Automatic quality of life prediction using electronic medical records.

Sergeui Pakhomov, Nilay D Shah, Penny Hanson, Saranya Balasubramaniam, Steven A. Smith

Research output: Contribution to journalArticle

18 Citations (Scopus)

Abstract

Health related quality of life (HRQOL) is an important variable used for prognosis and measuring outcomes in clinical studies and for quality improvement. We explore the use of a general pur-pose natural language processing system Metamap in combination with Support Vector Machines (SVM) for predicting patient responses on standardized HRQOL assessment instruments from text of physicians notes. We surveyed 669 patients in the Mayo Clinic diabetes registry using two instruments designed to assess functioning: EuroQoL5D and SF36/SD6. Clinical notes for these patients were represented as sets of medical concepts using Metamap. SVM classifiers were trained using various feature selection strategies. The best concordance between the HRQOL instruments and automatic classification was achieved along the pain dimension (positive agreement .76, negative agreement .78, kappa .54) using Metamap. We conclude that clinicians notes may be used to develop a surrogate measure of patients HRQOL status.

Original languageEnglish (US)
Pages (from-to)545-549
Number of pages5
JournalAMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium
StatePublished - 2008
Externally publishedYes

Fingerprint

Electronic Health Records
Quality of Life
Natural Language Processing
Quality Improvement
Registries
Physicians
Pain
Support Vector Machine

ASJC Scopus subject areas

  • Medicine(all)

Cite this

Automatic quality of life prediction using electronic medical records. / Pakhomov, Sergeui; Shah, Nilay D; Hanson, Penny; Balasubramaniam, Saranya; Smith, Steven A.

In: AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium, 2008, p. 545-549.

Research output: Contribution to journalArticle

Pakhomov, Sergeui ; Shah, Nilay D ; Hanson, Penny ; Balasubramaniam, Saranya ; Smith, Steven A. / Automatic quality of life prediction using electronic medical records. In: AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium. 2008 ; pp. 545-549.
@article{e54d63629d774f82b5a137632a2009f9,
title = "Automatic quality of life prediction using electronic medical records.",
abstract = "Health related quality of life (HRQOL) is an important variable used for prognosis and measuring outcomes in clinical studies and for quality improvement. We explore the use of a general pur-pose natural language processing system Metamap in combination with Support Vector Machines (SVM) for predicting patient responses on standardized HRQOL assessment instruments from text of physicians notes. We surveyed 669 patients in the Mayo Clinic diabetes registry using two instruments designed to assess functioning: EuroQoL5D and SF36/SD6. Clinical notes for these patients were represented as sets of medical concepts using Metamap. SVM classifiers were trained using various feature selection strategies. The best concordance between the HRQOL instruments and automatic classification was achieved along the pain dimension (positive agreement .76, negative agreement .78, kappa .54) using Metamap. We conclude that clinicians notes may be used to develop a surrogate measure of patients HRQOL status.",
author = "Sergeui Pakhomov and Shah, {Nilay D} and Penny Hanson and Saranya Balasubramaniam and Smith, {Steven A.}",
year = "2008",
language = "English (US)",
pages = "545--549",
journal = "AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium",
issn = "1559-4076",
publisher = "American Medical Informatics Association",

}

TY - JOUR

T1 - Automatic quality of life prediction using electronic medical records.

AU - Pakhomov, Sergeui

AU - Shah, Nilay D

AU - Hanson, Penny

AU - Balasubramaniam, Saranya

AU - Smith, Steven A.

PY - 2008

Y1 - 2008

N2 - Health related quality of life (HRQOL) is an important variable used for prognosis and measuring outcomes in clinical studies and for quality improvement. We explore the use of a general pur-pose natural language processing system Metamap in combination with Support Vector Machines (SVM) for predicting patient responses on standardized HRQOL assessment instruments from text of physicians notes. We surveyed 669 patients in the Mayo Clinic diabetes registry using two instruments designed to assess functioning: EuroQoL5D and SF36/SD6. Clinical notes for these patients were represented as sets of medical concepts using Metamap. SVM classifiers were trained using various feature selection strategies. The best concordance between the HRQOL instruments and automatic classification was achieved along the pain dimension (positive agreement .76, negative agreement .78, kappa .54) using Metamap. We conclude that clinicians notes may be used to develop a surrogate measure of patients HRQOL status.

AB - Health related quality of life (HRQOL) is an important variable used for prognosis and measuring outcomes in clinical studies and for quality improvement. We explore the use of a general pur-pose natural language processing system Metamap in combination with Support Vector Machines (SVM) for predicting patient responses on standardized HRQOL assessment instruments from text of physicians notes. We surveyed 669 patients in the Mayo Clinic diabetes registry using two instruments designed to assess functioning: EuroQoL5D and SF36/SD6. Clinical notes for these patients were represented as sets of medical concepts using Metamap. SVM classifiers were trained using various feature selection strategies. The best concordance between the HRQOL instruments and automatic classification was achieved along the pain dimension (positive agreement .76, negative agreement .78, kappa .54) using Metamap. We conclude that clinicians notes may be used to develop a surrogate measure of patients HRQOL status.

UR - http://www.scopus.com/inward/record.url?scp=73949126641&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=73949126641&partnerID=8YFLogxK

M3 - Article

SP - 545

EP - 549

JO - AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium

JF - AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium

SN - 1559-4076

ER -