Casemanage – Planning

Achieve better Case Management with Casematch’s lenght of stay prediction. The algorithm expects input from data that is known shortly after admission. These include demographic data (age, sex, etc.), diagnoses with POA flag (present on admission) and planned interventions (CHOP). With the input of this data and the learned knowledge from the eonum data pool, this results in the predicted length of stay of a patient. A hospital can therefore better schedule its interventions. Thus, for example, expensive weekend stays can be avoided, better bed and duty scheduling can be carried out and, in the end, costs can be saved.

Further applications of the algorithm for case management are under development: Prediction of the final DRG, possible DRG changes, identification of risk patients, the prediction of possible complications, assessment of the risk of re-entry or transfer. These developments are of interest for quality management. In this way, precautions can be taken in advance for high-risk patients to prevent possible complications. Please read our blog posts about this:

• Medizinische Einflussfaktoren auf die Verweildauerprognose (available only in German)
• Besseres Case Management dank Verweildauerprognose und künstlicher Intelligenz (available only in German)