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Benchmarking and Decision Making in the IVF Laboratory

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Abstract

Measuring the performance of the IVF laboratory is important for the purpose of monitoring current activities and also for further development. Although the most common indicator of performance is the clinics’ pregnancy rate, the IVF laboratory needs to monitor a larger number of parameters to acquire sufficient information of the daily processes. The chapter details the most common key performance indicators and suggests benchmark levels as well as gives advice on how to evaluate them. Aspects of improving decision making are discussed.

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References

  1. ESHRE Special Interest Group of Embryology and Alpha Scientists in Reproductive Medicine. The Vienna consensus: report of an expert meeting on the development of ART laboratory performance indicators. Reprod Biomed Online. 2017;35(5):494–510.

    Article  Google Scholar 

  2. Mortimer S, Mortimer D. Quality and risk management in the IVF laboratory. 2nd ed. Cambridge: Academic. Cambridge University Press; 2015.

    Book  Google Scholar 

  3. Alpha Scientists In Reproductive Medicine. The Alpha consensus meeting on cryopreservation key performance indicators and benchmarks: proceedings of an expert meeting. Reprod Biomed Online. 2012;25(2):146–67.

    Article  Google Scholar 

  4. Hirst WM, Vail A, Brison DR, Roberts SA. Prognostic factors influencing fresh and frozen IVF outcomes: an analysis of the UK national database. Reprod Biomed Online. 2011;22(5):437–48.

    Article  Google Scholar 

  5. Stiegler MP, Neelankavil JP, Canales C, Dhillon A. Cognitive errors detected in anaesthesiology: a literature review and pilot study. Br J Anaesth. 2012;108:229–35.

    Article  CAS  Google Scholar 

  6. Groopman J. How doctors think. New York: Houghton Mifflin Company; 2007.

    Google Scholar 

  7. Kahneman D. Thinking, fast and slow. New York: Farrar Straus Giroux; 2011.

    Google Scholar 

  8. Bazerman MH, Moore DA. Judgment in managerial decision making. 7th ed. Hoboken: Wiley; 2009.

    Google Scholar 

  9. Mukaida T, Oka C, Goto T, Takahashi K. Artificial shrinkage of blastocoeles using either a micro-needle or a laser pulse prior to the cooling steps of vitrification improves survival rate and pregnancy outcome of vitrified human blastocysts. Hum Reprod. 2006;21(12):3246–52.

    Article  CAS  Google Scholar 

  10. Van Landuyt L, Polyzos NP, De Munck N, Blockeel C, Van de Velde H, Verheyen G. A prospective randomized controlled trial investigating the effect of artificial shrinkage (collapse) on the implantation potential of vitrified blastocysts. Hum Reprod. 2015;30(11):2509–18.

    Article  Google Scholar 

  11. Flin RH, O’Connor P, Crichton M. Safety at the sharp end: a guide to non-technical skills. Aldershot: Ashgate Publishing, Ltd.; 2008.

    Google Scholar 

  12. Bruzelius LH, Skärvad P-H. Integrerad organisationslära (Integrated organization theory). 9th ed. Lund: Studentlitteratur; 2008.

    Google Scholar 

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Review Questions

Review Questions

  1. 1.

    How would you interpret a low value for cleavage rates in the embryology laboratory? Give examples of possible explanations and how to use the KPIs to find the root of the problem.

  2. 2.

    The embryology laboratory has a high rate of degenerated oocytes after ICSI. What is a possible explanation for this and which steps can be taken to improve the situation?

  3. 3.

    What steps can be taken in everyday work to improve decision making in complex and stressful situations?

  4. 4.

    Is your place of work a learning organization? Why/why not?

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Hreinsson, J. (2019). Benchmarking and Decision Making in the IVF Laboratory. In: Nagy, Z., Varghese, A., Agarwal, A. (eds) In Vitro Fertilization. Springer, Cham. https://doi.org/10.1007/978-3-319-43011-9_70

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  • DOI: https://doi.org/10.1007/978-3-319-43011-9_70

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-43010-2

  • Online ISBN: 978-3-319-43011-9

  • eBook Packages: MedicineMedicine (R0)

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