Clinical Informatics & Applications

1. Clinical Informatics & Applications JavedMostafa Biomedical Research & Imaging Center School of Information & Library Science Translational & Clinical Sciences Institute May 15, 2009 EPID 896 Clinical Research Curriculum seminar

2. Outline • Informatics • Roots and evolution • Emergence of clinical informatics • Data management and data mining • Carolina data warehouse for health

3. 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

4. An analogy Electrical Engineering Engineering & Applied Math Mechanical Engineering Civil Engineering

5. Few Informatics Examples

6. 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.

7. 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.

8. Critical Areas of Clinical Informatics • Care – provision of service to an individual • Health system – organization, policies, quality, data management Clinical Care Clinical Informatics The Health System Information & Communications Technology

9. Critical Areas in CI: Information Systems • System development & integration • Networks • Security • Data representation, manipulation, and sharing

10. 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.

11. Evolution of Data Management 1970s 1980s 1990s 2000+ 1960s Hierarchical Object- relational Web-integrated multimedia DBs Traditional files Relational Network Object- oriented ?

12. 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 = Table Name Job Branch

13. 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

14. DW Multidimensional Model • Example of Two- Dimensional vs. Multi- Dimensional

15. Multidimensional Star Schema • Star schema: • Consists of a fact table with a single table for each dimension.

16. DW OLAP • OLAP – OnLine Analytical Processing • Fast analysis of shared multidimensional information (FASMI) • Data mining is a critical aspect of OLAP

17. 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 …

18. 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)

19. Clinical Registries Outcomes Quality Reporting Public Health Cohort Analysis Patient Safety Pay 4 Perform CDW – H Strategic Vision Source Databases Applications, Analysis Tools, Search, Query, Mining, .. WebCIS CDR SOA Applications SOA Applications SOA Applications Rim? Systems Selective Text Extraction Portal Layer Tumor Registry External Collaborators Collaboration Layer Siemens DSS caBIG GE IDX Security Layer Information Federation Layer Other Operational Systems Staging Secure Exchange of information with outside entities. Images PubMed Research Genomics, Proteomics, etc. Extract Transform Load Data Warehouse Other… dbSNP Administrative Pillar Cleansing Linking Conforming Federated Data Sources External & Internal Biological, Images, Literature, etc.

20. 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

21. 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

22. CDW-H: As It Is Now … • Major Subject Areas in CDW include: Account Allergy Ambulatory Claim Charge Contact Information Core Measures Diagnosis Drug Drug Order Health Maintenance Immunizations Lab Results Medications Observation Order Organization Patient Patient Infection Patient Readmission Patient Visit Provider Payer Payment Problem Procedure Provider Vital Signs • Notes and Reports include: • Ancillary Reports • Cardiology Reports • Clinical Notes • ECG Reports • GI Reports

23. 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

24. 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.

25. Topics Covered in the Diabetes Data Mart • 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 • 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 • …

26. Diabetes: Dimensions and Facts

27. 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

28. Medical Record Access: Challenges De-identified data Limited data set Conduct Study - with a particular cohort Clinical data set

29. Access & Approval De-identified view IRB Approval/Data Use Agreement De-identified view Extracted Data for a Study

30. Summary of Access Rules • The following table summarizes the basic documentation requirements

31. 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

32. Logon to portal

33. Display of main CDW home page which will be the main source of information about CDW

34. Click on ‘Research Tools’ tab, to start a new search, click on ‘create A New Cohort search’ button

35. A default cohort selection query panel with available class and objects on the left side Class & Objects Filter Area

36. 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

37. 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

38. Similarly, drag and drop Radiology procedure name in the filter area; click on drop down to pick values from list; search for word ‘digital’

39. Highlight Radiology procedure name displayed for digital search and click on include button

40. Drag and drop Radiology Report Date column in the filter area; choose between filter condition; and choose date from calendar

41. Click on Run Query button to execute the cohort query selection

42. Report display by current age, gender, and race

43. 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

44. Query result for patient who had digital mammograms between May 2007 and Jun 2008 and also had heart disease

45. 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

46. Questions? • Javed • jm@unc.edu