Queensland Health

Healthcare Data Maturity:

From Data Lake to Data Wharf

to Data Marina

Dr Renato Iannella29 JULY – 1 AUGUST 2018

SYDNEY, AUSTRALIA

OverviewHealthcare has a large data ecosystem

We collect significant amounts of data for specific purposes

We don't share very well or reuse

Data Lakes are about the potentialfor Healthcare data to be optimised

Provides a reference platform for sharing and advanced Data Analytics

Design of the Data Lake will be constantly changing and maturing…

The Maturity Paradigm

Photo by Elliot Pannaman on Unsplash Photo by Enrapture Media on UnsplashPhoto by chuttersnap on Unsplash

Data Lake Framework

Operational Sources

Ingest

Raw Sources

Catalogue

Data Analytics

Optimised

Transformations

Consumption

Discovery DeliveryExternal Sources

Information Maturity CapabilitiesKnowledge - this capability is the collective knowledge of information across the enterprise

Standards - This capability is the alignment of information to conform to applicable standards

Consumption - This capability is the sharing of information across the enterprise to consumption points

Analytics - capability is the integration of information across the enterprise to support common objectives

Governance - This capability is the control, protection, and assurances of information across the enterprise

Environment - This capability is the platform for information platforms and services

Source: Gartner, 2017 Source: https://freshersplane.com/wp-content/uploads/2014/10/CMMI-Levels.jpg

Maturity - StandardsCommon views of healthcare data

Shared Semantics

Data Model Standards

ADHA, HL7, FHIR, ISO,

Jurisdictions…

Terminology, Reference Data

SNOMED, AMT, ICD…

Healthcare Standards

ACHS, Clinical Quality, HACs…

Identity

Local Patient Identifiers, IHI,

HPI-I, PHI-O…

Source: ISO:13940 Source: ADHA Participation Specification Source: WA Health Enterprise Information Model

BI Example

Source: eHealth Queensland, Benson ChoySource: Metro South HHS

Data Lake Maturity

Optimised Transformations

Engines

Reference ModelsBusiness Models

Data DictionaryReference Data

Terminology

Quality

Stewardship

Semantic ModelsAlgorithmsMachine Learning

Maturity - GovernanceData Lake - only the raw data gets in

…all other governance, consent, and provenance information is left behind

Needs to be digitally "re-created" more dynamically and holistically

Role of "Data Lake Data Custodian"

Proxy for Source Systems Data Custodian's Requirements (Catalogued)

Data In: Light Governance; Data Out: Heavy Governance

Access Policies for Personal/Sensitive Data

Sandbox - Anonymised Data

Focused Access - Subset

Trusted Teams - Full access

Research Use

Data Quality

Stewardship of the Transformation Rules

SummaryThe Data Lake provides a platform for

driving Healthcare improvements

Data Analytics Functions

Link to Action Plans (optimisation)

Develop a Data Lake Reference

Architecture

Wide opportunity for maturity areas

Roadmap the capabilities

Prepare for continuous platform and

services evolution

Healthcare Data Maturity: From Data Lake to Data Wharf to Data Marina

29 JULY – 1 AUGUST 2018

SYDNEY, AUSTRALIA