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E-mail: cdcinfo@cdc.gov | Web: www.cdc.govThe findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.
*Some counties have local clinics or hospitals contact migrant and complete evaluations
Mail to LHD**
Immigrant evaluated
Input data into EDN
Worksheetcompleted
Contact Migrant*
Form sent to IDPH/CDPH/
CCDPH
EDN
Illinois (IDPH)
Cook Co. (CCDPH)
Chicago (CDPH)
Jurisdictions
**LHD = local health department
OverseasPanel
Physicianexam
Electronic Disease
Notification
CDCQuarantine
Station review
Health Department
Port of EntryCBP1 Immigration
processing(500,0002)
Condition of public health
concern(24,0002)
1CBP=Customs and Border Protection2Annually, newly arriving immigrants
National Center for Emerging and Zoonotic Infectious DiseasesDivision of Global Migration and Quarantine
60% of TB cases reported in U.S. in 2010 occurred in foreign-born persons
All applicants for permanent residency and refugees complete pre-immigration medical evaluation
Some inactive TB overseas found to be active after entering the United States
CDC recommends re-evaluation of immigrants with TB conditions within 30 days of arrival
Complete EDN Data Flow
CDC surveillance system that tracks U.S.-bound migrants requiring medical follow-up
Notifies states of newly arriving migrants
Captures data from domestic follow-up medical evaluations
Accessed through CDC Secure Data Network
Replaced Information on Migrant Population (IMP) System, to which states did not have access, in October 2008
Background
Electronic Disease Notification (EDN)
System
EDN Data Flow in Illinois
Evaluate migrant follow-up in EDN to determine timeliness and completeness
Determine where improvements can be made to ensure migrants with TB conditions receive prompt follow-up
Explore why there are low rates of data entry into EDN’s follow-up module by Illinois
Make recommendations to improve rates of follow-up and EDN data entry
Objectives
Use of EDN in Illinois was evaluated using the 2001CDC Updated Guidelines for Evaluating Public Health Surveillance Systems.
Attributes considered included:
− Simplicity, Data Quality, Acceptability, Sensitivity, Representativeness, Timeliness, Stability, Usefulness
Methods
Participation• All immigrants and refugees with TB
conditions– U.S. arrival between October 1, 2008-
September 30, 2010– Illinois destination address
Data Collection EDN data extraction on Oct 15, 2010
(baseline)– High-priority variables identified by
IDPH Medical record review to obtain
unrecorded data– Collected high-priority variables and
entered into EDN– Compared data in EDN at baseline
and after data entry User interviews regarding EDN
– Conducted in-person or over phone (n=9)
Data Analysis Completed using SAS 9.2 Data Quality
– Percent complete at baseline and after data entry
Acceptability– Proportion of worksheets complete
by county at baseline and after data entry
Timeliness – Median days between time
intervals Stability
– Median time intervals over a 3-month period during and after the 2009 H1N1 pandemic• During H1N1 pandemic (April
22nd- July 22nd 2009)• After H1N1 pandemic (April 22nd
– July 22nd 2010)– Kruskal-Wallis non-parametric test
Representativeness– Comparison of distribution of TB
follow-up worksheet completion status at baseline and after data entry
Sensitivity– Completed follow-up evaluations
recorded in EDN at baseline compared to follow-up evaluations actually completed
EDN interview results were compiled to assess simplicity, stability, usefulness, and acceptability
Simplicity – EDN User Interviews
EDN users with direct access (Direct Users)– 100% (3/3) easy to use– 100% (3/3) easy to learn– 66.7% (2/3) not easy to gain initial access
Local health departments without EDN access (Non-Direct Users)– 100% (5/5) easy to fill out form– 60% (3/5) have problems sending back worksheet
Data Quality After data entry, number of started worksheets,
completed worksheets and completed evaluations in EDN dramatically increased
Figure 1: Complete* Worksheets in EDN at Baseline and After Data Entry (N = 1807)
Acceptability Overall low acceptabilityCompletion Rate by County Worksheet completion rate at baseline
– Mean rate: 23.5%– Range: 0% to 61.7% by county
Worksheet completion rate after data entry– Mean rate: 93.5% – Range: 64.8% to 100.0% by county
EDN User Interviews EDN user interviews indicated low willingness to use
system 62.5% (5/8) did not perform related activities on a
regular basis (direct and non-direct users) 60% (3/5) felt like filling out form takes away from
other duties (non-direct users)
Results
Representativeness
There was a significant difference in distribution of worksheet status at baseline and after data entry (p<0.01).
