Identification and validation of uterine perforation, intrauterine device expulsion, and breastfeeding in four health care systems with electronic health records

Mary S. Anthony, Mary Anne Armstrong, Darios Getahun, Delia Scholes, Jennifer Gatz, Renate Schulze-Rath, Debbie Postlethwaite, Maqdooda Merchant, Amy L. Alabaster, Giulia Chillemi, Tina Raine-Bennett, Fagen Xie, Vicki Y. Chiu, Theresa M. Im, Harpreet S. Takhar, Michael Fassett, Jane Grafton, David Cronkite, Laura Ichikawa, Susan D. ReedSiu Lui Hui, Mary E. Ritchey, Catherine W. Saltus, Elizabeth B. Andrews, Kenneth J. Rothman, Alex Asiimwe, Richard Lynen, Juliane Schoendorf

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

Objective: To validate algorithms identifying uterine perforations and intrauterine device (IUD) expulsions and to ascertain availability of breastfeeding status at the time of IUD insertion. Study design and setting: Four health care systems with electronic health records (EHRs) participated: Kaiser Permanente Northern California (KPNC), Kaiser Permanente Southern California (KPSC), Kaiser Permanente Washington (KPWA), and Regenstrief Institute (RI). The study included women ≤50 years of age with an IUD insertion. Site-specific algorithms using structured and unstructured data were developed and a sample validated by EHR review. Positive predictive values (PPVs) of the algorithms were calculated. Breastfeeding status was assessed in a random sample of 125 women at each research site with IUD placement within 52 weeks postpartum. Results: The study population included 282,028 women with 325,582 IUD insertions. The PPVs for uterine perforation were KPNC 77%, KPSC 81%, KPWA 82%, and RI 47%; PPVs for IUD expulsion were KPNC 77%, KPSC 87%, KPWA 68%, and RI 37%. Across all research sites, breastfeeding status at the time of IUD insertion was determined for 94% of those sampled. Conclusions: Algorithms with a high PPV for uterine perforation and IUD expulsion were developed at 3 of the 4 research sites. Breastfeeding status at the time of IUD insertion could be determined at all research sites. Our findings suggest that a study to evaluate the associations of breastfeeding and postpartum IUD insertions with risk of uterine perforation and IUD expulsion can be successfully conducted retrospectively; however, automated application of algorithms must be supplemented with chart review for some outcomes at one research site due to low PPV.

Original languageEnglish (US)
Pages (from-to)635-643
Number of pages9
JournalClinical Epidemiology
Volume11
DOIs
StatePublished - 2019

Keywords

  • Algorithm
  • Breastfeeding
  • Electronic health records
  • Intrauterine device
  • Postpartum
  • Validation study

ASJC Scopus subject areas

  • Epidemiology

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    Anthony, M. S., Armstrong, M. A., Getahun, D., Scholes, D., Gatz, J., Schulze-Rath, R., Postlethwaite, D., Merchant, M., Alabaster, A. L., Chillemi, G., Raine-Bennett, T., Xie, F., Chiu, V. Y., Im, T. M., Takhar, H. S., Fassett, M., Grafton, J., Cronkite, D., Ichikawa, L., ... Schoendorf, J. (2019). Identification and validation of uterine perforation, intrauterine device expulsion, and breastfeeding in four health care systems with electronic health records. Clinical Epidemiology, 11, 635-643. https://doi.org/10.2147/CLEP.S201044