Jan. 22, 2020
By 2030, AI will access multiple sources of data to reveal patterns in disease and aid treatment and care, according to a piece by Carla Kriwet, CEO, Connected Care and Health Informatics, Royal Philips, which was posted to the World Economic Forum web site. In addition, health-care systems will be able to predict an individual’s risk of certain diseases and suggest preventative measures. AI also is expected to help reduce waiting times for patients and improve efficiency in hospitals and health systems.
AI-Powered Predictive Care
AI and predictive analytics help us to understand more about the different factors in our lives that influence our health, not just when we might get the flu or what medical conditions we’ve inherited, but things relating to where we are born, what we eat, where we work, what our local air pollution levels are or whether we have access to safe housing and a stable income. These are some of the factors that the World Health Organization calls “the social determinants of health” (SDOH).
Other Articles to Explore
Networked Hospitals, Connected Care
Alongside predictive care comes another breakthrough related to where that care takes place. In 2030, a hospital is no longer one big building that covers a broad range of diseases; instead, it focuses care on the acutely ill and highly complex procedures, while less urgent cases are monitored and treated via smaller hubs and spokes, such as retail clinics, same-day surgery centers, specialist treatment clinics and even people’s homes.
Better Patient & Staff Experiences
Research has long shown that patient and staff experiences can have a direct effect on whether they get better or not. For clinicians, better work experiences became increasingly urgent – a decade ago they started suffering from huge rates of burnout, mainly caused by the stress of trying to help too many patients with too few resources.
In 2030, AI-powered predictive health-care networks are helping to reduce wait times, improve staff workflows and take on the ever-growing administrative burden. The more that AI is used in clinical practice, the more clinicians are growing to trust it to augment their skills in areas such as surgery and diagnosis.
