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Improving ICSI success rates following root cause analysis and use of system behaviour charts: the devil is in the detail!
A fertility clinic observed a reduction in its fresh intracytoplasmic sperm injection (ICSI) implantation rate key performance indicator (KPI) below benchmark threshold which was further monitored but did not improve. The clinic had been performing ICSI successfully for >16 years with good ICSI i...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9664290/ https://www.ncbi.nlm.nih.gov/pubmed/36351750 http://dx.doi.org/10.1136/bmjoq-2022-002003 |
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author | Woodland, Emma Carroll, Michael |
author_facet | Woodland, Emma Carroll, Michael |
author_sort | Woodland, Emma |
collection | PubMed |
description | A fertility clinic observed a reduction in its fresh intracytoplasmic sperm injection (ICSI) implantation rate key performance indicator (KPI) below benchmark threshold which was further monitored but did not improve. The clinic had been performing ICSI successfully for >16 years with good ICSI implantation rates meeting benchmark level. A root cause analysis (RCA) was conducted, including the input from an external observer, reviewing all systems and processes. A bundle of recommended changes was implemented as part of an improvement cycle with the aim to increase fresh ICSI implantation rates back to benchmark. Quality improvement (QI) methodology and tools were used including Statistical-Process-Control charts (BaseLine SAASoft). Measurements included standard clinical outcome data. KPIs were tracked following defined and controlled clinical and laboratory changes. Fresh ICSI implantation rates improved significantly (p=0.013, ChiSq). The improvement work was limited by its design of a plan-do-study-act (PDSA) cycle ‘intervention bundle’ as opposed to small PDSA cycles of single changes. Therefore, the improvement could not be attributed to any singular intervention within the bundle. It took longer than anticipated to see improvement due to the impact of the pandemic. The QI project highlighted the difficulty for clinics with low cycle volumes to sensitively monitor KPI’s in a timely and responsive way. The need to accumulate sufficient data to be confident of any trends/concerns means small clinics could be less responsive to any problems or too reactive to false positives. It is important to disseminate the learning from this improvement work because there is currently no agreed standardised optimal protocol for ICSI, resulting in clinics using slightly different approaches, and there are limited published reports where embryology KPI’s are tracked following defined and controlled laboratory/clinical changes. This project provides useful knowledge about ICSI improvement interventions and could be more effective within a larger clinic with higher cycle volumes. |
format | Online Article Text |
id | pubmed-9664290 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-96642902022-11-15 Improving ICSI success rates following root cause analysis and use of system behaviour charts: the devil is in the detail! Woodland, Emma Carroll, Michael BMJ Open Qual Quality Improvement Report A fertility clinic observed a reduction in its fresh intracytoplasmic sperm injection (ICSI) implantation rate key performance indicator (KPI) below benchmark threshold which was further monitored but did not improve. The clinic had been performing ICSI successfully for >16 years with good ICSI implantation rates meeting benchmark level. A root cause analysis (RCA) was conducted, including the input from an external observer, reviewing all systems and processes. A bundle of recommended changes was implemented as part of an improvement cycle with the aim to increase fresh ICSI implantation rates back to benchmark. Quality improvement (QI) methodology and tools were used including Statistical-Process-Control charts (BaseLine SAASoft). Measurements included standard clinical outcome data. KPIs were tracked following defined and controlled clinical and laboratory changes. Fresh ICSI implantation rates improved significantly (p=0.013, ChiSq). The improvement work was limited by its design of a plan-do-study-act (PDSA) cycle ‘intervention bundle’ as opposed to small PDSA cycles of single changes. Therefore, the improvement could not be attributed to any singular intervention within the bundle. It took longer than anticipated to see improvement due to the impact of the pandemic. The QI project highlighted the difficulty for clinics with low cycle volumes to sensitively monitor KPI’s in a timely and responsive way. The need to accumulate sufficient data to be confident of any trends/concerns means small clinics could be less responsive to any problems or too reactive to false positives. It is important to disseminate the learning from this improvement work because there is currently no agreed standardised optimal protocol for ICSI, resulting in clinics using slightly different approaches, and there are limited published reports where embryology KPI’s are tracked following defined and controlled laboratory/clinical changes. This project provides useful knowledge about ICSI improvement interventions and could be more effective within a larger clinic with higher cycle volumes. BMJ Publishing Group 2022-11-09 /pmc/articles/PMC9664290/ /pubmed/36351750 http://dx.doi.org/10.1136/bmjoq-2022-002003 Text en © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Quality Improvement Report Woodland, Emma Carroll, Michael Improving ICSI success rates following root cause analysis and use of system behaviour charts: the devil is in the detail! |
title | Improving ICSI success rates following root cause analysis and use of system behaviour charts: the devil is in the detail! |
title_full | Improving ICSI success rates following root cause analysis and use of system behaviour charts: the devil is in the detail! |
title_fullStr | Improving ICSI success rates following root cause analysis and use of system behaviour charts: the devil is in the detail! |
title_full_unstemmed | Improving ICSI success rates following root cause analysis and use of system behaviour charts: the devil is in the detail! |
title_short | Improving ICSI success rates following root cause analysis and use of system behaviour charts: the devil is in the detail! |
title_sort | improving icsi success rates following root cause analysis and use of system behaviour charts: the devil is in the detail! |
topic | Quality Improvement Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9664290/ https://www.ncbi.nlm.nih.gov/pubmed/36351750 http://dx.doi.org/10.1136/bmjoq-2022-002003 |
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