How AI Is Transforming Healthcare Supply Chains Through Smarter Data and Automation

How AI Is Changing Everything: Supply Chain in Healthcare

Healthcare companies are increasingly applying AI to streamline backend processes like contract review and management. While AI's clinical applications have been the primary focus until now, there's a growing shift toward using AI to improve operational efficiency.

Traditionally, healthcare, pharmaceutical, and medical technology firms invested heavily in AI for clinical purposes such as diagnosing breast cancer, identifying candidates for clinical trials, or speeding up drug and device evaluations. Now, medical centers are turning to AI to accelerate administrative tasks like contract generation, review, and management.

Preparing Data for Effective AI Analysis

Successful AI implementation depends heavily on how well data is prepared and structured. David Gould, chief customer officer at EncompaaS, highlights that any AI tool, including large language models (LLMs) or chatbots, requires uniform, structured data to function properly.

Structured data includes clearly classified information such as patient IDs, diagnostic codes, or supply prices already stored in healthcare databases. Unstructured data, like PDFs of vendor contracts, must be organized so AI algorithms can accurately extract relevant details.

Because contracts vary widely in format, AI must be trained to identify specific elements—like tables or clauses—within these documents. Without this, AI can only recognize a document as a whole, not its context or content type. This mismatch leads to ineffective searches and costly processing errors.

Preparing data also involves correcting historical records that may have been mislabeled or incompletely tagged. Ensuring proper metadata and compliance with privacy regulations such as HIPAA is critical before feeding data into AI systems.

Impact on Healthcare Personnel

Automating repetitive manual tasks offers significant benefits, especially for procurement and compliance teams. Matt Parker and Jacob Thompson from SpendMend emphasize that many healthcare professionals tasked with these duties are highly skilled yet spend hours on tedious data entry and contract management.

AI can drastically reduce this workload, freeing staff to focus on higher-value tasks. However, adopting AI often changes job roles. Jeremy Strong, vice president of supply chain at Rush University Medical Center, advises that organizations prepare for this by investing in employee retraining and upskilling.

Employees who learn to ask precise, targeted questions improve AI's ability to deliver accurate responses. For example, instead of manually sifting through thousands of contracts to identify those expiring within 30 days, an employee can quickly query the AI to retrieve this information—a process that used to take weeks.

Moving Forward

• Structure and classify data carefully to maximize AI effectiveness.
• Invest in ongoing employee training to adapt to new AI-driven workflows.
• Maintain strict compliance with privacy standards when handling sensitive healthcare data.

For healthcare managers looking to deepen their AI skills and guide their teams through this transition, exploring targeted AI training courses can be a practical step. Resources like Complete AI Training's healthcare-focused AI courses offer practical guidance tailored to supply chain and operational roles.