smartcare the new avatar of healthcare

Smart Care – The New Avatar of Healthcare

Dr. SB BhattacharyyaMBBS, MBA, FCGP

Member, EMR Standards Committee, MoH&FW, GoIMember, Health Informatics Sectional Committee, MHD

17, BISPresident (2010 – 2011), IAMI

Hony. State Secretary (2015), IMA Haryana

The times they are a’Changin…Bob Dylan (1964)

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Healthcare Internet of Things (HIoT)

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“Smart” Care, Not “Sick” Care

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Big Data in Healthcare

• High Volume• Data from all sorts of sources in electronic format

• High Velocity• Data from devices, monitors and variety of systems continuously streaming in

24x7

• High Variety• Data is in almost all types

• High Veracity• Data sources are dependable as they are mostly known

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Big Data in Healthcare

• Sources of data• Wi-Fi/Bluetooth/NCF-enabled personal healthcare monitoring devices,

wearables

• Smartphones/smart devices (iPod, iPad, etc.)

• Radio-diagnostic imaging devices

• Electronic medical records/health records

• Social media

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Big Data in Healthcare

• Data Types• Textual: EHR and clinical and nursing informatics systems

• Numeric: lab systems and devices

• Coded: EHR and devices

• Audio: EHR and lab systems

• Image: EHR and radio-diagnostic systems

• Video: EHR and radio-diagnostic systems

• Waveforms: monitors and devices

• Streaming binary data: wearables, bio-sensors, monitors

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Types of Data Analysis

• Prediction• Classification

• Regression

• Latent Knowledge Estimation

• Structure Discovery• Clustering

• Factor Analysis

• Domain Structure Discovery

• Network Analysis

• Relationship mining• Association rule mining

• Correlation mining

• Sequential pattern mining

• Causal data mining

• Distillation of data for human judgment

• Discovery with models

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Machine Learning Techniques Used

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Algorithm Application Areas

Linear Regression Cost predictions

Logistic Regression Likely outcomes (treatment/intervention)

Neural Networks Likely outcomes (treatment/intervention)

Support Vector Machines In place of linear / logistic regression

Classification (Decision Tree, OneR) and Clustering (K-Means, Cobweb)

Finding groups (clusters) of similar observations like clinical outcomes

Principal Component Analysis Data and image compression

Anomaly Detection (Signal Detection)Any significant observation (signal) amongst a ton of observations (noise)

Recommender Systems (Collaborative Filtering & Market Basket Analysis)

Drug & treatment suggestions based on care provider/patient/peer preferences - personalised medicine

Predictive Analytics

• Data pre-processing and visualisation

• Attribute selection

• Classification (OneR, Decision trees)

• Prediction (Nearest neighbour)

• Clustering (K-means, Cobweb)

• Association rules

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Application Areas

• Operational• Administrative

• Clinical

• Nursing

• Predictive• Clinical decision support

• Outcomes (prognostics) assessment

• Readmission prevention

• Adverse event avoidance

• Disease management

• Patient matching

• Personalised medicine

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“Intelligent” Healthcare

• Application uses advance algorithms, logic and/or artificial intelligence to simulate and/or replicate the decision-making process and guidance of expert clinicians

• Gathering data passive and/or actively from sensors, devices and human input to both understand the current health status of the user and provide confirmation or corrective guidance

New Face of Health Care…

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All images sourced from the Internet (Google Search) and used in good faith to help illustrate the point being made…

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