How AI is streamlining physician workflows

How AI is streamlining physician workflows
© iStock/metamorworks

In this article, Rahul Varshneya co-founder of software development firm, Arkenea, discusses how Artificial Intelligence is streamlining physicians’ workflows like no other technology.

Most of us imagine robots doing our jobs the moment we hear the term “Artificial Intelligence” (AI). And, since AI-driven systems are programmed in a way that enables them to make decisions based on very little human intervention, some people often ponder if machines will soon make the difficult decisions that we humans otherwise make.

This is especially true for the healthcare niche. Several industry experts believe that this technology is set to entirely transform the way in which healthcare is practised and delivered across the globe today. However, in order to decide what the future truly holds, it is important to separate fact from fiction, because AI is already here – and it is radically changing medicine.

One recent report by Accenture reveals that, when combined, key clinical health AI applications can potentially create $150bn in annual savings for the US healthcare economy by 2026.

In this piece, we will be looking at three ways in which AI is streamlining physicians’ workflows and care delivery like no other healthcare technology.

Enabling more accurate diagnoses earlier in the disease cycle

The best part about leveraging the potential of AI in healthcare is that it can be used to enhance various processes: right from gathering and processing valuable patient data to predicting and preventing diseases even before they start showing first signs.

Some of the ways it is already doing this include:

  • IBM Watson is a reliable AI system to diagnose cancer through a double-blinded validation study.
  • Google’s DeepMind Health can combine machine learning with neural science to build an algorithm with a neural network that can detect medical conditions faster.
  • AI in healthcare can help restore the control of movement in patients with quadriplegia through spinal motor neurons to regulate upper-limb prostheses.
  • AI systems are also helping physicians diagnose heart disease through cardiac image and create a remedy through automated editable ventricle segmentations.

The capability of AI-powered deep learning technologies to analyse images and recognise identical patterns that often lead to diseases at a later time opens up the possibility for developing algorithms that help doctors diagnose specific diseases in a faster and more accurate manner.

Furthermore, such algorithms can continually learn and update their knowledge base by themselves, thus augmenting their resulting quality of coming up with an accurate diagnosis.

AI-driven software can be programmed to precisely pinpoint signs of a certain disease in medical images such as x-rays, MRIs, and CT scans.

Existing solutions that have been working on similar lines are already using AI for cancer diagnosis by processing photos of skin lesions. Using such tools, doctors are rapidly diagnosing patients accurately and also prescribing the most suitable treatments for their conditions.

Boosting patient engagement for ameliorated outcomes

Artificial intelligence is fast becoming a fundamental part of the patient care continuum.

Not only is this technology instrumental in ameliorating physician workflows and considerably mitigating burnout, but modern-day patients are also placing more trust in letting providers integrate AI within their care plan.

Patients like the time and cost savings, availability, and personalised insights that come alongside the implementation of AI. According to a recent survey by Accenture, 47% of respondents were willing to rely on artificial intelligence when availing healthcare services.

This divulges a shift toward a more data-driven and personalised approach to patient engagement.

Some of the ways AI is helping physicians boost patient engagement include:

  • Use of AI and machine learning algorithms is helping healthcare organisations mine through the massive heaps of data available today to obtain actionable insights. By taking advantage of data-driven decision making, physicians can make more intelligent decisions that are aimed at boosting the overall levels of patient engagement while simultaneously improving outcomes.
  • AI-powered chatbots help in solving the patient’s accessibility challenges and play a crucial role in driving a seamless and satisfactory patient experience.
  • Use of AI and analytics to process the clinical data at hand accelerates care delivery and allows for interventions at an early stage, resulting in better outcomes and higher engagement.
  • By integrating AI into your practice management strategy, the areas of bottlenecks which also lower patient satisfaction levels can be identified and rectified.
  • Use of natural language processing (NLP), a subset of AI that recognises speech and text can be used for converting unstructured data in the form of physician notes or voice memos and converting it into structured data within the electronic health record systems (EHR). This frees up the physician’s time spent in doing manual data entry which can be more constructively utilized interacting with patients instead.

Furnishing quality data for improving the decision-making process

Deciding upon the method of diagnostics and selecting the right treatment plans have always been tricky processes.

The reason behind this is often that physicians have to simultaneously consider symptoms of a patient, all the existing treatment methods, possible research mistakes, potential side effects, diseases with very similar signs, and many more aspects while treating them.

Modern solutions based on AI technology are already helping doctors in processing vast amounts of health data fast, overcoming research obstacles, and ensuring the complete understanding of a patient’s health. Even when the disease is detected and classified, the treatment process can cause supplemental issues. A treatment plan does not simply include prescribing medicines and suggesting exercises, but also help patients manage their treatment programmes, co-ordinate care plans, and consider the peril of an adverse event occurring.

Modern AI algorithms already help doctors arrange a comprehensive approach to disease management. Moreover, they are often used to improve surgical robots that execute highly complex operations.

Apart from the ones mentioned above, AI and its related technologies have a lot of other applications in healthcare. It is important that physicians understand that this technology is here to help them and not replace them. They need to constantly be on the lookout for ways to improve their workflows by leveraging state-of-the-art technological innovations, not the other way around.

After all, an ideal future is one where technology and humans walk hand-in-hand to explore all possible scenarios that lead to a promising future and work towards making those possibilities a reality.

Rahul Varshneya
Guest author

Subscribe to our newsletter


Please enter your comment!
Please enter your name here