Automated surveillance methods for notifiablediseases: theory, practice, and evaluation: Automated surveillance methods for notifiable diseases: theory, practice, and evaluation Matthew Samore, MD
Utah Center of Excellence in Public Health Informatics
Epicenter for Prevention of Healthcare Associated Infection
Salt Lake VA Health Care System
University of Utah
Objectives: Objectives Define situation awareness and situation comprehension in the context of public health surveillance
Application of an inference engine to electronic health records for case identification
Evaluation of impact on public health surveillance work processes
Outline: Outline Surveillance theory
Surveillance practice
Surveillance evaluation
Surveillance Theory: Surveillance Theory
Paradigms and Models : Paradigms and Models The Panopticon
Archetype: “Total information awareness”
Signal detection theory
Trade-off between hit rate and false alarm rate
Situation awareness
Detection, diagnosis, prediction
What is situation awareness?: What is situation awareness? Comprehension of a dynamic environment
Understanding comprehension: Understanding comprehension A “phenomenon that emerges from an orchestra of cognitive processes”
Perception
Surface level
“Eventbase”
Semantic information extracted from perceptual input
Situation model
Integration of semantic information with prior knowledge Durso, et. al: Handbook of Applied Cognition
A tragic error: A tragic error “On a beautiful night in October 1978, in the Chesapeake Bay, two vessels sighted one another visually and on radar. On one of them, the Cost Guard cutter training vessel Cuyahoga, the captain saw the other ship up ahead as a small object on the radar, and visually he saw two lights, indicating that it was proceeding in the same direction as his own ship. He thought it possibly was a fishing vessel.
Since the two ships drew together so rapidly, the captain decided that it must be a very slow fishing boat that he was about to overtake.
Slide9: At the last moment the captain of the Cuyahoga realized that in overtaking the supposed fishing boat, which he assumed was on a near-parallel course, he would cut off that boat’s ability to turn as both of them approached the Potomac River.
So he ordered a turn to the port. This brought him directly in the path of the oncoming freighter, which hit the cutter. Eleven coastguardsmen perished.
The captain’s mental model: The captain’s mental model
Cell phone use during driving: Cell phone use during driving How it may affect comprehension of the dynamic environment of the road
Fail to check rearview mirror (attention)
At 4 way stop, may fail integrate spatial and temporal information to determine who has right of way and should enter intersection first
May recognize that driver in oncoming vehicle is distracted but fail to infer the appropriate situation model, that the car will not stop
Situation awareness and public health : Situation awareness and public health Relevance
The health of a population is indeed dynamic
Time horizons cover a wide range
The concept captures the data hungry nature of epidemiology and public health
Current health status
Current health care capacity
Early detection
Limitations: : Limitations: Vaguely expressed as goal of surveillance
Decisions or actions not specified
More importantly:
Description of the situation model is lacking
More effective use of the concept of situation awareness: More effective use of the concept of situation awareness Probe deeper
Interpretation of current state
Projected states
Measurement
Links theory to practice
Describing the current situation: Describing the current situation As given to computer scientist Yarden Livnat by Mary Hill, epidemiologist at Salt Lake Valley HD
“There is significant flu in the valley”
“Fever and coughs are rising”
“12 people hospitalized throughout the valley”
“20% are children”
“Most cases are rapid A”
“School absenteeism is high in middle/high schools”
“Btw, the hunting season started yesterday”
Mental maps of epidemiologists: Mental maps of epidemiologists GI outbreak scenario
Cluster of individuals with acute diarrhea who had eaten at a fast food restaurant
Preliminary analysis:
Approach to problem space varies substantially across public health personnel
Surveillance Practice: Surveillance Practice
Why syndromic surveillance (e.g., RODS) was perceived to be useful during Winter Olympic games (and other special events): Why syndromic surveillance (e.g., RODS) was perceived to be useful during Winter Olympic games (and other special events) At not very useful at other times
Thesis: Thesis Utility of syndromic surveillance depends on situation model
Under normal conditions, its value is highly limited
Current level of threat
Suspicion of departure from normality
Public Health Practice: Public Health Practice Based Research
Core Principles: Core Principles Partnerships and synergies
Active participation of health departments at local and state levels
Public health leadership or co-leadership of projects
Vision of public health research laboratory
Interdisciplinary collaboration at local and national levels
Utah Department of HealthOffice of Public Health Informatics: Utah Department of Health Office of Public Health Informatics Directed by Wu Xu, PhD
Goals
Coordinate statewide eHealth initiatives
Coordinate integration of projects
Create a laboratory for applied public health research
Develop theory and methods that advance information and population science in the context of public health practice
How CoE Projects Support Public Health: How CoE Projects Support Public Health Case Identification Case Investigation & Management Analysis Actions based on Results Data Dissemination RT-CEND Linkage projects
