Cargando…
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...
Autores principales: | , , , , , , , , , , , , |
---|---|
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 |
_version_ | 1783622724335173632 |
---|---|
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. |
format | Online Article Text |
id | pubmed-7735905 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT getahundarios identifyingectopicpregnancyinalargeintegratedhealthcaredeliverysystemalgorithmvalidation AT shijiaxiaom identifyingectopicpregnancyinalargeintegratedhealthcaredeliverysystemalgorithmvalidation AT chandramalini identifyingectopicpregnancyinalargeintegratedhealthcaredeliverysystemalgorithmvalidation AT fassettmichaelj identifyingectopicpregnancyinalargeintegratedhealthcaredeliverysystemalgorithmvalidation AT alexeeffstacey identifyingectopicpregnancyinalargeintegratedhealthcaredeliverysystemalgorithmvalidation AT imtheresam identifyingectopicpregnancyinalargeintegratedhealthcaredeliverysystemalgorithmvalidation AT chiuvickiy identifyingectopicpregnancyinalargeintegratedhealthcaredeliverysystemalgorithmvalidation AT armstrongmaryanne identifyingectopicpregnancyinalargeintegratedhealthcaredeliverysystemalgorithmvalidation AT xiefagen identifyingectopicpregnancyinalargeintegratedhealthcaredeliverysystemalgorithmvalidation AT sternjulie identifyingectopicpregnancyinalargeintegratedhealthcaredeliverysystemalgorithmvalidation AT takharharpreets identifyingectopicpregnancyinalargeintegratedhealthcaredeliverysystemalgorithmvalidation AT asiimwealex identifyingectopicpregnancyinalargeintegratedhealthcaredeliverysystemalgorithmvalidation AT rainebennetttina identifyingectopicpregnancyinalargeintegratedhealthcaredeliverysystemalgorithmvalidation |