Happy Together

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Collaboratively Connecting Across Systems and Providers – Happy Together November 7, 2017

Stacie Wolfe & Stephanie Vogt OhioHealth


Agenda

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About Us Session Objectives Sharing of Clinical Data – Viewing of Clinical Data – Using Clinical Data –

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Shared Learning Time


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Session Objectives

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How clinical data can be shared between healthcare organizations Understand why sharing clinical data is important to care coordination Understand how external organizations’ clinical data is reviewed/used


How we used to get Data

Requesting medical records the “old” way Calling to request records – Faxing request/Release of Information Authorization – Waiting to receive records –

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How we get Data now

Using Care Everywhere to get PHI from other organizations Push use case – planned transition – Pull use case – unplanned transition –

Where we get Data Direct Messages – Epic & non-Epic Organizations – State HIE – CliniSync’s Clinical Repository – Carequality participants – eHealth Exchange - VA – Surescripts NRLS –

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How we see it Care Everywhere AND Happy Together! Right data, right patient, right time One story, one view, & one patient record, no matter where the patient receive care For Providers – For Care Managers – via LPOC Report – For Patients – via OhioHealth MyChart – For Community Members – via OhioHealth Link –

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How we did it Mapping, mapping, and more mapping The Good – The Bad – The Ugly – there’s LOTS more to do –

Why do we have to map? We want external data, but we don’t value replication & incorrect data

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External Claims • Pulled in from specific payers to start –

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OhioHealthy and Health 4 payers

Patients under these payers are followed closely by Care Coordinators Data consists of: Hospital Admissions – ED Visits – Procedures – Diagnoses –

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How we use the data - Registries • Registries Epic Framework – Defines patient population – Collect data for the population – Data points enabled to pull in external information –

Uses for data Reports – Display in Patient Headers – Documentation –

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How we use the data - Analytics •

Predictive Models – – –

Risk Stratification of patients Used in variety of places in system Puts clinicians on same page

Types of Predictive Models

Epic Released

Evidence based 12

Statistically derived

Import Model

ACG (Johns Hopkins)

Optum One


Care Coordinator Workflows

Incorporated tools mentioned into Care Coordinator workflows –

Use of the reports and predictive models to stratify patients for outreach

Streamlined documentation for gathering additional data Assessments – Goals – Barriers to Care –

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Benefits to Care Coordinators • Ability to query organizations ahead of time • More robust picture of entire patient history –

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Allows Care Coordinator to focus on more important pieces More accurate identification of high risk patients –

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Cuts down on reiterative history gathering

Example: Patient seen at OhioHealth Hospital/ED 2 times, but OSU 6 times in last 6 months


Benefits to Patients

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Less repetition of past medical history, problems, allergies, medications Counters forgetfulness/ confusion –

Care Coordinator has access to the information even if patient can’t find it –

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“I take a little pink pill…”

Encounter Summary, Discharge Summary

No repeat testing (i.e. Labs, Imaging) Quality of care increases


Lessons Learned and Learning?

“New” journey in healthcare –

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We’re still learning

Ahead of vendors in some cases Organizations are all at different points in journey Lots of information available now Where do we store/ show the data? – How do we use it? –

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Operationalizing across system


Shared Learning Time

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Where do you have gaps in the electronic data available to you at your agency?

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How could having more data from external organizations help you engage your patients?


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