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2210. Evaluating the impact of staffing recommendations in maternity units
Invited abstract in session MC-17: Simulation models in healthcare, stream OR in Health Services (ORAHS).
Monday, 12:30-14:00Room: 40 (building: 116)
Authors (first author is the speaker)
| 1. | Louis Niffoi
|
| Laboratoire de Génie Industriel, CentraleSupélec | |
| 2. | Oualid Jouini
|
| Laboratoire Genie Industriel, Ecole Centrale Paris | |
| 3. | Marija Jankovic
|
| Laboratoire de Génie Industriel, CentraleSupélec, University of Paris Saclay | |
| 4. | Pierre-François Ceccaldi
|
| 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 to the quality of maternity care. However, the shortage of staff that France has been facing for several decades creates situations of understaffing. In order to determine the optimum number of midwives in a given department, several methods have been presented in the literature, e.g., a 1998 decree that sets out minimum staffing levels, recommendations from scientific societies, or calculation tools like the British BirthRate Plus tool. Yet, we lack evidence on how these models affect quality of care.
We observed the operation of a French public hospital maternity and built a discrete-event simulation model using Simul8 software. The simulation model reproduces the structure, staffing schedules and patient characteristics of the maternity. Because it has been shown that one-to-one care (one midwife for one patient) has a positive impact on service indicators such as readmission rates, stillbirth rates and average length of labour, we used the rate of one-to-one care in labor as our main output. We used design of experiment methods to determine the most influent factors in our model.
Using this model, we analysed the impact of different staffing recommendations on quality of care measured by the rate of one-to-one care. In the future, the model will be enriched with time-and-motion analysis data to provide more accurate estimates of how much time midwives can really devote to patient care in delivery units.
Keywords
- Health Care
- Simulation
Status: accepted
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