Michael Legg - Pathology SIG - Laboratory Medicine and Informatics in Proactive and Personalised Healthcare

14-15-Oct-2013 Informa National Pathology Fourm 2013 1

Laboratory Medicine and Informatics in the

Shift from Reactive to Proactive Healthcare Michael Legg - UNSW and Royal College of Pathologists of Australasia

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14-15 October 2013 National Pathology Forum 18

What is the role of informatics in PPPM?

• Informatics is both an enabler and driver in PPPM. Advances abound in

informatics and biological research but practical PPPM is in its infancy

and there is a disconnect in most health systems – especially with their

information systems

• Although challenging enough, more is required than bridging

bioinformatics and medical informatics – there is a need for high level

planning and co-ordination of informatics for PPPM

• The knowledge, work practices and informatics of laboratory medicine

must be more engaged for PPPM to meet its potential – sensitivity,

specificity and quality systems remain important

• More standardisation of health information, knowledge and informatics is

needed for discovery and for PPPM to be effective, efficient and safe

• Education in informatics and more specialist informaticians are needed


Informatics is central to proactive healthcare

It is needed to:

• Undertake the analysis of bio data, information and knowledge related

to molecular medicine and its links to disease for discovery and

service delivery

• Gather and synthesise inputs from machines and people for optimal

clinical decisions

• Engage consumers and provide the information and tools they need

to make decisions and change behaviours

• Learn from what has happened at the individual, process and health

system levels

• Manage the information and knowledge that health workers need to

make their jobs safer and easier

• Facilitate standardisation and remove inappropriate variation

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But we have some challenges

• We don’t have a shared understanding even of what constitutes the

domain of informatics in health or what to call its components

• The domain of informatics used for recording, analysing,

communicating and doing the business of healthcare I call health

informatics

• The domain of informatics used to unravel and understand the

molecular and cellular workings of biology I call bioinformatics

• In most places these domains are still operating in separate

universes

• After 50 years we are only just starting to realise health informatics

and we have only just commenced integrating that with

bioinformatics


Biomedical informatics and

personalised medicine

In Europe the informatics gap between bench and bedside is being

addressed by INBIOMEDvision through think-tanks and publications on

the themes

• Genotype-phenotype integration

• Re-use of clinical information for research

• Translational systems biology and bioinformatics

• Horizontal aspects

They call this work biomedical informatics


Genotype-phenotype integration

Trends

• To develop validated repositories and standards

• To develop specific tools and resources for proof of concept in

areas like rare diseases to gain clinicians trust

• To develop tools and resources based on genotype-phenotype

associations for patient stratification in clinical trials


Genotype-phenotype integration

Challenges

• Genotype-phenotype knowledge is large, complex, prone to

errors, and has small effects and uncertain conclusions

• Genotype-phenotype research data are not suitable for

packaging and display for clinical application or training

• Doctors are uninformed about the nature, limitations and

potential of modern genotype-phenotype knowledge

• Failure to discriminate between scenarios where molecular data

can be ‘predictive’ as opposed to risk modifying


Re-use of clinical information for research

Trends

• To propose few standards in the beginning and allow them to

evolve pragmatically

• To digitalise and standardise data capture to allow better quality

and optimisation for sharing and re-use for research

• To increase automation of data entry to facilitate clinicians and

clinical communities work

• To involve clinicians from different lines of work

• To promote projects for capturing clinical data that might be used

worldwide across regional and country boundaries and between

hospital and community settings


Re-use of clinical information for research

Challenges

• To unify and standardise items in the EHR

• To determine the minimum data to include ensuring better

quality of data entry or capture

• To ensure better interoperability of IT

• To incorporate new types of data (environmental, complete

genomes etc)

• To promote unification of regulations for EHR (legal, ethical,

security confidentiality)

• To study quality assurance especially in the analysis of

retrospective clinical data


Translational systems biology and

bioinformatics

Trends

• To standardise methodologies

• To standardise database formats

• To apply crowd-sourcing and collaborative-competition in

systems biology


Translational systems biology and

bioinformatics

Challenges

• To analyse high throughput studies (GWAS, PheWAS, EWAS)

to obtain bioinformatics signatures in molecular diagnostics,

prognostics, drug response and drug discovery

• To establish reliable and reproducible computational models

(molecular, cellular, organism, organ and population level)


Horizontal aspects

Trends

• To develop standards

• To retrieve and analyse data using data text mining and

semantic tools

• To retrieve information from population-based data mining

• To use cloud computing

• To design training programs for clinicians

• To develop patient-oriented tools for data sharing and patient

empowerment

• To promote collaboration between communities

(research/clinic/industry)


Horizontal aspects

Challenges

• Data management and integration

• Data security

• User interfaces

• Socioeconomic challenges

• Openness and sharing of information

• Physician education and training

• Patient empowerment

• Industry-academy collaboration

• Intellectual property


There is an elephant in the room


We don’t have the standards,

infrastructure or people

• There are massive storage and analysis requirements - much more

than generally recognised - the human pangenome at 1024 bytes is

1000 times all current world storage. As the number of sequenced

genomes increases, storage capacity will become limiting

• The current approach of diagnostic laboratories to genomic

medicine is unsustainable

• The healthcare related scientific community has too few

informaticians and unfortunately many of those that we do have are

without the breadth of understanding of the field to make the kind of

advances that are needed. This is well illustrated by the existing gulf

between health and bio-informaticians


Informatics standards

The only way forward is to agree what we will keep and how - but after

more than 20 years of standards development work there is no widely

accepted and adopted standards for:

• Grammar to communicate health care information – despite

progress with standards like HL7v2.x and CDA

• Information structures – despite progress with models like

HL7v3-RIM and OpenEHR

• Terminology – despite progress with SNOMED, LOINC, HUGO

and many others

• Rules and knowledge – despite progress with Arden Syntax,

GELLO and others


In short…

More than ten years after sequencing the

human genome we do not have the

knowledge, education or informatics tools to

implement clinical genetics, genomics,

proteomics, metabolomics or epigenetics

into practical personalised medicine


Science and innovation is the answer to the

looming threat to sustainable healthcare


What needs to happen…

• Informatics for PPPM has to be seen as a discipline in its own

right and be a research and education theme

• Work on integrative informatics has to be done globally and that

will require planning and engagement with the standards

development organisations

• Progress will require action based research using prototyping

and agile development in a real-world provider network

• Standardisation could start with existing registries and their

feeds


What are the benefits for patients and

healthcare?

• Digitisation of biology and health – will allow machines to help in discovery and delivery

– lead to a demystification of disease,

– the democratisation of healthcare

– and allow us to move from the treatment of disease to the

promotion and maintenance of wellness

• Digital technology has disrupted other sectors – medicine is

unlikely to remain immune from this

Health & Medicine

Michael Legg - Pathology SIG - Laboratory Medicine and Informatics in Proactive and Personalised Healthcare