The Importance of Unambiguous
Medical Terminology in Patient
Care and Research
Or, why doctors and healthcare administrators
shouldn’t glaze over when informatics is
discussed
Robert M Califf MD
Vice Chancellor for Clinical Research
Duke University
1
The Information Situation
 We are increasingly able to assimilate
information about the health of people when
measurements are made by machines
Lab data
Images
Test results (ECG, PFTs, etc)
Genomics, proteomics, metabolomics, etc.
 What are we missing?
The synthetic terms that tie the raw data into
actionable constructs about a person
2
Clinical Terminology
 We have excellent compliance with terms when
they are required for billing
 Unfortunately, these terms for billing are not
the same as the preferred terms for clinical
quality or research assessment
 If billing, patient care and research terminology
come together, we can make monumental
strides in clinical quality at all levels (patient,
practice, system, ? Population)
3
4
People are dying
because we don’t use
the same names for the
same things!
5
A Patient
 60 yo woman admitted to the ED with “chest
pain”
HR 100, sinus rhythm, BP 100/70, exam
unremarkable
ECG: sinus rhythm, ST segments abnormal
Labs: K 4.2, creatinine 1.5, LDL 130, troponin WNL
CXR: no abnormalities apparent in CV, lung, bone or
tissue structures
6
Possible Clinical Situations
 Mild throat tightness relieved with Mylanta
 Ripping pain going down the back
 Midsternal chest pain, relieved after 2nd NTG
 Pleuritic chest pain and extreme shortness of
breath
 Stabbing pain that lasts a few seconds and
then goes away
7
First AHRQ Unstable Angina Guidelines (1994)
 Eugene Braunwald, Chair
 Bob Jones (Duke) coordinating contract
 Largest RCT 650 patients with very few clinical
outcome studies
 Recommendations largely based on “expert
opinion”
 Then,….
The terminology got fixed!
8
The Great Baltimore Fire—No Standards!
Great Baltimore Fire of 1904
 One reason for the fire's duration was the lack of national
standards in fire-fighting equipment. Fire crews fire
engines came from as far away as Philadelphia and
Washington that day (units from New York City were on
the way, but were blocked by a train accident; they
arrived the next day). The crews brought their own
equipment. Most could only watch helplessly when they
discovered that their hoses could not fit Baltimore's
hydrants. High winds and freezing temperatures added
to the difficulty for firefighters and further contributed to
the severity of the fire. As a result, the fire burned over
30 hours, destroying 1,545 buildings spanning 70 city
blocks — amounting to over 140 acres.
Wikipedia 2009
10
Great Baltimore Fire
While Baltimore was criticized for its hydrants, this was a
problem that was not unique to Baltimore. During the
time of the Great Fire "American cities had more than six
hundred different sizes and variations of fire hose
couplings." It is known that as outside fire fighters
returned to their home cities they gave interviews to
newspapers that condemned Baltimore and talked up
their own actions during the crisis. In addition, many
newspapers were guilty of taking for truth the word of
travelers who, in actuality, had only seen the fire as their
trains passed through the area. All of this aside the
responding agencies and their equipment did prove
useful as their hoses only represented a small part of the
equipment brought with them. One benefit to this tragedy
was the standardization of hydrants nationwide
Wikipedia 2009
11
The Learning Health System at All Levels
 Individual health care transactions
Provider
Consumer
 Clinic and health system quality
 Research
Early phase
New products
Comparative effectiveness
 Population level quality
12
The Cost of a Long Life
U.S.
UC Project for Global Inequality
13
The Cycle of Quality: Generating Evidence to
Inform Policy
3
2
1
Data
Standards
NIH Roadmap
FDA
Critical Path
Early
Translational
Steps
4
Network
Information
5
Empirical
Ethics
Discovery Science
6
Priorities
and Processes
Outcomes
12
Transparency
to Consumers
Measurement
and
Education
11
Pay for
Performance
Performance
Measures
Clinical
Trials
7
Inclusiveness
8
Clinical
Practice
Guidelines
Use for
Feedback
on Priorities
10
9
Evaluation of Speed
and Fluency
Conflict-of-interest
Management
Califf RM et al,
Health Affairs, 2007
Ischemic Discomfort
Acute Coronary Syndrome
Presentation
Working Dx
ECG
Cardiac
Biomarker
Final Dx
No ST Elevation
ST Elevation
Non-ST ACS
UA
NSTEMI
Unstable
Angina
Myocardial Infarction
NQMI
Qw MI
Libby P. Circulation 2001;104:365, Hamm CW, Bertrand M, Braunwald E, Lancet 2001; 358:1533-1538; Davies MJ. Heart 2000; 83:361-366.
