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AI trends in healthcare
H2O enables value based care delivery
Continuum of careStakeholders throughout lifecycle of care• Patient• Provider• Payer• Manufacturer• Connected Services
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.
Divergent models for paymentPayment for service• Traditional• Individual interactions• Loosely coupled
Payment for outcome• Emerging• Collective result• Tightly integrated
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
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
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
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
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
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
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
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.
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