10 realities that healthcare organizations must understand about the data that fuel their technologies.
“A strategic supply chain must be able to tie its data to clinical product use as the basis for making informed purchasing decisions that facilitate positive clinical outcomes and a high ROI based on current reimbursement models.”— from “The Healthcare Supply Chain” by Christopher J. O’Connor
Optimizing the supply chain is a daunting challenge for most healthcare organizations. Much of the challenge is driven by failures in the sharing of information throughout the healthcare supply chain. These challenges lead to frustration with product selection, standardization, inventory management and cost, quality and outcomes (CQO) initiatives. Leveraging modern advances in big data and information technology should simplify things, but the lack of accurate, standardized information from manufacturers and distributors in a consumable format leads to manual processes and billions of dollars of waste.
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By understanding the most common data break points in the supply chain, organizations can improve operations, recapture workflow and improve patient outcomes. Based on my experience dealing with hundreds of healthcare organizations, the following are the most common break points within the supply chain, along with a few recommendations for addressing them. There are five common upstream break points and five common downstream break points. A good first step is to make sure your organization is using a standardized and accurate source of information to streamline purchasing decisions and reduce patient safety risks.
There are more than 6 million medical devices on the market from thousands of manufacturers — and the number is growing. Information about most medical devices is still hard to come by, leaving facilities with information that is incomplete. This makes it difficult to make informed purchasing decisions. Additionally, if the item master contains 500K items with some dating back to the 90’s, then it’s likely that some products are being ordered “off contract” or worse, products not approved by product evaluation committees. That lack of control can really cost a hospital. Implementing a single source of truth, backed by a solid compendium of medical device information, will fill in the blanks so that more informed purchasing decisions can be made. With this in place, hospitals can put up guard rails around the item master to make sure the end user is shopping from a pre-approved catalog of items.
An estimated $5 billion is wasted each year from expired, lost or otherwise unaccounted for medical devices and implants. This adds unnecessary complexity to purchasing decisions. Too many organizations cannot compare products and standardize, which has the potential to incur huge savings and improve patient safety. Keeping a master inventory list and medical device library that is up to date will help ensure products are properly accounted for when they are received into inventory and when used throughout the hospital. Also, tracking medical device information is now a necessity that is especially crucial for understanding product recalls. Industry experts estimate that 40 percent of medical devices recalled are not returned in a timely manner, which is unacceptable.
EHR integration needs to be part of a streamlined workflow, or busy professionals will skip, delay or create manual inaccuracies. With the U.S. Food and Drug Administration (FDA) regulation on the Unique Device Identifier (UDI), manufacturers are required to implement and label products with the UDI. This is important to identify products in use. A major roadblock is with EHRs, due to the slow uptake of managing the UDI flow through the inventory management systems to EHRs. By not having the UDI and all the correct attributes, this causes inaccuracies, incomplete documentation and an inability to identify patients for product recalls. This piece of the puzzle is incredibly important.
When it comes to supporting clinicians for quality care and improved patient outcomes, clinical decision support is necessary to reduce variation of care. Unfortunately, not all the appropriate clinical attributes are readily available to clinicians who wish to make optimal decisions. Providers need categorization beyond the standard for CQO assessments. Without this very valuable information, it is difficult to compare like products to standardize across a system.
The ability of hospitals and health systems to evaluate medical devices is based on outcomes data and comparative effectiveness, to make informed clinical and financial decisions. This is a huge break point for hospitals. Not having accurate categorization beyond UNSPSC or the ability to group and evaluate products, makes it difficult for value analysis committees to be effective and meet their CQO objectives.
Creating and sending a purchase order without the necessary product information can be time-consuming for everyone downstream. Purchase orders that do not contain the correct information end up on someone’s desk. It opens databases up to a high risk of human error that can lead to inaccurate reports and mistakes in billing. Pre-populating inventory systems with more complete information can alleviate these issues. Missing information creates real latency on payments and, as a result, missed reimbursements and late fees.
Without an automated process to capture charges and usage, item use can slip through the cracks or be coded incorrectly. Not having the right billing codes is lost revenue for the healthcare provider every year. Providers only have 72 hours to file a claim with Medicare and Medicaid, so capturing the billing codes in time can provide hard dollar savings for any organization.
We are only partially there in terms of adopting the UDI as the go-to identifier for medical devices — and we have a few years to go on Class I devices. In the meantime, facilities can put solutions in place to streamline data collection electronically and make more informed purchasing decisions. Other identifiers, like the global trade item number and catalog numbers, are still widely used and necessary for transactions, but they can be challenging to manage and maintain with the data churn in the healthcare industry.
Today, many organizations dedicate multiple staffers just to assist accounts payable with the 72-hour window allowed for reimbursement. Most organizations want to compare the purchase order price to the contracted price, compared to the invoice price. Automating this process can alleviate a lot of headaches and reduce the amount of time spent checking for mistakes. Again, the missing accounts payable and billing codes often create latency and missed reimbursements, causing significant lost revenue. Organizations need to invest in technology to optimize and streamline this process and to achieve greater real-time visibility into exceptions.
Big data and machine learning are two of the most significant technology trends of the past few years. Unfortunately, few organizations can see into their supply chain due to data challenges. Having the right data and grouping can enable reporting and analytics to provide actionable insights for hospitals and health systems. It’s one thing to have the data, but it’s another thing to have accurate actionable knowledge that you can rely on and, more importantly, act on.
Data are the foundation for supply chain transformation, and there is a great need for accurate, standardized data that can be used across the supply chain and clinical systems. Having actionable data that is ready to use and up to date saves time and labor, eliminating errors that affect tracking, analysis and purchasing decisions. My recommendation is to create a visual representation of your supply chain to identify the data break points and share this document internally to get everyone on the same page. Once you have identified the break points, it is time to address them one by one until the supply chain is whole again.
Lee Ann McWhorter is the Strategic Alliances Director for FDB Prizm, a medical device knowledge base platform from First Databank. Lee Ann has more than 18 years' experience working with multiple stakeholders in the hospital supply chain including GPOs, distributors, manufacturers and providers. Lee Ann’s passion is taking unstructured and undifferentiated data and turning it into actionable knowledge. Connect with Lee Ann via Twitter and LinkedIn.Get the best insights in healthcare analytics directly to your inbox.
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