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Linking lay people to the professional literature
An application of natural language processing to
free-text e-mail
Patricia Flatley Brennan, RN, PhD, FAAN University of Wisconsin- Madison
Supported by Grants from the National Library of Medicine (LM 6249); Intel Corporation (Advanced Technologies for
Health@Home), and Wisconsin Alumni Research Foundation (The Kellet
Professorship )
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Plan for the talk• Provide an update of the final results
of the HeartCare randomized field experiment
• Apply NLP tools to decode patient messages
• Describe current work in two areas:– Community capacity building– Infrastructure-building
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The HeartCare Team• Investigators
– University of Wisconsin-Madison• Patti Brennan• Barrett Caldwell (Now Purdue)• Mary Ellen Murray• Dave Gustafson
– Case Western Reserve University• Shirley Moore • Sree Sreenath
– Cleveland Clinic Foundation• Ralph O’Brien
• Undergraduate, Graduate, and Post-Doctoral trainees
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Meeting the Challenges of CABG
Recovery• Monitor, Manage, Mend, Motivate
• Demands in the discharge encounter
• Patient-centered, tailored information
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HeartCare
Recovery requires communication andtailored health information
• Peer and professional communication• Information sequenced over time and
tailored to the patient’s needs– Weeks 1-2: Symptom Management– Week 3-6: Resume physical activity– Weeks 6-12: Return to prior function– Weeks 12-26: Adopt healthy behaviors
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HeartCare Evaluation • Randomized Field Evaluation
– 6 Months experimental period– 140 adults recovering from CABG surgery
• Mean age: 63; 35% Female; 19% Non-majority– Outcome Measures
• Symptom Inventory, Sickness Impact Profile, POMS (Depression), Family function, Health Behavior change
• Three Groups– Usual Care – CHIP, An Audiotape Intervention – HeartCare: WWW-based recovery support
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Does access to HeartCare improve
recovery from CABG?
Yes!
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0
5
10
15
20
25
30
35
0 1 2 3 4 5 6
Sickness Impact Profile (SIP)
SIP
Months Since Surgery
CHIP
HeartCare
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0
2
4
6
8
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0 1 2 3 4 5 6
POMS Depressive Symptom ScaleD
ep
ress
ion
Months Since Surgery
CHIP
HeartCare
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Summary• Participants in the HeartCare group
recovered faster, with fewer symptoms, than those using the CHIP intervention.
• Participants use HeartCare intensively during the early recovery phase.
• E-mail used more often than public forum
• Information reviewed on most encounter
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What’s needed to make HeartCare-like interventions
Scalable?• Strategies to understand information
needs• Characterization of the ways lay people
organize health information• Sustainable knowledge management
approaches• Alignment of the CHI investments with
the community’s health information assets
• Robust health information infrastructure
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What’s needed to make HeartCare-like interventions
Scalable?• Strategies to understand information
needs• Characterization of the ways lay people
organize health information• Sustainable knowledge management
approaches• Alignment of the CHI investments with
the community’s health information assets
• Robust health information infrastructure
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Message to the NurseDear Connie, I've been out of the loop for a few weeks. I had a setback with the appearance of a blood clot 2 weeks ago and was back in the hospital for a week. I was released a week ago Friday and now am on several new medications. With all these new meds, I feel nauseous almost all the time and frequently dizzy. I have a visiting nurse coming to see me 3x a week, and she monitors my blood pressure, temperature and checks my legs for possible clots. But nothing seems to help the nauseous feeling and I have little appetite. The medication I am now taking are … I suspect the Lasix may be the culprit, since I had been on it a LONG time ago and it made me nauseous, but I don't know. Do I really need to be on all of these now? I take alot of them at the same time (meal time), but should I change this and stagger them? What order should I take them, or are there alternatives to this medication for now? Any advise you could give me before I go back to see my internist on Tuesday would be helpful, then I could discuss it with him again. I see the cardiologist on Thursday and hope to be cleared to start cardiac rehab after that. Right now, however, it is slow going and discouraging. Thanks, Bill
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Can existing
UMLS lexical tools decode
patient information needs?
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SPECIALIST lexicon
Dear Connie, I've been out of the loop for a few weeks. I had a
setback with the appearance of a blood clot 2 weeks ago and
was back in the hospital for a week. I was
released a week ago Friday and now am on
several new medications.
Mapped terms
that can launch
searches of
electronic resources
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Background
• Federal initiatives to meet lay people’s information needs
• Most common stimulus: query phrases• But…
– Consumers’ don’t speak UMLS– Information need arise in colloquial conversations
• However,– The UMLS and its lexical tools exist-- exploitable?– Electronic resources applying machine-readable
indexing approaches
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USUAL APPROACHES
• Human intermediary • Natural language interpretation
– Awakening from the dream stage• Terminological strategies
– Query terms– Indexing Initiative
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Can NLP tools built to manage professional
vocabularies help patients?
