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Clinical Informatics & Applications
Javed MostafaBiomedical Research & Imaging CenterSchool of Information & Library Science
Translational & Clinical Sciences Institute
May 15, 2009
EPID 896 Clinical Research Curriculum seminar
Outline
• Informatics – Roots and evolution– Emergence of clinical informatics
• Data management and data mining
• Carolina data warehouse for health
Informatics
• A discipline which is concerned with effective and efficient use of computing to promote discovery, creativity, decision-making, and productivity
– A wide variety of sub-disciplines exists
An analogy
Engineering& Applied Math
ElectricalEngineering
MechanicalEngineering
CivilEngineering
Few Informatics Examples
Informatics in Relation to Medicine & Health
• Many associated domains exist, sometimes leading to confusion .. .– Bionformatics– Health informatics– Biomedical informatics– Medical informatics– Clinical informatics
• Additionally … nursing informatics, public health informatics …
Huang, R.Q. (2007). Competencies for graduate curricula in health, medical and biomedical informatics: a framework, Health Informatics Journal, Vol 13(2): 89–103.
Clinical Informatics
• American Medical Informatics Association (AMIA) recently approved the Core Content of of Clinical Informatics– Clinical Informaticians transform health care by
analyzing, designing, implementing, and evaluating information and communication systems
… that enhance individual, population health outcomes, improve patient care, and strengthen the clinician-patient relationship
Gardner et al. (2009). Core content for the subspecialty of clinical informatics. JAMIA, 16(2), 153-157.
Critical Areas of Clinical Informatics
• Care – provision of service to an individual• Health system – organization, policies, quality,
data management
Clinical Care
The HealthSystem
Information &CommunicationsTechnology
Clinical Informatics
Critical Areas in CI: Information Systems
• System development & integration
• Networks
• Security
• Data representation, manipulation, and sharing
A Key Challenge in CI: Data Management
• Volume of data growth is rapid
• Type of data is heterogeneous
• Need systematic way to aggregate – For retrieval and analysis
• To support decision making, quality control, and long-term projects such as research
Hersh, W. (2009). Information Retrieval: A Health and Biomedical Perspective, NYC:Springer.
Evolution of Data Management
1960s 1970s 1980s 1990s 2000+
Traditionalfiles
Hierarchical
Network
Relational
Object-relational
Object-oriented ?
Web-integratedmultimedia DBs
Relational Model
Relation is a term that comes from mathematics and represents a simple two-dimensional table. Representation based on logical associations only! No pointers …
Relation = TableName Job Branch
Relational Model
• 1980-1990+• E.F. Codd proposed the Relational Model• Simple and elegant and scales with ease
• Combined with Structured Query Languages (SQL) offers a powerful mechanism for data organization and access
DW Multidimensional Model
• Example of Two- Dimensional vs. Multi- Dimensional
REGION
REG1 REG2 REG3
P123
P124
P125
P126::
PRODUCT
Two Dimensional Model
::
Three dimensional data cube
Product
Reg 1P123
P124
P125
P126
Reg 2 Reg 3
Region
Multidimensional Star Schema
• Star schema:– Consists of a fact table with a single table for each
dimension.
DW OLAP
• OLAP – OnLine Analytical Processing– Fast analysis of shared multidimensional
information (FASMI)
• Data mining is a critical aspect of OLAP
DW Data Mining
• Prediction: – Determine how certain attributes will behave in the future.
• Identification:– Identify the existence of an item, event, or activity.
• Classification: – Partition data into classes or categories.
• Optimization:– Optimize the use of limited resources.
• Referred to as PICO …
Carolina Data Warehouse for Health Evolution
• UNC health care system started developing electronic medical records almost 20 years ago
• Inpatient and outpatient care in UNC hospitals, clinics and affiliated satellite practices throughout central North Carolina
• Paperless with full nursing notes, physician order entry, progress notes, laboratory, procedure notes, discharge summaries, medication lists, and the ability to write prescriptions available on-line
• 24/7 used by over 1900 physicians, 3000 nurses, with hundreds of thousands of patients each year
• Two years ago UNC Health Care System (UNCHCS) initiated development of an enterprise-wide data warehouse, the Carolina Data Warehouse for Health (CDW-H), to meet the dual challenges of enhancement of quality of care and clinical research with our patient populations (invested > $7 million so far)
CDW – H Strategic Vision
Portal Layer
Applications, Analysis Tools, Search, Query, Mining, ..
Information Federation Layer
Federated Data SourcesExternal & Internal
Biological, Images, Literature, etc.
Data Warehouse
Security Layer
ExtractTransform
Load
TumorRegistry
WebCISCDR
ResearchGenomics,
Proteomics, etc.
CleansingLinking
Conforming
PubMed
dbSNP
External Collaborators
Other Operational
Systems
Images
Other…
Source Databases
Rim?Systems
GE IDX
Pay
4 Pe
rfor
m
Publ
ic H
ealth
Clin
ical
Reg
istr
ies
Patie
nt S
afet
y
Qua
lity
Repo
rting
Coho
rt A
naly
sis
Out
com
es
Staging
Colla
bora
tion
Lay
er
caBI
G
Secure Exchange of information with outside
entities.
