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Problems with Current Approaches to Clinical Data. William R. Hogan, MD Associate Professor of Biomedical Informatics University of Pittsburgh Director, Medical Vocabulary/Ontology Services UPMC. UPMC Overview. Facilities 20 Hospitals 400 Ambulatory sites with 2300 physicians

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Problems with current approaches to clinical data

Problems with Current Approaches to Clinical Data

William R. Hogan, MD

Associate Professor of Biomedical Informatics

University of Pittsburgh

Director, Medical Vocabulary/Ontology Services

UPMC


Upmc overview
UPMC Overview

  • Facilities

    • 20 Hospitals

    • 400 Ambulatory sites with 2300 physicians

    • 16 Long-term care facilities

    • 43 Academic/community cancer centers

    • International ventures in Italy, Ireland, Britain

  • Information technology

    • 200 clinical applications from 120 vendors

    • 610 system interfaces

    • $1B investment over 5 years


But one key element was missing
But One Key Element was Missing

  • Interoperability

    • 3 inpatient Electronic Medical Records (EMRs)

    • 3 outpatient EMRs

    • Ancillary systems (lab, radiology, registration, etc)

    • Commercial laboratories (e.g., Quest)

  • dbMotion, Inc.

    • Interoperability solution based on HL7 v3 reference information model

    • Facilitating data exchange for over 70% of Israel


Problem 1 a finding is many things
Problem 1: A Finding is Many Things…

  • The term “finding” does little to discriminate among:

    • Entities and their qualities

    • Surmises, hypotheses, beliefs, degrees of belief, and statements about entities and their qualities

    • Observations/methods of finding entities/qualities

  • Thus, we get:

    • Type 2 diabetes mellitus (disorder)

    • Uncertain viability of pregnancy (finding)

    • On examination - equivocally anemic (disorder)

    • Admitted to a children's home (finding)

    • On examination - dead - unattended death (finding)


Problem 2 but not everything
Problem 2: …but Not Everything

  • Situation: used in SNOMED-CT for conditions/ procedures:

    • That are absent or have not occurred

    • Pertain to someone other than subject of medical record

    • That occurred or were present in the past

  • Findings, by contrast, have a “default context”:

    • Present

    • Subject of medical record

    • Current or some specified time


Thus we get
Thus, we get:

  • No family history of cardiovascular accident or stroke (situation)

  • Absence of signs and symptoms of physical injury (situation)

  • Electrocardiogam improved compared to prior study (situation)

  • Pathology examination findings absent (situation)

  • Past myocardial infarction diagnosed on ECG AND/OR other special investigation, but currently presenting no symptoms (disorder)



Past history of colon cancer increases one’s risk. Thus, to determine “average risk”, you need to know if this risk factor is present.


The following could also be problematic
The following could also be problematic… to determine “average risk”, you need to know if this risk factor is present.

  • Body mass index 20-24 - normal (finding)

  • Erythrocyte sedimentation rate (ESR) abnormal (finding)

  • C-reactive protein abnormal (finding)

  • Lupus hepatitis (disorder) is aSystemic lupus erythematosus (disorder)

  • On examination - equivocally anemic (disorder) is aAnemia (disorder)

  • Chronic hypertension complicating AND/OR reason for care during childbirth is a Pregnancy-induced hypertension


Epistemological basis of finding
Epistemological Basis of “Finding” to determine “average risk”, you need to know if this risk factor is present.

  • According to SNOMED-CT User Guide (p. 42):

    Concepts in [the Clinical Finding] hierarchy represent the result of a clinical observation, assessment, or judgment, and include both normal and abnormal clinical states.

  • SNOMED is not alone:

    • RadLex: Cardiovascular disease is a Imaging observation

    • NCI Thesaurus: Death is a Finding


Proposed definition
Proposed Definition to determine “average risk”, you need to know if this risk factor is present.

  • Clinical Finding =def.

  • A representation of a bodily feature of a patient that is recorded by a clinician because the feature is hypothesized to be of clinical significance.

    Emphasis is mine.

  • Caution:

    • Be careful to distinguish the feature itself from…

    • The method, timing, certainty, etc. related to how we found it

    • And the record of all the above


Ontology vs epistemology
Ontology vs. Epistemology to determine “average risk”, you need to know if this risk factor is present.

  • Ontology*

    The science of what is, of the kinds and structures of objects, properties, events, processes and relations in every area of reality

  • Epistemology†

    • The study of how cognitive subjects come to know the truth about given phenomena in reality

    • …it encompasses the ways in which physicians come to know about the existence of given diseases in given patients

*Smith B. Ontology. In: Floridi L, ed. The Blackwell Guide to Philosophy of Computing and Information: Blackwell Publishing 2003.

†Bodenreider O, Smith B, Burgun A. The ontology-epistemology divide: A case study in medical terminology. In: Varzi A, Vieu L, editors. Proceedings of the Formal Ontology in Information Science Conference (FOIS 2004); 2004; Turin; 2004.


Per snomed ct
Per SNOMED-CT to determine “average risk”, you need to know if this risk factor is present.

  • Disease is a Clinical Finding

  • Also, per the User Guide:

    IS_A relationships are also known as “Supertype-Subtype relationships”

  • Thus, a disease is a subtype of …result of a clinical observation, assessment, or judgment…

  • And so is a Drug action, Edema, Deformity, and Administrative statuses


But, to determine “average risk”, you need to know if this risk factor is present.

