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 IC...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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BMJ Publishing Group
2022-11-01
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| Series: | BMJ Open Quality |
| Online Access: | https://bmjopenquality.bmj.com/content/11/4/e002003.full |
| _version_ | 1827903178836803584 |
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| author | Michael Carroll Emma Woodland |
| author_facet | Michael Carroll Emma Woodland |
| author_sort | Michael Carroll |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-13T00:09:19Z |
| format | Article |
| id | doaj.art-0fc82f381e4f4f23bc021c1d8eb62cd7 |
| institution | Directory Open Access Journal |
| issn | 2399-6641 |
| language | English |
| last_indexed | 2024-03-13T00:09:19Z |
| publishDate | 2022-11-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | BMJ Open Quality |
| spelling | doaj.art-0fc82f381e4f4f23bc021c1d8eb62cd72023-07-12T16:00:07ZengBMJ Publishing GroupBMJ Open Quality2399-66412022-11-0111410.1136/bmjoq-2022-002003Improving ICSI success rates following root cause analysis and use of system behaviour charts: the devil is in the detail!Michael Carroll0Emma Woodland1Department of Life Sciences, Manchester Metropolitan University, Manchester, UKDepartment of Life Sciences, Manchester Metropolitan University, Manchester, UKA 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.https://bmjopenquality.bmj.com/content/11/4/e002003.full |
| spellingShingle | Michael Carroll Emma Woodland Improving ICSI success rates following root cause analysis and use of system behaviour charts: the devil is in the detail! BMJ Open Quality |
| 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 |
| url | https://bmjopenquality.bmj.com/content/11/4/e002003.full |
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