Guest post by Dhiren Patel, Digital Health Informer.
Being born with a heart condition I have had a chance to see how healthcare has evolved or stagnated in innovation because of inherent risk to the bottom line. Reducing revenue, patient risk and pressure from big pharma and insurance has kept the status quo. It’s crazy to think that we can order food from our phones and yet can’t even schedule our appointments online at most physicians offices and hospitals. We have the most expensive and least effective healthcare system in the world, it’s broken so we need to fix it.
There is a lack of technology in healthcare as a whole. Think about when you go into a doctor’s office and you tell them what’s wrong or if you go to a hospital and nurses are tracking your symptoms, they still write it on a piece of paper at most hospitals and physicians offices! Well, what happens when the nurse or doctor can’t read what’s been written or worse what if that paper gets lost. To put that in perspective, hospital errors are the number three leading cause of death in the U.S.
Where there is some technology it is often difficult to use and is not standardized so if you go to an emergency room that doctor will likely have to spend time trying to get your primary care doctor on the phone to better understand how to care for you. It’s happened to me before, the ER doctors spent hours trying to track down my cardiologist to get a rundown on what medications or tests need to be run on me, all the while I was lying there in pain waiting for care. Standardization of basic medical protocols needs to happen. Even better, a shared database of all the different medical protocols and AI can run through to find the right match or machine learning like autocorrect and predictive typing on your phone.
Too much data
Today’s doctor and healthcare providers receive copious amounts of data, whether that’s from your daily activity data, your daily measurements, data from scans, DNA testing data, etc., that they must go through in order to properly diagnose a patient. Sometimes there’s too much data for the doctors to consider and so they cut bait with some of it to rank all the clutter. On top of all that data they are looking into a system to find how that data correlates with your back pain, sleep issues and whatever another symptom you are looking at then finding the proper medication for you. All of this takes time away from the doctor to properly develop a relationship with the patient and better diagnose patients problems. Let’s dive into how machine learning and AI’s can help with this.