A computable phenotype for asthma case identification in adult and pediatric patients: External validation in the Chicago Area Patient-Outcomes Research Network (CAPriCORN)

Majid Afshar, Valerie G. Press, Rachel G. Robison, Abel N. Kho, Sindhura Bandi, Ashvini Biswas, Pedro C. Avila, Harsha Vardhan Madan Kumar, Byung Yu, Edward T. Naureckas, Sharmilee M. Nyenhuis, Christopher D. Codispoti

Research output: Contribution to journalArticle

Abstract

Objective: Comprehensive, rapid, and accurate identification of patients with asthma for clinical care and engagement in research efforts is needed. The original development and validation of a computable phenotype for asthma case identification occurred at a single institution in Chicago and demonstrated excellent test characteristics. However, its application in a diverse payer mix, across different health systems and multiple electronic health record vendors, and in both children and adults was not examined. The objective of this study is to externally validate the computable phenotype across diverse Chicago institutions to accurately identify pediatric and adult patients with asthma. Methods: A cohort of 900 asthma and control patients was identified from the electronic health record between January 1, 2012 and November 30, 2014. Two physicians at each site independently reviewed the patient chart to annotate cases. Results: The inter-observer reliability between the physician reviewers had a κ-coefficient of 0.95 (95% CI 0.93–0.97). The accuracy, sensitivity, specificity, negative predictive value, and positive predictive value of the computable phenotype were all above 94% in the full cohort. Conclusions: The excellent positive and negative predictive values in this multi-center external validation study establish a useful tool to identify asthma cases in in the electronic health record for research and care. This computable phenotype could be used in large-scale comparative-effectiveness trials.

LanguageEnglish (US)
Pages1-8
Number of pages8
JournalJournal of Asthma
DOIs
StateAccepted/In press - Nov 10 2017

Fingerprint

Asthma
Outcome Assessment (Health Care)
Pediatrics
Electronic Health Records
Phenotype
Physicians
Validation Studies
Research
Sensitivity and Specificity
Health

Keywords

  • algorithm
  • Asthma
  • electronic health record

ASJC Scopus subject areas

  • Pediatrics, Perinatology, and Child Health
  • Immunology and Allergy
  • Pulmonary and Respiratory Medicine

Cite this

Afshar, Majid ; Press, Valerie G. ; Robison, Rachel G. ; Kho, Abel N. ; Bandi, Sindhura ; Biswas, Ashvini ; Avila, Pedro C. ; Kumar, Harsha Vardhan Madan ; Yu, Byung ; Naureckas, Edward T. ; Nyenhuis, Sharmilee M. ; Codispoti, Christopher D./ A computable phenotype for asthma case identification in adult and pediatric patients : External validation in the Chicago Area Patient-Outcomes Research Network (CAPriCORN). In: Journal of Asthma. 2017 ; pp. 1-8
@article{cb90478665ad4caa9647f8f3b979e9a8,
title = "A computable phenotype for asthma case identification in adult and pediatric patients: External validation in the Chicago Area Patient-Outcomes Research Network (CAPriCORN)",
abstract = "Objective: Comprehensive, rapid, and accurate identification of patients with asthma for clinical care and engagement in research efforts is needed. The original development and validation of a computable phenotype for asthma case identification occurred at a single institution in Chicago and demonstrated excellent test characteristics. However, its application in a diverse payer mix, across different health systems and multiple electronic health record vendors, and in both children and adults was not examined. The objective of this study is to externally validate the computable phenotype across diverse Chicago institutions to accurately identify pediatric and adult patients with asthma. Methods: A cohort of 900 asthma and control patients was identified from the electronic health record between January 1, 2012 and November 30, 2014. Two physicians at each site independently reviewed the patient chart to annotate cases. Results: The inter-observer reliability between the physician reviewers had a κ-coefficient of 0.95 (95\{%} CI 0.93–0.97). The accuracy, sensitivity, specificity, negative predictive value, and positive predictive value of the computable phenotype were all above 94\{%} in the full cohort. Conclusions: The excellent positive and negative predictive values in this multi-center external validation study establish a useful tool to identify asthma cases in in the electronic health record for research and care. This computable phenotype could be used in large-scale comparative-effectiveness trials.",
keywords = "algorithm, Asthma, electronic health record",
author = "Majid Afshar and Press, {Valerie G.} and Robison, {Rachel G.} and Kho, {Abel N.} and Sindhura Bandi and Ashvini Biswas and Avila, {Pedro C.} and Kumar, {Harsha Vardhan Madan} and Byung Yu and Naureckas, {Edward T.} and Nyenhuis, {Sharmilee M.} and Codispoti, {Christopher D.}",
year = "2017",
month = "11",
day = "10",
doi = "10.1080/02770903.2017.1389952",
language = "English (US)",
pages = "1--8",
journal = "Journal of Asthma",
issn = "0277-0903",
publisher = "Informa Healthcare",

