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STI eCR Learning Community: Webinar 3September 28, 201711:00 – 12:00 p.m. EDTSlide2
STI eCR Learning Community Webinar 3Please use the link below to register for the webinar: https://attendee.gotowebinar.com/register/8982498011696551425
You are dialed in as an attendee and will be muted until the Q&A portion.
Today’s webinar will be recorded.
Check back at
phii.org/ecr-sti
under Learning resources for this and previous recordings.
Objectives for webinar
Present the AllianceChicago pilot eCR implementation
Overview the evaluation findings
Discuss major lessons learned and next steps for eCRSlide3
Recap from the 2nd WebinarProvided updates from the AllianceChicago pilot eCR implementationIntroduced the evaluation plan
Discussed use of local codes vs standard health IT vocabularies Slide4
Vision for this Learning CommunityToday (Webinar 3) provides a wrap-up of the AllianceChicago pilot implementation progressOutputsRevised PHII Technical GuidanceDocumentation of AllianceChicago experience
New eCR eLearning module available
for
the public health
community (Coming Soon!)Slide5
Webinar 3 Agenda
Time:
Topic:
11:00-11:05
Welcome (Natalie
Viator
, PHII
)
11:05-11:15
Pilot Implementation Updates
(Jeremy Carr, Elizabeth McKnight AllianceChicago)
11:15-11:30
Evaluation
Findings
(
Roxane Padilla,
AllianceChicago; Natalie Viator, PHII)
11:30-11:40
Feedback and
Lessons Learned (Andrew Hamilton, AllianceChicago)
11:40 – 11:55
Questions and Discussion (All)
11:55 – 12:00
Closing Statement and Wrap
Up
(Jim
Jellison, PHII
)Slide6
Pilot Implementation Updates Slide7
Scope of Pilot Implementation
EHR applies case detection logic to patient encounter data in EHR
Patient’s data meet reporting criteria
EHR* builds case report
EHR* sends case report
*may involve middleware
(e.g., 3rd party interface engine)
AllianceChicago (
GE Centricity)
Match to trigger codes
Pull case report elements
Patient’s encounter data entered into EHR
Receive case report
De-duplicate from
ELR
Categorize for case classification
Add case to surveillance system
Conduct case investigation
Case notification to CDC
Illinois Department of Public Health
...
We are hereSlide8
EHR Build Progress – Summer 2017Integrating FHIR eCR into current dayAllianceChicago worked closely with GE around development of the new FHIR integrationAllianceChicago is participating in limited availability testing of FHIR testing
GE Schedule to release FHIR
integration
with CPS version 12.3 in the Fall of 2017Slide9
EHR Build Progress – Summer 2017User (e.g., provider, nurse) enters data in Centricity EHR Updates to problems, medications, or lab results prompt update to interface engine (IE) IE cross references specific trigger logic (per the PHII technical guidance)
IE requests eCR data elements via FHIR and sends positive results to the Department of Health (DoH)
No-DiscardSlide10
PHII/DSTDP Case Detection Logic
Patient Encounter Scenario
Diagnosis
Lab Test Performed
Positive Lab Result (Named Organism)
Positive Lab Result (Presence vs. Absence)
Treatment
Prescribed
Send eCR?
1
ü
û
û
û
û
YES
2
û
û
ü
û
û
YES
3
û
ü
û
ü
û
YES
4
û
ü
û
û
û
NO
5
û
û
ûû
üNO
Note that AllianceChicago’s clinical partners have no equivalent for the Positive Lab Result (Named Organism) codes represented in Patient Encounter Scenario 2. Therefore, eCRs were created only from scenarios 1 and 3 for both gonorrhea and chlamydia.Slide11
Evaluation FindingsSlide12
Evaluation PlanGoalProvide data (both quantitative and qualitative) to analyze the performance of the emerging technical guidance (PHII, HL7)
Will help inform necessary changes for future technical guidance revisions to meet the needs of the STI surveillance communitySlide13
Background and MeasuresNear North Health Service CorporationEight (8) comprehensive Health Center sitesPilot Start Date: May 1st
, 2017
Pilot End Date: June 30
th
, 2017
Age
of pilot population: 15 and
over
USPSTF recommends screening in adults and adolescents ages
15-65
N=12,420
patient encountersSlide14
Background and Measures: Burden of Disease
Case Counts of Gonorrhea:
11,082
(Cook County, 2015)
17,130
(Illinois, 2015)
Case Counts of Chlamydia:
39,539
(Cook County, 2015)
69,610
(Illinois, 2015)Slide15
Evaluation AreasCase detection logic (i.e., triggering) efficacy
Completeness of eCR
Overall feedback and lessons learnedSlide16
Case Detection Logic (i.e., triggering) Efficacy
Did
the trigger code value sets perform as intended in the EMR system?
Frequency
2x2 tables comparing eCR triggers with paper-based case reportsSlide17
Frequency of STI Trigger CodesSlide18
ICD-10: Chlamydial infection, unspecified [A74.9
]
Chlamyd DNA* + Positive
ICD-10: Gonococcal infection, unspecified [
A54.9 ]
GC DNA Probe* + Positive
*Proprietary code with LOINC equivalent
Frequency of STI Trigger CodesSlide19
Methods for Comparing Positive Cases Identified with eCR vs Paper Case ReportsInstructed the 8 clinical sites to continue filling out the paper form per usualCollected physical paper forms at end of study period“Paper” case report considered present if either the physical form or a scanned copy was attached to the patient encounter in EHR
Question:
Will eCR yield an increase in the number of cases reported compared to the paper case reporting method alone? Slide20
2x2 Table for ChlamydiaSensitivity: Chlamydia – 100%Specificity: Chlamydia – 99.5%
The eCR case detection logic identified 56 additional chlamydia cases that were not reported on paper. This represents a 147% increase in reporting from the clinic sites.
Subsequent EHR chart review confirmed that all of the additional cases were triggered appropriately.
Paper Case Report Present
Yes
No
eCR
Identified
Case
Yes
38
56
94
No
0
12,326
12,326
38
12,382
n=12,420 Slide21
2x2 Table for Gonorrhea
Paper Case Report Present
Yes
No
eCR
Identified
Case
Yes
13
16
29
No
0
12,391
12,391
13
12,407
n=12,420
Sensitivity: Gonorrhea – 100%
Specificity:
Gonorrhea
– 99.9%
The use of eCR resulted in 16 additional gonorrhea case reports that would not have been reported using the paper-based case report alone. This represents a 123% increase in reporting.
Subsequent EHR chart review confirmed that all of the additional cases were triggered appropriately. Slide22
Completeness of eCR*
How complete is the
eCR
at the time it is populated?
Data
elements
populated
D
ata
elements
not
populated
No equivalent data elements stored in EHR
Data element not relevant in ambulatory setting
Methods
Examined a sample of 60 of the
eCRs
generated from the pilotConformed to HL7 CDA® R2 Implementation Guide: Public Health Case Report, Release 2: the Electronic Initial Case Report (
eICR), Release 1, STU Release 1.1 - US RealmSlide23
eCR Data Element Completeness* (n=60)
Data Element
No. of eCRs with Data Element
Populated
% Complete
Data Element
No. of eCRs with Data Element
Populated
% Complete
Date of the Report
60
100
Patient Ethnicity
60
100
Provider
Name
60
100
Occupation
50
100
Provider Email
4575Visit Date/Time
60100
Facility Phone60
100Symptoms (list)60
100Patient Name
60100Lab Results
60100Patient Phone59
98.3Diagnoses60
100Parent/Guardian Phone16
26.7Medications**
60100
Patient Address60100
Patient Sex
60100
Patient Race60
100
*Selected data elements only.
