How AI in healthcare supply chain management (SCM) can cut costs Alex Behrens - September 9, 2019 6:00 AM |Categories: Cost Management, Healthcare Supply Chain Management, Technology | Tags: General News Artificial intelligence has the potential to transform the healthcare industry in monumental ways. Far from having computers make decisions about diagnosis or treatment options, however, many advancements on the horizon deal with the more mundane aspects of managing healthcare facilities and professionals that impact one of the biggest challenges in modern medicine — cost control.Syft, a provider of healthcare-focused solutions that changed its name this year from Management Health Solutions, researched the potential benefits of modernizing healthcare supply chain management (SCM) in its recent report, “The Next Link in the Chain,” focusing on how hospitals can pursue the cost-savings associated with optimizing their supply chains through standardization, enhanced forecasting and more robust data capture. Citing a 2018 Navigant Consulting report, hospitals who implement these changes can expect to save 17.7% on supply expenses, or $11 million each year on average.Enterprise SolutionsIt’s not surprising that many hospitals are behind the curve when it comes to collecting, storing and analyzing data. Privacy laws and a sensible priority for treatment and care above data quality mean that many hospitals don’t track the costs of items that are used in the operating room and still use ad hoc Excel spreadsheets and other basic tools to try to manage their supply chain.According to the Syft report, implementing enterprise solutions is the key to allowing hospitals and other healthcare facilities to leverage machine learning to standardize supplies with support from data on treatment outcomes, rather than relying on the anecdotal perception or personal preference of surgeons that represent over half of the supply costs for an average hospital.Artificial intelligence also allows standardization for commodity supplies, enabling deeper analysis of large volumes of data comparing cost and effectiveness of different products. AI can also produce more accurate supply forecasts by combining a number of statistical techniques and refining algorithms over time, leading to fewer rush orders when supplies run out and expirations when more than required are purchased.Cost of CareUnderstanding the total cost of care for both individuals and in the aggregate is vital for helping hospitals understand where cost-savings can be achieved without impacting patient outcomes.Closely related to understanding the flow of commodity supplies around a facility, the use of barcodes, QR codes and advanced scanning tools that make tracking important data points as seamless as possible will be required for tracking cost of care. Syft reports AI will be used to create and update benchmarks in near real-time, allowing human doctors to implement strategies like outpatient care or opting to avoid additional expensive tests if they haven’t been shown to improve outcomes, especially in cases where other factors have already pushed costs close to the benchmark.Providing data to back up doctors who recommend against additional tests or treatment in circumstances where outcomes are not improved can provide huge cost-savings aggregated across millions of annual cases.Additionally, arguments against “just-in-case” testing and treatment often requested by patients or relatives because third-party insurance will cover the cost will ultimately help bring costs for those procedures closer to equilibrium. This imbalance — how providers are able to raise prices well beyond what would otherwise be charged in circumstances where the payer is different than the receiver of services — is called the “third-party payer problem.” The Syft report says the changing nature of healthcare costs require organizations to consider AI and machine learning.“As supply chain costs overtake staffing costs and as value-based care gains traction, managing the supply chain while enhancing quality changes from nice-to-have to a necessity. An enterprise-wide SCM solution using ML can provide the advanced monitoring and predictive SCM capabilities necessary to create a winning strategy,” the report states.“Progressive organizations understand that an effective supply chain will improve efficiency, reduce costs, decrease variation and waste. Using AI-enhanced SCM will allow hospitals to achieve these goals by improving their ability to accurately monitor, forecast and review supply utilization.” Related ArticlesAfternoon Coffee: U.S. to urge Japan, South Korea to end trade spat; Healthcare supply chain inefficiencies cut into profitHealthcare Supply Chain Has Its Own Needs, Challenges: An Insider’s ViewSustainability and Supplier Data: EcoVadis, Healthcare Firms Share Information for 'Responsible Health Initiative'At HIMSS, Healthcare Technology Focuses on Telemedicine, Payment Platforms, Cybersecurity for Medical DevicesA 2019 Wish: U.S. Healthcare Supply Chain Leadership Will Learn to ‘Just Say No’ Share on Procurious Discuss this: Cancel replyYour email address will not be published. Required fields are marked *CommentName * Email * Website Notify me of follow-up comments by email. Notify me of new posts by email. This site uses Akismet to reduce spam. Learn how your comment data is processed.