The Role of the FAIR Guiding Principles for an effective Learning Health System

The Role of the FAIR Guiding Principles
for an effective Learning Health System
Michel Dumontier
Institute of Data Science
Brightlands Institute for Smart Society
Maastricht University
1
micheldumontier::KR4HC:2021-06-16

The Learning Health System (LHS)
An integrated social and technological
system that seamlessly embeds
continuous improvement and innovation
for the effective delivery of healthcare.
A key part of the digital LHS is the
information system to support the
collection and intelligent use of data and
knowledge. Applications include
surveillance, predictive modeling,
comparative effectiveness research, and
clinical decision support
2

Clinical Practice Guidelines
Provide recommendations intended to
optimize patient care that are informed
by a systematic review of evidence and
an assessment of the benefits and harms
of alternative care options.
Lengthy and expensive process to build
these CPGs. Systematic literature review
with expert involvement. Harder to
implement and monitor.
Example: AHA/ASA CPG on early management of acute ischemic stroke
analyzed 421 published references and produced 217 recommendations
Ann. Intern. Med. 168 (2018) JC63.
3

Guideline Clearing House (NGC)
• Getting the latest guidelines for any condition is challenging
• The (US) National Guideline Clearing House (NGC) est. 1998
• ~2550 unique guideline summaries, free to download in XML
(56 attributes)
• Funding ended in 2018 -> no longer accessible.
• Other commercial options do exist, but not nearly the same
level of curation, and not free to use.
4

Complex clinical situations lack clear guidelines
Derived from Fig 1 of J Gen Intern Med. 2014 Mar; 29(3): 529–537.
• Underrepresented groups
• Rare diseases
• Co-morbidity
genetics
5

Case
79-year-old woman, with osteoporosis, osteoarthritis, type 2
diabetes, hypertension, and chronic obstructive pulmonary disease is
seen in a primary care practice
Following guidelines:
- 12 separate medications
- Drug regimen of 19 doses per day, taken 5 times per day
- 14 non-pharmacologic or self-management interventions recommended
- Minimum of 2-4 primary care follow-up appointments per year and
specialty visits needed
- Multiple potential drug-drug/drug-food/drug-disease interactions to
monitor.
Boyd et al. JAMA. 2005;294(6):716–24.
6

Disease-comorbidity co-occurrence in CPGs
HTN
DM
HL
OB
STR
ASM
OSP
FIB
AD
COPD
DEP
CKD HF
ARTH
IHD
Node = No. of guideline summaries
Edge = No. of mentions of comorbid condition
Co-prevalence of Chronic Diseases among
Medicare Beneficiaries, 2012
HTN
DM
HL
OB
STR
ASM
OSP
FIB
AD
COPD
DEP
CKD
HF
ARTH
IHD
Node = Prevalence
Edge = Co-prevalence
Leung TI, Jalal H, Zulman DM, Dumontier M, Owens DK, Musen MA, Goldstein MK. Automating Identification of Multiple Chronic Conditions in
Clinical Practice Guidelines. AMIA Jt Summits Transl Sci Proc. 2015 Mar 25;2015:456-60. PMID: 26306285; PMCID: PMC4525235.
HTN Hypertension
DM diabetes mellitus
HL Hyperlipidemia
STR Stroke
ASM Asthma
FIB atrial fibrillation
AD Alzheimer’s dementia
OSP Osteoporosis
COPD chronic obstructive
pulmonary disease
DEP Depression
CKD chronic kidney
disease
HF heart failure
ARTH Arthritis
IHD ischemic heart
disease
OB obesity

The digital LHS continuously advances medical science
and maximizes desirable outcomes for individuals
Practice-based medicine
can fill the gaps where
there is insufficient study
or evidence to make
strong recommendations.
Leung, Dumontier. Stud Health Technol Inform. 2019
Clinical
Practice
Guidelines
Patient Data
Scientific
Research
Personalized
Medicine
Medical Practice
+ Consumer
Health
8

Towards Personalized Medicine
Safe and effective practice- and
evidence-based medicine creates digital
health information that fuels scientific
research, suggests evidence-based
recommendations, and helps to realize
the vision of personalized medicine.
9

An international, bottom-up framework for
the discovery and reuse of digital content
for people and the machines they use
10

http://www.nature.com/articles/sdata201618 11

12

Making FAIR Data
Data
Ontologies,
Vocabularies
Standard data
format Standardized Metadata
FAIR Data
Standardized Data
Schema
Datatypes
Analyze Transform Publish
Provenance
Licensing
Standardized
Data
Access
Standard
metadata
format
Metadata
ontologies +
Vocabularies
Gather
+ +
13

