hxr 2016: data insights: mining, modeling, and visualizations- farid jamshidian
TRANSCRIPT
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How Empathy Drives Data
Products
Farid Jamshidian, PhD
Helping Patients Choose Care with Confidence
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Amino's mission is to connect everyone to the best health care possible. We're committed to creating the clearest picture of American health care so everyone
can choose care with confidence.
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Quick, painless – and personal
1. Personalize your searchFirst, we’ll ask you a few easy questions so we can tailor your list of matches.
2. See what’s importantYou can check out detailed stats on each doctor’s experience with your exact needs.
3. Book your appointmentWe’ll play phone tag with the doctor’s office to get you a convenient slot.
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Consumer experience, powered by big data
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From data to insights• Massive volume of
raw data arriving daily from multiple sources
• Layers of preparation• Claims data
structuring• Ontological
mapping• Episode grouping• Scalable
computation
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It’s hard to find a doctor who actually has experience with your condition or the procedure you’re planning
Problem #1
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Solution: Care Match
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Amino’s Care Match algorithm What is Care Match? A ranking algorithm that matches patients with doctors based on the number of similar patients they have treated—people with the same condition, same gender, and in the same age range.
How does Care Match work? Assesses the similarity between the patient and the doctor’s other patients and ranks the results
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Problem #2 There’s no such thing as a board-certified “pancreas”
expert.
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Solution: Focus Areas
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Data mining to identify focus areas
Gastroenterologists
Irritable Bowel Diseases
Food allergies
1. Identify the right dataSelect relevant diagnoses or procedures for grouping the doctors
2. Create clusters Group doctors based on how often they perform a set of procedures or diagnose a condition
3. Hand label the clusters Label the clusters in simple understandable terms using expert knowledge
4. Assign doctors to clusters Determine the focus areas for each doctor based on similarity to the clusters
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Focus areas in practice
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How do you know what actually goes on in a doctor’s office – the procedures, patient outcomes, quality of
care?
Problem #3
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Solution: Risk Adjusted Decision Factors
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What is a C-section decision factor? To help patients understand how a doctor’s C-section rate compares to a typical doctor who delivers babies:
1. Doctors C-section rate: Measure the actual C-section rate for the pregnant patients a doctor treats
2. Predicted C-section rate from a model: Analyze the typical practices of all other doctors in the United States who deliver babies using a model to predict the C-section rate for patients like the ones who see the doctor
3. Classification: Compare the two numbers and determine whether the doctor’s C-section rate is lower than, similar to, or higher than predicted
Data modeling to identify outcomes
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The responsibility with visualizationAccurate Our goal with every analysis is to accurately and responsibly present facts that help patients make decisions about their care.
ParsimoniousPresent clear and easily understandable results.
Engaging and empathetic to the patientsAlways have the patients in mind.
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Final ThoughtsIt’s all about the patients! All of our efforts are to engage and empower patients. Data, modeling, and visualization are all means to helping patients make better decisions.
Healthcare in the age of Big Data. We live in the age of Big Data and the possibilities are endless. Big data will bring detailed information on all aspects of healthcare to patients and influence their choices.
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Choose care with confidence.