Post on 18-Nov-2014
description
A Methodology for Quantitative Measurement of Quality and Comprehensiveness of a Research Data Repository
(IDR Snapshot)
Vojtech Huser MD PhD
Vojtech Huser, MD, PhDVojtech Huser, MD, PhD
2
Acknowledgement Wisconsin Institute for discovery
Private branch: Morgridge Institute CTSA grant (NIH (NCRR) 1UL1RR025011)
U of Wisconsin-Madison + Marshfield Clinic Marshfield Clinic Research foundation
marshfieldclinic.org/birc
Vojtech Huser, MD, PhDVojtech Huser, MD, PhD
3
Agenda Introduction Methods
Design requirements Measure components
Results Marshfield Clinic
Discussion/Conclusion
marshfieldclinic.org/birc
Vojtech Huser, MD, PhDVojtech Huser, MD, PhD
4marshfieldclinic.org/birc
Clinical Informatics Subfield of Biomedical Informatics
Background
Biomedical and Health Informatics
Bioinformatics(cellular and molecular)
Informatics = Technology + Information + People
Public Health Informatics
(population)
Medical (Clinical) Informatics
(person)
Translational InformaticsResearch Informatics
Hersh BMC Medical Informatics and Decision Making (2009) 9:24 doi:10.1186/1472-6947-9-24
Background
Vojtech Huser, MD, PhDVojtech Huser, MD, PhD
5marshfieldclinic.org/birc
Clinical Informatics Subfield of Biomedical Informatics
Background
Biomedical and Health Informatics
Bioinformatics(cellular and molecular)
Informatics = Technology + Information + People
Public Health Informatics
(population)
Medical (Clinical) Informatics
(person)
Translational InformaticsResearch Informatics
Hersh BMC Medical Informatics and Decision Making (2009) 9:24 doi:10.1186/1472-6947-9-24
Background
Vojtech Huser, MD, PhDVojtech Huser, MD, PhD
6
Introduction Advances
Federated research data warehouse Future data growth
Conduct of research RCT vs. cohort and case-control studies
IDR = Integrated Data Repository Choice of multiple institutions Quick evaluation of an IDR
marshfieldclinic.org/birc
Frueh FW. Back to the future: why randomized controlled trials cannot be the answer to pharmacogenomics and personalized medicine. Pharmacogenomics 2009;10(7):1077-81.
TRIAD
Vojtech Huser, MD, PhDVojtech Huser, MD, PhD
7
SHRINE: Query federation example
Weber at al. (2009) Application of Information Technology: The Shared
Health Research Information Network (SHRINE): A Prototype Federated Query Tool for Clinical Data Repositories
JAMIA 2009;16:624-63
Fusaro et al. Electronic Medical Record Analysis Using Cloud
Computing AMIA CRI summit, 2010
marshfieldclinic.org/birc
Vojtech Huser, MD, PhDVojtech Huser, MD, PhD
8
Motivation Motivation
10 institutions with IDRs; budget allows only 3; How do you choose?
Tracking improvement within an organization
Assumptions (limitations) Goal: lifetime and complete EHR (+genetics, +behavior, +environment) Improvement limits General measures (rather then project specific) Simple evaluation, pragmatic approach Dichotomous approach to data sources (not profiling them) Early stage (community interest solicitation)
linkedin.com/in/vojtechhuser
Vojtech Huser, MD, PhDVojtech Huser, MD, PhD
9
Measure Measures
Qualitative description Quantitative: Simple counts, Composite measure
Composite scores: APGAR, FICO, Google PageRank Score: A short-hand way to communicate about a complex concept
Data warehouse quality Size (1M vs. 10M), quality (billing data vs. structured EHR data)
Possible requirements Design issues
Completeness, Concision (simple), Measurability (objective, reliable), Independence
Our requirements Intuitive to interpret Facilitates improvement Fairness
linkedin.com/in/vojtechhuser
Vojtech Huser, MD, PhDVojtech Huser, MD, PhD
10
Data Structures (VDW)
linkedin.com/in/vojtechhuser
Vojtech Huser, MD, PhDVojtech Huser, MD, PhD
11
Data Structures (i2b2)
linkedin.com/in/vojtechhuser
Vojtech Huser, MD, PhDVojtech Huser, MD, PhD
12
Data Structures (HealthFlow)
linkedin.com/in/vojtechhuser
healthcareworkflow.wordpress.com
Vojtech Huser, MD, PhDVojtech Huser, MD, PhD
13
Data structures (data schemas) VDW
Several tables Data domain specific
structures Optimized for queries,
users
i2b2, HealthFlow One event table (+ attributes)
Generic data structures Flexibility, extensibility
Vojtech Huser, MD, PhDVojtech Huser, MD, PhD
14
Event table (IDR Snapshot v1)
code.google.com/p/IDRSnapshot
(Event-DOB) + ‘3000-01-01’
Vojtech Huser, MD, PhDVojtech Huser, MD, PhD
15
Results Events table (ev_measure01)
Generation took 2.5 hours Size: 43 GB (includes additional info)
code.google.com/p/IDRSnapshot
Vojtech Huser, MD, PhDVojtech Huser, MD, PhD
16
Code
code.google.com/p/IDRSnapshot
Vojtech Huser, MD, PhDVojtech Huser, MD, PhD
17
Code
code.google.com/p/IDRSnapshot
Vojtech Huser, MD, PhDVojtech Huser, MD, PhD
18
Code
code.google.com/p/IDRSnapshot
Vojtech Huser, MD, PhDVojtech Huser, MD, PhD
19
Cross institution comparison
code.google.com/p/IDRSnapshot
Vojtech Huser, MD, PhDVojtech Huser, MD, PhD
20
Monitoring
code.google.com/p/IDRSnapshot
Vojtech Huser, MD, PhDVojtech Huser, MD, PhD
21
What’s in it for me? Use it
Download our SQL code Use it to evaluate your IDR
Collaborate with us Paper in writing (3 institutions involved so far)
IDR Snapshot version 2
code.google.com/p/IDRSnapshot
IRB note: aggregate numbers
Vojtech Huser, MD, PhDVojtech Huser, MD, PhD
22
Future work Learn from IDRs of other institutions IDR Snapshot version 2
Event table structure HL7 vMR (lite, SQL format)
Delphi method to extend measures Qualitative measures (transfers, insurance, PHR, family history) Institutional context Quantitative measures (general level, more complex “average patient“ pattern)
Structured data Beyond claims data (e.g. nursing homes, decision support audit trails)
Specialty snapshot Prioritizing CDS interventions CKD example (dialysis data)
code.google.com/p/IDRSnapshot
Vojtech Huser, MD, PhDVojtech Huser, MD, PhD
23
Thank you huser.vojtech@marshfieldclinic.org http://code.google.com/p/idrsnapshot
Slides: http://www.linkedin.com/in/vojtechhuser http://marshfieldclinic.org/birc Questions?