notifiable Infectious Diseases (NNID; e.g., West Nile Virus) NEDSS: Supports Reporting and Notification of Selected NNID plus Elevated Blood Lead Levels, PHLIS, and FoodNet NETSS: Supports Reporting and Notification of Selected NNID Surveillance World (e.g., BRFSS)

28. Collaborative Work with CSTE • 2007 CSTE-CDC State Reportable Conditions Assessment (SRCA) • Major change in methodology to solicit and document reporting requirements • All reporting requirements (ID and non-ID) in all NNDSS reporting jurisdictions • Transitional step toward working with OntoReason to gather reporting requirements in a Knowledgebase (Kb) at the local level • Objective of Kb: Provide a central up-to-date listing of reportable conditions by jurisdiction to facilitate more complete case-reporting to Public Health and to reduce the burden on Public Health stakeholders to gather this information on their own

29. Additional Work with CSTE • 2008 SRCA • Development of algorithms to trigger case reporting from the healthcare sector to local, county, and state public health • Transform human-readable national surveillance case definitions to machine-readable format

30. Collaborative Work with CDC Programs on Data Marts • Development of NCIRD Data Mart • Includes but is not limited to bacterial meningitis and invasive respiratory disease pathogens • Vaccine-preventable diseases (VPDs) • Development of NNDSS Data Mart • Develop a plan to transition data storage and analysis to NEDSS formats for processing of all NNDSS data • Must address existing independent Data Marts containing NNDSS data • Automated logical error-checking with feedback and summary reports to data providers • Current and historical data

32. The History ofNETSS-to-NEDSS Robert Fagan

33. In the Beginning • Before 1985: no direct electronic transmission of public health surveillance data • States did send aggregated counts of 49 National Notifiable Diseases (NNID) to CDC via paper and phone (versus the 77 NNID in 2008) • Data elements: state, MMWR week/year, disease, total count • Slow and difficult to update • The Territory of American Samoa still sends aggregated data by phone or fax • Disease counts sent to CDC based on state-determined definitions, not nationally standardized case definitions

34. 1985: Beginning of the Electronic Era • Extrapolating data from paper reports difficult • Strong need for detailed case reports • Six States with ample resources and staff volunteered for Electronic Surveillance Project (ESP)

35. 1985 – 1990: ESP • Electronic Surveillance Project (ESP) was a national 5-year pilot project for electronic notifiable diseases • Each state developed their own version of an electronic health reporting system • Each state included different coding structures, protocols, and diseases • Only commonality was the 40-byte message standard • CDC developed data-interchange standard to translate received messages • A positive CDC assessment of the pilot supported the development of National Electronic Telecommunications System for Surveillance (NETSS)

36. 1990: NETSS • Developed coding to better reconcile national and state records • Initially intended to expand to all CDC programs • Satisfied states with intuitive, easy-to-use, easy to understand, stable system which needed limited resources…however, • Limited resources restricted the scope of NETSS to event-based PHS • No contact tracing • No case management • Case reporting was event-based, not patient-based

37. 1993 – 1995: EPSVPD • Expanded Program for Surveillance of Vaccine Preventable Diseases: version of NETSS tailored to VPD program • Deployed in two years • Employed by 100% of states • No funding provided to states by CDC • Dedicated, salaried CDC FTE helped states to implement NETSS

38. 1994: CDC Program Participation • STD program initiated move to NETSS • Meningitis, Lyme disease, Hepatitis, and VPD programs extracted data from and integrated into NETSS by 1994 • Double reporting • TB • Immunizations • HIV did not participate • Fear of confidentiality issues • Reluctant to share resources • NETSS matured as far as possible by 1994

39. Enhancing NETSS • 1995: EPO proposed updating NETSS from DOS-based system • States already moving operating systems to Windows • Push for move to Windows-based system at CDC • Further NETSS updates denied in anticipation of migration to a newer system • Existing candidate systems in use by states were reviewed for possible adoption • CSTE requested an updated, application-independent, data interchange system • Health Information Surveillance and Systems Board (HISSB): CDC-wide surveillance committee formed in response to the Katz Report

40. 1998: Integration Project Goals • New NETSS data elements were requested by CDC programs • Define a common user interface, core data dictionary, and architecture for data model • Standardize electronic security protocols

41. 1998: Integration Project • 11 systems involved: NETSS, STD*MIS, HARS, SHAS, ASD, PSD, TIMS, PHLIS, UD, ABC, FoodNet • Dr. Claire Broome worked to establish the title and funds • 1999 – Letter from J. Koplan, CDC Director: “I am requesting that any other surveillance systems development effort be postponed or suspended until you obtain a waiver from HISSB” • 1999: NEDSS Operating Working group (NOW) formed to create National Electronic Disease Surveillance System (NEDSS)

42. NETSS vis-à-vis NEDSS • NETSS • OMB-approved forms • NEDSS • 10-years elapsed between last update to NETSS and inception of NEDSS, during which major changes in disease epidemiology occurred and new laboratory tests developed • JAD sessions held with federal and state and local public health staff to identify data elements to integrate into NEDSS • OMB-approved forms • Paper-based, supplemental reporting enhancements to NETSS • Surveillance program worksheets

43. 1999 – Present: NEDSS “The National Electronic Disease Surveillance System (NEDSS) is an initiative that promotes the use of data and information system standards to advance the development of efficient, integrated, and interoperable surveillance systems at federal, state and local levels.  It is a major component of the Public Health Information Network (PHIN)” http://www.cdc.gov/nedss/

44. Public Health Information Network (PHIN) • Engaged in improving public health by developing and disseminating best practices in research and processes to achieve meaningful and interoperable public health information systems • PHIN was an outgrowth of NEDSS to embrace broader public health surveillance and IT needs borne from shortcomings during 9/11 and anthrax events

45. ESP & NETSS: Lessons Learned (1) • Use an industry standard approach for message creation, not a proprietary software • Create Data Interchange/Message as first step • Broadly distribute the message format; this allows the project to leverage state resources to build solutions • Develop the CDC side of the system right away after distribution of message format to allow CDC to accept data • Develop recommendation for core record part of the application and publish it • Offer the CDC developed software v1.0 free; use only core information allowing rapid deployment

46. ESP & NETSS: Lessons Learned (2) • Work with CDC programs to co-develop disease specific program modules • Divide CDC programs into groups by deployment versions as resources allow • Emphasize Analysis Visualization and Reports (AVR); never release without strong analysis access to data • Start from the very beginning working with user representative partnerships committed to using the developed application • Solutions must accommodate the differences among states as the reporting protocols vary from state to state; public health is a state mandate not federal • Hire dedicated, salaried CDC employee to help states implement NETSS ESPVPD

47. Where do we find ourselves now?

48. NEDSS: Yesterday, Today, and Tomorrow Scott Danos, M.P.H.

49. Clinical Labs WHO Patient Registry Hospital or Healthcare System Healthcare Providers Notifiable Diseases Data Flow Confidential Morbidity Report Event Notification ELR Case Reporting State or Local Health Department Case Notification STD Data Hepatitis Data TB Data

50. NEDSS Characteristics • Patient-centric • Involves highly complex, relational data to support dynamic relationship • NBS: complex physical database • Requires large effort to sustain • Challenges in supporting multiple data formats both standards-based and non-standards-based • Inevitable difficulty in translating data from paper to electronic format