Satyakam Mohanty


AI is getting increasingly sophisticated at doing what humans do but in faster, more efficient and cost effective way. According to CB insights study by 2020, healthcare organizations will spend an average of $54 million on artificial intelligence projects, with investments primarily geared toward improving business operations. There is no doubt that the potential AI holds for healthcare is vast.

Here are five of the advances in healthcare AI that appear to have the most potential.

Virtual Nurses

From interacting with patients to directing patients to providing the most effective care, digital or virtual nurses can provide wellness checks through voice and AI. The program uses ML to support patients, specializing in chronic illnesses. Available 24/7, these Virtual nurses can answer questions, monitor patients and provide quick answers and potentially can potentially save the healthcare industry $20 billion annually.

Medication Management

One of AI’s biggest potential benefits is to help everyone stay healthy so they don’t need a doctor, or at least not as often. AI enabled smartphone apps can monitor the use of medication by patients. They monitor if patients are taking their prescriptions and help them manage their condition.  The usage of Internet of Medical Things (IoMT) in consumer health applications is also greatly helping people live a healthier life by managing their wellness. There are smart belts now with built-in mechanisms that alert people when they overeat. Such applications and many others like these encourage healthier behaviour in individuals and help with the proactive management of a healthy lifestyle. Further, AI increases the ability of healthcare providers to better understand day-to-day patterns and needs of the people they care for, which in turn provides better feedback, guidance and support for staying healthy.

Risk prediction with Electronic Health Records

Improving care requires the alignment of big health data – the EHRs with appropriate and timely decisions. Historically, risk models were derived using data from large epidemiologic cohorts or clinical trials. But now predictive analytics can support clinical decision-making and actions as well as prioritise administrative tasks. Using pattern recognition, these advanced analytics systems can identify patients at risk of developing a condition – or seeing it deteriorate due to lifestyle, environmental, genomic, or other factors.

NLP to improve clinical documentation process

A study published in the Annals of Internal Medicine found that for every hour doctors were seeing patients, they were spending nearly two additional hours on paperwork. EHR documentation process contributes to increased physician workloads resulting in diminished quality of documents replete with irrelevant, redundant, and erroneous information and physician dissatisfaction. Ideally this isn’t the best use of physician’s training and ability. With advanced AI enabled tools like voice-to-text transcription technology, doctors can help order tests, prescribe medications and write chart notes. NLP could be helpful in improving clinical documentation, EHR use, and provider workflows.

Automate workflow and administrative tasks

Another major area that AI could play a big role in healthcare is in administrative areas. It is expected that this could result in $18 billion in savings for the healthcare industry as machines can help doctors, nurses and other providers save time on tasks. AI-powered solutions that rely on ML can help health care providers cut documentation time and improve reporting quality. Computer-assisted physician documentation (CAPD) systems offer real-time clinical documentation guidance that helps providers ensure their patients receive an accurate clinical history and consistent recommendations.

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