Holistic Health Records and Big Data Analytics for Health Policy - - PowerPoint PPT Presentation

Holistic Health Records and Big Data Analytics for Health Policy Making & Personalized Health

Lydia Montandon (Atos) · Project Coordinator Dimosthenis Kyriazis (Un. of Piraeus) · Technical Coordinator

Content

• The ‘What’
• The ‘Why’
• The ‘How’
• The ‘Who’

July 8, 2017 2

July 8, 2017 3

The ‘What’

Information Acquisition

Evidence-based Health Policies Creation Policies Evaluation Simulations Big Data Management Data Governance Reliable Info Data Visualization & Analytics

Heterogeneous Data Sources

+

Collective Knowledge = [SHHR]

1 2 5 4

CrowdHealth Snapshot

Chronic diseases Medication centres Social networks Living labs Public environments

July 8, 2017 4

3

July 8, 2017 5

Terminology & Acronyms

EHR PHR SHHR HHR Holistic Health Records Personal Health Records Electronic Health Records Health-related elements and additional data (e.g. nutrition, lifestyle choices, etc.) Social Holistic Health Records Cluster / network of HHRs

July 8, 2017 6

Terminology & Acronyms (cont’d)

Policies KPIs Parameters of policies that can be monitored, evaluated, adapted, etc. Health Analytics Risk Analytics, Forecasting, Causal Techniques and Clinical Pathways Mining APIs & Gateways Interfaces of devices / data sources Situational Knowledge Context Analysis

July 8, 2017 7

The ‘Why’

July 8, 2017 8

The CrowdHEALTH Story

Wearables & Smart devices

(a) Fragmented Health Strategies (b) Inefficient personalized health care

• Independent and heterogeneous services
• Limited data exploitation
• Health Records (EHRs & PHRs) of limited value

EHR EHR EHR PHR PHR PHR EHR data data

Specific Health Policies

• Ineffective and untargeted health policies

Social care data Medical device data Personal data (health, social, lifestyle) Healthcare data Laboratory medical data

Current Approaches

July 8, 2017 9

The CrowdHEALTH Story

Wearables & Smart devices

CrowdHEALTH Platform

HHRs Public Health Policies

Experience & Relationships with other HHRs

Social care data Medical device data Personal data (health, social, lifestyle) Healthcare data Laboratory medical data

Social HHRs

Contextual Information

(a) Public Health Strategies (b) Personalized Medicine, Healthy Life Support and Disease Prevention

Security Framework Big Data Platform

July 8, 2017 10

The ‘How’

▶ Social HHRs mean HHRs that are enriched / updated with information from

• ther HHRs (their “experiences”) to propose health-oriented activities.

▶ Exploitation of collective knowledge by adopting partially or completely elements (care plans, practices, activities, etc) included in other HHRs

• Based on clusters of different elements – e.g. nutrition-related

July 8, 2017 11

Evolution of health records

Health Record Holistic Health Record (HHR) Social HHR Social HHRs (Clusters of HHRs)

HHRs & Social HHRs ▶ Objectives:

• Exploitation of heterogeneous data

sources and compilation of collective knowledge through Social HHRs.

• Ensuring secure cross-sector and

multi-actor data exchange.

▶ Innovations:

• Compilation of collective knowledge

for the provision of efficient public health policies and services.

• Creation of a security framework for

trust management, adaptive selections, data anonymization, access control, and authorization.

July 8, 2017 12

Objectives, Innovations & Propositions (1/3)

Propositions

• HHR structures enabling

capturing of different data

• Contextual analysis tools
• Clustering / classification

technologies for analyzing HHRs and their networks / HHRs clusters

• Users’ preservation, and

data integrity techniques

• Access control schemes

Data Management ▶ Objectives:

• Facilitating new insights to healthcare

by exploiting all available data sources.

• Data visualization for analyzing
• utcomes in a meaningful and

proficient way.

▶ Innovations:

• Provision of added value real-time

HHRs and health policies.

• Incremental data visualization

techniques delivering data analytics

• utcomes.

July 8, 2017 13

Objectives, Innovations & Propositions (2/3)

Propositions

• Big data LeanXcale

platform

• Dynamic data sources

integration technologies

• Data cleaning and sources

reliability techniques

• Data aggregation

mechanisms (feeding HHRs)

• Data monitoring and

visualization workbench

Health Policies ▶ Objectives:

• Modelling, creation and co-innovation
• f multi-modal health policies.
• Evaluation and adaptation of cross-

domain policies.

▶ Innovations:

• Dynamic knowledge extraction

through data deriving from data sources, social HHR networks, and predictive risk/causal analysis, with respect to all health determinants.

• Dynamic knowledge extraction

through the outcomes of simulations and evidence based approaches.

July 8, 2017 14

Objectives, Innovations & Propositions (3/3)

Propositions

• Structural representation

including several KPIs

• Health analytics

(algorithms)

• Prediction / forecasting
• Clinical pathways
• Risk identification
• Causes analysis
• Identification of closed

groups for simulations

• Evaluation of policies from

closed groups

July 8, 2017 15

July 8, 2017 16

The ‘Who’

July 8, 2017

Who participates in CrowdHEALTH?

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July 8, 2017 18

Use Cases – Pilots

July 8, 2017 19

5 Use Cases – 6 Pilots

• HULAFE
• KAROLINSKA

Health centers

• BIOASSIST

Chronic diseases

• CARE ACROSS

Social networks

• DFKI

Living labs

• UNI LJUBLJANA

Public environments

July 8, 2017 20

Factsheet

Factsheet

• Multidisciplinary International Research

and Innovation Project

• Funded by Horizon 2020 Programme of

the European Commission

• 19 Partners
• Project coordinator: Atos Spain
• Technical coordinator: Uni of Piraeus
• Duration: March 2017 – February 2020
• Funding: 5 Mio
• Project Officer: G. ROESEMS-KERREMANS

July 8, 2017 21

July 8, 2017 22

Inspired?

July 8, 2017 23

“Collective wisdom driving public health policies”

▶ Numerous health ICT services

• Several health services
• Limited data exploitation
• Inefficient personalization in

health care provisioning

• Health records (EHRs & PHRs)
• f specific value
• Ineffective, untargeted, and

fragmented health policies

Today

▶ Health policies exploiting big data

• Heterogeneous data sources

integration

• Holistic health records (HHRs)
• Data analytics on aggregated

data

• Exploitation of collective

knowledge

• Multi-modal targeted policies

Tomorrow

THANKS

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Questions? www.crowdhealth.eu