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

Data are the tools for quality improvement

“Learning Healthcare System”

Data Sources

Clinical Data Review medical records

Administrative Data Bases

Registries Clinical Trials

ProprietaryUHC, Premier,

HMO’s

GovernmentVAH, CMS

Specialty organizations

Industry registries

CDC, States

NIH funded

Industry/FDA

wwww.ClinicalTrials.gov

Build your own

• 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

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)

StateUHC Clinical

Data Base (CDB)

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)

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

UHC Risk Adjustment Overview 2008

AgeGenderRaceSocioeconomic 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 careDRG-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

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

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

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

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.

CRIS

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

Data management tool, each investigator enters and monitors own data

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

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