Recommendations for FAIR CPGs
• Use of unique, persistent identifiers, such as a Digital Object Identifier (DOI) or
TrustyURI
• Rich, standardized descriptions of CPGs that can be indexed by CPG repositories
• Make use of standard identifiers for representational elements (e.g.
medications, diseases/phenotypes/co-morbidities/adverse events, procedures,
labs)
• Formal and standardized representations of CPGs (e.g. Patient-Intervention-
Comparison-Outcome + format: JSON-LD).
• Detailed provenance regarding how/when the CPGs were developed (e.g.
authors, contributors, methods, resources/publications used, metadata)
• Clear, standard licenses (ideally open/free) for CPGs & their metadata
- Make CPG summaries (metadata) available, even if CPG is behind a paywall!
14

What if CPGs contained
structured bits of knowledge?
micheldumontier::KR4HC:2021-06-16 15

Then these articles would directly contribute to our
collection of structured knowledge

And relevant bits could be collectively retrieved for
discovery, verification, and further analysis

Data Science. 2017 1(1-2):139-154. DOI: 10.3233/DS-170010
http://www.tkuhn.org/pub/sempub/

19

"AIMOVIG is indicated for the preventive
treatment of migraine in adults."
20

• Dashboard
- Latest nanopublications (by you and the
community)
• Knowledge Curation
- Structure input through semantic templates
- Support input (e.g. autocomplete via terminology
services)
• Knowledge Publication
- Digital signing
- ORCID
• Knowledge Discourse
- Commenting
- Indicating Approval/Disapproval
- Retraction

Form autocomplete with term/id support

http://purl.org/np/RAQDNFfhHGiatY6Vqfh-YoX1uCNsQNqLizUeHoUygRttQ

The Knowledge Collaboratory
27

10M+ nanopubs in a decentralized network
http://purl.org/nanopub/monitor
28

Scientific claims should be traceable and verifiable
• Valid citation of scientific evidence is
important to mitigate the
propagation of inaccurate claims.
• Citation distortion occurs when a
claim is stated as fact yet actually
has no supportive empiric evidence.
• Scholarly work and popular media
claim that “300 to 400 U.S.
physicians die by suicide annually.”
• Performed scoping literature review
articles published 1903-2018
revealed 49 claims concerning rate
of US physician suicide
https://doi.org/10.1101/2020.05.16.20101881 29

30

Element for a LHS
31

• Bring the analysis to the data
• Citizens/public and private
organisations provide consent and
control access
• Transparent and authorized data
analytics in trusted, secure,
protected environments
• Aggregated results/models are
returned
Stud Health Technol Inform. 2019 Aug 21;264:373-377. doi: 10.3233/SHTI190246.

FAIR principles can facilitate the development,
management and stewardship of CPG knowledge
• The FAIR principles aim to address issues in digital resource
discovery, accessibility, interoperability, and reuse.
• The FAIR principles strengthen the connection between CPGs and the
best evidence that support them.
• The FAIRness of digital objects can be automatically assessed,
enabling accountability and transparency of data quality on which
CPGs are based.
33

Make CPGs machine actionable
• A consortium of Dutch researchers and IKNL
• Guideline recommendations represented as
clinical decision trees
• Fully data driven, uses 114 data items
• 376 unique subpopulations described in the
Dutch national breast cancer guideline
• Implemented in Oncoguide as clinical
decision support system
• SNOMED CT coding in ART-DECOR format.
REST interfaces
• www.oncoguide.nl
JCO Clin Cancer Inform. 2019; 3: doi: 10.1200/CCI.18.00150
34

Summary and Prospects
The digital LHS holds great potential, but it is held back by the difficulty in
accessing or developing key assets
• Machine actionable, evidence-based clinical practice guidelines
• Sufficiently detailed and representative patient data
• Robust and accurate models constructed from practice-based
medicine to support medical decision making in complex situations
The FAIR Principles offer a framework that is relevant to creating the
digital LHS and should be taken into consideration to component
resources easier to find, access, and reuse – provided that law, culture,
and ethics also advanced with these developments.
35

Acknowledgements
CPGs: Tiffany Leung
Nanopubs: Tobias Kuhn
PHT: Chang Sun, Johan van Soest, Lianne Ippel,
Annemarie Koster, David Townend, Andre Dekker
36

michel.dumontier@maastrichtuniversity.nl
Website: http://maastrichtuniversity.nl/ids
The mission of the Institute of Data Science at Maastricht University is to foster a
collaborative environment for multi-disciplinary data science research,
interdisciplinary training, and data-driven innovation .
We tackle key scientific, technical, social, legal, ethical issues that advance our
understanding across a variety of disciplines and strengthen our communities in the
face of these developments.
37

The Role of the FAIR Guiding Principles for an effective Learning Health System

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