AI’s capacity to transform healthcare in its digital odyssey
From cloud integration to AI innovations, new technologies have the capacity to transform healthcare operations to address vexing challenges.
The pandemic accelerated the healthcare industry’s adoption of more modern digital technologies. One of the most notable changes was the shift toward remote patient care, made possible by the increasing adoption of cloud-based solutions. As cloud-based solutions become more prevalent in healthcare, they will continue transforming healthcare providers’ clinical, financial, personnel and supply chain operations.
A recent survey of hospital and health system leaders revealed that 45 percent of respondents have already implemented cloud-based supply chain management technologies, while 24 percent plan to adopt these technologies within the next two years. By 2026, 70 percent of responding hospitals say they are likely to have a cloud-based approach to supply chain management, setting the stage for the industry’s digital transformation.
An intelligent predictive path
The migration to the cloud has paved the way for implementing machine learning (ML), artificial intelligence (AI) and generative AI by establishing centralized unified data repositories. These repositories are needed to train algorithms and bring intelligence to day-to-day workflows.
By harnessing the power of AI-driven technologies, healthcare providers can analyze vast volumes of data and gain valuable insights. This can help improve patient outcomes while reducing the associated costs of care. In addition, AI can automate repetitive and mundane tasks when properly implemented, allowing healthcare professionals to focus on more valuable work.
We’ve already seen significant innovations in patient care. For example, AI models have become sophisticated enough to provide a preliminary diagnosis for imaging and lab screenings, but human expertise remains an integral part of the process. What’s exciting is that ML, AI and generative AI models are poised to transform healthcare operations as well.
Supply chain leaders are shifting their focus from transactional processes to strategic planning and decision-making. AI has the potential to transform and bring resilience and transparency to the sometimes fragile healthcare supply chain, helping to ensure the availability of critical healthcare products and services.
For instance, AI models can be used to create a more adaptive, resilient supply chain by more accurately predicting the impact of natural disasters or geopolitical events on the global supply chain, enabling providers to proactively mitigate potential product shortages. Other areas in the healthcare supply chain where ML and AI are expected to have a transformation impact include the following.
Improved demand planning and forecasting. AI can be used to analyze inventory utilization data, both historical and current, to predict the demand for various medical supplies and equipment more accurately. With the help of AI, supply expenses can be reduced by 22.6 percent. Additionally, it helps ensure the right product arrives at the right time for the right procedure, further improving clinical outcomes.
Intelligent inventory. In the ever-evolving healthcare landscape, the integration of optimized, intelligent inventory management systems has emerged as a transformative solution. The influx of vast amounts of data within the supply chain provides a wealth of structured and unstructured data, offering fertile ground for training artificial intelligence (AI) models. This paradigm shift enables healthcare organizations to fine-tune their inventory management processes, fostering a more proactive approach to predicting supply shortages or expirations based on factors like seasonal patterns and low stock levels and reducing the tendency to hoard or carry excess inventory. With AI models equipped with the right data sets, healthcare organizations can adopt a more efficient, cost-effective and waste-reducing inventory management strategy.
Supplier relationship management. The impact of intelligent inventory management extends beyond the walls of healthcare institutions, influencing the dynamics of provider-supplier relationships. Leveraging AI-powered tools and techniques enables providers to delve into predictive analytics, offering insights into supplier behavior and the ability to foresee potential risks or opportunities. Armed with this knowledge, healthcare providers can make more informed decisions regarding supply management, thereby nurturing and fortifying long-term relationships with suppliers.
Anticipating supply disruptions through AI strengthens provider-supplier collaborations and empowers healthcare institutions to proactively seek clinically suitable substitutes or alternative solutions in the face of challenges. This forward-thinking approach helps ensure patients receive uninterrupted, high-quality care, even amid unforeseen supply chain disruptions.
Carbon footprint optimization. By analyzing data related to transportation routes, packaging materials and supplier locations, AI models can provide insight into the environmental impact of procurement and transportation decisions and suggest more environmentally friendly alternatives. This aligns with sustainability goals and can lead to cost savings, which is a win-win for healthcare providers, patients, and the environment.
A word to the wise
There’s been a lot of conversation about AI's potential “dangers” in healthcare, and we would be wise to contemplate those concerns.
Not only must we consider what the responsible use of AI and its applications looks like for our industry, but we must also be cautious of AI's potential to produce erroneous results, especially when in comes to generative AI. Until these innovations genuinely mature, we must ensure that humans remain a part of the decision-making process, incorporating intuition and judgment into the workflow and model.
In addition, we need to integrate responsible and ethical AI best practices into the algorithms themselves, including being mindful of unconscious bias. The data that feeds these models must be diverse, accurate and ethical.
Healthcare is on the cusp of a significant digital transformation as it embraces the latest technologies, such as cloud-based systems, digital tools, machine learning and AI models. While a great deal of complexity is involved in this journey, the benefits will enable the industry to reduce waste and spending while improving outcomes for all stakeholders.
Archie Mayani is chief product officer at GHX; she drives the design and development of a contemporary, intelligent and resilient healthcare supply chain management platform and solutions with a dedicated product development team.