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HTH979 Syndromic Surveillance

HTH979 Syndromic Surveillance. Catherine Schulten HC Business Development Mgr Catherine.Schulten@Sybase.com August 16, 2004. Syndromic Surveillance.

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HTH979 Syndromic Surveillance

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  1. HTH979 Syndromic Surveillance Catherine Schulten HC Business Development Mgr Catherine.Schulten@Sybase.com August 16, 2004

  2. Syndromic Surveillance • “The term “syndromic surveillance” applies to surveillance using health-related data that precede diagnosis and signal a sufficient probability of case or an outbreak to warrant further public health response. • Though historically, syndromic surveillance has been utilized in situations where resources are to target investigation of potential cases, its utility for detecting outbreaks associated with bioterrorism is increasingly being explored by public health. • CDC Epidemiology Program Office

  3. Syndromic Surveillance • Syndromic surveillance is an investigational approach where health department staff, assisted by automated data acquisition and generation of statistical alarms, monitor disease indicators continually (real-time) or a least daily (near real-time) to detect outbreaks of diseases earlier and more completely than would otherwise be possible with traditional public health models (e.g., by reportable disease surveillance, telephone consultation, etc.) • CDC Working Group on Syndromic Surveillance Systems, “Framework for Evaluating Public Health Surveillance Systems for Early Detection of Outbreaks”, April ‘04

  4. Of ever increasing importance • “The U.S. should seek to enhance the global capacity for response to infectious disease threats…” • “Investments should take the form of financial and technical assistance, operational research, enhanced surveillance, and efforts to share both knowledge and best public health practices across national boundaries” • “The U.S. should take a leadership role in promoting..a comprehensive system of surveillance for global infectious diseases” • IOM, “Microbial Threats to Health: Emergence, Detection and Response”, May 2003

  5. Outbreak Detection • The ability of a system to detect an increase in incidence of disease above background at the earliest possible stage depends upon: • The timely capture and processing of the data produced by transaction of health behaviors (e.g., over the counter pharmaceutical sales, Emergency Dept. visits) or health care activities (lab test volume) that may indicate an outbreak • The validity of the data collected and the quality of those data • The detection methods applied to this processed surveillance data to distinguish routine events from those indicative of an outbreak

  6. Outbreak Detection • Early detection of outbreak can be achieved in three ways • By timely and complete receipt, review, and investigation of disease case reports • By improving the ability to recognize patterns indicative of a possible outbreak early in its course, such as through analytic tools that improve predictive value of data at an early stage of outbreak • Through receipt of new types of data that can signify an outbreak earlier in its course

  7. 1. Timely Receipt and Review of Data • Timeliness is measured by the lapse of time from exposure to the disease agent to the initiation of a public health intervention

  8. 2. Improving Ability to Recognize Patterns • Statistical tools for pattern recognition and aberration detection can be applied to screen data for patterns warranting further public health investigation and to enhance recognition of subtle or obscure outbreak patterns • “Victims of an anthrax attack might present to emergency departments with flu-like or respiratory syndromes. The identification of abnormally high visit rates relies on a good understanding of the normal patterns of healthcare utilization. Once expected rates of utilization are established, alarm thresholds can be set for public health alerts.” CDC, “Considerations for distinguishing influenza-like illness from inhalation anthrax” JAMA 2001

  9. Pattern Recognition Yearly patterns, respiratory visits Yearly ensemble average of daily respiratory-related visit totals, shown from June through June, reveals peaks in visits during the fall, winter and spring. Children’s Hospital Boston, ED

  10. Pattern Recognition • Automated analysis and visualization tools can lessen the need for frequent and intensive manual analysis of surveillance data

  11. Visualization ESSENCE – GIS Map of the National Capital Region for Respiratory Syndrome ESSENCE – Electronic Surveillance System for the Early Notification of Community-based Epidemics

  12. 3. Ability to Receive New Data Types • Many new surveillance systems use data that are not diagnostic of a disease but that might indicate the early stages of an outbreak (indicator data types) • Requirement to add unique data to refine signal detection to capture exposure and and other data relevant to managing an outbreak and • to add data providers to increase population coverage and detect or track low frequency events

  13. Public Health Data Repository For Syndromic Surveillance Sources of Syndromic Surveillance Data Hospital ED - Chief Complaint & ICD-9 LAB Orders Lab Primary Care - Chief Complaint & ICD-9 Pharmacy Rx and Off-the-Shelf purchases Absenteeism from School & Work document Home Health Reports Clinical Impression on Ambulance log sheets Web Veterinary Other Federal Agencies (CDC, FDA, EPA) Verbal Nursing Hotlines Poison Control Center Hotlines Self Reporting

  14. Public Health Data Repository For Syndromic Surveillance Outputs for Syndromic Surveillance Results User Public Health Officials Hospitals Alert Primary Care Physicians Report Other State & Federal Agencies (CDC, FDA) First Responders (Rescue, Fire, Police)

  15. Key Features of a Successful Syndromic Surveillance System • System Usefulness – • Does the system contribute to early detection of outbreaks? • System Flexibility – • Ease of adaptation, ability of the system to change as needs change with minimal time, personnel and other resources to make the change • Ability to apply evolving data standards and code sets (e.g., HL7, ICD 9 and 10, SNOMED, LOINC) • Ability to shift from outbreak detection to outbreak management

