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

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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

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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

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Issues to consider

Will the new electronic systems impact workflow?

• Who will be affected?

• Will the impact be positive or negative?

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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,

Mail

Study Location

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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

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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

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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

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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

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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

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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

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Date Collection Form

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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

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Number of reports triaged by day

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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

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Details on Missing Data

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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

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Interval between Report and Triage Date

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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)

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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

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Next Steps

• Develop an ongoing monitoring system to evaluate impact of surveillance systems on workflow

• Issues: Is this feasible with the existing infrastructure?

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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