The decision model used for my topic is the top-down decision tree model. This decision tree measures the optimum recovery rate for the non-compliant patients. There isn’t really a threshold values that would cause the tree to flip. In this case, my decision tree would flip if I have too many variables in addition to the three types of non-compliant patients, or the outcome of these non-compliant patients in addition to the nursing home or hospitalization. Other possible patients’ category could be broken down to patients’ educational level, cultural background, personal or religious belief. Other possible outcomes in addition to the two provided in the decision tree could be 100% recovery rate, 50% recovery rate, or worse-case scenario death.
The weakness to my analysis is that my calculations were based on the …show more content…
(Deshpande, 2011) From the decision tree, we can see that generally patients are split into two categories, either the patients are compliant to their treatment or not compliant to their treatment. For patients who are compliant to their treatment, they are on their way to recovery. For patients who are non-compliant to their treatment, they are then split again into three different categories, which are patients who have been taking their medications incorrectly, patients who never refill their medications and the third category is patients who cannot identify their medications. Among patients within these three categories, patients are then predicted to either end up in a nursing home or back into the hospital for further treatment due to their non-compliant. For readers and executive management, one can easily see that 70% of the non-compliant patients within each category ends up in the nursing home and then 30% ends up in the
The weakness to my analysis is that my calculations were based on the …show more content…
(Deshpande, 2011) From the decision tree, we can see that generally patients are split into two categories, either the patients are compliant to their treatment or not compliant to their treatment. For patients who are compliant to their treatment, they are on their way to recovery. For patients who are non-compliant to their treatment, they are then split again into three different categories, which are patients who have been taking their medications incorrectly, patients who never refill their medications and the third category is patients who cannot identify their medications. Among patients within these three categories, patients are then predicted to either end up in a nursing home or back into the hospital for further treatment due to their non-compliant. For readers and executive management, one can easily see that 70% of the non-compliant patients within each category ends up in the nursing home and then 30% ends up in the