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Reducing Preventable Readmissions through Predictive Analytic Models

Reducing Preventable Readmissions through Predictive Analytic Models. Curt Sellke - Vice President of Analytics. IHIE Background. Nation’s largest Health Information Exchange (HIE) Founded in February 2004 Based on the technology, knowledge, and experience of the Regenstrief Institute

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Reducing Preventable Readmissions through Predictive Analytic Models

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  1. Reducing Preventable Readmissions through Predictive Analytic Models Curt Sellke - Vice President of Analytics

  2. IHIE Background • Nation’s largest Health Information Exchange (HIE) • Founded in February 2004 • Based on the technology, knowledge, and experience of the Regenstrief Institute • Providing services to 96 hospitals (39 health systems), 25,000 clinicians, and 4 payers • Serving an area with a population of about 6.5 million people

  3. IHIE CDR Data IHIE operates one of the nation’s largest Clinical Data Repositories (CDR) • 1 Network • 96 Hospitals • 25,000 Physicians • 500,000 Daily Data Transactions • 16,3000,000 Patients • 120,000,000 Radiology Images/Reports • 6,600,000,000 Pieces of Clinical Data (15TB)

  4. Health Data Sources Value Added Services IHIE Services Hospitals Physician Clinical Data Repository (INPC™) • MPI & Record Locator Service • Longitudinal Patient View Clinical Results Delivery (D4D®) • Web-based portal or EMR delivery • No Cost to Physicians • ACO & Analytic Services • ADT Alerts • Predictive Analytics Public Health Integration and Automation • Bio-surveillance • Communicable Disease Reporting • Immunizations Federal Government Services • SSA Disability Determination • VA’s VLER Program Meaningful Use Supporting Services • Transitions of Care • Public Health Integration Physician Offices Health Information Exchange Patient Labs / Imaging Centers Physician Network Applications Data Repository Public Health Payers Physician Data Governance Rx

  5. Outside Indiana

  6. Why Predictive Analytics? • Lots of Rich, Disparate Data is needed to “Power” Predictive Models; IHIE is a fantastic source for this data • Strong Market Need, Limited Experience and Expertise especially developing Predictive Models that use Clinical Data versus Claims Data • Huge Opportunities and Value if you can be Predictive/Interventional versus Retrospective/Reactive • We believe it is the “Right” next Step in the Evolution of a Successful HIE (HIE 2.0)

  7. Do you know where your patient is? As a member of a CMS chartered ACO, a patient can seek care anywhere in or outside the ACO. They are not bound to a single network or provider. This makes knowing where your patient is or has been even more challenging especially when you have clinical & financial responsibility for that patient!

  8. ADT Alerts Enables Providers to: • Track where and when care has been delivered, especially if outside of the patient’s attributed care network • Information comes from HL7 ADT (Admission/Discharge/Transfer) Messages • Examine the patient’s chief complaint • Process the preliminary diagnosis • Optimize care site transitions • Identify providers in the continuum of care

  9. ADT Alerts Architecture Today

  10. ADT Alerts Case Study ADT Alerts to Reduce ED Visits • Results of a 6 month pilot with a managed health care plan in Indiana: • 53% reduction in non-urgent ED visits • 68% increase in Primary Care office visits • Nearly $4 million saved

  11. Making ADT Alerts more predictive, More valuable We are working with Predixion Software to develop a model to predict the probability of a preventable readmission occurring within 30 days of discharge We are “wiring” this predictive model into our ADT Alerts system; any time an inpatient admission happens, we will score the probability of that patient being readmitted within 30 days of discharge

  12. Future ADT Alerts Architecture (Q2 of 2014)

  13. Other Potential use casesOutside ACOs ADT Alert on Admission and/or Discharge to the Patient’s PCP to enable more effective transitions of care Medicare is financially supporting “Transitional Care Management Services” by encouraging PCPs to see Patients within 7 to 14 days of discharge and providing new CPT Codes (99495 and 99496) to provide payment for these services ADT Alerts coupled with a Prediction of the potential for Readmission within 30 days can help PCPs and their staff focus resources on those patients that have the highest probability for readmission

  14. Thank You Curt Sellke Vice President, Analytics csellke@thrivehds.com Office: 317-735-4084 Twitter: @CurtSellke

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