Dr Christina Saville BSc, MSc, PhD
Research Fellow
Christina is a Research Fellow within the Workforce and Health Systems theme in Health Sciences. She has been researching nurse staffing since 2017. This work has been funded by National Institute for Health Research (NIHR) Applied Research Collaboration (ARC) Wessex and NIHR grants.
Christina’s background is in Operational Research, the branch of Mathematics that uses advanced quantitative techniques to help make better decisions. She is interested in how Operational Research techniques can be applied to decisions in healthcare, particularly staffing decisions.
Planning safe staffing levels is complicated so we need to make use of advanced methods. Setting nurse staffing levels at the average needed may be putting patients at risk.
As part of a large project across four hospitals, she analysed data to understand the variation in demand for nursing. In particular, she compared requirements measured by a widely-used staffing tool (the Safer Nursing Care Tool) with professional judgements of staffing adequacy. She developed a computer simulation in Anylogic (www.anylogic.com) to model the costs and consequences of alternative nurse staffing approaches. She also analysed the relationship between staff working long shifts and professional judgements of staffing adequacy.
Her current project involves working with hospitals in Wessex. The project aims to understand which ward characteristics mean the Safer Nursing Care Tool provides good estimates of the staffing levels required, and which ward characteristics mean that the number might need to be adjusted or further considered by taking into account the expertise of ward leaders.
In 2018, Christina obtained her PhD thesis in the Operational Research group in the School of Mathematics. The topic was mathematical modelling of breast diagnostic clinics. It involved analysing whether information provided by general practitioners when referring patients to diagnostic clinics could be used to predict patients’ risks of receiving normal/ abnormal diagnoses, and simulated alternative ways cancer diagnostic clinics could be organised if this information were used. Prior to this, she worked as an Operational Research Consultant at British Airways.