Cardiovascular Disease

1. How Long Before the Clinical Diagnosis of
Heart Failure are HF Signs and Symptoms
First Documented in the Medical Record?
Steven R. Steinhubl, Jimeng Sun, Roy J. Byrd, Zahra Daar, Rajakrishnan
Vijayakrishnan, Shahram Ebadollahi, Walter F. Stewart
Geisinger Medical Center, Danville, PA and IBM T.J. Watson Research Center,
Hawthorne, NY
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2. Background
• Decompensated HF is the leading cause of hospital
admissions for US Medicare patients.
• Therapeutic interventions exist for the HF patient that
have been proven to reduce HF admissions by ~33%
and decrease mortality by up to ~50%.
• The diagnosis of HF in the primary care population is
challenging:
– Primary care physicians feel uncomfortable making a HF
diagnosis1.
– False-positive diagnosis in over 30%2, and false negative in
over 20% of elderly COPD patients3.
– There is marked variability, even among cardiologists, as to
what findings are considered diagnostic for HF4.
1BMJ 2003;326(7382):196 2Eur Heart J 1991; 12: 315-321 3BMJ 2005; 26:1887-94
4J Am Coll Cardiol 1986;8:966-70
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3. Background
• A better understanding of the time course of the
earliest clinical manifestations of HF may help
improve the earlier diagnosis of the HF patient.
• The limited available
data evaluating the
onset of HF signs
and symptoms have
focused only on the
days to weeks
preceding an acute
HF exacerbation.
Am J Med. 2003;114:625–630
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4. Objective
Identify the time course for the
presentation of HF signs and symptoms
in the months to years preceding a HF
diagnosis through the application of a
sophisticated natural language
processing protocol to longitudinal EHRs
in a large primary care population.
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5. Methods
• The dataset used for this project consisted of the full
records for 50,625 patients followed in the primary
care network of the GHS, consisting of 4,644 cases and
45,981 group-matched controls.
• The features used for machine learning include
assertions and denials of Framingham HF criteria.
• Extracted by text mining tools consisting of a pipeline
of dictionary, grammar and text analysis engines
developed and deployed within the UIMA system.
• In total, there are over 3.3 million clinical notes, with a
total of 4,484,666 Framingham criteria mentions;
892,805 of these were affirmed criteria.
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6. Methods – Framingham Criteria
MAJOR SYMPTOMS MINOR SYMPTOMS
1. Paroxysmal Nocturnal Dyspnea 1. Bilateral Ankle Edema
(PND) or Orthopnea
2. Neck Vein Distension (JVD) 2. Nocturnal Cough
3. Rales 3. Dyspnea on ordinary exertion
4. Radiographic Cardiomegaly 4. Hepatomegaly
5. Acute Pulmonary Edema 5. Pleural effusion
6. A decrease in vital capacity by 1/3 of
6. S3 Gallop
the maximal value recorded
7. Increased Central Venous Pressure 7. Tachycardia (>120 BPM)
(> 16 cm H2O at RA)
8. Circulation Time of 25 seconds
* Not utilized in this analysis as not
9. Hepatojugular Reflux (HJR)
documented in routine clinical
10.Weight loss 4.5kg in 5 days in practice.
response to treatment
Heal • Teach • Discover • Serve N Engl J Med. 1971;285:1441-1446.

7. Results – Patient Characteristics
Cases (N=4,644)
Mean Age (years) 70.9
Female (%) 48.4
EF < 50% (%) 45.3
Hypertension (%) 61.9
Diabetes (%) 31.8
Known CAD (%) 25.5
Valvular Heart Disease (%) 4.2
COPD (%) 18.4
Chronic Kidney Disease (%) 4.4
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8. Results: Average Days Prior to Clinical
Diagnosis of Criterion Documentation
# of Patients in Whom Criteria Average # of Days
were Identified Prior to Clinical Prior to Clinical
Diagnosis Diagnosis
Ankle Edema 3875 (83%) 238
PND 1691 (36%) 210
Dyspnea on
3840 (83%) 200
Exertion
Rales 1410 (30%) 133
Radiographic
1207 (26%) 83
Cardiomegaly
JVD 549 (12%) 77
Night Cough 374 (8%) 53
Tachycardia 409 (9%) 45
Pleural Effusion 772 (17%) 43
Hepatomegaly 246 (5%) 38
S3 Gallop 130 (3%) 18
Weight Loss 151 (3%) 15
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9. Results: Percentage of Patients with Select Criterion
in the 4 Years Prior to Clinical Diagnosis
Year 4 Year 3 Year 2 Year 1
70
Percent with Criterion Documented
65
60 62.3
Mean
238 Days Mean
50 200 Days
49.5
45.3
40
36.7
34
30
25.2
20 23.2
Mean Mean 17.9
210 Days 17.2
133 Days
10 11.3 10.1
8.4 7.3
6.2 5.2
0
Ankle Edema PND DOE Rales
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10. Limitations
• Text and data mining are not perfect in their
ability to recognize and appropriately label
Framingham criteria. (overall F-score ~0.93)
• There is substantial variability in whether and
how various clinicians document HF signs and
symptoms.
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11. Summary
• This is the first study we are aware of to
identify the prevalence and timing of onset of
HF signs and symptoms in the months to
years preceding a clinical HF diagnosis.
• In many HF patients the signs and symptoms
of HF are first documented well before clinical
diagnosis; on average > 6 months.
• These results suggest that automated text and
data mining of the EHR may play an important
role in the earlier identification of the HF
patient in the primary care setting.
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12. Ongoing Work: Matrix Presentation of
Symptom / Sign Co-occurrence

13. Ongoing Work: Outflow Graph of
Relationships Between Different Criterion