**Medications listed in eCR not likely to include STI treatment given the timing of the follow-up treatment visit.Slide24
eCR Data Elements Not PopulatedPatient Class, Hospital UnitNot populated as AllianceChicago serves only ambulatory providersDeath DateNot populated in this
context
Pregnant, Immunization Status, Travel History
No single data element equivalent for this in the EHRSlide25
Feedback and Lessons LearnedSlide26
Feedback and Lessons Learned
The
PHII/DSTDP case detection logic was
programmed into the commercial EHR system and successfully generated eCRs as anticipated
Mappings between the standard code systems (LOINC, SNOMED-CT) and the local proprietary codes used in the Centricity EHR were not available
Pilot was a pre-general release of the FHIR technology
Impeded progress and created challenges including lack of a reference build, lack of experience of the technology in a real world setting
Logistical issues with project management
eCR
case detection logic does
NOT include medications
In ambulatory workflow, an eCR will trigger based on the
lab test performed in conjunction with the positive
lab
result, but
the STI treatment information will not be available at the time the eCR is sent
No trigger to update the eCR when the treatment information becomes availableSlide27
Next Steps/RecommendationsCollaborate with
IDPH/CDPH
as they develop the ability
to receive
eCRs and onboard into their surveillance system
Revising data to capture in the eCR
Medications administered at the follow-up treatment visit
Medications prescribed at the follow-up treatment visit
O
ther follow up (e.g., partner screening referral)
Slide28
General Questions and DiscussionSlide29
Closing Statement and Wrap UpSlide30
Overview of the STI eCR ProjectSlide31
Important MilestonesDemonstrated ability to work with EHR companies and health care providers on eCRUtilizing new HL7 standard for eCRTrigger logic performed well; is based on vocabulary standards for clinical terms
Public health agencies demonstrating capacity to onboard eCRs (Utah, Illinois, others)
Future work:
Work with HL7 to improve eCR standard
Develop capability to capture disease-specific dataSlide32
Wrap-UpSlides will be posted to phii.org/ecr-stiThank you for joining us!Slide33
AcknowledgmentsCDC Division of STD PreventionShelia Dooley-EdwardsNinad Mishra
Mark Stenger
Hillard
Weinstock
CDC OPHSS
Bill MacKenzie
Laura Conn
Nedra Garrett
Sanjeev Tandon
Public Health Informatics Institute
Sheereen Brown
Michael
DeMayo
Tonya Duhart
Jim Jellison
Claire LoeDaniela O’Connell
Natalie ViatorAllianceChicagoJeremy CarrAndrew HamiltonElizabeth McKnight
Roxane PadillaJessica ParkFred RachmanConsultantsTed KleinGib ParrishPartnersJim Daniel (ONC)
Meredith Lichtenstein (CSTE)Janet Hui (CSTE)Slide34
AcknowledgmentsColorado Arthur Davidson (DH)Dean McEwen (DH)Don Ryan (DH)
Mark Thrun (DH)
Diane Weed (DH)
Cindy Loftin (CDHE)
Anita Watkins (CDHE)
Massachusetts
Molly Crockett (MDPH)
Gillian Haney (MDPH)
Michael Klompas (HMS)
Catherine Rocchio (CI)
Sita Smith (MDPH)
Bob Zambarano (CI)
Utah
Rachelle Boulton (UDH)
Joel Hartsell (UDH)
David Jackson (UDH)
Susan Mottice (UDH)Jon Reid (UDH)Amanda Whipple (UDH)Expert Panel (Year 2)Rachelle Azor (VA)
Brendan Bedard (NY)Joan Chow (CA)Gillian Haney (MA)Joel Hartsell (UT)
Kim Pfeifer (WA)Shu McGarvey (consultant to CDC)Susan Mottice (UT)Fred Rachman (AllianceChicago)Jeff Stover (VA)Slide35
AcknowledgmentsIllinois Department of HealthTodd DavisSiva Guntupalli
Stacey Hoferka
Vinay Ugrappa
Chicago Department of Public Health
Cristal Simmons
Marion Tseng
RCKMS
Shu McGarvey
Julie Lipstein
Janet Hui
Catherine Staes
Jeff Benning
Pilot grantees
This project is supported by cooperative agreement number U38OT000216-2 from the
Centers for Disease Control and Prevention, Division of STD Prevention. Slide36
Glossary C-CDAConsolidated Clinical Document Architecture; widely implemented HL7 specification used to standardized the content and structure of clinical care summariesCentricity Practice Solution (CPS)EHR product implemented at AllianceChicago facilitiesFHIR
Fast Healthcare Interoperability Resources; an emerging standard for the electronic exchange of healthcare information developed by HL7
GE
GE Healthcare, a division of General Electric; the vendor that develops and supports the Centricity Practice Solution EHR product