144. Evaluating the impact of staffing recommendations in maternity units in France: combining simulation and time-and-motion study
Invited abstract in session FA-1: Simulation 2, stream Sessions.
Friday, 9:00-10:30Room: NTNU, Realfagbygget R5
Authors (first author is the speaker)
| 1. | Louis Niffoi
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| Laboratoire de Génie Industriel, CentraleSupélec | |
| 2. | Oualid Jouini
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| Laboratoire Genie Industriel, Ecole Centrale Paris | |
| 3. | Marija Jankovic
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| Laboratoire de Génie Industriel, CentraleSupélec, University of Paris Saclay | |
| 4. | Pierre-François Ceccaldi
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| Service de Gynécologie-Obstétrique et Médecine de la reproduction, Hôpital Foch | |
| 5. | Guillaume Lamé
|
| Laboratoire de Génie Industriel, CentraleSupélec |
Abstract
Sufficient midwifery staff is crucial for the quality of maternity care. However, shortage of staff creates situations of understaffing, extending delays and compromising care continuity. In order to determine the required number of midwives in a given department, several guidelines have been presented in the literature. Yet, we lack evidence on how these guidelines affect quality of care, and on midwives’ activities and their availability to provide continuous support during labour.
In order to map and quantify midwives’ activities, we observed midwives during a full shift and interviewed them afterwards, giving us a better understanding of their work. The first results of this study show a distribution of midwives’ worktime. Most of their time is spent almost equally between direct care and administrative work (approximately a third of time on each). A significant part is also dedicated to communication, mainly between colleagues, to support collective situation awareness.
We then implemented these results in simulation models of birthing areas of several French maternities. We varied the number of midwives in the system, and their availability for direct care, to evaluate the effect of staffing recommendations on continuous support during childbirth. In preliminary results, guidelines lead to frequent under- and over-staffing, showing the impact of variability on patient support. Final results will help inform trade-offs on staffing levels.
Keywords
- Modelling and simulation
- Workforce planning and scheduling
Status: accepted
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