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Identifying Ectopic Pregnancy in a Large Integrated Health Care Delivery System: Algorithm Validation

BACKGROUND: Surveillance of ectopic pregnancy (EP) using electronic databases is important. To our knowledge, no published study has assessed the validity of EP case ascertainment using electronic health records. OBJECTIVE: We aimed to assess the validity of an enhanced version of a previously valid...

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Autores principales: Getahun, Darios, Shi, Jiaxiao M, Chandra, Malini, Fassett, Michael J, Alexeeff, Stacey, Im, Theresa M, Chiu, Vicki Y, Armstrong, Mary Anne, Xie, Fagen, Stern, Julie, Takhar, Harpreet S, Asiimwe, Alex, Raine-Bennett, Tina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7735905/
https://www.ncbi.nlm.nih.gov/pubmed/33141678
http://dx.doi.org/10.2196/18559
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author Getahun, Darios
Shi, Jiaxiao M
Chandra, Malini
Fassett, Michael J
Alexeeff, Stacey
Im, Theresa M
Chiu, Vicki Y
Armstrong, Mary Anne
Xie, Fagen
Stern, Julie
Takhar, Harpreet S
Asiimwe, Alex
Raine-Bennett, Tina
author_facet Getahun, Darios
Shi, Jiaxiao M
Chandra, Malini
Fassett, Michael J
Alexeeff, Stacey
Im, Theresa M
Chiu, Vicki Y
Armstrong, Mary Anne
Xie, Fagen
Stern, Julie
Takhar, Harpreet S
Asiimwe, Alex
Raine-Bennett, Tina
author_sort Getahun, Darios
collection PubMed
description BACKGROUND: Surveillance of ectopic pregnancy (EP) using electronic databases is important. To our knowledge, no published study has assessed the validity of EP case ascertainment using electronic health records. OBJECTIVE: We aimed to assess the validity of an enhanced version of a previously validated algorithm, which used a combination of encounters with EP-related diagnostic/procedure codes and methotrexate injections. METHODS: Medical records of 500 women aged 15-44 years with membership at Kaiser Permanente Southern and Northern California between 2009 and 2018 and a potential EP were randomly selected for chart review, and true cases were identified. The enhanced algorithm included diagnostic/procedure codes from the International Classification of Diseases, Tenth Revision, used telephone appointment visits, and excluded cases with only abdominal EP diagnosis codes. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and overall performance (Youden index and F-score) of the algorithm were evaluated and compared to the validated algorithm. RESULTS: There were 334 true positive and 166 true negative EP cases with available records. True positive and true negative EP cases did not differ significantly according to maternal age, race/ethnicity, and smoking status. EP cases with only one encounter and non-tubal EPs were more likely to be misclassified. The sensitivity, specificity, PPV, and NPV of the enhanced algorithm for EP were 97.6%, 84.9%, 92.9%, and 94.6%, respectively. The Youden index and F-score were 82.5% and 95.2%, respectively. The sensitivity and NPV were lower for the previously published algorithm at 94.3% and 88.1%, respectively. The sensitivity of surgical procedure codes from electronic chart abstraction to correctly identify surgical management was 91.9%. The overall accuracy, defined as the percentage of EP cases with correct management (surgical, medical, and unclassified) identified by electronic chart abstraction, was 92.3%. CONCLUSIONS: The performance of the enhanced algorithm for EP case ascertainment in integrated health care databases is adequate to allow for use in future epidemiological studies. Use of this algorithm will likely result in better capture of true EP cases than the previously validated algorithm.
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spelling pubmed-77359052020-12-18 Identifying Ectopic Pregnancy in a Large Integrated Health Care Delivery System: Algorithm Validation Getahun, Darios Shi, Jiaxiao M Chandra, Malini Fassett, Michael J Alexeeff, Stacey Im, Theresa M Chiu, Vicki Y Armstrong, Mary Anne Xie, Fagen Stern, Julie Takhar, Harpreet S Asiimwe, Alex Raine-Bennett, Tina JMIR Med Inform Original Paper BACKGROUND: Surveillance of ectopic pregnancy (EP) using electronic databases is important. To our knowledge, no published study has assessed the validity of EP case ascertainment using electronic health records. OBJECTIVE: We aimed to assess the validity of an enhanced version of a previously validated algorithm, which used a combination of encounters with EP-related diagnostic/procedure codes and methotrexate injections. METHODS: Medical records of 500 women aged 15-44 years with membership at Kaiser Permanente Southern and Northern California between 2009 and 2018 and a potential EP were randomly selected for chart review, and true cases were identified. The enhanced algorithm included diagnostic/procedure codes from the International Classification of Diseases, Tenth Revision, used telephone appointment visits, and excluded cases with only abdominal EP diagnosis codes. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and overall performance (Youden index and F-score) of the algorithm were evaluated and compared to the validated algorithm. RESULTS: There were 334 true positive and 166 true negative EP cases with available records. True positive and true negative EP cases did not differ significantly according to maternal age, race/ethnicity, and smoking status. EP cases with only one encounter and non-tubal EPs were more likely to be misclassified. The sensitivity, specificity, PPV, and NPV of the enhanced algorithm for EP were 97.6%, 84.9%, 92.9%, and 94.6%, respectively. The Youden index and F-score were 82.5% and 95.2%, respectively. The sensitivity and NPV were lower for the previously published algorithm at 94.3% and 88.1%, respectively. The sensitivity of surgical procedure codes from electronic chart abstraction to correctly identify surgical management was 91.9%. The overall accuracy, defined as the percentage of EP cases with correct management (surgical, medical, and unclassified) identified by electronic chart abstraction, was 92.3%. CONCLUSIONS: The performance of the enhanced algorithm for EP case ascertainment in integrated health care databases is adequate to allow for use in future epidemiological studies. Use of this algorithm will likely result in better capture of true EP cases than the previously validated algorithm. JMIR Publications 2020-11-30 /pmc/articles/PMC7735905/ /pubmed/33141678 http://dx.doi.org/10.2196/18559 Text en ©Darios Getahun, Jiaxiao M Shi, Malini Chandra, Michael J Fassett, Stacey Alexeeff, Theresa M Im, Vicki Y Chiu, Mary Anne Armstrong, Fagen Xie, Julie Stern, Harpreet S Takhar, Alex Asiimwe, Tina Raine-Bennett. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 30.11.2020. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on http://medinform.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Getahun, Darios
Shi, Jiaxiao M
Chandra, Malini
Fassett, Michael J
Alexeeff, Stacey
Im, Theresa M
Chiu, Vicki Y
Armstrong, Mary Anne
Xie, Fagen
Stern, Julie
Takhar, Harpreet S
Asiimwe, Alex
Raine-Bennett, Tina
Identifying Ectopic Pregnancy in a Large Integrated Health Care Delivery System: Algorithm Validation
title Identifying Ectopic Pregnancy in a Large Integrated Health Care Delivery System: Algorithm Validation
title_full Identifying Ectopic Pregnancy in a Large Integrated Health Care Delivery System: Algorithm Validation
title_fullStr Identifying Ectopic Pregnancy in a Large Integrated Health Care Delivery System: Algorithm Validation
title_full_unstemmed Identifying Ectopic Pregnancy in a Large Integrated Health Care Delivery System: Algorithm Validation
title_short Identifying Ectopic Pregnancy in a Large Integrated Health Care Delivery System: Algorithm Validation
title_sort identifying ectopic pregnancy in a large integrated health care delivery system: algorithm validation
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7735905/
https://www.ncbi.nlm.nih.gov/pubmed/33141678
http://dx.doi.org/10.2196/18559
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