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. 2019 Jul 23:11:635-643.
doi: 10.2147/CLEP.S201044. eCollection 2019.

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

Mary S Anthony  1 , Mary Anne Armstrong  2 , Darios Getahun  3 , Delia Scholes  4 , Jennifer Gatz  5 , Renate Schulze-Rath  6 , Debbie Postlethwaite  2 , Maqdooda Merchant  2 , Amy L Alabaster  2 , Giulia Chillemi  2 , Tina Raine-Bennett  2 , Fagen Xie  3 , Vicki Y Chiu  3 , Theresa M Im  3 , Harpreet S Takhar  3 , Michael Fassett  3 , Jane Grafton  4 , David Cronkite  4 , Laura Ichikawa  4 , Susan D Reed  4   7 , Siu Lui Hui  5 , Mary E Ritchey  1 , Catherine W Saltus  8 , Elizabeth B Andrews  1 , Kenneth J Rothman  8 , Alex Asiimwe  6 , Richard Lynen  9 , Juliane Schoendorf  10
Affiliations

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

Mary S Anthony et al. Clin Epidemiol. .

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.

Keywords: algorithm; breastfeeding; electronic health records; intrauterine device; postpartum; validation study.

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Conflict of interest statement

RS-R, AA, RL, and JS are employees of Bayer, the marketing authorization holder for three IUD brands among others that were included in this study. AA reports stocks from Bayer. MAA is the Principal Investigator at the KPNC site and employed by KPNC. She also reports grants from Bayer AG, during the conduct of the study and outside the submitted work. DG is employed by KPSC and reports grants from Bayer Pharma AG, during the conduct of the study and received grants from Bayer Pharma AG, Centers for Disease Control and Prevention, and the US National Institutes of Health/National Institute of Child Health and Human Development (NIH/NICHD), outside the submitted work. DS is employed by KPWA and reports grants from Bayer, during the conduct of the study. JG is employed by RI and reports grants from Bayer AG, during the conduct of the study and outside the submitted work. DP is employed by KPNC and reports grants from Bayer AG, during the conduct of the study and outside the submitted work. ALA is an employee of KPNC. GC is an employee of KPNC and reports grants from Bayer AG, during the conduct of the study and outside the submitted work. TR-B and MM are employees of KPNC and reports grants from Bayer A.G, during the conduct of the study and reports consulting fees paid to KPNC from TEVA pharmaceutical, outside the submitted work. MF is employed by KPSC and reports grants from Bayer, during the conduct of the study; grants from Bayer and NIH/NICHD, outside the submitted work. DC is employed by KPWA and reports grants from Bayer, during the conduct of the study. SDR is employed by KPWA and reports grants from Bayer AG, during the conduct of the study. MSA, MER, CWS, EBA, and KJR are employed by RTI Health Solutions. The authors report no other conflicts of interest in this work.

References

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