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AI trends in healthcare
H2O enables value based care
delivery
Continuum of care
Stakeholders throughout lifecycle of care
• Patient
• Provider
• Payer
• Manufacturer
• Connected Servic...
Value Based Care
• Value-Based Care (VBC) is a strategy used by
purchasers to promote quality and value of
health care ser...
Divergent models for payment
Payment for service
• Traditional
• Individual interactions
• Loosely coupled
Payment for out...
VBC needs advanced data & analytics
• Arriving at the best value requires optimizing cost and
benefit across all links in ...
360° view of stakeholder
• In Healthcare there isn’t a single customer
• At any point during the delivery of care each
of ...
360° view of the patient
• Project length of recovery and
success rate given the different
treatment options
• Which optio...
360° view of the provider
• Develop tailored treatment
recommendations based on
empirical outcome evidence
across all pati...
360° view of the payer
• Analyze patient characteristics
and the cost and outcomes of
treatments to identify the most
clin...
360° view of the manufacturer
• Optimize profitability of product
supply chain (manufacture,
distribution, and delivery) t...
Converge all 360° views = Sphere view
• Aggregating each 360°
perspective results in a sphere
view of knowledge
• Necessar...
Enabling the sphere view at warp
speed
H2O provides:
• Data science in a box. Easily apply math and
predictive analytics t...
H20 as core engine of the sphere
Clinical
Financial
Practice
Workflow
Supply chain
Classification
Regression
Feature
Engin...
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AI trends in health care - Manuel Salgado, Mckesson

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Manuel Salgado, Sr. Data & Analytics Manager at McKesson, talks about the AI trends in healthcare. #h2ony

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Published in: Data & Analytics
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AI trends in health care - Manuel Salgado, Mckesson

  1. 1. AI trends in healthcare H2O enables value based care delivery
  2. 2. Continuum of care Stakeholders throughout lifecycle of care • Patient • Provider • Payer • Manufacturer • Connected Services
  3. 3. 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.
  4. 4. Divergent models for payment Payment for service • Traditional • Individual interactions • Loosely coupled Payment for outcome • Emerging • Collective result • Tightly integrated
  5. 5. 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
  6. 6. 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
  7. 7. 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
  8. 8. 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
  9. 9. 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
  10. 10. 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
  11. 11. 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
  12. 12. Enabling the sphere view at warp speed H2O 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.
  13. 13. H20 as core engine of the sphere Clinical Financial Practice Workflow Supply chain Classification Regression Feature Engineering Aggregation Deep Learning PCA, GLM Random Forest / GBM Ensembles Fast Modeling Engine Streaming Nano Fast Scoring Matrix Factorization Clustering Munging Ingestion

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