OBJECTIVE: To assess the development of local clinical dashboards in line with UK national guidance and to identify ongoing issues being faced by maternity units, across an entire health region, in developing quality assurance systems. STUDY DESIGN: A mixed-methods study involving all consultant-led maternity units in the South West of England Strategic Health Authority region (SWSHA). An electronic survey, followed by semi-structured interviews with the lead obstetrician and risk management midwife (or equivalent) of each maternity unit, to investigate methods employed to monitor outcomes locally, particularly the development of tools including maternity dashboards. Interviews were audio recorded, transcribed and thematically analysed to identify conceptual categories and themes. RESULTS: 12/15 eligible consultant-led maternity units participated in the study and 10/12 (83%) of these used a dashboard. There was an excessive number of non-standard indicators used by the maternity units, with 352 different quality indicators (QIs), covering 37 different indicator categories, with up to 39 different definitions for one particular QI. Issues identified were: an excess of indicators, disproportionate time taken to produce the dashboard, uncertainty surrounding thresholds for alert within the dashboards and a desire for more guidance and standardisation of indicators, and their use. CONCLUSIONS: Following recommendation by the Royal College of Obstetricians and Gynaecologists, maternity dashboards have been widely adopted by maternity units across the SWSHA to provide a local quality assurance system. There is, however, wide variation in both the quality indicators monitored and their definition. There is an urgent requirement for a national and international core set of maternity QIs. Further guidance is also required to inform alert thresholds for adverse outcomes. These perinatal data are collected electronically, and automating the production of a standardised dashboard is both possible and desirable.
OBJECTIVE: To assess the development of local clinical dashboards in line with UK national guidance and to identify ongoing issues being faced by maternity units, across an entire health region, in developing quality assurance systems. STUDY DESIGN: A mixed-methods study involving all consultant-led maternity units in the South West of England Strategic Health Authority region (SWSHA). An electronic survey, followed by semi-structured interviews with the lead obstetrician and risk management midwife (or equivalent) of each maternity unit, to investigate methods employed to monitor outcomes locally, particularly the development of tools including maternity dashboards. Interviews were audio recorded, transcribed and thematically analysed to identify conceptual categories and themes. RESULTS: 12/15 eligible consultant-led maternity units participated in the study and 10/12 (83%) of these used a dashboard. There was an excessive number of non-standard indicators used by the maternity units, with 352 different quality indicators (QIs), covering 37 different indicator categories, with up to 39 different definitions for one particular QI. Issues identified were: an excess of indicators, disproportionate time taken to produce the dashboard, uncertainty surrounding thresholds for alert within the dashboards and a desire for more guidance and standardisation of indicators, and their use. CONCLUSIONS: Following recommendation by the Royal College of Obstetricians and Gynaecologists, maternity dashboards have been widely adopted by maternity units across the SWSHA to provide a local quality assurance system. There is, however, wide variation in both the quality indicators monitored and their definition. There is an urgent requirement for a national and international core set of maternity QIs. Further guidance is also required to inform alert thresholds for adverse outcomes. These perinatal data are collected electronically, and automating the production of a standardised dashboard is both possible and desirable.
Authors: Wouter T Gude; Benjamin Brown; Sabine N van der Veer; Heather L Colquhoun; Noah M Ivers; Jamie C Brehaut; Zach Landis-Lewis; Christopher J Armitage; Nicolette F de Keizer; Niels Peek Journal: Implement Sci Date: 2019-04-24 Impact factor: 7.327