deepthi rajeev, ms, msc
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Evaluating the Impact of Electronic Disease Surveillance Systems On Local Health Department Work Processes. Deepthi Rajeev, MS, MSc Department of Biomedical Informatics University of Utah. 10/28/2009. - PowerPoint PPT PresentationTRANSCRIPT
Deepthi Rajeev, MS, MSc
Department of Biomedical Informatics
University of Utah
Evaluating the Impact of Electronic Disease Surveillance
Systems On Local Health Department Work Processes
10/28/2009
2
Steps in the Reporting Process
Laboratories, hospitals, doctors:• Identify condition• Recognize that it is reportable• Collect data and transmit clinical and laboratory
information to public health
Health Departments:• Receive clinical and laboratory reports• Trigger an investigation if indicated• Implement control measures to prevent further
exposure and transmission
3
Problems for local health departments• Manual reporting process (fax)
• Insufficient data in initial case report
• Manual triage of initial case report Time consuming, but not quantified
• Reports belong to other jurisdictions
• Duplicate reporting
• Lack of shared information
NETSS
Manual entry
Local Health Dept
Electronichealth record
Lab informationsystem
NETSS
Manual entry
State Health Dept
Fax
* No interface to receive electronic information
* No shared public health records
Former Reporting Process in Utah
Reporting entities
Fax
Fax
Phone
Physician
Infection Preventionist
Others
NEDSS
Manual entry
Local Health Dept
Electronichealth record
Lab system
Manual entry
State Health Dept
Fax
RTCEND= electronic transmission of case reports
NEDSS = shared public health records
New Reporting Process in Utah
Other reporting entities
Fax
Fax
Phone
Physician
Infection Preventionist
HL7
(RT-CEND)Electronic
health record
Intermountain Healthcare
Others
6
Issues to consider
Will the new electronic systems impact workflow?
• Who will be affected?
• Will the impact be positive or negative?
7
Research Objectives
• Identify metrics to monitor impact on workflow as new systems are developed and implemented
• Collect baseline data
• 8000+ reports per year
• Reports from Laboratories,
Hospitals, Clinics, State Health
Department, other local Health
Departments, Community, Jail…
• Formats: Fax, Phone call, Email,
Study Location
9
Methods to select metrics
• Observation Study - observed tasks performed by various personnel at SLVHD
• Interviewed SLVHD personnel - Triage nurse, data entry, nurse, nurse manager
• Documented workflow associated with processing a case report and validated workflow
• Identified tasks that were frequent, important, and measurable
• Identified metrics to measure the selected tasks
10
Timestamps for timeliness evaluation
Case detected
(date of lab results or diagnosis)
Reported to public health
Entry in
surveillance database
Investigation ends
Investigation starts
Time to diagnose case
Reporting Time
Time until case is triaged
Time to review (establish jurisdiction and reportable condition status) + time for initial data entry
Time until case is investigated
Time until case investigation is completed
Goal: shorten this
time interval
Start triage process
Onset of disease
11
SLVHD workflow
Triage
Report
Initial Data
Entry
Assignment
Investigation and
implementation
of control measures
Review and assign
case classification
Archive Case
Information
Forward to
state health
department
StopStart
Does the report have all the information required to identify:
• if the condition is reportable?
• if SLVHD is the responsible health department?
Identify if the report belongs to a new case or is an update to an existing case
12
Metrics for Triage Process• Relevance of the reports received:
# (%) of reports with new information including: o new unique (non-duplicate) caseso updated information
# (%) of duplicate reports# of out-of-county cases
• Follow-up:# of phone calls to gather additional information Type of additional information required # of times data required was obtained # of times forwarding of reports to data entry
was delayed
13
Metrics for Data Entry Process
• Time required to identify whether information on a newly arrived report has previously been reported (i.e., new or existing case)
• Time required to enter data into the computer
• Number of reports entered each day and week
Baseline data collection
15
Methods
• Direct observations at Salt Lake Valley Health Department
• July 6 - 13, 2009
• Data collection form
• Extracted timestamps from NEDSS that were collected as part of routine work processes
16
Date Collection Form
17
Distribution of Reports Received
380 reports received for 33 different diseases
45%
13%
19%
23%
New unique reports for Salt
Lake County (n=172)
Updated information (n=50)
Duplicate reports (n=72)
Out-of-County reports (n=86)
76% reports from Utah Department
of Health
18
Number of reports triaged by day
19
Incomplete Reports
Of 380 reports,
• 105 reports (32%) required additional information 99 phone calls made 63 reports (60%) were held for additional
information and not forwarded to data entry immediately
20
Details on Missing Data
21
Time to Triage Reports
• Average 3 mins 31 sec / report– 3 mins 30 sec for SLVHD cases
– 3 min 38 secs for Out-of-county cases
• Total time to triage cases (before forwarding to data entry) : 12:20:40 (hh:mm:ss) – ~ 26% FTE
22
Interval between Report and Triage Date
23
Time for Initial Data Entry
Observed 29th - 30th June 2009
• 62 reports entered
• Time to identify if report already exists in NETSS: 12 seconds/ report in NEDSS: 35 seconds/report
• Time to enter data in NETSS: 49 seconds/ report *
in NEDSS: 3 min 9 seconds/ report
*During study, only part of the data was entered in NETSS (NEDSS was the main system in use)
24
SLVHD Timeliness
Case detected
(date of lab results or diagnosis
Reported to public health
Entry in
surveillance database
Investigation ends
Investigation starts
Time to diagnose case
Reporting Time
Time until case is triaged
Time to triage
Time until case is investigated
Time until case investigation is completed
Goal: shorten this
time interval
Start triage process
Onset of disease
7 days
6 days
1 day
0 days
7 days
25
Next Steps
• Develop an ongoing monitoring system to evaluate impact of surveillance systems on workflow
• Issues: Is this feasible with the existing infrastructure?
26
Acknowledgements• CDC- Utah Public Health Informatics Center of Excellence
(Grant # 8P01HK000030)
• Rui Zeller
• Andrea Price
• Jon Reid
• Catherine Staes
• Ilene Risk
• Richard Kurzban
• Mary Hill
• Kris