Information Exchange for Detection and Monitoring: Clinical Care to Health Departments

1. Information Exchange for Detection and Monitoring: Clinical Care to Health Departments Janet J Hamilton, MPH Florida Department of Health Bureau of Epidemiology

2. Different data needs from clinical care for different surveillance activities • Vitals • Registries – cancer, birth defects etc. • Reportable disease/condition surveillance • Outbreak management • Periodic active surveillance • Emergency situations

3. Reportable disease/condition surveillance • The traditional core of public health surveillance • Learn about every person with a reportable disease to: • Identify promptly all cases of diseases or conditions that require public health intervention; • Detect outbreaks, changing trends or patterns in disease occurrence; • Plan, assess or evaluate control and prevention interventions.

4. Conditions for which clinician case reporting has been used • Infectious diseases • Birth defects • Cancers • Occupational diseases • Environmental diseases • Child abuse

5. How does PH get needed information? • The initial report alone (from either clinician or the laboratory) often does not have all the information PH needs for completing follow up and documentation of individuals with reportable diseases • PH needs Person, Place, Time (Who, When, Where, What): • Clinical (and lab) information to confirm the diagnosis • Treatment or medications given to the patient • Where the exposure/event occurred • Denominator present (total exposed/impacted) • Environmental setting • How the patient may have become ill (insect bites, foods consumed, travel locations, etc.) • Further prevention actions needed (e.g. exposed family members needing treatment or vaccine)

6. Syndromic Surveillance • Might better be called pre-diagnostic surveillance • Detect events at the community level before diagnoses are made • Monitor the progress of larger events once recognized • Speed vs completeness • Data sources: ED or clinic visits, poison control center calls, EMS run reports, absenteeism, key words in tweets or search engines, news reports, blogs

7. Defining data management needs during outbreaks and events • What data does public health need for outbreak management and investigation • What is different about outbreaks? • Review some examples: • Anthrax • H1N1 • Fungal meningitis • Lots of media attention and need for data multiple times a day

8. Anthrax 2001

9. Anthrax 2001 - Challenges • > 600 suspect cases reported and triaged; only 8 confirmed (7 cutaneous and 1 inhalation) • Site investigations needed at multiple locations (media outlets, hospital, USPS distribution center) • No system available to manage huge volume of data related to laboratory specimens • Suspect and Confirmed Cases • Potentially Exposed people at worksites (> 2500 nasal swabs) • Environmental specimens at all affected sites (> 1270 specimens) • > 3,000 “White powder events” • Need to capture, describe and easily retrieve relationships between people, sites, specific exposures, environment, courses of prophylaxis, laboratory results

10. H1N1, early on - Challenges • New, many susceptibles in the population • Communicable • Complex contact tracing (home, work, and healthcare contacts) • Need for case isolation and quarantine of contacts • Laboratory diagnosis challenging; esp. initially testing only available at CDC; public health not prepared to be the only clinical diagnostic location

11. Fungal meningitis - Challenges • New, unexpected, non infectious • Need specific specialized ID consults for treatment • Long incubation periods • Long courses of treatment • Many exposed • Multiple specimens over time • Detailed clinical record reviews • Changing role of public health for health care associated infections; patient provider relationships

12. Outbreak and event detection needs • Establish data flow connections; leverage electronic feeds • prior to events • balance between speed of information vs completeness • Public health goal: reduce time accessing and gathering information  patients are contacted sooner  source of illness is identified more quickly leading to improved disease prevention

13. Event Monitoring • ESSENCE ED Chief Complaint “Meningitis,” Statewide, 9/1-10/26/2012 Note: Visit spike on 10/12-10/13 is due to bacterial meningitis outbreak

14. Dashboard-Morbidity Post-Disaster Wilma Landfall Wilma Landfall Wilma Landfall Wilma Landfall Wilma Landfall Earthquake 14

15. Specific Query – Drowning in those <1-4 yrs old Uses that go beyond our typical surveillance purposes. Other program areas may also benefit. Example: Combining ED and Mortality data in one graph

16. ESSENCE-FL: Pneumonia andinfluenzamortality data from the Office of Vital Statistics, Florida 2003-2010 • Mortality due to the 2009 H1N1 virus was only slightly increased, however the increases were seen unusually early in the year

17. Further discussion - Where do we go from here? • Provider understanding – role of public health, closing the loop - communicating results/info to providers • Clinical data (coded) in EHRs often insufficient for outbreak management • How realistic is a public health query / access / portal into EHRs for use after an outbreak has been identified or disease report has been made?

18. Case-detection from EHRs? • Determine where might be more complete than passive clinician-based reporting • Not clear how much more timely it would be • How would you assure a high positive predictive value? • Would you put a human in the loop? • Would you want to wait for the final diagnosis at discharge? • If not, how do you detect potential cases before a diagnosis is entered in the chart? • Expand conversation beyond infectious