I've been doing some extensive research on the potential value of conceptually applying the heritage algorithm in a healthcare provider setting (hospitals, etc). From a data analytics perspective, the scope for developing this algorithm undoubtedly exists. However, various similar algorithms (with the purpose of identifying patients at risk of admission or preventing 'unnecessary hospitalizations') have been developed and implemented across the globe for a number of years now. Due to the fact that some of these algorithms are disease based, they tend to have much higher accuracies as opposed to the heritage 'accuracy threshold' of 0.4.
How does the heritage algorithm then differ, if at all, from these algorithms?