04/19/2024 | Press release | Distributed by Public on 04/19/2024 16:29
In healthcare, managing inventory isn't just a matter of cost savings. It's a critical component of patient care. Artificial intelligence revolutionizes how healthcare providers manage supplies, from syringes and gloves to life-saving drugs. This blog post explores the impact of AI-powered inventory management in healthcare, outlining how these new technologies can help to identify patterns and trends in medical inventory usage.
The following sections provides a high-level overview of how Oracle can help customers to digitally transform and derive greater business insights by using the following steps:
Healthcare facilities face a unique set of challenges in inventory management, including the need for a wide range of supplies, the critical nature of many products, and the fluctuating demand creates a complex environment. Moreover, traditional inventory methods often lead to overstocking, which ties up capital, or understocking, which can be detrimental to patient care. In such a scenario, the precision and efficiency offered by AI are not just beneficial, but necessary.
Inventory lifecycle: Define, count, replenish, optimize.AI in healthcare is revolutionizing the industry by using advanced algorithms and computational techniques to analyze complex medical data, improve diagnostics, personalize treatment plans, enhance operational efficiency, and ultimately, enable delivery of better patient care.
AI is enhancing periodic automatic replenishment (PAR) level medical inventory management in the following ways:
The OCI solution for inventory optimization can be achieved in 2 different ways using various A.I and Machine learning services. Please Refer to Diagrams below for 2 recommended approaches for the solution.
Oracle Machine Learning enables you to solve key enterprise business problems and accelerates the development and deployment of data science and machine learning (ML)-based solutions. Benefit from scalable, automated, and secure machine learning to meet the challenges of data exploration and preparation, as well as model building, evaluation, and deployment. Whether your interests include APIs for SQL, Python, R, or REST, or you prefer no-code user interfaces, Oracle provides support for solution development and deployment.
An example architecture diagram for a solution on OCIOCI Data Science is a fully managed platform for teams of data scientists to build, train, deploy, and manage ML models using Python and open source tools. Data Science integrates with the rest of the OCI stack, including Oracle Functions, Data Flow, Autonomous Data Warehouse, and Object Storage. Oracle Accelerated Data Science (ADS) software developer kit (SDK) is a Python library that's included as part of the Data Science service, which has many functions and objects that automate or simplify the steps in the data science workflow, including connecting to data, exploring, and visualizing data, training a model with AutoML, evaluating models, and explaining models. ADS also provides a simple interface to access the Data Science service model catalog and other OCI services, including Object Storage.
Overall, AI-driven PAR level medical inventory management systems offer healthcare facilities the ability to optimize inventory levels, improve supply chain efficiency, and enhance patient care outcomes through proactive and data-driven decision-making. AI enhances PAR level management in healthcare by optimizing inventory levels, improving supply chain efficiency, mitigating risks, and enabling proactive decision-making based on real-time data and predictive analytics.
With Oracle SaaS cloud business applications and Cerner EMR and EHR and inventory Management system like PeopleSoft as data sources, customers can extract and aggregate data to predict optimal inventory level that helps reduce costs and improve patient care outcomes.
To try any of the technologies we've mentioned, you can evaluate Oracle Cloud Infrastructure today for free with no commitment.
For more information, see the following resources: