Download Development of a BRIDG-Harmonized Multipurpose Information System

Development of a BRIDG-Harmonized
Multipurpose Information System for an
Academic Cancer Center
February 23, 2017
Thomas R. Klumpp, MD, FACP
Professor of Medical Oncology
SAS Certified Professional (Version 8)
Thomas Jefferson University
Philadelphia
Background: Typical Academic Cancer Center
Laboratory
Information
Systems
Research
Information
Systems
Radiology
Information Systems
EMR Systems
Scheduling Systems
Administrative
Information
Systems
Tumor
Registries
Quality Management
Information Systems
Billing Systems
Protocol
Management
Systems
Specimen Repositories
Fox Chase-Temple BMT Information System
Real-Time
Clinical
Decision
Support
Document
Management
Teaching
Patient
Care
QualityAssured Data
Repository
Administrative
Decision
Data Required for Accreditation
Support
and Certification for Blue-Cross,
Aetna, Cigna, URN, CIBMTR,
NMDP, BMT Info Net, BMT-CTN,
Care Science, FACT, Cancer
Registry, etc.
Research Planning,
Execution, and
Analysis
Quality
Management
Marketing and
Recruiting
BMT online
Information
System
(BMTIS)
Personnel and Funding
Name
Role
Funding
Mouneer Odeh
Project Administrator
IS&T
Nick DeGregorio
Project Coordinator
Rad Onc, IS&T
Tom Klumpp, MD
Medical Director
Med Onc, IS&T, SKCC
Michael Li, PhD
Statistician
IS&T
Eric Chen, PhD
Bioinformaticist
IS&T
Dania Beadle, MS
Bioinformaticist
Med Onc
Laurie Harris
Relational Data Modeler
IS&T
Joe Neff
Applications Developer
IS&T
Ed Bruner
Applications Developer
Med Onc, SKCC
Phil Mahre
Epic Team
IS&T
Catherine Smith
Bioinformatics Student
Drexel University
Lisa Wen
Bioinformatics Student
Drexel University
Work Plan: Iterative Approach, Starting with BMT
Iteration 1
• Quality assured relational
database tracking 36 “Inner
Core” data elements
• Online data entry application
for primary data manager
• Data extracts to support realtime analyses at BMT team
meetings
Iteration 2
• Tracking ~100 data elements in
robust, quality assured
database
• Online data entry for BMT
coordinator
• Online access to interactive
insights for all team members
• Bidirectional interface of BMT
application database and OJDT.
Improved outcomes due to
use of quality-assured data to
guide clinical decision-making.
• Incorporate high-quality data
into real-time clinical decisionmaking, including real-time
actuarial analyses of EFS, OS,
TRM, RFS, within subsets of
patients
• Accurate real-time tracking of
volume and outcomes data for
the program as a whole or
within key subsets of patients
• Streamlined intake procedure
• Partial electronic submission to
CIBMTR
• Tracking referral patterns,
length-of-stay, readmissions,
etc.
• Electronic submissions to
ASBMT, BMT Infonet
• More complete electronic
submissions to CIBMTR
• Full electronic submission to
CIBMTR on TED-level patients
• Electronic submissions to
insurance companies
High-Impact
Science
• Reduced duplication of data
entry by research staff
• More rapid completion of
research analyses
• BMT coordinator’s duplicative
data input is reduced
dramatically
• Accurate tabulation of pts
eligible for research protocols
• Automated notification to
Research Coordinators re:
protocol-eligible patients
• Support for translational
research
• Dramatic reduction of
duplication of effort by research
data staff
• Support for basic research
Program of
Global
Distinction
• CIBMTR and NCI have already • Improved support for status as
• Increased ability to attract and
expressed interest in this
NCI-designated Comprehensive
retain research talent
project
Cancer Center
• Substantial support for status as
NCI-designated Comprehensive
Cancer Center
ForwardThinking
Education
• Inclusion of accurate researchquality data in teaching
• Bedside access to BMT
database & analytics while
rounding
Solution
Delivered
Patient Benefit
Clinical
Excellence
Program
Administration
•
• Increased accuracy of
physicians' predictions of
patient outcomes
• Improvements in outcomes
metrics
• Online, ad hoc analytics for
qualified faculty
Iteration 3
Iteration 4
• Tracking ~500 data elements in • Tracking full set of qualityassured CIBMTR TED-Level
comprehensive, quality assured
database
data elements (~1,000
• Online data entry for additional
elements)
BMT staff
• Online data entry for all BMT
• Automated protocol activation
data specialists
transmission
• Eliminate ~20 duplicative data
• Eliminate ~ 10 duplicative data
repositories in total
repositories
• Integration into Epic including
bidirectional data flow
• Streamlined follow-up
• Decreased readmissions
procedure
• Faster insurance approvals
(shorter waits for BMTs)
• High-stringency clinical quality
• Protocol adherence/deviation
management analyses
statistics
• Online, ad hoc analytics for
qualified students
First Iteration Software Overview
Prospective
Data Capturing
- Demographics window
- Transplant window
- Follow-Up Window
Retrospective
Data Grab
- CIBMTR/DBTC File
- SPSS File (Lori)
- BMT Consecutive list
- BMT ProgInfo file
- “BMT Database”
s
A
S
S
Q
L
Staging File
ROR/
Data Entry
ROR/
Data QA
Quality-Assured
Core Data
Repository
IDA/SQL
FN3
FormsNet
Windows
Training and Reference
Documentation
SQL
AGNIS
Reporting File
CIBMTR/Forms
Net Database
Biomedical Research Integrated Domain Group Model
NCI, FDA, CDISC, HL7, ISO (BRIDG)
Retrospective Data Gathering
Prospective
Data Capturing
- Demographics window
- Transplant window
- Follow-Up Window
Retrospective
Data Grab
- CIBMTR/DBTC File
- SPSS File (Lori)
- BMT Consecutive list
- BMT ProgInfo file
- “BMT Database”
s
A
S
S
Q
L
Staging File
ROR/
Data Entry
ROR/
Data QA
Quality-Assured
Core Data
Repository
IDA/SQL
FN3
FormsNet
Windows
Training and Reference
Documentation
SQL
AGNIS
Reporting File
CIBMTR/Forms
Net Database
POSTGRES
TRANSPLANT
4B
TEMP5
4C
POSTGRES 4D
PATIENT
BASE
TEMPC
TEMP8
4I
4E
POSTGRES
PATIENT
TRANSPLANT
4A
4C
TEMP4
TEMP7
4E
TEMP9
4I
4H
4H
POSTGRES
TEMPA
CLINICAL
PRESENTATION
TEMPB
TEMPB
TEMP9
TEMPD
4F
4G
POSTGRES
CLINICAL
PRESENTATION
POSTGRES
DIAGNOSIS
4J
COMBINED
POSTGRES
4K
BMT
PROGRAMINFO
LIST
1
TEMP10
TEMP2
3
BMT
CONSECUTIVE
LIST
2
TEMP1
3
5
TEMP3
5
TEMP11
CIBMTR
DBTC
SPSS FILE
6
8
TEMP12
TEMP14
9
7
7
TEMP13
9
TEMP15
10
J9
SAS PROGRAM TO DETECT AND CORRERCT ERRORS
AND INCONSISTENCIES IN THE PRIMARY KEY VARIABLES
J9
Postgres
Data Values
SPSS
Data Values
Consecutive List
Data Values
Program Info
List Data
Values
CIBMTR
Data Values
CIDS
Reference
Values
CIDS
Reference
Values
CIDS
Reference
Values
CIDS
Reference
Values
CIDS
Reference
Values
Consensus
Values (J10)
SAS PROGRAM TO DETECT AND CORRERCT ERRORS IN NON-PRIMARY
KEY VARIABLES IN THE EXISTING BMT DATA REPOSITORIES
Questions?