Using AI to Optimize the Health Care Service Chain
The rise of AI technology has also opened the doors to many promises to change, revolutionize, accelerate the development of, and digitize many industries across the board.
According to Grand View Research, the global artificial intelligence market size was valued at $39.9 billion in 2019. Moreover, the speed of growth is not going to reduce in the next few years; the market is expected to grow at a compound annual growth rate (CAGR) of 42.2% from 2020 to 2027.
Medicine, among all industries, has been the most optimistic about the major changes that AI applications will bring about in the nearest future. Artificial intelligence in the medicine market was valued at $4490.3 million in 2020 and is expected to reach $34882.58 million by 2026 and grow at a CAGR of 39.8% over the forecast period (2021–2026). More so, a survey by Optum has found that most executives in medicine personally anticipate a much faster return on investment in AI technology than originally expected.
When it comes to the exact contributions that AI promises, a lot of the projections have been centered around therapy and healthcare professional support in various treatment and diagnostics processes. The majority of hopes associated with AI applications focus on improving the speed and correctness of diagnoses, acceleration of drug testing and development, and ways that medical professionals can leverage the technology in day-to-day patient work.
What truly deserves more conversation and discussions is also the role that AI can play in optimizing the supply chain in healthcare — an essential building block in ensuring that the promises AI brings to the healthcare industry become reality in the first place. The supply chain is, indeed, the “behind the scenes” to drug development, diagnosis, and treatments, so tackling supply chain optimization first is how it will become possible to discover the true scope of how AI can transform healthcare in the future.
Especially in the context of the COVID-19 pandemic, the inefficiencies in the supply chain backing national and international healthcare have come to the surface and can no longer be ignored. What are some realistic applications of AI capabilities that can spur the optimization of supply chains in healthcare? Let’s take a look at a few of them.
Automating tasks and processes
One of the most appealing aspects of artificial intelligence is its ability to learn to perform mundane, low-involvement tasks at a much higher speed than humans. With the technology’s ability to recognize and reproduce patterns in behavior, AI gradually takes on the administrative, repetitive tasks that usually take up a lot of time from professionals and allows them to focus on more vital, high-stakes tasks, while AI speeds up the overall process immensely.
With the help of AI-powered robots, it’s possible to relay repetitive, time-consuming tasks to the machine, while healthcare personnel focuses on human-judgment-driven and expertise-requiring work. Anything from paperwork, such as claims and contracts, to price monitoring, can be turned over to AI.
Smoothing out operations
Using AI to analyze and establish the best transportation and distribution routes is another application that can allow creating an agile framework for delivering products and professionals to locations where primary care is needed. While AI has already been used to devise the most optimal routes to deliver patients to hospitals, a similar concept for AI application can be leveraged to develop more optimal ways to distribute treatments to other healthcare centers, retail units, and even patient homes. This doesn’t just allow to streamline operations internally and externally in healthcare facilities, but it also allows to increase the speed and maximize efficiency in the process.
Matching patients with the best products
Very often, patients go through multiple cycles of various treatments to finally land specific products that work best for them. But here is where AI comes in: with access to data about product properties and performance in clinical trials, as well as detailed patient information and history, artificial intelligence can perform in-depth matching of patient profiles with the best solutions uniquely suited to their individual conditions. This will help significantly decrease treatment time periods for patients, improve treatment efficacy and better repurpose treatments in order to achieve better results and distribute products to the right locations — exactly where they are needed the most.
While AI’s predictive capabilities have been noted and highly regarded in the area of genomics and drug testing, there is another opportunity here that can prove these advancements useful for the overall supply chain processes. If predictive analytics made it possible to foresee larger groups of patients to show certain medical and healthcare needs, it would be possible to optimize the supply chain in such a way as to deliver the necessary products and services to the locations where they would be needed the most, at the right time. Being able to predict and foresee patient populations in large numbers could prove to be immensely beneficial in guiding manufacturers and distributors in the most efficient way possible.
The last — but not least — important advantage to supply chain optimization is the agility to face any major interruptions that have historically caused disruptions in both national and international healthcare processes. The COVID-19 pandemic has proven how susceptible the chain of medical supplies has been to date; it has also uncovered a need for a more advanced, AI-powered chain that will be ready to withstand the weight of such major challenges and global crises. Relying on AI to optimize inventory and supply will be a crucial change that the healthcare industry needs to undergo to achieve resilience and flexibility moving into a more digitized future.