Predictive Allocation of Temperature-Sensitive Specialty Medications: A KPI-Driven Framework for Shortage Resilience in Underserved U.S. ZIP Codes

The gap suggested in the discussion will be bridged in the proposed work being done specifically on the lack of drugs in underserved ZIP codes with a particular interest in temperature sensitive drugs (a cool chain delivery system will be required). The problem affecting these regions could be inefficiencies in the supply chain and absence of adequate healthcare facilities to make sure relevant drugs are available. This research study will result in a KPI-oriented model that will see to it that the distribution strategy of these medicines is optimized in a manner that they are distributed to the needy populations at the right time.

The model utilizes the most up-to-date technologies, including SAP, SQL, and power BI to consider current data, predict changes in demand, optimize the distribution, and reduce stockouts and spoilage. This pilot study shows that the stockout is less three times, the decay rate is less 4 times and delivery is improved one quarter. The results prove the hypothesis that the framework could contribute to making dispensing medicine more effective and safer. These study possibilities are quite wide to assist all areas which are underprivileged providing equal access to healthcare. It can also lead to reduced health disparities and equitable health care outcomes across the risk communities because this model helps to ensure more consistent access to life-saving drugs.