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AI allows standardization for commodity supplies, enabling a more in-depth analysis of large volumes of data comparing the cost and effectiveness of different products.
FREMONT, CA: Artificial Intelligence (AI) has the potential to alter the healthcare industry in numerous ways. Far from having computers make decisions about treatment or diagnosis options, much advancement on the horizon deal with the more mundane aspects of managing healthcare professionals and facilities that affect one of the biggest hurdles in contemporary medicine—cost control.
It is not startling that most hospitals are behind the curve when it comes to gathering, storing, and examining data. Privacy laws and a sensible priority for diagnosis and care above data quality mean that most hospitals do not track the costs of items used in the operating room. Additionally, it also implies that they still use excel spreadsheets and other basic tools to manage their supply chain.
Implementing enterprise solutions is the key to permit hospitals and other healthcare facilities to leverage machine learning to regulate supplies with support from data on treatment outcomes, rather than relying on the unreliable perception or personal preference of surgeons that represent over half of the supply costs for an average hospital. AI also allows standardization for commodity supplies, enabling a more in-depth analysis of large volumes of data comparing the cost and effectiveness of different products. Moreover, AI can generate more detailed supply forecasts by merging several statistical procedures and refining algorithms over time, leading to a few rush orders when stocks run out and expirations when more than expected are purchased.
Cost of Care
Knowing the total cost of care for both individuals is vital for helping hospitals learn where cost-savings can be achieved without affecting patient outcomes. Closely related to understanding the flow of product supplies around a facility, the use of QR codes, barcodes, and advanced scanning tools that make tracking chief data points as seamless as possible will be essential for monitoring the cost of care.
Furthermore, AI will be used to create and update standards in near real-time. It allows human doctors to employ strategies like outpatient care or to opt to evade additional expensive tests if they have not been shown to enhance outcomes, particularly in cases where other factors have already pushed costs close to the benchmark.