Best Practices and Common Problems in Healthcare Data Management
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Kara L. Nadeau, Healthcare Industry Contributor
Tuesday, April 7, 2026
Kara L. Nadeau, Healthcare Industry Contributor
Healthcare supply chain performance increasingly depends on the quality and usability of item master data. As the system of record for products, suppliers and transactions, the item master serves as the backbone of the healthcare supply chain, enabling accurate purchasing, inventory management and financial transactions across hospitals and health systems.
Ensuring the accuracy, timeliness and completeness of this data is essential for achieving the “perfect order” and supporting efficient, high-quality patient care.
A recent article in Becker's Hospital Review highlights the criticality of the item master to supply chain performance, pointing to Community Memorial Healthcare in Ventura, Calif., where "the highest-ROI supply chain investment wasn’t a robot or warehouse automation system. It was the item master."
As healthcare organizations scale and complexity grows, managing item master data has become increasingly complex. Healthcare organizations must navigate large volumes of data, constant updates from suppliers and partners, and disconnected systems that make it difficult to maintain consistency across the supply chain.
Poor data quality and the absence of a master data management strategy can increase the administrative burden, leading to more manual corrections and operational inefficiencies. These challenges not only reduce efficiency but also limit an organization’s ability to respond proactively to disruption and cost pressure.
Healthcare data management is the systematic process of collecting, storing, securing and analyzing information in digital form. In the context of item master data, effective healthcare data management ensures that critical supply chain information is accurate and accessible, supporting broader healthcare industry goals, including exceptional patient care. Find out why effective and efficient item master data management can maximize cloud ERP system investments.
As healthcare supply chains evolve, leading organizations are moving beyond manual data management toward more connected, intelligent approaches. According to Gartner, health systems are heavily investing in "AI and automation solutions, enterprise resource planning systems (ERP), and advanced analytics and data management."
Rather than treating item master data as a static repository, they are building connected, governed data foundations that enable consistency across systems and partners. Increasingly, this foundation is enhanced with automation and AI-enabled analytics to surface risks earlier, reduce manual intervention and support more informed decision-making in real time.
This shift from manual data management to connected, intelligent data strategies is critical to improving operational efficiency, strengthening financial performance and supporting value-based care. Clean, trusted and connected item master data is no longer just a data management priority—it is a strategic capability that enables more resilient, proactive supply chain operations.
| Without Clean Data | With Clean, Connected Data |
| Manual intervention required | Automated transactions |
| Pricing discrepancies | Accurate pricing alignment |
| Delayed orders | On-time delivery |
| Limited visibility | Proactive decision-making |
| Increased administrative burden | Reduced manual work |
| Frequent manual review | Streamlined workflows |
By leveraging AI-powered automation, predictive analytics and a unified data foundation, providers can improve data quality, reduce inefficiencies and make more confident, proactive decisions. Trusted master data is essential for the healthcare industry, as it underpins care coordination and value-based care initiatives.
This article explores the importance, challenges and best practices for managing item master data in healthcare—and how a more connected data strategy can help strengthen operational, financial and clinical performance.
While every healthcare organization faces unique challenges, most encounter similar issues: inaccurate, duplicate or incomplete data—often referred to as “dirty data”—that creates errors and rework across procurement, inventory management and patient billing processes.
Data quality issues frequently arise due to fragmented data and disparate systems, where information is scattered across multiple independent sources that lack seamless integration. This fragmentation undermines data reliability, patient safety and regulatory compliance.
Incomplete information in item master data can lead to mismatched or duplicate records, increasing the risk of errors in patient care and billing.
Fragmented patient data scattered across electronic medical records, billing systems, laboratories, and third-party sources can create care gaps and costly billing errors.
Addressing organizational silos early is essential to ensure effective healthcare data management and to prevent these challenges from escalating.
| Challenge | Impact |
| Data inaccuracies | Errors in procurement and billing |
| Duplicate records | Inefficiencies and rework |
| Missing attributes | Incomplete decision-making |
| Disconnected systems | Lack of visibility |
| Data quality issues | Operational inefficiencies, compliance risks |
| Fragmented data | Care gaps, billing errors |
Provider organizations are increasingly adopting digital technologies and automation to improve item master data quality and streamline processes.
Health data management and health information management play a critical role in this effort by systematically organizing, integrating and analyzing digital health data in systems such as ERPs and EHRs, which enhances data quality, supports better patient outcomes and strengthens data security.
Electronic data interchange (EDI) has already helped shift the industry from manual processes—such as emails and phone calls—to more automated, standardized workflows. But as data complexity grows, organizations need to go further in their health data management approaches.
Improving item master data requires a combination of data standardization, automation and continuous monitoring. Building clinician trust through effective change management is also crucial for successful master data management (MDM) implementation.
| Best Practice | Outcome |
| Data standardization | Consistent information across systems |
| Automation | Reduced manual work |
| Continuous monitoring | Ongoing data accuracy |
| Connected systems | Better visibility and alignment |
| MDM solution | Healthcare-specific data management |
| Comprehensive view | Improved decision-making and transparency |
Master data management (MDM) is gaining renewed focus in the current environment of supply chain volatility and complexity with the rapidly increasing need for trusted ERP data to support resilient procurement and contracting operations. During the 2026 GHX Summit, May 11-14 in New Orleans, panelists from Mount Sinai Health System and Beth Israel Lahey Health will present their best practices for achieving best-in-class MDM that strengthens supply chain operations for today’s demands.
Their session will include practical tips to enhance item master governance and utilization, item data integrity and contract alignment, which serve as the foundation for a strong, MDM-driven supply chain. Find out more here.
Healthcare master data management (MDM) platforms play a critical role in consolidating and governing key healthcare data entities, supporting the management of patient, provider and location data. A strong foundation of clean, connected data is essential for improving accuracy and aligning information across systems.
The use of data standards across providers, suppliers, distributors and group purchasing organizations (GPO) has become a core data management strategy for building connected healthcare data foundations.
In the pharmacy supply chain, the Drug Supply Chain Security Act (DSCSA) is representative of how the healthcare industry is building a connected foundation for healthcare data management. The DSCSA "outlines steps to achieve an interoperable and electronic way to identify and trace certain prescription drugs at the package level as they move through the supply chain."
The Act requires use of international standards as defined by GS1, including GS1 Global Location Numbers (GLN), which identify who is involved in transactions and where activities occur across the supply chain. By uniquely identifying parties and locations, it improves product tracking, streamlines processes, and enhances global transaction visibility.
Healthcare organizations are under increasing pressure to manage complex supply chains while adapting to constant change—making accurate, consistent, and accessible master data more critical than ever.
Without a strong data foundation, fragmented information can slow decision-making, disrupt operations, and strain supplier relationships. Manual processes only compound the challenge, making it difficult to maintain clean, reliable data at scale.
To keep pace, organizations are turning to intelligent automation. By digitizing and integrating data management within cloud ERP environments, they can unify, cleanse and continuously monitor item data—from item masters to purchasing and contract information. The result is stronger data integrity, greater efficiency, and a more resilient supply chain that supports better patient outcomes and cost control.
Connected data and AI-driven analytics enable teams to identify patterns, understand root causes and make more informed decisions—supporting better operational control and resilience.
If you are attending the 2026 GHX Summit in New Orleans, May 11-14, don't miss the breakout session - The Data Behind Resiliency: AI in Action with Sarasota Memorial Health Care and LeeSar. They will share how they partnered to pilot GHX Resiliency Center, helping bring a powerful two-sided communication hub to life for the entire GHX community.
Learn how real-time visibility, substitute guidance and scalable communication tools reduce operational noise, protect revenue, and enable providers and suppliers to act with confidence during uncertainty.
Access the full agenda here.