}

A computable phenotype for asthma case identification in adult and pediatric patients : External validation in the Chicago Area Patient-Outcomes Research Network (CAPriCORN). / Afshar, Majid; Press, Valerie G.; Robison, Rachel G.; Kho, Abel N.; Bandi, Sindhura; Biswas, Ashvini; Avila, Pedro C.; Kumar, Harsha Vardhan Madan; Yu, Byung; Naureckas, Edward T.; Nyenhuis, Sharmilee M.; Codispoti, Christopher D.

In: Journal of Asthma, 10.11.2017, p. 1-8.

Research output: Contribution to journalArticle

TY - JOUR

T1 - A computable phenotype for asthma case identification in adult and pediatric patients

T2 - Journal of Asthma

AU - Afshar,Majid

AU - Press,Valerie G.

AU - Robison,Rachel G.

AU - Kho,Abel N.

AU - Bandi,Sindhura

AU - Biswas,Ashvini

AU - Avila,Pedro C.

AU - Kumar,Harsha Vardhan Madan

AU - Yu,Byung

AU - Naureckas,Edward T.

AU - Nyenhuis,Sharmilee M.

AU - Codispoti,Christopher D.

PY - 2017/11/10

Y1 - 2017/11/10

N2 - Objective: Comprehensive, rapid, and accurate identification of patients with asthma for clinical care and engagement in research efforts is needed. The original development and validation of a computable phenotype for asthma case identification occurred at a single institution in Chicago and demonstrated excellent test characteristics. However, its application in a diverse payer mix, across different health systems and multiple electronic health record vendors, and in both children and adults was not examined. The objective of this study is to externally validate the computable phenotype across diverse Chicago institutions to accurately identify pediatric and adult patients with asthma. Methods: A cohort of 900 asthma and control patients was identified from the electronic health record between January 1, 2012 and November 30, 2014. Two physicians at each site independently reviewed the patient chart to annotate cases. Results: The inter-observer reliability between the physician reviewers had a κ-coefficient of 0.95 (95% CI 0.93–0.97). The accuracy, sensitivity, specificity, negative predictive value, and positive predictive value of the computable phenotype were all above 94% in the full cohort. Conclusions: The excellent positive and negative predictive values in this multi-center external validation study establish a useful tool to identify asthma cases in in the electronic health record for research and care. This computable phenotype could be used in large-scale comparative-effectiveness trials.

AB - Objective: Comprehensive, rapid, and accurate identification of patients with asthma for clinical care and engagement in research efforts is needed. The original development and validation of a computable phenotype for asthma case identification occurred at a single institution in Chicago and demonstrated excellent test characteristics. However, its application in a diverse payer mix, across different health systems and multiple electronic health record vendors, and in both children and adults was not examined. The objective of this study is to externally validate the computable phenotype across diverse Chicago institutions to accurately identify pediatric and adult patients with asthma. Methods: A cohort of 900 asthma and control patients was identified from the electronic health record between January 1, 2012 and November 30, 2014. Two physicians at each site independently reviewed the patient chart to annotate cases. Results: The inter-observer reliability between the physician reviewers had a κ-coefficient of 0.95 (95% CI 0.93–0.97). The accuracy, sensitivity, specificity, negative predictive value, and positive predictive value of the computable phenotype were all above 94% in the full cohort. Conclusions: The excellent positive and negative predictive values in this multi-center external validation study establish a useful tool to identify asthma cases in in the electronic health record for research and care. This computable phenotype could be used in large-scale comparative-effectiveness trials.

KW - algorithm

KW - Asthma

KW - electronic health record

UR - http://www.scopus.com/inward/record.url?scp=85033697434&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85033697434&partnerID=8YFLogxK

U2 - 10.1080/02770903.2017.1389952

DO - 10.1080/02770903.2017.1389952

M3 - Article

SP - 1

EP - 8

JO - Journal of Asthma

JF - Journal of Asthma

SN - 0277-0903

ER -