Modelling midwifery care demand and supply – analysis of longitudinal routine hospital data
Bibliographic record
Abstract
Introduction A staffing shortage of registered nurses and midwives was identified in Switzerland. There is no recommendation on midwifery staffing and current staffing levels in Swiss maternity wards are unknown. The aim of this study was to model current care demand and care supply by midwives in a maternity department of a Swiss university hospital. Methods Single-centre retrospective observational longitudinal study investigated a time frame of four years (2019-2022). The main setting of interest was the labour ward with 2,500 births annually. Working with routine hospital data, we included all maternal and neonatal patients who were admitted as inpatients to the study setting. Registered midwives from the labour ward, who are scheduled in a three-shift pattern (day, late, and night shift) were also included. To model the care demand side, we worked with the number of birthing parents and newborns. Based on the goal to provide 1-to-1 care we counted the number of midwifery working hours as care supply and the number of hours patients were present as care demand for each shift. Care demand hours were subtracted from care supply hours for each shift to calculate the supply-demand-match. Results In total 10,458 births occurred during 4,383 shifts. Preliminary results show high variation in the number of births daily with a range from zero up to 17 births during one day and a yearly average of seven births per day ([ Fig. 1 ]). Abb. 1 The average number of care supply was 44.1 hours per shift (SD+/- 6.6 hours), and 48.4 hours for care demand (SD+/- 17.1 hours). Regarding the mismatch between care supply and care demand, this resulted in -4.3 hours per shift (SD+/- 15.4 hours) or -0.5 midwives per shift ([ Fig. 2 ], only the year 2022 is shown representatively for the complete time frame). On average one midwife was missing during day shifts (mean=-8.0 hours, SD+/-15.9 hours), a good match was apparent for late shifts (mean=-0.4 hours, SD+/- 14.5 hours), and half a midwife was missing during night shifts (mean=-4.5 hours, SD+/- 14.8 hours). Abb. 2 Discussion Showing this match between care demand and care supply increases the understanding of the current staffing schedule in one Swiss university hospital. Given that we will face continued staffing shortages in the near future, it is critical to search for solutions to improve the match between demand and supply. Without any additional midwifery staff there is potential through improved alignment between care demand and care supply. Adapting staff scheduling based on the number of pregnant parents registered for birth in the hospital per month might offer this possibility. In this representation of care demand we didn"t include the complexity of patients, which will be done in a next step to improve the understanding of care demand variation in Swiss labour wards and its effect on the supply-demand-match. Publication History Article published online: 15 November 2023 © 2023. Thieme. All rights reserved. Georg Thieme Verlag KG Rüdigerstraße 14, 70469 Stuttgart, Germany
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".