DSIDE INTERACT Outbreak response, advisories, other actions Rx Drug Deaths Readmission/Mortality
Leveraging the electronic health record: Leveraging the electronic health record Real-Time Clinical Electronic Notifiable Disease Surveillance
Electronic health record-based syndromic surveillance
Text processing
Leads
Utah Department of Health
Lisa Wyman, Melissa Stevens Dimond, David Jackson, Corona Nigatuvai, Robert Rolfs
University of Utah
Catherine Staes, Deepthi Rajeev
Intermountain Healthcare
Scott Evans, Per Gesteland
VA
Brett South, Matthew Samore, Adi Gundlapalli, Sylvain DeLisle
Data visualization and decision support: Data visualization and decision support Pathogen-specific surveillance (GermWatch)
Heterogenic data visualization
Public health decision support
Interactive simulation
Key investigators include:
Per Gesteland, Carrie Byington, Andy Pavia, Adi Gundlapalli, Yarden Livnat, Frank Drews, Laverne Snow, Chris Barrett, Stephen Eubank, Madhav Marathe, Jim Koopman, Yong Yang, Robert Rolfs
RT-CEND Project: RT-CEND Project Health care system:
Rule-based detection of notifiable diseases
Message sending
Electronic case transmission
Health department
Message receiving
Integration into workflow at local and state level
Slide28: Electronic
Medical
Record Laboratory
Data Data
Driver Decision
Support
Engine Medical
Logic
Modules Code
Tables 2 3 4 Alert
File 5 1
Slide29: Alert
File Time
Driver Reportable
Disease
Monitor Electronic
Medical
Record ICP Daily
Printout
Counts of notifiable diseases alerted: Counts of notifiable diseases alerted
Slide31: EMR Daily
report NETSS faxed Manual entry Local Health Dept Intermountain HC State Health Dept CURRENT data flow Email or fax Alert file NETSS Manual entry
Slide32: EMR Daily
report NETSS faxed Simplified view of NEW data flow Email or fax Alert file Study/
NEDSS Data views, reports, extracts NETSS Manual entry Manual entry HL7message Local Health Dept State Health Dept Intermountain HC
Electronic case transmission: Electronic case transmission Work led by Deepthi Rajeev, Catherine Staes, Scott Evans
Compiled required data fields
Modeled the HL7 message structure for reporting from healthcare systems to local & state health departments
Evaluated existing messaging models, for instance PHIN implementation
Allows transmission of multiple lab tests based on one or multiple specimens in a single message
Message structure implemented
Planned work on health care system side: Planned work on health care system side Automated HIPAA documentation
Chart review validation
Message receipt &workflow integration: Message receipt & workflow integration Appropriate data flow between state and local health departments
Utah Department of Health
Lisa Wyman, Corona Nigatuvai, David Jackson, Melissa Stevens Dimond, Robert Rolfs
Salt Lake Valley Health Department
Heath Harris, Mary Hill, Ilene Risk
Davis County Health Department
Brian Hatch, Nicole Stone
NEDSS implementation in Utah: NEDSS implementation in Utah Current status:
Vendor: Collaborative Software Initiative
Funded by grant from Novell
Open source software model
Agile, rapid development method underway
Enhancing situation comprehension: Enhancing situation comprehension Leveraging the electronic health record to support public health investigation
Start with possible event of public health interest
Use pre-defined and ad hoc queries on a health care system data warehouse to support evaluation
Collect additional epidemiologic data: how are cases linked?
Who, what, where, when
How “good” are electronic health record-based case criteria?: How “good” are electronic health record-based case criteria? May be better or worse than conventional criteria
Conventional case criteria constitute a reference standard but are never a true gold standard
Wit h respect to disease occurrence in a target population
Sensitivity is virtually always less than 100% because of incomplete clinical evaluation and testing
Lack of true gold standard with respect to
Surveillance Evaluation: Surveillance Evaluation
Conceptual framework: Conceptual framework Six core activities
Detection
Registration
Confirmation
Reporting
Analyses
Feedback.
Public health action
Acute (epidemic-type) responses
Planned responses Mcnabb, et. al. , BMC Public Health, 2002
Evaluation of public health information system implementation: Evaluation of public health information system implementation
Formative evaluation
Semi-structured interviews
Survey administration
Information technology acceptance model
Fit to workflow
Observation of efficiency of work processes
Measurement of timeliness, completeness, accuracy
Assessment of the application development process
Time Line: Time Line
Synthesis: Synthesis
Tier 1: Event Detection: Tier 1: Event Detection Trade-offs
Reliability versus validity of case criteria
“False alarm rate” versus “hit rate” Our project
activities Text processing
Rash syndromes
Rule development
Central nervous system
infections
Tier 2: Cognitive processes: Tier 2: Cognitive processes Our related research activities Center of Excellence
in Public Health
Informatics
Public health
decision-making
Simulation-based
decision support
Tier 3: Broader Public Health Goals: Tier 3: Broader Public Health Goals Our related research activities Informatics
Information
exchange
Data linkage
Epidemiology
Epidemic models
Valid ecologic
inference
Slide47: Syndromes Sensors Pathogen-
specific
Notifiable
diseases
Local/state
health dept-
centered
activities Evaluation of
existing systems
(ELR, RODS, others)
New system implementation
BioSense
NEDSS
RT-CEND Tier 4:
System
Performance