Artificial intelligence (AI) and machine learning are becoming more prevalent in healthcare, driving the industry’s evolution in the process.
In fact, recent reports indicate that spending on AI in medicine is projected to grow at an annualized rate of 48% between 2017 and 2023.
And the potential of artificial intelligence is poised to have a huge impact on healthcare. For instance, machine learning can provide data-driven clinical decision support (CDS) to physicians and hospital staff, which would result in increased revenue potential. In that same token, a subset of AI designed to identify patterns called deep learning uses algorithms and data to give automated insights to healthcare providers.
How are today’s providers already leveraging AI to streamline operations, provide better patient care, and more? Read on for the answer.
How AI Helps Healthcare
The healthcare ecosystem stands to benefit from AI in a multitude of ways, such as automating tasks and analyzing big patient data sets to deliver better healthcare faster and at a lower cost.
The following are a few ways that AI delivers significant benefits to the healthcare field:
- Currently, administrative tasks make up 30 percent of healthcare costs. When AI is leveraged to automate tasks like pre-authorizing insurance, following up on unpaid bills, and maintaining records, healthcare professionals are free to focus on more complex duties and save money in the process.
- AI can analyze big data sets, quickly pulling together patient insights and performing predictive analysis, which helps the healthcare provider identify key areas of patient care that require improvement.
- Wearable healthcare technology also uses AI to better serve patients by analyzing data points to alert users and their healthcare professionals on potential health issues and risks. Being able to assess one’s own health through technology both empowers the patient and eases the workload of professionals by preventing unnecessary hospital visits or remissions.
Which technologies make up AI? Read our definitive guide for insights!
7 Ways AI Is Being Used In Healthcare
As AI becomes more sophisticated, it only follows that its various applications will be more efficient, advanced, and provide cost savings. And when it comes to healthcare, AI is already being used in a number of ways.
Let’s take a look at a few of them:
1. Early Detection – you might be surprised to learn that AI is already being used to detect diseases like cancer more accurately and in their early stages. And this application is both saving lives and preventing false diagnoses. For instance, according to the American Cancer Society, a high proportion of mammograms yield false results, which results in an astounding 1 in 2 healthy women being told they have breast cancer.
Now, AI is enabling review and translation of mammograms 30 times faster with 99 percent accuracy, reducing the need for unnecessary biopsies and the spread of misinformation. Further, the aforementioned consumer wearable healthcare technology and other medical devices that are supported by AI are being used to monitor early-stage heart disease, allowing doctors to better oversee and detect potentially life-threatening episodes at earlier, more treatable stages.
2. Diagnosis – Cognitive technology is being used by healthcare systems to review and store more medical information faster than any human can. Further, general-purpose learning algorithms are being built into neural networks that mimic the human brain and can help clinicians and researchers solve real-world healthcare problems.
3. Decision-Making – Improved care results from aligning big health data with real-time decisions, with predictive analytics providing clinical decisions support and actions while prioritizing administrative tasks. Specifically, leveraging pattern recognition to identify patients at risk of developing a condition due to lifestyle, genetics, or other factors, is another area where AI is being increasingly used.
4. Treatment – AI-powered technology is also able to help clinicians have a more comprehensive approach for disease management, better coordinate care plans, and help patients better manage and comply with long-term treatment programs.
Further, robots have been used in medicine for more than 30 years, and range from commonplace laboratory robots to highly complex surgical robots that can either aid a human surgeon or perform operations unassisted. A part from surgery, robots are used in hospitals and labs for repetitive tasks, in rehabilitation, physical therapy, and to support those with long-term conditions.
5. End-of-Life Care – As people’s life expectancies continue to increase, robots are being tapped to potentially provide revolutionary end-of-life care by helping people remain independent, which would reduce the need for hospitalization and care homes. Further – perhaps in the distant, distant future – AI combined with advancements in humanoid design are enabling robots to have ‘conversations’ and other social interactions with elderly people to provide companionship.
6. Research – According to the California Biomedical Research Association, it takes an average of 12 years for a drug to travel from the research lab to the patient. Only five in 5,000 of the drugs that begin preclinical testing ever make it to human testing and just one of these five is ever approved for human usage.
Furthermore, on average, it will cost a company $359 million to develop a new drug from the research lab to the patient. AI, on the other hand, can be used to streamline drug discovery and drug repurposing processes, which could cut costs and the time to market for new drugs.
7. Training – With AI, trainees can undergo naturalistic simulations in ways that are not enabled by simple, computer-driven algorithms. With natural language processing and the ability to draw instantly from a large database of scenarios, AI computers can challenge the trainee with new questions, decisions, and bits of advice.
Further, the training program can learn from previous responses and adjust challenges to continually meet their needs. Finally, training can be done from anywhere, including on a smartphone or while travelling.
SAI for Healthcare
Our experience in healthcare began in 2000 when our healthcare industry business unit was created to help companies in healthcare take advantage of game-changing technological opportunities.
Since its inception, our team has constantly evolved in response to the complex and ever-changing needs of healthcare. Further, our SAI suite – Stefanini Artificial Intelligence – draws from technologies like intelligent automation, machine learning, and natural language processing to create customized AI solutions for our clients.
One of those solutions is Sophie, a virtual assistant that understands natural language, learns, and generates answers. Supported by powerful problem-solving algorithms, Sophie turns data into insight, has reasoning capability, and can hold natural conversations. Further, it is accessible 24/7, resulting in an improved patient experience.
The secret to successful digital transformation? Find partners who are experts not just in AI, but in life sciences and healthcare. At Stefanini, we know how to find the balance between technology and valuable human input. The field of health will always need human connections; we know how AI solutions and virtual assistants like Sophie can fill in gaps.
Contact us today to see how we can work together to co-create the right AI solution for your organization!
