There are 48 or 49 kinds of input data used to train two different neural networks. The inputs include basic demographics, admission history, family support systems, ability to care for self, diagnosis information, etc. There are four output neurons. Four networks were trained using 500-600 cases, two each on two different years of annual data. In this way, the predicted LOS for particular patients could be compared between two years at the institution which had undergone major organizational changes.
Psychiatric diseases are the most difficult to predict.
In addition, varying standards and funding policies make care more susceptible to chaos and difficult to compare between locations. Neural networks provide a means to predict the effectiveness of care for a specific location. Several neural networks can be trained with patient data from particular time periods, which will provide a method of judging the effectiveness of changing policy, procedure, or available resources.