Figure 2: Distribution of Worksheet Status in EDN at Baseline and After Data Entry (N=1807)
Timeliness The time interval from disposition to EDN entry is
where most improvement can be made in Illinois
Table 1: Timeliness of Steps in EDN Process
Sensitivity Assessed by comparing:
– Number of completed evaluations documented in EDN at baseline
– Number total of completed evaluations after data entry (gold standard)
Of total follow-up evaluations completed, 36.3% documented in EDN at baseline
Time Intervals* NMedian Days
IQR**
Arrival to EDN State Notification
FY 2009FY 2010
915892
388
19 – 575 - 15
State Notification to Initiation
653 20 9-44
Arrival to InitiationFY 2009FY 2010
513522
2620
13-6412-40
Initiation to Disposition 987 24 5-67
Disposition to EDN Entry*** 320 78 32.5-184
*Excluded negative time intervals**IQR = Inter-quartile range; used to control for data accuracy issues***Used baseline data only
Stability All time intervals were significantly longer during H1N1
pandemic Biggest time difference is disposition to physician
signature, with 118.5 days during and 29 days after H1N1
Table 2: Comparison of time intervals during and after the H1N1 pandemic
EDN User Interviews on Stability EDN system itself is fully operational, but stability of
follow-up is affected by lack of resources– 100% direct EDN users stated system was operating
fully 75-100% of the time– 62.5% EDN users (direct and non-direct) stated
related activities not a priority when resources are limited
Usefulness 66.7% said EDN did NOT provide adequate data for
surveillance of analysis 100.0% said EDN did NOT produce adequate feedback or
reports on data in EDN
Users’ Suggestions for Making EDN More Useful Users to CDC/Division of Global Migration and Quarantine
(DGMQ)– Provide summary reports on worksheets
completed/worksheets outstanding– Supply regular surveillance reports– Send reminders for pending worksheets– Create online instructions on completion of worksheet
Local Health Departments (LHD) to Illinois State– Make worksheet electronic to send back through email– Send reminders/mechanism to track “pending”
worksheets– Incorporate into Illinois National Electronic Disease
Surveillance System– Train healthcare providers on filling form out, sending
form back, requesting replacement forms, etc.
Median Times (days)During H1N1
After H1N1
p-value
Arrival to Initiation of exam*
no time limit 27.0 19.0 0.01
Initiation within 90 days of arrival
27.0 14.0 0.01
EDN Notification to Initiation*
no time limit 27.0 14.5 0.001
Initiation within 90 days of arrival
20.5 12.5 0.28
Disposition to physician signature*
118.5 29.0 0.01
Physician signature to EDN Entry**
38.0 19.0 0.02
*Medians calculated only for migrants with U.S. arrival during specified time frame **Medians calculated only for completed evaluations during specified time frame
General Conclusions Use of EDN’s follow-up module is low in Illinois Does not accurately portray follow-up evaluation
efforts As changes to EDN occur, additional guidance,
training, and resources for health departments may improve use of the follow-up module
ConclusionsStrengths of EDN Only national system to track first-time migrants
with TB conditions Standard system for all jurisdictions Electronic system provides real-time data sharing Easy and straightforward to use once initial access
obtained Fully operational 75-100% of timeWeaknesses of Use of EDN in
Illinois Data quality– Low proportion of data entered in Illinois
Timeliness of follow-up evaluation data entry Follow-up data entry is unstable, especially when
resources are low
CDC/DGMQ Improve online guidance on how to fill out
worksheet Consider electronic version of worksheet for non-
direct users Send feedback, summary and surveillance reports
to users Develop reminder system for pending or
incomplete reports
Recommendations
Illinois Consider resources needed to improve follow-up
data entry Allow EDN access at local level Provide guidance and recurring training for LHD
– Especially on how/when to fill out worksheets for those who never initiate a follow-up evaluation
Develop reminder and tracking system for LHD
This study was supported in part by an appointment to the Applied Epidemiology Fellowship Program administered by the Council of State and Territorial Epidemiologists (CSTE) and funded by the Centers for Disease Control and Prevention (CDC) Cooperative Agreement Number 5U38HM000414
Acknowledgements
Neha Shah, MD & Josh Jones, MD, Chicago Department of Public HealthDemian Christiansen, DSc, Cook County Department of Public HealthMichael Arbise & Peter Ward, Illinois Department of Public Health
Contact Information Teal R. Bell, MPHCDC/CSTE Applied Epidemiology Fellow Quarantine and Border Health Service BranchDivision of Global Migration and QuarantineTel: 404-718-1188TRBell@cdc.gov
Evaluation of the Use of the Centers for Disease Control and Prevention’s Electronic Disease Notification System Tuberculosis Follow-up in Illinois
T. Bell, MPH , a,b N. Molinari, PhDa, M. Selent, DVM, a S. Blumensaadt, c B. Puesta, c R. Philen, MD, a D. Lee, MPH, a N. Cohen, MDa
a Centers for Disease Control and Prevention, Atlanta, Georgia, United States, b Council of State and Territorial Epidemiologists, Atlanta, Georgia, United States c Centers for Disease Control and Prevention, Chicago Quarantine Station, Chicago, Illinois
*Indicated by high-priority variablesWorksheet started = at least one high-priority variable filled outCompleted worksheet = a worksheet containing all high-priority variables according to dispositionCompleted evaluation = disposition of “completed evaluation,” starting and completing treatment if applicable
26.5% 23.5%17.5%
94.2% 93.5%
48.4%
0
200
400
600
800
1000
1200
1400
1600
1800
Worksheets started in EDN
Completed worksheets in EDN
Completed Evaluations in EDN
Fre
qu
ency
Baseline
After Data Entry
73.6%
5.8%
2.9%
0.8%
5.9%
45.1%
17.6%
48.4%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Baseline After Data Entry
Per
cen
t
Complete Worksheet: Evaluations Completed
Complete Worksheet: Evaluations Not Completed Incomplete Worksheet in EDN
Worksheet not started
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