  • Diseases, signs, symptoms, etc. all exist regardless of whether a clinician finds them

  • Failure to “find” (i.e., diagnose) cancer is a leading cause of malpractice claims


Problems with epistemological criteria
Problems with Epistemological Criteria to determine “average risk”, you need to know if this risk factor is present.

  • Cannot differentiate true subtype from what is known:

    • Presbyterian vs. Unknown religion

    • Chronic hypertension complicating AND/OR reason for care during childbirth vs. Chronic hypertension

  • Whatever we say is true of all instances of the type Religion, the computer will assume to be true of the Unknown religion,too


Pubmed as barometer of scientific terms
PubMed as Barometer of Scientific Terms to determine “average risk”, you need to know if this risk factor is present.

We gave Chronic hypertension complicating AND/OR reason for care during childbirth every chance. It’s just not a subtype of chronic hypertension.


Epistemology and combinatorial explosion
Epistemology and Combinatorial Explosion to determine “average risk”, you need to know if this risk factor is present.

  • Rash

    • Cutaneous eruption (morphologic abnormality), with synonym Rash

    • Eruption of skin (disorder), with synonym Rash

    • Complaining of a rash (finding)

    • On examination - a rash (finding)

    • On examination - rash present (situation)

  • Fever

    • Fever - 386661006

    • On exam – fever - 271897009

    • Fever symptoms - 248427009

    • Feeling feverish - 103001002

Will we eventually need: On digital photograph transmitted by a telemedicine device – a rash (finding)?


Epistemology and time
Epistemology and Time to determine “average risk”, you need to know if this risk factor is present.

  • Today, I document the problem list:

    • History of - myocardial infarction in last year

    • Recent weight gain

    • New onset angina

    • Hepatitis A - current infection

    • Newly diagnosed diabetes

  • The patient returns to the office for the first time two years from now.

We also need a coherent, shared representation of disease vs. course of disease


Epistemology and negation
Epistemology and Negation to determine “average risk”, you need to know if this risk factor is present.

  • If the EMR says:

    NOT Colitis presumed infectious

  • Does that mean:

    NOT Colitis

  • Or

    NOT presumed infectious

    (and then, is it certainly not infectious or certainly infectious, or have we just stopped presuming altogether and chosen instead to remain agnostic about whether the colitis is of infectious origin?)


Logical conjunction as set membership
Logical Conjunction as Set Membership to determine “average risk”, you need to know if this risk factor is present.

  • Contradiction!

  • Someone forgot to tell the computer :

    • About complications

    • When complications are present vs. absent

  • But the real issue is more subtle…


Neither is a subtype of diabetes mellitus
Neither is a Subtype of Diabetes Mellitus to determine “average risk”, you need to know if this risk factor is present.

  • There are no instances (and there never has been) of the diseaseType II diabetes mellitus with neuropathy

  • Nothing is both elevated blood glucose and nerve damage at the same

  • However, there are millions of instances of human with:

    The diseaseType II diabetes mellitus,and

    the diseaseNeuropathy, where the former caused the latter.

  • Similarly, for Hypertensive heart and renal disease with both (congestive) heart failure and renal failure (disorder)

Thus this term represents two diagnoses in a set, that are erroneously conjoined with AND.


To which diagnosis disease in the set do the following apply
To which diagnosis/disease in the set do the following apply to determine “average risk”, you need to know if this risk factor is present.?

  • Onset date

  • Method of diagnosis

  • Date diagnosis made

  • Uncertainty

  • Course (acute, chronic, etc.)

  • Negation

  • Treatment


Conclusions recommendations
Conclusions/Recommendations to determine “average risk”, you need to know if this risk factor is present.

  • Avoid finding and its younger sibling situation as catch-as-catch-cans

    • Distinguish carefully and always between what was found, the finding process, and the record of the finding

    • A disease is not a finding***

  • No epistemological criteria for ontology terms

    • More work on course of disease vs. disease

    • Does a different course imply a different subtype?

  • Avoid logical conjunction/disjunction of terms, especially diseases and their complications



From: ontology… Fiorillo, Anthony MD Sent: Monday, August 13, 2007 10:20 AMTo: Hogan, William RSubject:

Bill   FYI the limits of both ICD and SnowMed;  I was unable to find a dx specific to this patients new dx. Submucosal colonic Leiomyoma.  Here is a snap shot of the search:

Note that ICD9 assumes Leiomyoma occur only in the uterus when they can occur any where there is smooth muscle!

A problem that the “finer granularity” of ICD-10-CM does not address, incidentally.


53 results in ICD-9-CM and SNOMED-CT combined. Mixture of “Body structure” and “Clinical Finding”.


Trying to be helpful i conduct the search also and respond
Trying to be helpful, I conduct the search also, and respond…

Although SNOMED does have Leiomyoma of stomach and Leiomyoma of esophagus, it does not have even leiomyoma of colon let alone a submucosal one.

Looks like the best you could do in either case is “Benign tumor of the colon”, which isn’t terribly helpful.


The final outcome
The Final Outcome? respond…

He is asymptomatic; found on screening colonoscopy.  I used an annotated SnowMed code 74391019

74391019 is Leiomyoma (body structure)

It was 52nd of 53 search results.


The issue s
The Issue(s)? respond…

  • Clinician reproducibility

    • Some will choose body structure

    • Some might choose clinical finding

    • Few will care about the distinction, let alone try to understand, or even succeed if they do

    • Vendors obviously don’t care, either

  • This user

    • Cared about ontology (what the leiomyoma was)

    • Didn’t care about epistemology (the fact that someone found it on colonoscopy)


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