NLM GEORGIA BIOMEDICAL

INFORMATICS COURSE

September 14 – 20, 2014

What is informatics?

What is biomedical informatics?

• “The field that concerns itself with the cognitive,

information processing and communication tasks of

medical practice, education and research, including the

information science and the technology to support these

tasks.”

Greenes RA, Shortliffe EH.

JAMA 1990 Feb 23; 263(8):1114-20.

Burning Platform: Overwhelming ComplexityS

ets

of

Fa

cts

pe

r D

ec

isio

n

1000

10

100

5

Human

Cognitive

Capacity

2000 20101990 2020

SNPs, haplotypes,

gene expression

profiles, post-

translational

modification

Decisions by clinical

phenotype

Stead WW. Beyond expert-based practice. IOM (Institute of Medicine). Evidence-based medicine and the

changing nature of health care: 2007 IOM annual meeting summary,(Introduction and Overview, p. 19).

Washington, DC: The National Academies Press 2008.

Socio-cultural

determinants of

health

Today’s Presentation

• Medical Vocabularies

• Electronic Health Records, Meaningful Use, and Health

Information Exchange

• Semantic Medline

• Data Visualization

• Other Topics

• Future Research Priorities

• How this applies to my/our work

Medical Vocabularies

• MeSH

• CPT

• DRG

• SNOMED-CT

• ICD-10

• NDC

• RxNorm

• LOINC

• FMA

• GO

• NANDA

• NIC

• NOC

• GHHCC

• PCDS

• Omaha

• AORN

• ICNP

• PSY

• MMX

• MDDB

• CSP

• HCDT

• DSM4

• LCH

• NCISEER

• OMIM

• QMR

• PDQ

• VANDF

• ULT

• SOP

• PPAC

Desiderata for Controlled Vocabularies

Cimino JJ. Desiderata for controlled medical vocabularies

in the Twenty-First Century. Methods of Information in

Medicine; 1998;37(4-5):394-403.

• Content

• Concept Orientation

• Concept Permanence

• Nonsemantic Concept Identifiers

• Polyhierarchy

• Formal Definitions

• Reject “not otherwise classified”

UMLS – A Metathesaurus

“The purpose of the [Unified Medical Language System] is to improve the ability of computer programs to ‘understand’ the biomedical meaning in user inquiries and to use this understanding to retrieve and integrate relevant machine-readable information for users.”

- Donald A.B. Lindberg, 1993

UMLS – A Metathesaurus

UMLS – A Metathesaurus

Some ways to use it

• Reconstructing source terminologies

• Finding additional synonyms for source terms

• Automated translation

Informatics Standards

Informatics Standards

Standards here already:

• Billing (ICD-9-CM, ICD-10-CM, CPT4, DRG)

• Data interchange (HL7)

Standards on the way:

• Health data (CDA)

• Terminology

• Infobuttons

Office of the National Coordinator drives adoption

http://www.healthit.gov/sites/default/files/pdf/fact-sheets/onc-office-of-

interoperability-and-standards.pdf

Electronic Health Records

2004 – President Bush announces goal to have every

American covered by an EHR by 2014

2009 - Health Information Technology for Economic and

Clinical Health Act (HITECH)

Incentive Payments

14

Meaningful Use Stages

Data capture and sharing

Advanced clinical processes

Improved outcomes

15

Stage 1

Stage 2

Stage 3

What’s Next?

• 3 years: Ensure use,

work on data standards,

address policy/trust

issues

• 6 years: Incorporate

patient-generated data,

improve data

aggregation/analytics,

automate CDS and CQI

• 10 years: the Learning

Health System

Using the EHR for Discovery

De-identification

Synthetic Derivative ~ 2 million records

De-identified DNA repository>170k samples

VanderbiltBioVU

Clinical

Notes

Physician

Orders

Patient and Staff

Messaging

Billing

codes

Labs, Radiology, Test

Results

Electronic Medical Record

Health Information Exchange

Health Information Exchange

• Health information exchange (HIE) is the electronic

movement of health-related information among

organizations according to nationally recognized

standards.

-Health Resources and Services Administration

Health Information Exchange

Why early ones failed

• Funded with temporary investments and grant support

• Health systems perceive risk > benefit

• Old habits

nomatterwheremovie.com

Semantic Medline

• Typical search technologies rely on similarity…

Semantic Medline

• …not meaning.

Semantic Medline

• This isn’t really about whether smoking causes asthma…

Semantic Medline

• Literature-based discovery and the problem of “mutually

oblivious literatures”

Medical literature as a potential source of new knowledge.

Swanson DR.

Bull Med Libr Assoc. 1990 Jan;78(1):29-37.

PMID: 2403828

These literatures never cite each other.

Semantic Medline

• SemRep extracts meaningful predications

Tamoxifen Breast carcinomaTREATS

CDKN1A gene Breast carcinoma

ASSOCIATED_WITH

Aromatase Inhibitors Breast carcinomaTREATS

CDKN1A gene BARD1 geneSTIMULATES

Semantic Medline

• Useful for discovering mechanistic links

Semantic Medline

Successes so far

• A closed literature-based discovery technique finds a mechanistic

link between hypogonadism and diminished sleep quality in aging

men [Miller et al., Sleep 2012, PMID 22294819]

• Semantic MEDLINE for discovery browsing: using semantic

predications and the literature-based discovery paradigm to

elucidate a mechanism for the obesity paradox [Cairelli et al., AMIA

Annu Symp Proc 2013, PMID 24551329]

Try it yourself

• Request a license to access the UMLS Metathesaurus

Browser, Semantic Medline, and more

https://uts.nlm.nih.gov/home.html

Data Visualization

• “From data to insight”

TwinList

https://www.youtube.com/watch?v=YXkq9hQppOw

Other Topics

• Genomics

• Mathematical Modeling

• NLM Resources

• Clinical Research Informatics

• Big Data and the Cloud

• Consumer Health/Social Media

• Disaster Informatics

• Public Health Informatics

• Telehealth and Imaging

• Organizational Issues

Marching Orders

• Natural language

understanding

• Interactive

publications

• Clinical Trials

• Reproducibility of

results

Apply now for 2015 sessions

• Spring dates: April 12-18

• Fall dates: September 27 – October 3

• To

apply:http://gru.edu/library/greenblatt/informaticscourse/appl

y.php