Engineers Are Applying AI in the Healthcare Industry: Here’s How
Lockdowns should’ve helped the healthcare system 'catch up,' but a lack of technological solutions and agility has prevented the industry from updating its tech stack.
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When the pandemic first started causing widespread infections and illness, governments around the world enacted drastic safety measures — lockdowns, deferral of elected surgeries, etc. — to contain the spread and, critically, to prevent healthcare systems from being overrun. The lockdowns should’ve helped the healthcare system 'catch up,' but a lack of technological solutions and agility prevented healthcare systems from using this time to update their tech stack.
AI in Healthcare
Engineers can help healthcare organizations fill those gaps, automating processes so clinicians have more time to focus on patients and creating products that help health systems deliver value-based care. Here are a few examples of how engineers are making a difference with AI in the healthcare industry:
- Engineers have already created AI-driven products that healthcare systems use to streamline tasks like billing, documentation, risk adjustment coding, and quality measurement to achieve greater efficiency. AI-assisted workflows make useful applications for clinical work like diagnostics and risk management possible, and AI can also improve patient engagement programs to better manage care and connect patients with needed assistance. Natural language processing (NLP) is being used to help doctors document care more easily, or improve customer support with chatbots. Another use of NLP is to find information about patients that just isn’t available in the structured databases of electronic medical records. Text can reveal the subjective nature of the patient’s experience and describe outcomes that are often not otherwise available or require a human to spend a lot of time finding. Extracting this information from the clinical notes can greatly enrich knowledge about patients and care paths used to treat them.
- There is simply too much data for humans in healthcare roles to consume. Engineers are addressing this with AI-assisted processes that use machine learning algorithms to mine electronic health records and charts to provide operational or clinical insights. For example, data science engineers at Apixio mine unstructured data to help doctors spot evidence of chronic conditions that human analysis might miss, leading to more personalized and targeted care. Engineers have also developed platforms capable of analyzing huge datasets to give clinicians relevant information for individualized treatment plans, using AI algorithms and NLP to find insights in unstructured text and electronic health records.
- An exciting area of research over the past 10 years has been in deep learning, which enables engineers to develop far more sophisticated neural nets (NN), and not just the NN making headlines that understand language. These networks have revolutionized computer vision, provide insights into temporal relationships and make it possible to encode knowledge that can be shared across many use cases. Applications include tasks like improving medical imaging analysis, flagging potentially harmful medication interactions, helping doctors deliver more precise care by analyzing patient health histories, and helping researchers optimize clinical trials with better patient participant selection.
- Machine vision/computer vision is at work helping clinicians more accurately analyze images like X-rays and CT scans, diagnose conditions via telemedicine and even assist with surgeries. Researchers are developing AI that can assist physicians by augmenting their own skills. It can help draw their attention to the key elements of a scan faster or serve as a backstop against errors due to the overwhelming work demands clinicians often face.
The healthcare sector is the largest employer in the U.S., and demand will keep rising for the foreseeable future, while the supply of workers lags. California alone will need an additional 500,000 new allied healthcare workers by 2024. But engineers have a role to play in meeting the need for expanded healthcare capacity too. The best hospital system in the world can’t serve its community effectively if there simply aren’t enough clinicians and ancillary staff to keep up with the demand for care.
By working on new and emerging technologies in the healthcare sector, engineers can give healthcare workers more time to deliver one-on-one patient care. Advanced technology can also ensure that the care patients receive is more personalized and effective. Engineers are applying AI to transform the healthcare sector, one innovation at a time.
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