Evidence map›Paper›PMID 33141678›Full record

ArticleJMIR medical informatics2020

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

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 and 3 more

Abstract read
In one paragraph

Article in JMIR medical informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Darios GetahunDepartment of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, CA, United States.ORCID https://orcid.org/0000-0003-3610-8841
Jiaxiao M ShiDepartment of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, CA, United States.ORCID https://orcid.org/0000-0001-8397-3729
Malini ChandraDivision of Research, Kaiser Permanente Northern California, Oakland, CA, United States.ORCID https://orcid.org/0000-0003-4817-9540
Michael J FassettDepartment of Obstetrics and Gynecology, Kaiser Permanente West Los Angeles Medical Center, Los Angeles, CA, United States.ORCID https://orcid.org/0000-0002-3369-5916
Stacey AlexeeffDivision of Research, Kaiser Permanente Northern California, Oakland, CA, United States.ORCID https://orcid.org/0000-0001-8988-6976
Theresa M ImDepartment of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, CA, United States.ORCID https://orcid.org/0000-0001-6688-9146
Vicki Y ChiuDepartment of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, CA, United States.ORCID https://orcid.org/0000-0002-0698-6419
Mary Anne ArmstrongDivision of Research, Kaiser Permanente Northern California, Oakland, CA, United States.ORCID https://orcid.org/0000-0002-6521-5729
Fagen XieDepartment of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, CA, United States.ORCID https://orcid.org/0000-0002-1565-0490
Julie SternDepartment of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, CA, United States.ORCID https://orcid.org/0000-0002-0888-0810
Harpreet S TakharDepartment of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, CA, United States.ORCID https://orcid.org/0000-0002-2734-4896
Alex AsiimweBayer AG, Berlin, Germany.ORCID https://orcid.org/0000-0002-7633-0220
Tina Raine-BennettDepartment of Health Systems Science, Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, CA, United States.ORCID https://orcid.org/0000-0003-2035-2276

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSurveillance 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.

objectiveWe 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.

methodsMedical 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.

resultsThere 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%.

conclusionsThe 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.

Indexed as

ectopic pregnancyelectronic databaseelectronic health recordspredictive valuepregnancyvalidation

Identifiers

PMID33141678
PMCPMC7735905

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.