Healthcare is more complex than ever. The global shortage of skilled workers and operational inefficiencies, and the desire for high-quality and efficient care is more than ever before.
In addition to the task of making the huge amounts of data collected on all levels usable, IT managers in the healthcare sector are constantly under pressure to increase efficiency.
Missing information from health data
The topic of AI is not new; it has been discussed for decades.
But most healthcare facilities are still at the very beginning here, according to healthpally.
AI is increasingly gaining a foothold in this area because it allows new insights to be gained from huge amounts of data – a more than welcome support for the constantly overloaded staff.
The amount and granularity of stored digital medical and health data has grown exponentially.
But only a fraction of it is actually used to improve the efficiency and quality of patient care.
This enormous increase in quantity and diversity poses a challenge for all executives concerned, because the speed of data collection far exceeds the analytical capabilities, says chaktty.
Healthcare providers have an incredible amount of data, but they don’t get much insight from it, according to businesspally magazine.
An example: Which of the 2000 diabetics treated are the 10 who have to be called in because they need different treatment? That is exactly the information that doctors need.
AI applications in healthcare
The potential of artificial intelligence to improve healthcare is limitless.
It gives the opportunity for health workers to understand the clinical data collected and fully integrate it into the health care service delivery.
The main use of all AI-driven health solutions needs extensive connection between data scientists, interaction designers, clinicians and other health workers.
In the following, we introduce you to four applications of artificial intelligence that have the potential to fundamentally transform healthcare
- Enhance performance and efficiency
At the departmental and organizational level, the ability of AI to sift through large amounts of data can support administration in optimizing performance and productivity and help to better utilize existing resources, thus realizing time and cost savings.
In radiology, for example, AI can be used to optimize referral management, scheduling and the preparation of examinations.
- AI helps in making clinical decisions
With AI-enabled solutions, large amounts of clinical data can be merged to gain a holistic view of the patient.
This supports the entire clinic staff in their decision-making, optimizes the success of the treatment and leads to better population health.
The need for new knowledge and the support of clinical processes through these findings is enormous,” said Dr. Smythe.
Whether the precise implementation of interventions or the effective deployment of personnel: Doctors have to struggle with all these things. That is a fact. ”
- Management of population health
When systems for clinical decision support are combined with patient self-management, population health can also benefit from AI.
As the population gets older, so does the desire to age at home.
This makes better management of chronic diseases necessary, but also contributes to a better quality of life.
If the health data of millions of people are brought together, analyzed and activated, insights can be gained into how socio-economic, genetic and clinical factors as well as human behavior are correlated.
This gives health care providers the opportunity to offer targeted, preventive health care outside the walls of the hospital.
- AI helps to improve patient care
As recently as 2015, patients reported that they had to take X-rays, test results and other important health data from one practice to another.
Several referrals meant a considerable effort, the symptoms had to be described again to every new doctor, and yet there were gaps in the patient’s history.
It was all a bitter reality. Yet patients expect more personalized, intelligent, and convenient healthcare.
The big driving force behind AI in healthcare is increasingly engaged patients, who are more caring about their own concerns and better understanding their own needs.
Health care providers are called upon to respond more closely to patients and “pick them up”. The services required must be available at all times, not just in the event of an acute illness