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Bacal V, Russo M, Fell DB, et al. A systematic review of database validation studies among fertility populations. Hum Reprod Open. 2019;2019(3):hoz010doi: 10.1093/hropen/hoz010.
Bacal, V., Russo, M., Fell, D. B., Shapiro, H., Walker, M., & Gaudet, L. M. (2019). A systematic review of database validation studies among fertility populations. Human reproduction open, 2019(3), hoz010. https://doi.org/10.1093/hropen/hoz010
Bacal, V, et al. "A systematic review of database validation studies among fertility populations." Human reproduction open vol. 2019,3 (2019): hoz010. doi: https://doi.org/10.1093/hropen/hoz010
Bacal V, Russo M, Fell DB, Shapiro H, Walker M, Gaudet LM. A systematic review of database validation studies among fertility populations. Hum Reprod Open. 2019 Jun 06;2019(3):hoz010. doi: 10.1093/hropen/hoz010. eCollection 2019. PMID: 31206038; PMCID: PMC6561328.
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Hum Reprod Open. 2019 Jun 06;2019(3):hoz010. doi: 10.1093/hropen/hoz010. eCollection 2019.

A systematic review of database validation studies among fertility populations.

Human reproduction open

V Bacal, M Russo, D B Fell, H Shapiro, M Walker, L M Gaudet

Affiliations

  1. School of Epidemiology and Public Health (SEPH), University of Ottawa, Ottawa, Canada.
  2. Department of Obstetrics and Gynecology, University of Ottawa, Ottawa, Canada.
  3. Ottawa Hospital Research Institute, Ottawa, Canada.
  4. Department of Obstetrics and Gynecology, University of Toronto, Toronto, Canada.
  5. Mount Sinai Fertility, Toronto, Canada.
  6. Children's Hospital of Eastern Ontario Research Institute, Ottawa, Canada.
  7. Institute for Clinical Evaluative Sciences, Ottawa, Canada.

PMID: 31206038 PMCID: PMC6561328 DOI: 10.1093/hropen/hoz010

Abstract

STUDY QUESTION: Are routinely collected data from fertility populations adequately validated?

SUMMARY ANSWER: Of the 19 studies included, only one validated a national fertility registry and none reported their results in accordance with recommended reporting guidelines for validation studies.

WHAT IS KNOWN ALREADY: Routinely collected data, including administrative databases and registries, are excellent sources of data, particularly for reporting, quality assurance, and research. However, these data are subject to misclassification bias due to misdiagnosis or errors in data entry and therefore need to be validated prior to using for clinical or research purposes.

STUDY DESIGN SIZE DURATION: We conducted a systematic review by searching Medline, Embase, and CINAHL from inception to 6 October 2016 to identify validation studies of databases that contain routinely collected data in an ART setting. Webpages of international ART centers were also searched.

PARTICIPANTS/MATERIALS SETTING METHODS: We included studies that compared at least two data sources to validate ART population data. Key words and MeSH terms were adapted from previous systematic reviews investigating routinely collected data (e.g. administrative databases and registries), measures of validity (including sensitivity, specificity, and predictive value), and ART (including infertility, IVF, advanced reproductive age, and diminished ovarian reserve). Only full-text studies in English were considered. Results were synthesized qualitatively. The electronic search yielded 1074 citations, of which 19 met the inclusion criteria.

MAIN RESULTS AND THE ROLE OF CHANCE: Two studies validated a fertility database using medical records; seven studies used an IVF registry to validate vital records or maternal questionnaires, and two studies failed to adequately describe their reference standard. Four studies investigated the validity of mode of conception from birth registries; two studies validated diagnoses or treatments in a fertility database; four studies validated a linkage algorithm between a fertility registry and another administrative database; one study created an algorithm in a single database to identify a patient population. Sensitivity was the most commonly reported measure of validity (12 studies), followed by specificity (9 studies). Only three studies reported four or more measures of validation, and five studies presented CIs for their estimates. The prevalence of the variable in the target population (pre-test prevalence) was reported in seven studies; however, only four of the studies had prevalence estimates from the study population (post-test prevalence) within a 2% range of the pre-test estimate. The post-test estimate was largely discrepant from the pre-test value in two studies.

LIMITATIONS REASONS FOR CAUTION: The search strategy was limited to the studies and reports published in English, which may not capture validation studies from countries that do not speak English. Furthermore, only three specific fertility-based diagnostic variables (advanced reproductive age, diminished ovarian reserve, and chorionicity) were searched in Medline, Embase, and CINAHL. Consequently, published studies with other diagnoses or conditions relevant to infertility may not have been captured in our review.

WIDER IMPLICATIONS OF THE FINDINGS: There is a paucity of literature on validation of routinely collected data from a fertility population. Furthermore, the prevalence of the markers that have been validated are not being presented, which can lead to biased estimates. Stakeholders rely on these data for monitoring outcomes of treatments and adverse events; therefore, it is essential to ascertain the accuracy of these databases and make the reports publicly available.

STUDY FUNDING/COMPETING INTERESTS: This study was supported by Canadian Institutes of Health Research (CIHR) (FDN-148438). There are no competing interests for any of the authors.

REGISTRATION NUMBER: International Prospective Register of Systematic Reviews ID: CRD42016048466.

Keywords: ART; database; infertility; quality assurance; reproductive epidemiology; validation

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