Electronic Algorithm Is Superior to Hospital Discharge Codes for Diagnoses of Hypertensive Disorders of Pregnancy in Historical Cohorts

Natasa M. Milic, Elisabeth Codsi, Yvonne S. Butler Tobah, Wendy M. White, Andrea G. Kattah, Tracey L. Weissgerber, Mie Saiki, Santosh Parashuram, Lisa E. Vaughan, Amy L. Weaver, Marko Savic, Michelle M. Mielke, Vesna D. Garovic

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


Objectives: To develop and validate criteria for the retrospective diagnoses of hypertensive disorders of pregnancy that would be amenable to the development of an electronic algorithm, and to compare the accuracy of diagnoses based on both the algorithm and diagnostic codes with the gold standard, of physician-made diagnoses based on a detailed review of medical records using accepted clinical criteria. Patients and Methods: An algorithm for hypertensive disorders of pregnancy was developed by first defining a set of criteria for retrospective diagnoses, which included relevant clinical variables and diagnosis of hypertension that required blood pressure elevations in greater than 50% of readings (“the 50% rule”). The algorithm was validated using the Rochester Epidemiology Project (Rochester, Minnesota). A stratified random sample of pregnancies and deliveries between January 1, 1976, and December 31, 1982, with the algorithm-based diagnoses was generated for review and physician-made diagnoses (normotensive, gestational hypertension, and preeclampsia), which served as the gold standard; the targeted cohort size for analysis was 25 per diagnosis category according to the gold standard. Agreements between (1) algorithm-based diagnoses and (2) diagnostic codes and the gold standard were analyzed. Results: Sensitivities of the algorithm for 25 normotensive pregnancies, 25 with gestational hypertension, and 25 with preeclampsia were 100%, 88%, and 100%, respectively, and specificities were 94%, 100%, and 100%, respectively. Diagnostic code sensitivities were 96% for normotensive pregnancies, 32% for gestational hypertension, and 96% for preeclampsia, and specificities were 78%, 96%, and 88%, respectively. Conclusion: The electronic diagnostic algorithm was highly sensitive and specific in identifying and classifying hypertensive disorders of pregnancy and was superior to diagnostic codes.

Original languageEnglish (US)
Pages (from-to)1707-1719
Number of pages13
JournalMayo Clinic proceedings
Issue number12
StatePublished - Dec 2018

ASJC Scopus subject areas

  • General Medicine


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