SelectiveText
Extraction
AdministrativePillar
SOAApplications
SOAApplications
SOAApplications
SiemensDSS
CDW-H: As It Is Now …• A retrospective, persistent record of cleansed,
transformed, and stored data originating from operational systems
• The “one source of truth” for reporting, analytic, and data mining
• Data organized logically into subject areas for the user’s benefit without regard to its source system
• Reports, analytics, and decision making will be consistent across the entire organization
CDW-H: As It Is Now …• Data is refreshed periodically (24-48 hrs) and is
not real time data
• CDW is not designed to replace or augment daily operational activities, but to support those activities through analytical retrospective processes
• Designed to address overall organizational priorities under the governance of the CDW Oversight and Operations Committees
CDW-H: As It Is Now …• Major Subject Areas in CDW include:
AccountAllergyAmbulatory ClaimChargeContact InformationCore MeasuresDiagnosisDrugDrug Order
Health MaintenanceImmunizationsLab ResultsMedicationsObservationOrderOrganizationPatientPatient Infection
Patient ReadmissionPatient Visit ProviderPayerPaymentProblemProcedureProviderVital Signs
Notes and Reports include:•Ancillary Reports
•Cardiology Reports
•Clinical Notes
•ECG Reports
•GI Reports
Data Set Size
• Number of Tables in Staging area: 219• Number of Columns in Staging area: 3,849• Number of Tables in ADS: 202• Number of Columns in ADS: 2,840• Number of Tables in Inpatient Datamart: 81• Number of Columns in Inpatient Datamart: 1,581• Number of Tables in Diabetes Datamart: 21• Number of Columns in Diabetes Datamart: 504
• Total number of unique Patients: 1.8 Million • Total number of unique Accounts: 4.5 Million
Data Marts• Focused subset of atomic store data to support specific analytical requirements
……
• The data is organized by Dimension and Facts
• Fact Tables contain the desired detailed information– Diabetes Facts: Last A1c, Last LDL, BP, Bilateral Amputee, Onset Date, Insulin Use, Micro
Albumin, etc.
• Dimensions are distinct threads of information that allow the facts to be summarized in specific ways
– Diabetes Dimensions: Patient, Clinic, Provider, Date, Visit, etc.
• Dimensions are expanded fully to provide the aggregation required– For example, the date dimension would specify the calendar date, the day of the week,
weekday / weekend, month, quarter, and year.
Topics Covered in the Diabetes Data Mart
Subject Areas: •Allergies •Discharge Medications •Drug Orders •Health Maintenance•Lab Results •Patient Diagnosis •Patient Medications•Patient Problems •Patient Procedures •Patient Providers•Visits•Vitals
Facts:•Diabetes •Diabetes Clinical Measures• …
Dimensions:•Allergen•Clinic•Date•Diagnosis•Division•Drug•Drug Order Master•Health Maintenance Category•Health Maintenance Standard QA•Hospital Service•Lab Tests•Order Master•Patient•Procedure•Provider•System User•Visit•Vital Master
Diabetes: Dimensions and Facts
Research Portal: Gateway for Researchers and Students
• An application to expose the various key features of the CDW-H in a user friendly way– Metadata and business terms
• A portal to find useful related resources and services related to the CDW-H
• Currently, offers a Cohort Discovery Service as a pre-research step
Medical Record Access: Challenges
De-identified data
Limited data set
Clinical data set
Conduct Study - witha particular cohort
Access & Approval
De-identified view
De-identified view Extracted Data for a Study
IRB Approval/Data Use Agreement
Summary of Access Rules
• The following table summarizes the basic documentation requirements
Level of Access Rule Scope of Data
De-identified No authorization needed
Must not contain any HIPAA defined data elements that may potentially reveal identity
Limited data set Requires signed Data Use Agreement
Largely de-identified PHI but may include some identifiers
Complete set Authorization / Wavier of Authorization
PHI that includes identifiers beyond the limited fields
Cohort Selection Demo• Project Summary Descriptions:
– Need to determine which woman with digital mammograms performed at UNC between May 2007 and June 2008 who also have a documented history or new diagnosis of cardiovascular disease
• Logon to portal• Construct cohort query • Review the results• Refine cohort query• Review the results
Logon to portal
Display of main CDW home page which will be the main source of information about CDW
Click on ‘Research Tools’ tab, to start a new search, click on ‘create A New Cohort search’ button
A default cohort selection query panel with available class and objects on the left side
Filter Area
Class &Objects
Remove filter criteria by highlighting and clicking on remove button, or pressing delete button, or dragging and dropping on the class list
Remove Button
Drag & Drop
Create a new filter with drag and drop Gender Code in filter area; choose filter condition as ‘Equal to’ from the list; and enter ‘F’ for female
Similarly, drag and drop Radiology procedure name in the filter area; click on drop down to pick values from list; search for word ‘digital’
Highlight Radiology procedure name displayed for digital search and click on include button
Drag and drop Radiology Report Date column in the filter area; choose between filter condition; and choose date from calendar
Click on Run Query button to execute the cohort query selection
Report display by current age, gender, and race
Edit the query to refine the selection by clicking on Edit Query button; add diagnosis code to filter area; choose between condition; enter heart disease codes; and click on Run Query to execute the refined query
Query result for patient who had digital mammograms between May 2007 and Jun 2008 and also had heart disease
TraCS Service Center
• Please visit: http://tracs.unc.edu
• Check the Research Resources area …
• A set of consultants – Clinical Research Analysts– System/Business Analysts – DB Programmer
Questions?
• Javed • [email protected]