AI in "Healthcare"
The fragmented nature of the healthcare supply chain costs billions in value and reduces the healthcare sector's ability to overcome the challenge it faces.
Business Challenges
Although AI plays a vital role in Healthcare, there are very few discussions about the role AI and Machine Learning in the healthcare supply chain, compared with other areas, such as improved disease diagnosis and drug development. The healthcare industry is facing many changes that pose new challenges to healthcare organizations big and small. In particular, the fast-evolving government regulations, technological innovations, and patient expectations create a new environment in which running a medical practice isn’t just about treating patients anymore.
How can AI help?
Artificial intelligence has the potential to transform the healthcare industry in monumental ways. Improving the healthcare supply chain could give people around the world access to safer and more affordable medications and devices. It can also reduce costs and create additional revenue sources for manufacturers. One of the most underestimated areas is data governance. The beauty of AI is that it can analyze large amounts of data to identify patterns and hidden correlations that would otherwise take humans considerably longer to decipher, if at all.
Use cases
Supply Standardization: Some of the provider-preferred items can be extremely costly, but standardizing them is a challenging task. Physicians lack the time and resources required to compare the associated costs and patient outcomes when assessing options in the marketplace. However, AI could provide doctors with tools that give them real-time statistics about how certain supplies perform. Such information makes a supply standardization goal more straightforward.
Inventory Level Optimization: Health systems must speedily and accurately assess the demand for inventory. Otherwise, providers may hoard supplies to avoid running out, or delays could occur while waiting for replenishments. Hospitals often use the time-series method of forecasting demand. It uses past usage trends to predict future needs. AI can improve upon traditional time-series forecasting by allowing health systems to continually update forecasts. AI also gets smarter with use.
Operating Room Throughput: Having the right supplies on hand is crucial in an operating room. Any supply-related mishaps could cause patient complications, as well as frustration for the responsible surgeons. AI will revolutionize the operating room and materials manager’s ability to plan for and deliver critical supplies at the right time and place, and at the right cost.
Procedural Throughput: The opportunities to cut costs by applying AI and machine learning to SCM don’t stop at operating room procedures. They extend to any other treatments happening within hospital operations. With the data-driven insights provided, health care facility managers can become more informed about the average supply-related expenses for particular procedures and make adjustments when necessary.
Why choose us?
The application of artificial intelligence in healthcare industry is a win-win for all— improving supply chain efficiencies, lowering operating costs, and leading to improved patient outcomes.
We at RadomeTech believe AI is crucial for every business entity. Thus we have a developed a tool which lets the user have the power of Artificial Intelligence and Machine Learning !
