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PRODUCTS & SERVICES


(EHRs), the use of that information is often limited by concerns about privacy,” she continued. “Scanning medical device or pharmaceutical barcodes into patients’ EHRs at point of care as they are admin- istered provides data that is crucial not only in a product recall or alert, but also for tracking the product’s effects.” Artificial Intelligence (AI) should play a vital role as it provides “unprecedented computing power” for data gathered from millions of patients across many geo- graphical locations “to enable proactive and predictive analytics that can be used to quantify occurrences of side effects, product performance issues and adverse events, O’Bara noted. “The ‘machine learning’ of AI can detect and identify links between co-occurring and seemingly unrelated conditions or outcomes, drastically multiplying the power of data analytics to inform and educate the medical community and advance the practice of medicine,” she said. “In addition, automated informa- tion sharing has the potential to help reduce clinicians’ role in data collection and assimilation, freeing them to focus on patient care.”


O’Bara sees the capabilities of comput- ing power hamstrung by privacy mea- sures, and hampering efforts to analyze data around product use and effects on individual patients. Still, cybersecu- rity must be an “increasingly important prerequisite for locking down patient information without losing its value,” she added.


The end game represents the continu-


ous and seamless validation of inventory at each touchpoint across the healthcare supply chain, according to Mike Schiller, Vice President, Healthcare Engagement, SteriTrack. In this scenar- io, Schiller highlights “at each of these touchpoints a product can be scanned and the end-user alerted, in real-time, if the product is affected by a recall.” Schiller credits Mike Nolan, President of Automatic Identi- fication Systems (AIS), for this vision, which, he further argues that “baseline infrastructure and technology already exist to make this vision a reality. “There are applications available today that have the ability to access recall and adverse event databases where a scan of the UDI Device Identifier (UDI-DI) and Production Identifier (UDI-PI) would confirm whether a product is affected by a recall,” Schiller said. Touchpoints include order fulfilment activities at the


Mike Schiller


manufacturer or distributor level where scan technology is typically incorporated, receiving activities, subsequent stocking activities and point-of-care consumption within the healthcare organization setting where scan technology may or may not be deployed, he added.


Schiller describes a potential scenario:


The first validation touchpoint would oc- cur during the product pick activity at the manufacturer or distributor warehouse. For the second validation touchpoint, pri- or to shipping the order, the manufacturer or distributor would include the UDI-DI and the UDI-PI into a “license plate-type” barcode for all of the product that has been packaged in the box or carton. For the third and fourth validation touch- points, this barcode license plate would be scanned at the receiving location, and the individual product would be scanned at the stock location, capturing both the stocked quantity and the stock location. Validation touchpoints five and six occur when the product is picked for consump- tion and consumed at the point of care. He also believes this model could be carried downstream into the home health setting where consumers would have the ability to scan products ensuring their safety prior to use.


Horizon scanning


Beyond capabilities and technology cur- rently available, sources point to several options to reach the next level of develop- ment. Those options center on real-time access to information. Artificial intelligence (AI) capabilities seem the most attainable. “We at National Recall Alert Center are


happy to report that Artificial Intelligence (AI) is already a major part of every recall we transmit to our member facilities and we use it in our four-phase data filtering system,” NRAC’s Cohen said. He further added that they would like to incorporate RFID technology in the future. Rfxcel’s Wong calls for IoT technology to provide real-time, one-way and two- way notifications to consumers during a recall. For example, an IoT-enabled bottle can monitor storage conditions (e.g., temperature, light, humidity) and send alerts if pre-set parameters are exceeded and the integrity of the product is at risk. “This two-way feedback introduces enormous amounts of complex data into the supply chain, which can be difficult for traditional systems to process,” Wong indicated. “Artificial intelligence (AI) can deal with these large volumes of data, enabling smarter monitoring of the drug supply chain to not only manage recalls


but provide proactive warnings about products that may need to be recalled due to incorrect handling or storage.” Because the recall process is so complex, multiple stakeholders need to be aware right away when specific devices are affected, such as implants, according to Champion’s Casady. Electronic scanning facilitates preventive measures and may portend predictive capabilities. “Utilizing scanning and/or RFID tech- nology can play a major role in preventing hospital administration from ever picking up and using recalled implants,” Casady said. “Further, as passive identification technologies become more commonplace, patients and their primary care physicians should also be able to be made aware of concerns.” Casady forecasts a day when regular an- nual check-ups involve a scan of implants to ensure none is negatively impacted. “The specificity of UDI provides tremen- dous potential for artificial intelligence (AI) to help predict and identify early trends with recalls,” he noted. “Today, recalls tend to be highly reactionary with providers attempting to catch up with communications as they are released. I envision a day where data is mined to help manufacturers figure out additional related implants that are at risk. This type of predictive information could also help hospitals prepare and understand how widespread or impactful a recall might become. Eventually, past trends may also help providers navigate and determine which implants are safest to use based on prior recall data available at their fingertips.”


Workday’s Lohkamp believes that absent of a “perfect process,” providers should have enough available technology to improve their recall process. Just follow the paper-to-digital trail. “Ideally, recall notices would come in electronically, using modern webservice technology, and actions could be quickly initiated,” Lohkamp noted. “Unfortu- nately, since many recall notices come in on paper or via PDF, many health systems struggle to pull the notice into an electronic format so it can be easily searched and matched. Artificial intelli- gence, and specifically machine learning, can be leveraged first to capture data off the document and then to go through the data to identify things like GTIN, lots, serial numbers and more. Once in electronic form, that data can be used to automatically search your ERP to deter- mine if that item was ever purchased and if it is still on-site.” HPN


Page 46 hpnonline.com • HEALTHCARE PURCHASING NEWS • January 2020 45


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