surveillance of peripheral arterial disease cases …...right lower extremity critical limb...

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©2017 MFMER | slide-1 Surveillance of Peripheral Arterial Disease Cases Using Natural Language Processing of Clinical Notes Naveed Afzal , Sunghwan Sohn, Christopher G. Scott, Hongfang Liu, Iftikhar J. Kullo, Adelaide M. Arruda-Olson

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©2017 MFMER | slide-1

Surveillance of Peripheral Arterial

Disease Cases Using Natural Language Processing of Clinical

Notes Naveed Afzal, Sunghwan Sohn, Christopher G. Scott, Hongfang Liu, Iftikhar J. Kullo, Adelaide M. Arruda-Olson

©2017 MFMER | slide-2

Peripheral arterial disease (PAD)

• Affects 8.5 million in US, 200 million worldwide • Associated with high risk of mortality and morbidity • Under-diagnosed and undertreated • Lack of awareness of PAD-associated risks for

adverse cardiovascular outcomes • Diagnosed by ankle-brachial index (ABI) test but this

method remains underutilized

Kullo & Rooke: NEJM, 2016; Hirsch et al: JAMA, 2001; Gerhard-Herman et al: J Am Coll Cardiol, 2016

©2017 MFMER | slide-3

Background

• Manual methods for disease surveillance are costly, time-consuming and inconsistent

• Automated surveillance of clinical notes from EHRs may effectively identify PAD cases

• Use NLP to extract PAD related information from narrative clinical notes

©2017 MFMER | slide-4

Objectives • To develop and validate a PAD surveillance

system using NLP for detection of PAD symptoms from narrative clinical notes

©2017 MFMER | slide-5

PAD diagnosis based on ABI test

•  Reports were in PDF format and were not part of clinical notes

•  PAD cases •  ABI ≤ 0.90 rest or post-

exercise •  ≥20% decrease ABI after

exercise •  High ABI >1.40 = poorly

compressible arteries

•  Controls •  Normal ABI results

•  Date of ABI testing = index date

Kullo & Rooke: NEJM, 2016

©2017 MFMER | slide-6

Concept features and rules

Documents, patient IDS, dates

NLP Algorithm

System output

EHR System

Sentence Detection

Tokenization

Concept Identification

Assertion

Patient Classification

Evaluation

ABI (Gold

Standard)

©2017 MFMER | slide-7

PAD-NLP Algorithm • Expert clinician manually reviewed clinical notes

•  20 patients with PAD •  20 patients without PAD

• Created list of PAD-related keywords for NLP algorithm prototype

• List of keywords refined by manual review of charts by a board certified cardiologist

Afzal et al: J Vasc Surg, 2017

©2017 MFMER | slide-8

Examples of keywords for confirmation of PAD Right lower extremity critical limb ischemia. She has history of peripheral vascular disease

She has been followed in the Wound Care Center this year for ulcerations to the toes of her right foot

Ultrasound shows severe right lower extremity atherosclerotic disease, beginning at the level of the right common femoral artery Noninvasive lower extremity arterial study demonstrated indeterminate ankle-brachial indices due to poorly compressible vessels bilaterally His past medical history is also significant for peripheral arterial occlusive disease with aorto-bifemoral bypass, Peripheral vascular disease Critical limb ischemia right lower extremity LLE ischemia Noncritical infrapopliteal level lower extremity arterial occlusive disease bilaterally Lower extremity atherosclerosis obliterans Severe lower extremity arterial occlusive disease

Examples of keywords for exclusion of PAD There is no evidence of critical limb ischemia No evidence of PAD Vascular lab - normal lower extremity arterial study No evidence of arterial occlusive disease

©2017 MFMER | slide-9

Keywords - NLP algorithm Confirmation - Disease Location

lower extremities/extremity; lower limbs/limb; Leg /legs; Iliac/femoral/tibial/popliteal artery/ arteries; Distal/ infrarenal /abdominal aorta/aorto (bi)iliac/ aorto (bi)iliac/aorto(bi)-iliac; aorto-(bi)femoral; foot, toe, toes, shin; plantar, heel, ankle, interdigital; below/above knee, Claudication /calf pain; Ischemic ulcer/ulcers; ASO/Arteriosclerosis obliterans/ arterial sclerosis obliterans/ atherosclerotic disease; PAD/ Peripheral arterial disease/Peripheral vascular disease /Peripheral arterial occlusive disease

Confirmation - Diagnosis Arterial occlusive disease/occlusion/occluded; Stenosis; non compressible vessels (NCV), non-compressible arteries (NCA), poorly compressible vessels (PCV), stiff vessels/ arteries ischemia; positive ABI/ankle brachial index/ vascular labs/ extremities study /arterial studies; revascularization/recanalization/bypass/angioplasty/PTA/stenting/stent/graft/endarterectomy/ endarterectomies; thrombectomy/thrombosis/thromboembolectomy/embolectomy/ embolectomies

