1. DATA Role of data in QI and Scholarship Characteristics of “good” data Sources/categories of data Administrative databases – pros &cons New Informatics support for Scholarship, QI, and Translational Research

3. Data are the tools for quality improvement “Learning Healthcare System”

4. Data Sources Clinical Data Review medical records Administrative Data Bases RegistriesClinical Trials Proprietary UHC, Premier, HMO’s Government VAH, CMS Specialty organizations Industry registries CDC, States NIH funded Industry/FDA wwww.ClinicalTrials.gov

5. Clinical data (National Surgical Quality Improvement Program) –Prospective data collection, chart abstraction –Expensive, labor-intensive –Face validity among physicians Administrative data base (UHC’s CDB, Premier, Thomson- Reuters) –Always retrospective, Claims data (medical record coding) –Can study resource use and cost of care –Very efficient way to collect data –I2B2 – Integrating Informatics for Biology and Bedside –HERON (Healthcare Enterprise Repository Ontological Narration) at KUMC –Software program - integration of EPIC, Clinical information, IDX of retrospective data Difference between Clinical Data and Administrative Data Bases

6. Where do the data elements come from ? Physician: Documentation of patient care Coders: Assignment of codes to diagnoses and procedures Creation of a ‘CLAIM’ with patient demographics; DRG; diagnoses and procedures; LOS; charges; admission/discharge dates, status; physician; etc. Payers (e.g. CMS, BCBS) State UHC Clinical Data Base (CDB)

7. Risk Model High RiskLow Risk A robust model should assign higher probability of death to patients who died than to those who survived, at least 70% of the time (i.e. c-index >= 0.70) Survived Died

8. UHC Risk Adjustment Overview 2008 Age Gender Race Socioeconomic status (Medicaid, self pay, charity, no charge) Admission status (emergency) Transfer status, acute hospital, nursing home Up to 30 comorbid or chronic conditions (e.g. diabetes, liver disease, obesity) Palliative care DRG-specific conditions Ventilator on Day 1 Severity-of-illness class for DRG based models risk of mortality Potentially avoidable complications (not input into the model) Separate regression models for Cost, LOS, mortality for each DRG Expected mortality Expected cost Expected LOS Inputs

9. What Variables Are Studied Performance based on: Hospitals Product Lines DRGs & MS-DRGs Diagnoses / Procedures Physicians Discharge Date/Month/Year Patient Demographics Resource Utilization*: Blood Products Drugs Imaging Tests ICU Med/Surg Supplies Pharmacy * Resource Manager Almost anything having to do with an inpatient stay (ambulatory variables currently in development) Risk Adjusted Outcomes – Observed and Expected (O/E) for LOS, Mortality and Cost Complications, Readmissions, AHRQ Patient Safety Indicators Risk Adjusted Outcomes – Observed and Expected (O/E) for LOS, Mortality and Cost Complications, Readmissions, AHRQ Patient Safety Indicators

10. If you want to use UHC database? Develop your proposal Contact : Chris Wittkopp – Organizational improvement Discuss your proposal and her assessment of data retrieval strengths Write short proposal with background, purpose, methods Submit proposal to Human Subject review If QI project can get exemption

14. Frontiers (CTSA)Biomedical Informatics Goals Portal for investigators to access clinical and transitional research resources, track usage, and provide informatics consultative services Create a platform, HERON, to integrate clinical and biological data for translational research Link biological tissues to data generated by research cores Leverage statewide telemedicine and Health Information Exchange (HIE) to support community based translational research

15. What is HERON? HERON (Healthcare Enterprise Repository for Ontological Narration) is a search discovery tool that allows you to search de- identified data from various hospital and medical center sources that include but are not limited to Epic/O2 (the hospital electronic medical record), IDX (the clinical billing system), KU Hospital Cancer Registry, KU Biospecimen Repository, REDCap (selected projects), Social Security Death Index, and University HealthSystem Consortium (Quality Measure Data). By combining the various data sources, researchers can look at the data in new ways not available when viewing data in one source at a time. Why should I use HERON? HERON is a powerful tool that can save time during your research process. Searching across multiple data resources allows you to view data trends, key in on your research criteria, modify your search requirements and see how the data changes. This is a good tool to employ at the start a research project as it saves time by helping you focus and define your research. The HERON tool also provides analysis tools, such as the Timeline and the Cancer Survival Analysis tools.

16. Larger projects where biostats sets up data sets, does monitoring and auditing, ie funded RCT

17. Data management tool, each investigator enters and monitors own data

18. Frontiers (CTSA)Biomedical Informatics Goals 1) Portal for investigators to access clinical and transitional research resources, track usage, and provide informatics consultative services 2) Create a platform, HERON, to integrate clinical and biological data for translational research 3) Link biological tissues to data generated by research cores 4) Leverage statewide telemedicine and Health Information Exchange (HIE) to support community based translational research

22. Summary Data is essential for Scholarship, Quality Improvement and Education Sources of data are multiple Clinical Administrative Registry Informatics for Integrating Biology with Bedside –HERON –Data Management Systems –CRIS –RedCap