Using hospital routine data to estimate case complexity

Effective distribution of increasingly scarce staff resources and optimal distribution of tasks are currently among the primary concerns of nursing management professionals. Accounting for the case complexity of the patients on the wards is a central part of this process. In a 2017 study, we showed how LEP data can be used to estimate case complexity. Building on those results, and based on data from a Swiss hospital, we have now developed a statistical model that can be used to predict patients’ clinical case complexity. This model is particularly well-suited for practical application because it is based solely on routine data that are already available before or during the hospital stay, thus allowing for real-time prediction with no additional data collection effort.

We will be presenting the model as part of a talk at the Nursing Informatics Conference in July. Our research article will appear in the conference proceedings and will be linked on the LEP homepage. Three LEP employees will be attending the conference in Manchester, and they look forward to meeting you there.

For projects relating to case complexity, we are currently looking for practice partners
•    who would like to implement the case complexity model with us to help support nursing management teams, and/or
•    who are interested in a research project on automatic estimation of nursing case complexity.
If interested, please contact Glorianna Jagfeld.

Further information:
Research report on estimating case complexity on the basis of LEP data (in German): Ranegger, R., Baumberger, D., & Bürgin, R. (2017). Forschungsbericht: Bedarfs- und kompetenzorientierte Personaleinsatzplanung gemäss GuKG 2016 - eine Tätigkeitsanalyse (Teil A). St. Gallen, Switzerland: LEP AG
New: English summary of the research report
Nursing Informatics Conference Manchester, UK, 28-31 July 2024