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HEXAnord2?Copenhagen 13 Sept 2012

A pipeline for capturing, cleaning and reasoning about patient events

Øystein Nytrø, Rune Sætre

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Motivation

• Are we looking for a use case?– or are we just fiddling about with tools and toys?

• Why do we want to capture, clean and reason about patient events– Utilize existing guidelines (to save a patient, clinical)– Improve quality of care for an existing group of patients

• Research, secondary use

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• 13 år • Systemisk Lupus

Erythematousus - SLE • + alvorlig proteinuri • + Anti-fosfolipid antistoff • + betennelse i bukspyttkjertel

(pancreatitt) • Blodfortynnende behandling?

• Frankovich, J., C. A. Longhurst, et al. (2011). "Evidence-based medicine in the EMR era." New England Journal of Medicine.

• Ingen litteratur • STRIDE – Stanford Translational Research Integrated Database Environment • En kliniker + 4 t • Søkte opp alle 98 pas med denne diagnosen • Så på risikofaktorer for trombose

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Secondary use, data research

• The coming age of data-driven medicine: translational bioinformatics' next frontier, JAMIA 2012;19: editorial Nigam H Shah, Jessica D Tenenbaum

• «We believe that the time is ripe for medicine to embrace Big Data, to usher in the age of data-driven medicine—and to truly enable proactive, predictive, preventive, participatory, and patient-centered health. Data-driven medicine will enable the discovery of new treatment options based on the multi-model molecular measurements on patients and learning from the trends hidden among the diagnoses, prescriptions, and discharge summaries of millions of patient encounters logged by clinical practitioners. The increasing synergy between the Translational Bioinformatics Summit and the Clinical Research Informatics Summit is an indication of this impending convergence. This is an exciting time when medicine begins utilizing massive amounts of data to discover patterns and trends and to make predictions in a manner that is a mainstay of web-scale computing.42»

• Hva skal til? • (Lysark fra HUGIN/flyt)

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Relevant literatur

• Ohno-Machado L. Informatics research to enable clinically relevant, personalized genomic medicine.J Am Med Inform Assoc 2012;19:149–50.

• Floratos A, • Honig B, • Pe'er D, • et al . Using systems and structure biology tools to dissect cellular phenotypes. J Am Med Inform Assoc 2012;19:171–5.

• Musen MA, Noy NF, Shah NH, et al. The National Center for Biomedical Ontology. J Am Med Inform Assoc 2012;19:190–5.

• Kohane IS, • Churchill SE, • Murphy SN . A translational engine at the national scale:

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Demo

• uCompare– http://u-compare.org/

• Brat– http://brat.nlplab.org/

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«Keeping patients out of hospital»Capturing care trajectories (PasTas)

CareTrajectory

As experienced

As documented

As

… done

As planned

Asper

norm

Asintended

or wanted

Asa collaborative

process

As oneamong more

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Trajectory technology

Capture & reasoning• NLP• Data quality and referent

tracking.• NER & events• Anonymization• Temporality, persistence

and event reasoning

Alignment:• Clustering & search• Process models

Analysis:• Query & visualization• «Carelets»• Care mapping for individual og

group.

Evaluation – Properties of the good trajectory:• User-understandable process

features• Composability• Borders• Simple criteria

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Does trajectories exist?

• From a healthcare point of view? – No

• In one HIS? – Hardly, even with nice, global identifiers. Lots of

noise and errors

• Across HIS?– Do not know

• Health data has … low quality and validity, because noone uses them…

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Rune’s CV

• 2003: MSc Computers: BusTUC @ atb.no• 2006: PhD Computer Science NTNU

– Natural Language Understanding (NLU): GeneTUC

• 2010: Postdoc University of Tokyo, TsujiiLab– Natural Language Processing (NLP): MedIE

• 2012: Postdoc NTNU: UbiCompForAll– End User Service Composition

• 2015: Postdoc NTNU– Keeping Patients Out of the Hospital

14Fastlege-Vakten

Japan + α

15Fastlege-Vakten + α