ai trends in health care - manuel salgado, mckesson
TRANSCRIPT
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AI trends in healthcare
H2O enables value based care delivery
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Continuum of careStakeholders throughout lifecycle of care• Patient• Provider• Payer• Manufacturer• Connected Services
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Value Based Care• Value-Based Care (VBC) is a strategy used by
purchasers to promote quality and value of health care services. The goal of any VBC program is to shift from pure volume-based payment, as exemplified by fee-for-service payments to payments that are more closely related to outcomes.
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Divergent models for paymentPayment for service• Traditional• Individual interactions• Loosely coupled
Payment for outcome• Emerging• Collective result• Tightly integrated
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VBC needs advanced data & analytics
• Arriving at the best value requires optimizing cost and benefit across all links in the treatment value chain
• This necessitates each link to analyze the data from their own perspective in relation to all others
• Having a framework for advanced analytics that enables fast & agile development of machine learning models to answer the multitude of questions over large amounts of data is necessary to thrive in this payment environment
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360° view of stakeholder• In Healthcare there isn’t a single customer• At any point during the delivery of care each
of these stakeholders becomes the client in need of a 360° view
• Each with different but related questions that involve the other stakeholders
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360° view of the patient• Project length of recovery and
success rate given the different treatment options
• Which option will be the most effective at the lowest cost across providers and treatments
• Estimate cost throughout life of treatment amongst different payers
• Predict additional services based on other patients that have undergone similar treatment
Patient
Payer
Manufacturer
Services
Provider
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360° view of the provider• Develop tailored treatment
recommendations based on empirical outcome evidence across all patients
• Predict profitability across treatments and actual payer fee schedules
• Optimize services portfolio to maximize clinical and financial success
Provider
Payer
Manufacturer
Services
Patient
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360° view of the payer• Analyze patient characteristics
and the cost and outcomes of treatments to identify the most clinically effective and cost-effective treatments to apply
• Profile disease on a broad scale to identify predictive events and support prevention initiatives
• Detect fraud and check claims for accuracy and consistency
Payer
Patient
Manufacturer
Services
Provider
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360° view of the manufacturer• Optimize profitability of product
supply chain (manufacture, distribution, and delivery) to current and future demand
• Tailor R&D expense to conditions and treatments with highest future demand, positive outcomes and need across patient populations
• Focus marketing efforts with better segmentation across geographies, payer response, and disease types
Manufacturer
Payer
Patient
Services
Provider
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Converge all 360° views = Sphere view• Aggregating each 360°
perspective results in a sphere view of knowledge
• Necessary to obtain a holistic view across the continuum of care that will derive the most value for holistic treatment
• Machine learning and advanced analytics underpin this information model
Manufacturer
Payer
Patient
Services
Provider Payer
Patient
Manufacturer
Services
Provider Provider
Payer
Manufacturer
Services
PatientPatient
Payer
Manufacturer
Services
Provider
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Enabling the sphere view at warp speedH2O provides:• Data science in a box. Easily apply math and
predictive analytics to solve your most challenging business problems
• Multiple interfaces (from no code UI to advanced integration R, Java, Scala, Python, JSON)
• Supports data in any form. Connect to data from HDFS, S3, SQL and NoSQL data sources
• Massively Scalable Big Data Analysis. Train a model on complete data sets, not just small samples, and iterate and develop models in real-time with H2O’s rapid in-memory distributed parallel processing
• Nano-fast Prediction Engine Score data against models for accurate predictions in nanoseconds.
H2O enables:• Speeds up data analysis, model building,
deployment and scoring• Derive analytic models using either supervised
(classification/regression) or unsupervised (clustering) on existing data to derive new insights from data
• Turn the insights into a working predictive model that can then be used on new data cases to forecast outcomes
• Model can be integrated and used in real-time as part of the regular operational flow of an application. It can also be used in batch mode to score millions of cases at once.
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H20 as core engine of the sphere
Clinical
Financial
PracticeWorkflow
Supply chain
ClassificationRegression
Feature Engineering
Aggregation
Deep Learning
PCA, GLM
Random Forest / GBM Ensembles
Fast Modeling Engine
Streaming
Nano Fast Scoring
Matrix Factorization Clustering
Munging
Ingestion