Anderson JL, et al. J Am Coll Cardiol. 2007;50:e1-e157, Figure 1. Reprinted with permission.
6 Medical Therapies Proven to Reduce Death
MI:
Therapy
# pts
Aspirin
18,773
23%
2.4%
+++++
Fibrinolytics
58,000
18%
1.8%
++++
Beta blocker
28,970
13%
1.3%
++++
ACE inhibitor
101,000
6.5%
.6%
+
54,360
15%
1.2%
+++++
20,312
21%
2.1%
++++
17,617
23%
2.7%
++++
ACE inhibitor
9,297
17%
1.9%
++++
ACE inhibitor
7,105
23%
6.1%
+++++
Beta blocker
12,385
26%
4%
+++++
Spironolactone
1,663
30%
11%
+++++
2nd prev: Aspirin
Beta blocker
Statins
CHF:
Reduction in deaths:
Relative Absolute C/E
Goals for CRUSADE:
Improve Adherence to ACC/AHA Guidelines for
Patients with Unstable Angina/Non-STEMI
Acute Therapies
Discharge Therapies
 Aspirin
 Aspirin
Evaluating the Process of Care
Clopidogrel
 Clopidogrel
 An adherence score is applied to each patient.
 Beta
Blocker
incorporating
the components
of Blocker
process of care.
 Beta
 Heparin
(UFH or
LMWH)
 then
ACE Inhibitor
 The score
from
each patient
combined for all
patients
 Early
Cath at each hospital.  Statin/Lipid Lowering
Typical scores ranged from 50 to 95%.
 GP IIb-IIIa Inhibitor
 Smoking Cessation
 All
400 hospital
adherence scores then ranked in
All receiving
cath/PCI
quartiles — best to worst.  Cardiac Rehabilitation
Circulation, JACC 2002 — ACC/AHA Guidelines update
CRUSADE:
Overall Adherence Score Trends Over Time
80%
77.9% 78.0%
79.3%
75.2%
72.3%
73.0%
73.6%
71.0%
70%
69.6%
68.1%
60%
Q1
'02
Q4
'02
Q3
'03
Q2
'04
% In-hospital Mortality
CRUSADE: Link Between Overall ACC/AHA
Guidelines Adherence and Mortality
8
Adjusted
Unadjusted
6
4
2
Every 10%  in guidelines adherence
 11%  in mortality
0
<=25%
25–50%
50–75%
>=75%
Hospital Composite Quality Quartiles
Peterson et al, ACC 2004
Impact of Quality
Improvement on Outcomes
in ACS
Trilogy in American Heart Journal
January 2009
Treatment of STEMI Patients
Fibrinolysis
1990
52.5%
2006
27.6%
Primary PCI
2.6%
43.2%
D2N time*
59 min
29 min
In-hosp mortality
D2B time**
7%
111 min
6%
79 min
*Fibrinolysis-eligible pts who rec’d fibrinolysis
**Non-transfer pts who rec’d primary PCI since 1994
100
Acute Therapy
Trends
90
80
70
60
50
40
STEMI
Aspirin
Beta blockers
Any heparin
% Adherence
30
20
10
0
100
90
80
70
60
50
40
30
20
10
0
1990
NSTEMI
1993
1996
1999
2002
2005
Discharge
Therapy Trends
100
90
80
70
60
50
40
STEMI
Aspirin
Beta blockers
Lipid-lowering agent
% Adherence
30
20
10
0
100
90
80
70
60
50
40
30
20
10
0
1994
NSTEMI
1997
2000
2003
2006
In-hospital Mortality 1994–2006
1994
2006
Overall
STEMI
10.4%
11.5%
6.3%
8.0%
NSTEMI
7.1%
5.2%
In 20 Years…
 All people in developed nations will have —
An electronic health record
Biological samples
Digitized images
 Healthcare will be personalized using an individual’s
images, samples and clinical data.
 The health of a community will be monitored using
aggregate records.
