Editorials by Jorie

Enhancing Hospital Efficiency With AI Technology

Updated: Nov 10, 2022

Technology has changed the face of healthcare in many ways. Improvements in the industry over the last decade have been a direct result of technological innovation. As technology continues to get smarter, faster, and more reliable, it seems like the possibilities are endless. The world around us is changing rapidly, and with our aging populations and public health crises, enormous pressures are on provider workloads, which impact patient safety risks and patient experiences.

Healthcare providers must deliver higher quality care, improve patient outcomes, reduce costs, and become more efficient while applying the latest developments in drug therapy. Artificial intelligence (AI) and machine learning (ML) are likely to have a tremendous impact on the future of the healthcare industry for patients, physicians, and medical researchers.

The incredible ways of AI

Healthcare environments have enormous datasets to be leveraged. Intelligent integration of AI and machine-learning methods into workflows will improve healthcare delivery of all stakeholders. One of the primary questions being asked about AI and ML today is seemingly the most basic: how can these technologies be most effectively used? What do I as a physician or healthcare organization get from applying AI in my practice or hospital? What are the critical use cases?

Artificial intelligence can act as a prescreening tool for doctors, providing them with key pieces of background information on the patient before they are seen. This technology can also provide augmentation, acting as a second opinion on treatment and diagnosis.

Neural Networks using AI Computer Vision

“Computer vision imaging is an early harbinger,” said Adam Culbertson, innovator in residence at the Healthcare Information and Management Systems Society. Even in radiology and other diagnostic imaging fields, artificial intelligence is not in wide use yet. Of those surveyed by Reaction Data, just 14% said they had been using machine learning for a while, and 27% (the largest portion) said they were one or two years away from adopting the technology.

As the healthcare industry faces an ever-increasing amount of work, it is turning to artificial intelligence to automate back-office processes and make them more efficient. Neural networks, a more complex form of machine learning, have been used in healthcare research since the 1960s and have been used for categorization applications like determining whether a patient will acquire a particular disease. They view problems in terms of inputs, outputs and weights of variables or ‘features’ that associate inputs with outputs. The analogy to the brain's function is relatively weak.

In conclusion

The advancements in artificial intelligence (AI) and machine learning (ML) within the healthcare industry are just beginning. As these technologies continue to grow and improve, the insights and capabilities they will provide to healthcare professionals and patients will be truly transformational.

Artificial intelligence can either automate or augment the work of clinicians and staff. Many repetitive tasks will be fully automated, and AI will help health professionals perform better at their jobs and improve outcomes for patients. The use of artificial intelligence in healthcare provides numerous benefits, including automating tasks and analyzing big patient data sets to deliver better healthcare faster, and at a lower cost. According to Insider Intelligence, 30% of healthcare costs are associated with administrative tasks.

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