Assuring Quality in Assisted Reproduction Laboratories: Assessing the Performance of ART Compass - a Digital Art Staff Management Platform

Overview

Journal J Assist Reprod Genet

Publisher Springer

Specialties Genetics
Reproductive Medicine

Date 2023 Jan 13

PMID 36637586

Authors

Carol Lynn Curchoe

Charles Bormann

Elizabeth Hammond

Scarlett Salter

Claire Timlin

Lesley Blankenship Williams

Daniella Gilboa

Daniel Seidman

Alison Campbell

Dean Morbeck

Affiliations

Soon will be listed here.

Abstract

Purpose: Staff management is the most cited ART/IVF laboratory inspection deficiency. Small ART/IVF clinics may be challenged to perform these activities by low staff volume; similarly, large ART/IVF networks may be challenged by high staff volume and large datasets. Here, we sought to investigate the performance of an automated, digital platform solution to manage this necessary task.

Methods: The ART Compass (ARTC) digital staff management platform was used to assess the clinical decision-making of ART laboratory staff. The survey modules presented standardized instructions to technologists and measured inter- and intra-technologist variability for subjective "clinical decision-making" type questions. Internal and external comparisons were achieved by providing technologists two answers: (1) a comparison to their own lab director and (2) to the most popular response collectively provided by all lab director level accounts. The platform is hosted on HIPAA compliant Amazon web servers, accessible via web browser and mobile applications for iOS (Apple) and Android mobile devices.

Results: Here, we investigated the performance of a digital staff management platform for single embryologist IVF practices and for three IVF lab networks (sites A, B, C) from 2020 to 2022. Embryology dish preparation survey results show variance among respondents in the following: PPE use, media volume, timing of oil overlay, and timing of moving prepared dishes to incubators. Surveying the perceived Gardner score and terms in use for early blastocysts reveals a lack of standardization of terminology and fair to poor agreement. We observed moderate inter-technologist agreement for ICM and TE grade (0.47 and 0.52, respectively). Lastly, the clinical decision of choice to freeze or discard an embryo revealed that agreement to freeze was highest for the top-quality embryos, and that some embryos can be highly contested, evenly split between choice to freeze or discard.

Conclusions: We conclude that a digital platform is a novel and effective tool to automate, routinely monitor, and assure quality for staff-related parameters in ART and IVF laboratories. Use of a digital platform can increase regulatory compliance and provide actionable insight for quality assurance in both single embryologist practices and for large networks. Furthermore, clinical decision-making can be augmented with artificial intelligence integration.

Citing Articles

Application of a methodological framework for the development and multicenter validation of reliable artificial intelligence in embryo evaluation.

Gilboa D, Garg A, Shapiro M, Meseguer M, Amar Y, Lustgarten N Reprod Biol Endocrinol. 2025; 23(1):16.

PMID: 39891250 PMC: 11783712. DOI: 10.1186/s12958-025-01351-w.

A review of artificial intelligence applications in in vitro fertilization.

Zhang Q, Liang X, Chen Z J Assist Reprod Genet. 2024; 42(1):3-14.

PMID: 39400647 PMC: 11806189. DOI: 10.1007/s10815-024-03284-6.

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