Patient presents with lung cancer — undifferentiated tumor in her mediastinum. Doctors don’t want to operate because there is a 15% risk of death with surgery. Within a month, patient dies, not of lung cancer, but suffocation. Turns out tumor was pressing on diaphragm and making it hard to breathe. Biggest fear during entire ordeal… don’t let me suffocate to death. Happiest during the process? Sitting with other patients discussing types of wigs.
IDEA The answer to EHR lies in the support group, not the doctor’s office. While every cancer is unique, there are non-obvious relationships that bind all these patients together. Imagine computers analyzing thousands of lung cancer patients and thin slicing each into very small groups. These groups belong to slightly larger groups, etc. In other words, patients form classes within a taxonomy.
Each new patient gets classified and algorithms use this information to find patients with very similar (EHR) records. The computer may immediately recommend a brain scan to see if the tumor has metastasized. Algorithms know that in this patient’s disease classification, X% of patients also have brain tumors. Algorithms would also tell surgeons that a 15% mortality rate is acceptable. Get as much of the tumor as possible to provide relief to the diaphragm. The algorithms are self-learning and get smarter as more patients are added to the database.