As organizations move to cloud-based ERP platforms, ensuring clean, standardized and governed data is critical to maximizing value and avoiding downstream issues.
Grady Health System and Medisys Health Network partnered with GHX to consolidate, cleanse and enrich legacy data, implement integrations for streamlined access to high-quality content, and align pricing strategies to preserve ERP data integrity across critical workstreams. This work helped support more efficient operations and improved procure-to-pay performance following cloud ERP go-live.
See how these organizations approached it in their GHX Summit 2025 session on demand.
Organizations that succeed take a structured, repeatable approach to data management.
When item master data is accurate, standardized and connected across systems, healthcare organizations can:
| Benefit | Impact |
| Reduced manual effort | Increased efficiency |
| Better inventory management | Fewer shortages |
| Improved pricing accuracy | Lower costs |
| Improved patient outcomes | Better quality of care |
Strategic healthcare data management strategies involve healthcare organizations not only cleaning up dirty item master data but also enriching it to boost the power of their data analytics capabilities. For example, Allina Health has increased the percentage of its item master (list of all products) with pre-identified and clinically approved substitutes from 68% to 75%, and doubled its auto-substitution product list from 700 to 1,400.
Enriching item master data with GS1 Global Trade Item Numbers (GTIN) is another key strategy. GTINs, aligned with the FDA’sUDI rule, are essential to item-level traceability, accurate claims and recall readiness across the supply chain. Using GTINs as a source of truth to accurately identify and track medical devices in the supply chain - from manufacturing through to patient records - can improve operational efficiency and healthcare delivery.
In a 2026 GHX Summit breakout session, UC Health will share how its GTIN initiative became a catalyst for aligning supply chain, financial and clinical processes around a single source of truth. By integrating GTIN data into Oracle item master and Epic workflows, they have supported barcode scanning at the point of care in the OR.
Learn more about the session - and the event taking place May 11-14, 2026 in New Orleans - here.
As healthcare systems grow in scale and complexity, managing item master data becomes significantly more challenging.
Advocate Health - where supply chain was managing more than 300,000 items - redefined the role of the item master—from a static formulary to a system that enables clean transactions.
This shift allowed the organization to improve visibility, support accurate transactions and connect data to measurable financial outcomes.
Watch the full presentation.
As healthcare supply chains continue to grow in complexity, organizations must move beyond manual data management toward more connected and intelligent approaches.
By investing in clean, connected and AI-enhanced item master data, providers can improve efficiency, reduce costs and deliver higher-quality patient care.
Item master data in healthcare supply chain management refers to the centralized set of product, supplier and pricing information used to support purchasing, inventory management and financial transactions across healthcare organizations. Health data management plays a key role by systematically organizing, integrating and analyzing digital health data such as electronic medical records (EMR)/electronic health records (EHR), which helps improve patient care and maintain data privacy.
Item master data contains the information that drives supply chain transactions. Accurate and complete data supports efficient ordering, inventory management and billing processes.
The primary challenge is the constant change in data across suppliers, contracts and systems. Maintaining accuracy and consistency across all partners and platforms is difficult without automation and connected data strategies. Data privacy is also a critical concern, as healthcare professionals must ensure sensitive information is protected and managed in compliance with regulations like HIPAA.
Organizations can improve item master data by adopting digital technologies, automating data management processes and leveraging a connected, unified data foundation to ensure consistency across systems.
Automation reduces manual data entry, minimizes errors and helps ensure data is continuously updated and aligned across systems.
A unified data foundation connects data across systems and workflows, enabling better visibility, faster decision-making and improved operational performance.
Healthcare organizations that invest in data standardization, automation and continuous monitoring have achieved higher data accuracy, reduced errors and improved supply chain performance.
Kara L. Nadeau has 25+ years’ experience as a writer/content creator for the healthcare industry, serving clients in fields including medical supplies and devices, pharmaceuticals, supply chain, technology solutions, and quality management.
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