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Houston Department of Health and Human Services

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  • 1. Syndromic Surveillance for Early Event Detection with Real Time Online Disease Surveillance (RODS) Houston Department of Health and Human Services Wes McNeely MS, MPH, Epidemiology Supervisor (PHP) A.J. Rosario MD, MPH Systems Analyst (PHP)
  • 2. Definition
    • Syndromic surveillance for early outbreak detection is an investigational approach where health department staff…monitor disease indicators continually (real-time) or at least daily (near real-time) to detect outbreaks of diseases earlier and more completely than might otherwise be possible with traditional public health methods. The distinguishing characteristic of syndromic surveillance is the use of indicator data types.
    --Excerpt from MMWR May 7, 2004 / 53(RR05)1-11
  • 3. Hardware - PHIN
    • PHIN - Public Health Information Network
      • Server Cluster uses Microsoft Windows Advanced Server 2003 platform
      • Web Server, Application Server, Database
      • Database Server hosts Oracle 9 i
      • Resides at HDHHS
  • 4. Software - RODS
  • 5. Hospital Sends Data
    • Hospital admits patient into Emergency Room (ER) and generates a computer record of visit
    • Hospital formats ER admissions record into HL-7 or other “messaging” format
    • Hospital “message router” uploads record to HDHHS PHIN through a secure Virtual Private Network connection (VPN)
  • 6. “ Message” MSH 1 |^~& ||UPMC (hosp) ||RODS| 200003171458 || ADT^A04 | 20000317145841029270 (message control ID) 2 |P|2.3 |<CR> 3 PID ||||||| ^017 (age) | M ||| ^^^^12345 ^^^^| <CR> PV1 || E || D |||||||||||||||||||||||||||||||||||||||| 200109130045 (admit time) || <CR> PV2 ||| ABDOMINAL PAIN (chief complaint) | <CR> DG1 ||I9|789.09| ABDOMINAL PAIN-SITE NEC (diagnosis desc.) | <CR> NK1 |||| ^^^^12345 ^^||| EMP | <CR> IN1 |||||||||||||||||||||||||||||||||||||||||||| ^^^^12345<CR> <ETX> 4
  • 7. RODS Receives Data
    • RODS “listens” for new data uploaded into folder and “consumes” the message
    • RODS chops up the text containing the complaint information (“parses the string”)
    • RODS classifies the chopped up complaint text using “Natural Language Processing” (NLP) into one (1) of seven (7) possible syndromes related to bioterrorism
  • 8. Complaint text classification ( CoCo)
  • 9. Syndrome Classification Accuracy
    • “ The sensitivity of a naive Bayes classifier using triage diagnoses was 0.63, the specificity was 0.94, and the area under the ROC curve was 0.82”.....
    • “ We conclude that a naive Bayes classifier of free-text triage diagnosis data provides more sensitive and earlier detection of cases [than other methods].”
    • “ The sensitivity achieved should be sufficient for syndromic surveillance system designed to detect moderate to large epidemics.”
    • Ivanov, O., M. M. Wagner, et al. (2002). &quot;Accuracy of three classifiers of acute gastrointestinal syndrome for syndromic surveillance.&quot; Proc AMIA Symp: 345-9.
  • 10. Syndromes
    • RODS assigns syndromic categories to the complaint
      • Gastrointestinal
      • Constitutional
      • Respiratory
      • Rash
      • Hemorrhagic
      • Botulinic
      • Neurological
      • Other
  • 11. Database
    • RODS imports the data with syndrome field added into Oracle 9i database
    MSH 1 |^~& ||UPMC (hosp) ||RODS| 200003171458 || ADT^A04 | 20000317145841029270 (message control ID) 2 |P|2.3 |<CR> 3 PID ||||||| ^017 (age) | M ||| ^^^^12345 ^^^^| <CR> PV1 || E || D |||||||||||||||||||||||||||||||||||||||| 200109130045 (admit time) || <CR> PV2 ||| ABDOMINAL PAIN (chief complaint) | <CR> DG1 ||I9|789.09| ABDOMINAL PAIN-SITE NEC (diagnosis desc.) | <CR> NK1 |||| ^^^^12345 ^^||| EMP | <CR> IN1 |||||||||||||||||||||||||||||||||||||||||||| ^^^^12345<CR> <ETX> 4
  • 12. Pretty data
  • 13. Pretty data ü ü
  • 14. Pretty data ?
  • 15. Graphs
  • 16. RODS Analyzes the Data
    • RODS analyzes the data to detect unusual patterns every 4 hours
      • Time Series
        • Recursive Least Squares (RLS)
        • CuSum
        • Linear Models
      • Spatial analysis
        • Scan Statistics
      • Multivariate analysis
        • WSARE ( W hat’s S trange A bout R ecent E vents?)
  • 17. Alerts Syndromic Signal
  • 18. Output
  • 19. Output
  • 20. Syndromic Trends
  • 21. Graph3 Gastrointestinal
  • 22. Graph2 Neurological
  • 23. Graph4 Botulinic
  • 24. Graph1 Respiratory
  • 25. Graph1 Respiratory  BURN-IN PHASE 
  • 26. Interface Upgrades
    • Version 4.0
  • 27. Upgrades1
  • 28. Upgrades2
  • 29. Upgrades3
  • 30. Upgrades4
  • 31. Upgrades5
  • 32. Contact Information RODS Laboratory HDHHS [email_address] 713-794-9181 Epidemiologist Specialist Shola Adeleye, MD, MPH [email_address] 713-794-9181 Epidemiology Supervisor Wes McNeely, MS, MPH [email_address] 713-798-0884 DBA Annie Chen, OCA [email_address] 713-558-2493 Systems Analyst IV AJ Rosario, MD, MPH [email_address] 917-254-7278 User Interface, Developer Jeremy Espino, MD [email_address] 412-648-6738 Project Manager Daphne Henry
  • 33. Extra info - RODS Syndromes
    • Botulinic – ocular abnormalities, difficulty speaking, and difficulty swallowing.
    • Constitutional – non-localized, systemic problems including fever, chills, body aches, flu symptoms.
    • Gastrointestinal – pain or cramps anywhere in the abdomen, nausea, vomiting, and diarrhea.
    • Hemorrhagic – bleeding from any site, vomiting blood, nose bleed, or gastrointestinal bleeding.
    • Neurological – non-psychiatric complaints that relate to brain function.
    • Rash – any rash such as macular, papular, vesicular, petechial, purpuric, or hives.
    • Respiratory – problems of the nose, throat, and lungs. The presence of both clod and flu symptoms is counted in this category, not constitutional.
  • 34. Extra info - Sensitivity and Specificity Test Result + - Has Condition No Yes
  • 35. Extra info - ROC Curve
    • “ In signal detection theory, a receiver operating characteristic (ROC) is a graphical plot of the sensitivity (fraction of true positives - TP) vs. 1-specificity (the fraction of false positives - FP) for a binary classifier system as its discrimination threshold is varied.” http:// en.wikipedia.org/wiki/ROC_Curve