• Source document– 241 messages sent from patients to nurses in
the HeartCare project• Pass thru Metamap
– Parses text of electronic bibliographic databases
– Strips capitalization, ignores word order– Assigns candidates from UMLS– Scores the adequacy of the concept match
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Approach
• Stimulus text acquired– Sanitizing process – Human Subjects’ issues
• Preliminary Structuring– Demarked units– Title of message ---> Citation Title– Body of Message ---> Abstract
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Preliminary Results
• 241 Messages (1976 Utterances)• 15566 Phrases• 11,373 Candidate UMLS Concepts
found– (mean 32.91 ; sd 42.7741)
– 9903 phrases had no candidates
• 7143 Mappings found (1.13; s.d.1.79)
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Observations
• Diagnosis, symptom and findings recognized
• Health service elements not recognized (appointments, medication renewals)
• No tolerance for mis-spellings• Idioms choke the system• Full UMLS may be too rich
– Metamorph – Post-processing to remove selected
components
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Preliminary Thoughts
• Promising but sparse; PARSING is key• Efficiency/interpretation tradeoff • Early work in a highly professional,
highly controlled stimulus had a 70% mapping
• Most messages deal with managing a health problem in the home ---> Nursing!
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Vocabularies used in the TestThe Six Nursing Vocabularies
Nursing Plus:International Classification of Primary Care (ICPC2E)International Classification of Primary Care- Am English (ICPC2AE)Micromedex DRUGDEX (MMX01)National Drug Data File (NDFF01)Thesaurus of Psychological Terms (PSY2001)WHO Adverse Drug Reaction Terminology (WHO97)
NursingPLUS + Medical Subject Heading 2003 (MSH_2003)
NursingPLUS + SNOMED International Version 3.5 (SMNI98)
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Vocabulary performance on a single message
NursingOnly
NursingPlus NursingPlus +MeSH
NursingPlus+SNOMED
CandidatesConcepts
15 54 85 114
MappedConcepts
13 42 57 70
Phrases w/ oneor more
maps
12 43 50 57
Mean concepts/phrase
1.08 .98 1.14 1.22
Errors 3 23 37 39
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How did the vocabularies perform?
NursingOnly
NursingPlus NursingPlus +MeSH
NursingPlus +SNOMED
CandidatesConcepts
1016 3734 5786 7366
Mapped Concepts 948 3094 4439 5078
Phrases w/ one ormore maps
871 2863 3995 4383
Mean concepts/phrase
1.09 (0.28) 1.08 (0.30) 1.11 (0.35) 1.16 (0.38)
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Mapping Adequacy
• Findings– True Positives– False Positives– Missing
• Trade-off of recall and precision• Zeng’s Model of Mapping:
– Lexical– Semantic– Mental Model
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The Contexts of Care• Living Environments
– Homes– Communities
• Social Environments– Families– Cultural Groups
• Psychological Environments– Illness representations– Human Information Processing
• Technological Environments– Telecommunication– Consumer Electronics
• Health Service Environment– Clinical Care Practices– Financing & Delivery Institutions
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What’s needed to make HeartCare-like interventions
Scalable?• Strategies to understand information
needs• Characterization of the ways lay people
organize health information• Sustainable knowledge management
approaches• Alignment of the CHI investments with
the community’s health information assets
• Robust health information infrastructure
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The Dodge-JeffersonHealthier Communities
Partnership
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Develop a model to generate design criteria
for health-related IT solutionsfrom an understanding of
citizen health information managment
behaviors and
community resources
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49 Households in Central Wisconsin
• Housing type– 39 Single Family, 9
Apartments, 1 Mobile Home
• Most of those interviewed live alone
• Over half of the 1 & 2 person families had one person over age 65
• Electronics– Phones: 49– Cable: 42– Internet: 26
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Health of the Household
• Respondents:– 7 Excellent; 12 Very Good; 10 Good; 3 Fair
• No one indicated Poor• Respondent’s assessment of household generally matched
• Health Concerns– Cancer, Cardiovascular disease, Hypertension, Arthritis
• Also: depression, memory problems, nutrition, wellness
• Income adequate• ? Health Insurance coverage• ? Health Care Provider
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Where Do People get Health Information?
0 5 10 15 20 25 30 35
Physician Clinic/Hospital Public Health Nurse
Library News Health Magazines
Internet Hotlines Reference Books
Alt Med Sources Family/Friends School
Classes Other
Physician
Family
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Appointments Contact Info Med Schedule Treatment
Medical History Insurance Labs X-Rays
Immunizations Birth/Death Records Self-Care Procedure Info
Self-Monitoring Provider info Literature Poison Control
Clinic/Hospital Info Other
Information Managed in the Home:
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Information Management in the home
• Information types named by at least 20 respondents– Appointment & Contact
Information– Medication– Treatment– Birth/Death records
• Household experiences– Average 10.2 (sd. 3.3)
information types– Number and variety
unrelated to age of respondents or presence of children
Where do they put all of this information?
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What’s needed to make HeartCare-like interventions
Scalable?1. Strategies to understand information
needs2. Characterization of the ways lay people
organize health information3. Sustainable knowledge management
approaches4. Alignment of the CHI investments with
the community’s health information assets
5. Robust health information infrastructure
Assessment of Community Health Information
Resources(ARCHIR)
PKI Approaches to
Secure E-Mail among
Health Professionals
Personal Consumer
Health Information Exchange(P-CHIE)
Community-Partnership Digitial
Library Project
Dodge-Jefferson Healthier Communities
Partnership
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Community-Centered Information System
Consumer Health Information
Network
Clinic
Hospital
Public Library
Pharmacy
FurtiveRecords
Dentist
State Health Dept
clinician
patient
trainee