  16. Key Features of a Successful Syndromic Surveillance System • System Acceptability – • Willingness of participants to contribute to data collection, analysis, use • Considers implications of HIPAA Privacy • Portability – • How well the system could be duplicated in another setting • System Stability – • How resilient the system is to system changes (e.g., change in coding from ICD9 to ICD10) • Frequency of downtime for services, software updates, etc

  17. How to Architect a Syndromic Surveillance Solution • Over the past few years there have been several projects undertaken to address the syndromic surveillance issue • Each project has it’s own unique strengths and methods to address data capture, storage, analytics, alarms, etc • CDC documents: • “PHIN Functions and Specifications, Version 1.2” http://www.cdc.gov/phin/architecture/index.htm • “Framework for Evaluating Public Health Surveillance Systems for Early Detection of Outbreaks” http://www.cdc.gov/mmwr/preview/mmwrhtml/rr5305a1.htm

  18. Real Time Outbreak and Disease Surveillance System Architecture (RODS) As presented at the 2003 National Syndromic Surveillance Conference

  19. Community Health Electronic Health Surveillance System (CHESS) Westchester County, NY As presented at the 2003 National Syndromic Surveillance Conference

  20. Syndromic Surveillance Architecture • Key components of the architecture • Supports multiple modes and protocols for communication (TCP/IP, FTP, email, phone, etc) • An HL7 “listener” to accept clinical messages from submitting clinical environments (hospital, lab) • An HL7 “parser” which extracts needed data from the HL7 messages • A “text file parser” that extracts data from electronic, non-HL7 messages • A “web interface” that allows for citizen self-reporting or for 1-800 hot line reporting • Capability to classify the data into syndromic categories • Syndrome Groups with Examples • Respiratory (common cold, sinus infection) • Fever/Malaise/Sepsis • Gastrointestinal (vomiting, diarrhea, abdominal pain) • Neurologic (headache, meningitis) • Dermatologic - Infectious (potential smallpox - vesicular rash) • Dermatologic - Hemorrhagic (bruising, petechiae - potential VHF) • Coma/Sudden Death

  21. Syndromic Surveillance Architecture • Key components of the architecture • “Relational Database” to store and provide access to syndromic data • “Analytic Engine” to detect anomalies within the data set that might be indicative of an outbreak • “Alerts” to provide warnings and meaningful information to appropriate personnel • Capable of accepting real-time and batched data 24/7 • Low tolerance for downtime • Adheres to federal and state Privacy and Security mandates • Capable of presenting reports in various ways (graphics, text, trends over time, geo-spatial, etc)

  22. Syndromic Surveillance Architecture R E F O R M A T Analytics HL7 Hospital Alert Reformat ebXML Lab Data Warehouse Report document ASCII TEXT Email, Fax Web P A R S E Web form entry Verbal User Privacy / Security High Availability

  23. Data Integration • EDI Gateway and Listener Nodes to accept data from disparate sources and formats, in real-time and batch • EDI Server to reformat message into a format acceptable by backend systems • HL7 Integration Engine specific for accepting, reformatting, parsing, routing, applying rules to HL7 transactions R E F O R M A T Analytics HL7 Hospital Alert Reformat XML Lab Data Warehouse Report TEXT document Web P A R S E Verbal User Privacy / Security High Availability

  24. Industry Warehouse Studio for Healthcare & IQ • DB schema for financial, administrative and clinical data • Optimized for analytics • Sybase IQ, highly scalable analytic engine • Supports ad hoc, user generated reports R E F O R M A T Analytics HL7 Hospital Alert Reformat XML Lab Data Warehouse Report TEXT document Web P A R S E Verbal User Privacy / Security High Availability

  25. Data Integration & SQL Anywhere Studio • Automate the generation of alarms, reports, etc depending upon preset conditions • Reports appropriately formatted and sent to various devices (PDA, cell phone) • Business Activity Monitoring to measure message movement throughout extended business processes & provide statistical calculations and reports • Scalable, bi-directional synchronization of information between the enterprise and remote systems, supports occasionally connected and near-real time connectivity • Server initiated synchronization delivers timely alerts to remote devices R E F O R M A T Analytics HL7 Hospital Alert Reformat XML Lab Data Warehouse Report TEXT document Web P A R S E Verbal User Privacy / Security High Availability

  26. R E F O R M A T Analytics HL7 Hospital Alert Reformat XML Lab Data Warehouse Report TEXT document Web P A R S E Verbal User Privacy / Security High Availability • Sybase Replication Server, Open Switch & Web Service Integration Suite • Robust set of solutions to protect data at rest and data in motion & provide a high availability solution • Web Services supports digital signatures, authentication, authorization, encryption, non-repudiation • Rep Server provides continuous operation despite hardware and/or software failures with guaranteed delivery of data • Open Switch provides a customizable mechanism for coordination of fail over events, ensures all transactions have been committed prior to migrating to warm stand-by and transparently switches to fail over server without disturbing the client

  27. Sybase Syndromic Surveillance Architecture • Sybase’s Value Proposition: • Sybase supplies all the components needed to develop a robust syndromic surveillance architecture • Can be built in stages, supporting increasing functionality and users over time • Single vendor with strong commitment to and understanding of the healthcare industry provides interoperable components to ensure faster delivery of solution

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