#HASummit14 Session #12: Sneak Peek: Improving Patient Engagement and Outcomes with Predictive...

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#HASummit14

Session #12:Sneak Peek: Improving Patient Engagement

and Outcomes with Predictive Analytics

Pre-Session Poll QuestionDoes your organization currently share predictive analytic results with patients?

a) Yesb) Noc) Unsure or not applicable

Lou CervoneDirector of Business IntelligenceCrystal Run Healthcare

Gregory Spencer, MDChief Medical OfficerCrystal Run Healthcare

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Our Organization

Physician-owned MSG in NY State, founded 1996

350+ providers, 30+ locations 40,000 commercial lives at risk 12,000 attributed beneficiaries Joint Venture ASC, Urgent Care,

Diagnostic Imaging, Sleep Center, High Complexity Lab, Pathology

Early adopter EMR (NextGen®) Accredited by Joint Commission Level 3 NCQA PCMH Recognition

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The Pain Point

How can we leverage the capabilities of our analytics platform to better engage and activate patients?

Can existing data be used interactively to help modify patient behavior?

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The Concept of a Flight Path

Example

Diabetes Cohort

Good Profile

Poo

r P

rofil

e

1. A1c < 72. LDL < 1003. BP < 130/80

1. A1c > 7 2. LDL > 100 3. BP > 130/80

$ COST per member per year (charges)

For > 1 year of encounters

(disease specific)(5 years, 26k patients)

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Poll Question #2

How are you currently engaging patients using data?

a) We actively use predictive analytics with patients to show them the predicted impact of their lifestyle choices

b) We share lab values and results with patients and verbally counsel them on long-term health implications of lifestyle choices

c) We share results only

d) Unsure or not applicable

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Our ApproachAnd

Results

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Our Goal

Using disease-specific: metrics, costs, analytics, simulation, and predicted outcomes… to engage both the

patient and clinician in more efficient diabetes care.

Our Approach

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What factors can predict “health”?

Lab Values Complications Risk Scores

Family History Substance Use Demographics

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Flight Path – Risk

Risk Prediction

Given everything we know about the patient, what is his expected “risk score”?

“What-if” analyses

Sliders will show how changing X (e.g., BMI) will affect the overall risk score

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Flight Path – Future complications

Predict the likelihood of developing one of 14 diabetes-related

complications and display the “next most likely”

Possible complications Ranked by “next likely”

Cataracts

Coronary Artery Disease

Diabetic Ketoacidosis

Diabetic Retinopathy

End Stage Renal Disease

Glaucoma

Peripheral Neuropathy

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Flight Path – Recommendations

• Compile list of recommendations for each complication

• Calculate recommendation score

• Sort recommendations from highest to lowest

• Present in both a patient view and clinician view

Likelihood of

developing

complication

Complication

Severity

Recommend Impact

Recommend Score

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Flight Path – Recommendations

Categorize recommendations by type/theme to facilitate patient’s

ability to process and remember

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Leveraging Predictive Layers

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Poll Question #3

Based on what you’ve seen, is this something you could envision implementing in your organization?

a) Yes

b) No

c) Unsure or not applicable

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Expected Results/Measurable Analytics

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• Gain patient understanding of the life choices and things within their control that can impact their potential clinical outcomes

• Show measurable improvement in patient engagement and clinical outcomes

• Inform future application development

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Future Plans

• Deploy application into clinical areaso Endocrinology, primary careo Diabetic nurse educator

• Evaluate effectivenesso Follow the cohort that has used the toolo Follow cost, Hemoglobin A1c, quality measure complianceo Patient Activation Measure (PAM)?

• Begin work on heart failure and subsequent additional applications

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Lessons Learned

1. Select your clinical conditions carefully

2. What you learn informs future applications and saves time

3. Manage the data

4. Decide on time parameters and how to treat values over time

5. Consider how the data is to be displayed for best effect

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Analytic Insights

AQuestions &

Answers

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Choose one thing…

Write down one thing will you do differently after hearing this presentation

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Thank You

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Session Feedback Survey

1. On a scale of 1-5, how satisfied were you overall with this session?

1) Not at all satisfied

2) Somewhat satisfied

3) Moderately satisfied

4) Very satisfied

5) Extremely satisfied

2. What feedback or suggestions do you have?

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Upcoming Speakers

3:45 PM – 4:35 PM

16) Delivering Excellence at Stanford Health Care

Amir Dan Rubin, President and CEO, Stanford Health Care

4:35 PM – 5:00 PM

17) The Future World of Value-Based Healthcare (Documentary featuring Michael Porter)

Caleb Stowell, MD, Vice President, Research and Development, International Consortium for Health Outcomes Measurement (ICHOM, Senior Researcher, Harvard Business School)

Location

Grand Ballroom

Grand Ballroom

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