Gene
tcagcgatagcgctagagcggctctctaggatctctagagctcgactaaagctctagcgcttagctagcgatcgagctagc
gcgggcgctcgcgctcgcgctagagcctagcgactacgatccgagctcgagctacgacgactcacgggctcgaagcta
cgcgcgatcgacgctcgtttccgcggacgctcgagctagcagcgatcgacgactacgagactacgactacgactatcag
cgatcgacatcaggccctcaaagcgctagacatcagcactacagcactacgacatcagcatcacgtacgacgactacc
gacactacgacgatcagactacacgacgctcgcatcagctttagcgctcagacgctatggcggactacggctagctgatc
gactaagcgatcgacatcagatcgggatcgcgctcatttcggcgatactagcgactacacgtcaaggctaaacgccctac
gcatcgctcccgcgcgcatatcgcatcgatcgatcagatcgatgctacgtcagcgatagcgctagagcggctctctaggat
ctctagagctcgactaaagctctagcgcttagctagcgatcgagctagcgcgggcgctcgcgctcgcgctagagcctagc
gactacgatccgagctcgagctacgacgactcacgggctcgaagctacgcgcgatcgacgctcgtttccgcggacgctc
gagctagcagcgatcgacgactacgagactacgactacgactatcagcgatcgacatcaggccctcaaagcgctagac
atcagcactacagcactacgacatcagcatcacgtacgacgactaccgacactacgacgatcagactacacgacgctc
gcatcagctttagcgctcagacgctatggcggactacggctagctgatcgactaagcgatcgacatcagatcgggatcgc
gctcatttcggcgatactagcgactacacgtcaaggctaaacgccctacgcatcgctcccgcgcgcatatcgcatcgatcg
atcagatcgatgctactcagcgatagcgctagagcggctctctaggatctctagagctcgactaaagctctagcgcttagct
agcgatcgagctagcgcgggcgctcgcgctcgcgctagagcctagcgactacgatccgagctcgagctacgacgactc
acgggctcgaagctacgcgcgatcgacgctcgtttccgcggacgctcgagctagcagcgatcgacgactacgagacta
cgactacgactatcagcgatcgacatcaggccctcaaagcgctagacatcagcactacagcactacgacatcagcatc
acgtacgacgactaccgacactacgacgatcagactacacgacgctcgcatcagctttagcgctcagacgctatggcgg
actacggctagctgatcgactaagcgatcgacatcagatcgggatcgcgctcatttcggcgatactagcgactacacgtc
aaggctaaacgccctacgcatcgctcccgcgcgcatatcgcatcgatcgatcagatcgatgctacgtcagcgatagcgct
agagcggctctctaggatctctagagctcgactaaagctctagcgcttagctagcgatcgagctagcgcgggcgctcgcg
ctcgcgctagagcctagcgactacgatccgagctcgagctacgacgactcacgggctcgaagctacgcgcgatcgacg
ctcgtttccgcggacgctcgagctagcagcgatcgacgactacgagactacgactacgactatcagcgatcgacatcag
gccctcaaagcgctagacatcagcactacagcactacgacatcagcatcacgtacgacgactaccgacactacgacg
atcagactacacgacgctcgcatcagctttagcgctcagacgctatggcggactacggctagctgatcgactaagcgatc
gacatcagatcgggatcgcgctcatttcggcgatactagcgactacacgtcaaggctaaacgccctacgcatcgctcccg
cgcgcatatcgcatcgatcgatcagatcgatgctactcagcgatagcgctagagcggctctctaggatctctagagctcga
ctaaagctctagcgcttagctagcgatcgagctagcgcgggcgctcgcgctcgcgctagagcctagcgactacgatccg
agctcgagctacgacgactcacgggctcgaagctacgcgcgatcgacgctcgtttccgcggacgctcgagctagcagc
gatcgacgactacgagactacgactacgactatcagcgatcgacatcaggccctcaaagcgctagacatcagcactac
agcactacgacatcagcatcacgtacgacgactaccgacactacgacgatcagactacacgacgctcgcatcagcttta
gcgctcagacgctatggcggactacggctagctgatcgactaagcgatcgacatcagatcgggatcgcgctcatttcggc
gatactagcgactacacgtcaaggctaaacgccctacgcatcgctcccgcgcgcatatcgcatcgatcgatcagatcgat
tcagcgatagcgctagagcggctctctaggatctctagagctcgactaaagctctagcgcttagctagcgatcgagctagc
gcgggcgctcgcgctcgcgctagagcctagcgactacgatccgagctcgagctacgacgactcacgggctcgaagcta
cgcgcgatcgacgctcgtttccgcggacgctcgagctagcagcgatcgacgactacgagactacgactacgactatcag
cgatcgacatcaggccctcaaagcgctagacatcagcactacagcactacgacatcagcatcacgtacgacgactacc
gacactacgacgatcagactacacgacgctcgcatcagctttagcgctcagacgctatggcggactacggctagctgatc
gactaagcgatcgacatcagatcgggatcgcgctcatttcggcgatactagcgactacacgtcaaggctaaacgccctac
gcatcgctcccgcgcgcatatcgcatcgatcgatcagatcgatgctactcagcgatagcgctagagcggctctctaggatc
tctagagctcgactaaagctctagcgcttagctagcgatcgagctagcgcgggcgctcgcgctcgcgctagagcctagcg
actacgatccgagctcgagctacgacgactcacgggctcgaagctacgcgcgatcgacgctcgtttccgcggacgctcg
agctagcagcgatcgacgactacgagactacgactacgactatcagcgatcgacatcaagcggcttctctatatatactta
26
Genome
Genome Life
Funding ($ in billions)
100 –
Source:
Device firms
80 –
Biotech firms
60 –
Pharma firms
40 –
Private
State/local
20 –
Federal—
non-NIH
0–
NIH
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003
Reproduced from Moses et al., JAMA 2005;294:1333-42
Comparative Pre-Approval Capitalized
Costs per Approved New Molecule
Millions (2004$)
1500
Original**
2004 Time Adjusted***
1000
500
848
363
424
1272
868
505
0
Preclinical**
Clinical
Total
** All R&D costs (basic research and preclinical development) prior to initiation of clinical testing
*** Based on a 5-year shift and prior growth rates for the preclinical and clinical periods
DiMasi et al. 2003