Exclusion Family history of, Upper extremities/Upper extremity; Arm/arms, hand(s); Brachial artery, axillary artery, radial artery, ulnar artery; carotid, innominate artery, subclavian artery; mesenteric artery; celiac artery; AAA, abdominal aortic aneurysm/abd aortic aneurysm; renal arteries/artery; coronaries, coronary arteries/ artery /cerebrovascular-disease /arteries/artery; Amputation; traumatic/trauma; sarcoma/osteoma; pseudoclaudication/pseudoclaudicatory pain; diabetic foot, hammer toe/ toes; vascular calcification; varicose veins

©2017 MFMER | slide-10

PAD-NLP Algorithm Rules

PAD One disease location keyword + one diagnostic

keyword within two sentences

Non-PAD 1) No PAD criteria 2) One exclusion keyword

©2017 MFMER | slide-11

Note Types   Note Sections   Service Groups  Consult   Impression / Report / Plan   Primary Care  

Subsequent Visit   Diagnosis   Hospital Internal Medicine  

Patient Progress   Principal/primary Diagnosis   General Medicine  

Supervisory   Secondary Diagnoses   Family Medicine  

Limited Exam   Past Medical/Surgical History   Critical Care  

Specialty Evaluation   Ongoing Care   Urgent Care  

Multisystem Evaluation   Immunizations   Cardiology  

Injection   Key Findings / Test Results   Vascular  

Educational Visit   Pre-Procedure Information   Pulmonary  

Hospital Service Transfer   Post-Procedure Information   Oncology  

  Vital Signs   Nephrology  

  Current Medications   Neurology  

  Revision History   Pathology  

  Special Instructions   Gastroenterology  

  Advance Directives   Vascular Wound Care  

  Discharge Activity   Vascular Surgery  

  Final Pathology Diagnosis   Cardiac Surgery  

Included

©2017 MFMER | slide-12

Note Types   Note Sections   Service Groups  Miscellaneous Chief Complaint Orthopedic

Test- Oriented Miscellaneous History of Present Illness Podiatry Dismissal Summary Family History Endocrinology Therapy System Reviews Emergency Medicine Emergency Medicine Hospital Admission Note Visit

Anticipated Problems and Interventions

Allergy

Hospital Admission Note Informed Consent Dermatology Emergency Medicine Visit Patient Education Sports Medicine

Physical Examination Spine Center Work Rehabilitation Plastic Surgery

  Nursing Home   Social Services   Addiction

Excluded

Afzal et al: J Vasc Surg, 2017

©2017 MFMER | slide-13

REP PAD Cohort • 1569 patients

•  806 cases •  763 controls

• Average age: 71 years • 44% women • 90% white

2000 2005

ABI test date 21-day

2015 2017 2010

©2017 MFMER | slide-14

©2017 MFMER | slide-15

Performance of PAD-NLP algorithm vs. gold standard (ABI)  

PPV   0.93  

Sensitivity   0.70  

NPV   0.80  

Specificity   0.95  

©2017 MFMER | slide-16

Temporality of PAD-NLP Algorithm • Compared temporal association between PAD-

NLP algorithm inception date (date on which NLP algorithm classified patient as PAD) with gold standard index date for each PAD patient

• For true positive cases, difference between NLP algorithm inception date and gold standard index date was measured in days

©2017 MFMER | slide-17

Temporality of PAD-NLP Algorithm

Before gold standard index date 329 cases (41%)

At gold standard index date 93 cases (12%)

After gold standard index date but within 21 day-window

141 cases (18%)

©2017 MFMER | slide-18

Temporality of PAD-NLP Algorithm

0

20

40

60

80

100

120

140

160

180

<-3000 -2999 to -2000

-1999 to -1000

-999 to -500 -499 to -100 -99 to -1 0 1 to 20

Number of patients

true positives

Number of days from ABI test

©2017 MFMER | slide-19

Discussion • PAD-NLP algorithm identified PAD cases from

clinical notes with high PPV • Prior to ABI test date in 41% of the cases from the

community • Delay in establishing PAD diagnosis despite

presence of PAD symptoms

©2017 MFMER | slide-20

Study Limitations • Data were retrieved from a single

academic medical center • Results may not be generalized to other

practice settings

©2017 MFMER | slide-21

Clinical Implications • Accurate and timely detection of actual or possible

PAD will: • Remind clinicians to order ABI testing confirming

diagnosis of PAD •  Implement risk modification strategies in PAD

patients • PAD-NLP algorithm may be incorporated to clinical

CDS to identify PAD patients • Future studies will evaluate impact of CDS system on

outcomes in PAD patients

©2017 MFMER | slide-22

Conclusions • PAD-NLP surveillance algorithm enabled

early identification of PAD with high PPV • This may promote diagnosis earlier in the

course of PAD

©2017 MFMER | slide-23

Acknowledgements

• Grants • NHLBI: K01HL124045 • NHGRI: HG04599 and HG006379 • NIA: R01AG034676 • NIGMS: R01GM102283A1

©2017 MFMER | slide-24

Questions ?

[email protected]