By Stewart Whiting
A study by Human Resources for Health projects there will be a shortage of 15 million healthcare providers worldwide by 2030.
At the same time, the largest living generation — the Baby Boomers — is aging; meaning that as we anticipate an influx of patients requiring critical care, we’re dealing with a waning pool of people equipped to treat them. Today’s providers and patients are already feeling the effects of this crisis. With doctors and nurses rushing from patient to patient, overloaded with patient data, it’s a challenge to absorb critical information and make accurate, efficient diagnoses. As a result, patients do not always get the care they need when they need it.
The good news is that artificial intelligence (AI) can help. Here’s a look at how the technology can help diagnose patients, monitor their health over time and inform provider actions to ensure optimal care is delivered.
Efficiently diagnose patients
Special-Pricing Available on Medical Displays, Patient Monitors, Recorders, Printers, Media, Ultrasound Machines, and Cameras.This includes Top Brands such as SONY, BARCO, NDS, NEC, LG, EDAN, EIZO, ELO, FSN, PANASONIC, MITSUBISHI, OLYMPUS, & WIDE.
Today’s patients come into healthcare environments with a significant amount of data already attached to them. From paper and electronic health records to family histories and their vital signs at intake, healthcare providers are overloaded with information before they’ve even seen a patient.
This, of course, can be problematic. It’s difficult enough to review and draw correlations between the various threads of patient information; that challenge becomes much harder when doctors and nurses are scrambling to determine the appropriate care plan while juggling a host of other patients.
AI-backed platforms can rectify this issue. By extracting patient data from existing records and from monitors and machines they may be hooked up to during a hospital stay, AI platforms can analyze millions of data points in seconds and learn how to identify innocuous patterns and combinations of early symptoms. With this information, providers can focus only on pertinent data that can help make decisions, and in some cases highlight information that may have otherwise gone overlooked.
For example, if a patient came in displaying early symptoms that may be indicative of a number of illnesses, an AI-backed platform would have the ability to quickly analyze all of the patient’s data and understand that the patient’s family has a history of an illness that these symptoms could point to. This would then allow the provider to quickly test for that illness and come to a conclusion quickly, as opposed to weighing or testing for numerous possible options.