Healthcare systems around the world are under extreme pressure as a result of staffing shortages, low retention rates and clinician burnout. In the U.S., due to higher turnover rate of nurses, hospitals have employed traveling nurses. On average, hospitals would save $3,084,000 per year by eliminating the need for traveling nurses, according to NSI. In England, meanwhile, staff shortages in the NHS are forecast to rise to 570,000 by 2036 on current trends. Given these pressures, it is understandable that healthcare professionals are now turning to generative AI for help.

Adoption of AI in healthcare is on the rise

Generative AI is a subset of artificial intelligence that learns from large volumes of data to create new content, such as text and images. Research from Avanade, a global professional services company focused on Microsoft, found that 90% of healthcare professionals believe that the impact of AI on people-focused processes and roles will make them more efficient.

Healthcare professionals are already looking to adopt generative AI in surprising numbers. According to Accenture, more than 50% of healthcare organisations plan to run ChatGPT-based pilots this year alone. Use cases in the healthcare sector centre on freeing up time for clinicians so they can spend more quality time with patients. These include capturing clinical encounters and summarising interactions such as past medical histories and health recommendations, providing patients with tailored educational materials and follow-up care recommendations, and reducing wait times by identifying patients most in need of care and targeting them with personalised coaching.

Prioritising and measuring is key

Generative AI represents a welcome shot in the arm for a sector in desperate need of efficiency and productivity gains. In the short term, healthcare CIOs need to focus on prioritising their use cases and ensuring they have a robust measuring framework in place to assess the results of trial deployment. As Don Scheibenreif, distinguished VP analyst at Gartner, put it during a recent symposium: “The era of AI-powered business will lead to unintended consequences without advance planning. CIOs need a way to light the way forward, even when everything seems new or murky.”

Experimentation with and deployment of generative AI needs to be thought of as a learning experience. With thoughtful selection of initial use cases as well as considerations around governance and how current and future processes may affect staff and patients alike, CIOs can forecast the likely impact of an AI application and gain buy-in from organisational leaders, “Meanwhile, by measuring the outcomes of early implementations, CIOs and their teams can learn what works best for their organisation, focus on the patient and provider, demonstrate value,  and build momentum for continued adoption” according to Erik Barnett, Advisory Lead at Avanade.    

Partnering for success

This is not, of course, a process that CIOs need to undertake alone. Partners like Avanade bring to bear deep capabilities and expertise to help healthcare organisations prioritise, customise, and optimise their AI trials. In the case of Avanade, this includes helping understand relevant use cases relating to Microsoft Copilot, a tool that integrates generative AI with Microsoft 365 to help professionals work faster and smarter. Working with a technology partner like Avanade can help CIOs accelerate their AI programmes and maximise the chance of success.

Generative AI will be a game changer for healthcare, freeing staff of time-consuming tasks and improving the service provided for patients. CIOs will play a crucial role in this development by ensuring the rapid and effective delivery of applications that will make the biggest impact soonest.

Avanade is a proud sponsor at HIMSS24 and will be exploring approaches for choosing initial use cases and modeling the costs and benefits that GenAI can deliver. Click here to register.

Learn more about Microsoft Copilot for healthcare here