Imagine a world where human error was been virtually eradicated from hospitals. The process of patient diagnosis and treatment is completely automated, with a certified doctor being the final gatekeeper to sign off on the recommendations wholly generated by a machine. This is the world envisioned by DeepMind, the AI division of Google that is seeing new applications in the medical field.
Human error in medicine is one of the leading causes of death in America – #3, in fact. The introduction of AI into the patient care process has the potential to drastically cut erroneous diagnoses as a result of the fact that we’re simply human beings. Regardless of how well-trained, diligent, and keen those who care for us are, how many times have you been told your nagging sore throat “is just a cold” when it eventually developed into strep throat or the flu? With the assistance of DeepMind-like AI, your medical history and physical information can be computed just as any variable would. By handing the reins of medicine to a specialized computer, small details and seemingly innocuous symptoms would be immediately flagged for further observation. This could also become crucial during moments when serious and life-threatening diseases share the same initial symptoms as more benign illnesses.
Today, patients staying for a particular duration of time may find themselves surrounded by machines such as the ones featured in the photo above. Although they may seem comprehensive and diligent in the care they’re administering, they are, in fact, simply “dumb” machines that are only showing outputs and administering minimal inputs. Nurses are the ones tasked with making routine rounds between each patient ward, during which they interpret biosigns, answer patients’ questions, and administer care in the form of medicines or treatments. In an AI-enabled health care facility, the machines would be able to actively interpret the outputs and administer care to the patient with minimal input from a caregiver. In the event of an emergency or post-op, a patient is extremely vulnerable. In such situations, milliseconds could mean the difference between life or death, time that is easily wasted for a nurse to arrive at the patient’s ward, interpret the data, and administer a solution.
I’ve included this graph to better illustrate the rate of patient deterioration and why it is such a problem in hospitals. A patient in the stages of deterioration will quickly slide towards death if proper care isn’t promptly administered. During a nurse’s rounds, and depending on the ratio of nurses to patients, a patient that is the last to be seen each round may have already entered into an irreparable state before a nurse can be in attendance. In the best case scenario, this patient may yet be saved if high-cost lifesaving techniques are used such as those found in intensive care units. With the shortage of nurses and doctors becoming an ever-increasing problem in the near-future, AI may be the answer to this critical problem that would otherwise take a generation of schooling and certifications to resolve.
What do you think? Even with the current abilities of AI, diagnosis and treatment would rarely be erroneous. But how comfortable would you feel if AI took over day-to-day caregiving in our hospitals?