Clinical Trial Summary
Patients who have an increased need for monitoring or therapy during their stay in hospital
are typically admitted to an intensive care unit. This is characterized by a large number of
diagnostic and therapeutic options. If this additional effort is no longer necessary, then
typically in most hospitals patients are transferred to wards with a lower presence of nurses
and physicians and reduced provision of extensive monitoring and therapeutic procedures such
as organ replacement procedures.
However, deintensification of medical and nursing care requires that previously monitored and
partially supported bodily functions are restored to the point where further monitoring is no
longer necessary. For this reason, transfer from an intensive care unit to the normal
inpatient area is only possible if the patient in question has neither an increased need for
monitoring nor an increased need for therapy. If this is not the case, then there is a risk
of life-threatening conditions in the normal ward, which can sometimes occur very quickly.
However, the need for further monitoring, or for continued intensive medical therapy, cannot
be easily assessed. There is no laboratory value or clinical examination method that can be
used to estimate beyond doubt whether a patient's condition could worsen if he or she is
transferred to the normal ward. For this reason, the decision to transfer is made on the
basis of the individual assessment by the attending physician. Although this is based on the
synopsis of a wide variety of examinations and laboratory findings, it is therefore subject
to large interindividual variations. Thus, the personal experience of the evaluating
physician has a considerable influence on the decision for or against a transfer to the
normal inpatient area.
In this respect, the decision to deintensify therapy, i.e. to transfer patients from
intensive care units to the normal care area, is challenging:
The assessing physician has to make a prediction from the combination of the available
findings under time pressure whether a transfer to the normal inpatient area is possible
without endangering the patient. In this situation, it would be desirable to have an
automated warning system that could describe the success of the transfer with sufficient
accuracy in the presence of specific laboratory constellations. In the best case, such an
approach would prevent dangerous transfers, but at the same time reduce unnecessary lengths
of stay in the ICU. Machine learning methods seem particularly suited to support such a
decision.