Innovation Gap Getting Wider
60
NMEs (New Drug Approvals)
53
PhRMA Member R&D Spending
$39.40
39
40
35
26
28
25
22
20
30
27
24
21
17
Pharma
Innovation
Gap
16
$11.50
11
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
04
20
05
0
Burrill & Company
“Real” Clinical Trials—Done in the Setting of
Health Care Delivery
 3 sets of data recording
Clinical documentation
Billing
Clinical trials documentation
 Tremendous cost of training for 3 different
vocabularies
 Redundant personnel costs of collecting same
data in different ways is massive
Clinical Trial Cost Estimates
$450
$400
Total
$350
Coordinating Center
$300
Site Payments
$250
Other
$200
$ In US 2007 Millions
$150
$100
$50
$0
Full Cost
Industry
Streamlined
Industry
More
Streamlined
Life Expectancy Around the World
Men
Women
38
42
Angola
52
Cambodia
57
70
China
73
US
75
Cuba
75
80
79
76
UK
81
77
Canada
82
78
85
Japan
0
20
40
60
Life expectancy (years)
80
100
These models are integrated
back into the clinical and
research workflow
These data support
building models in
critical domains: health
and disease, finance and
operations
Data are now consumable and
poolable in an institutional
data warehouse (DSR)
decision support for patient care, health
system, research and communities
business
value
disease health
model model
quality financial
model model
poolable, consumable data
DSR
Raw data are collected in
care and research activities
Data governance assures
that standards of data use,
quality, ownership, access,
and institutional compliance
are met
clinical
care
data
clinical
research
data
pre-clinical
discovery
data
data governance
Fundamental Informatics
Infrastucture--Matrix
Organizational Structure
Integrated at
“enterprise
level”
Electronic
Health
Records
Adaptable
to all!
Health
System A
Health
System B
Etc…
Disease Registries—Granular,
Detailed
Primary
Care
Mental
Health
Cancer
Cardiov
ascular
Etc…
Cardiac Hospitalizations – Counts
& Rates
Problem List Vocabularies
Dr. Kim Wah Fung
National Library of Medicine
The problem list



The problem list is a powerful way to organize and
communicate clinical data and reasoning - recommended
as an essential feature of an electronic medical record
(EMR)
Often the first (if not the only) part of clinical narration in
an EMR that uses a controlled vocabulary
Most institutions develop and use their own problem list
vocabularies


Often linked to ICD codes for billing or reporting
Some are mapped to SNOMED CT
37
Goals of research


To study the problem list vocabularies of large health care
institutions - size, pattern of use and the extent to which
they overlap with (or differ from) each other
To identify a CORE (Clinical Observations Recording and
Encoding) set of terms that are of high usage in most
problem lists
38
The CORE subset


The set of concepts that often appear in problem list
vocabularies and are frequently used
Ways to use this subset



As a ‘starter set’ to build local problem list vocabularies. If
subsequent local extensions can be added in a standardized way,
the divergence of these vocabularies can be minimized
Existing problem list vocabularies can be mapped to the CORE
concepts
Benefits


Reduce variability of problem list vocabularies
Facilitate sharing of problem list data
39
Desirable features of the CORE subset
 High
coverage of usage
 Small number of concepts
 Linkable to standard terminologies
 Supports reasoning
 Supports a standard mechanism for adding local
extensions
40
41
Effective Methods of Getting the Attention of
Doctors and Health System Administrators
 Appeal to humanitarian instinct
 Publicity for doing good
 Shame for doing bad
Distribute $34 Billion!
42
It will be shameful is some portion of that $34
billion allocation is not devoted to finalizing a core
terminology that is agreed to by all sectors
 Payors
Government and private
 Provider groups
Primary care and specialties
 Research regulators
FDA, NIH, CMS, VA, DOD
Pharma, Devices
 With international harmonization
43
How do we resolve the “Tower of Babel” of data
from EHRs, PHRs, registries, databases,
literature, and clinical trials?
44