Communicating medical device recalls: A rapid review of the literature.

OBJECTIVES: The U.S. Food and Drug Administration (FDA) currently regulates more than 190,000 different medical devices. Like all products, these devices may be subject to manufacturing problems, flawed designs, or new and unexpected risks, which in some cases require devices to be recalled. In 2021, the FDA's Patient Engagement Advisory Committee (PEAC) recommended that the FDA consider changes to the communication approach used for medical device recalls to make them more patient-focused, timely, and action-oriented. METHODS: To support this recommendation, we conducted a rapid review of literature published from 2008-2022 to capture and examine information on risk communication approaches, methods, and best practices for recall-related communications about medical products. RESULTS: We identified 23 articles to include in our review. CONCLUSION: Our review found a lack of research-based studies as well as gaps in understanding about consumer perspectives, comprehension, and communication preferences related to recalls. Despite these limitations, we identified current communication approaches, numerous challenges, and recommendations for communicating medical products recall information to consumers. PRACTICE IMPLICATIONS: Further research is needed to assess consumer attitudes, understanding, and preferences and to reach consensus on best practices for effectively communicating recall information to consumers of medical products.

Availability of Unique Device Identifiers for Class I Medical Device Recalls From 2018 to 2022.

This cross-sectional study describes the inclusion of unique device identifier in recall notices for moderate- and high-risk medical devices in the US.

Risk of Recall for Total Joint Arthroplasty Devices Over 10 Years.

BACKGROUND: Orthopaedic devices comprise nearly 20% of devices on the market and 12% to 20% of these devices undergo a recall within 10 years. More than 95% of these devices are approved without supporting clinical data through the Food and Drug Administration's 510(k) pathway. The risk of recall of orthopaedic arthroplasty devices approved through the 510(k) pathway has not been previously studied. METHODS: The FDA 510(k) database was queried for orthopaedic devices approved between January 01, 2008 and December 31, 2018 and subsequently codified to hip and knee arthroplasty devices using product codes. The database included 904 arthroplasty devices during the study period, with hip and knee making up 53.7% (485) and 46.3% (419) of devices, respectively. Information regarding numbers, dates, and reasons for recall were recorded. Cumulative incidence function was conducted to compare the risk of recall between hip and knee arthroplasty. RESULTS: In total, 94 (19.4%) hip and 85 (20.3%) knee devices were recalled. The hazard of recall by 10 years for hip and knee arthroplasty devices was approximately 24%, with no statistical differences between each region. The most common causes of recall were process control and device design, accounting for 29.6% and 26.3% of recalls, respectively, with no significant difference between study groups. CONCLUSION: The risk of recall for arthroplasty devices is more than that previously understood. Improved postmarket surveillance strategies along with increased physician participation in detecting and reporting device safety issues are necessary to strengthen patient safety.

Use of Recalled Devices in New Device Authorizations Under the US Food and Drug Administration's 510(k) Pathway and Risk of Subsequent Recalls.

Importance: In the US, nearly all medical devices progress to market under the 510(k) pathway, which uses previously authorized devices (predicates) to support new authorizations. Current regulations permit manufacturers to use devices subject to a Class I recall-the FDA's most serious designation indicating a high probability of adverse health consequences or death-as predicates for new devices. The consequences for patient safety are not known. Objective: To determine the risk of a future Class I recall associated with using a recalled device as a predicate device in the 510(k) pathway. Design and Setting: In this cross-sectional study, all 510(k) devices subject to Class I recalls from January 2017 through December 2021 (index devices) were identified from the FDA's annual recall listings. Information about predicate devices was extracted from the Devices@FDA database. Devices authorized using index devices as predicates (descendants) were identified using a regulatory intelligence platform. A matched cohort of predicates was constructed to assess the future recall risk from using a predicate device with a Class I recall. Main Outcomes and Measures: Devices were characterized by their regulatory history and recall history. Risk ratios (RRs) were calculated to compare the risk of future Class I recalls between devices descended from predicates with matched controls. Results: Of 156 index devices subject to Class I recall from 2017 through 2021, 44 (28.2%) had prior Class I recalls. Predicates were identified for 127 index devices, with 56 (44.1%) using predicates with a Class I recall. One hundred four index devices were also used as predicates to support the authorization of 265 descendant devices, with 50 index devices (48.1%) authorizing a descendant with a Class I recall. Compared with matched controls, devices authorized using predicates with Class I recalls had a higher risk of subsequent Class I recall (6.40 [95% CI, 3.59-11.40]; P<.001). Conclusions and Relevance: Many 510(k) devices subjected to Class I recalls in the US use predicates with a known history of Class I recalls. These devices have substantially higher risk of a subsequent Class I recall. Safeguards for the 510(k) pathway are needed to prevent problematic predicate selection and ensure patient safety.

Association Between Regulatory Submission Characteristics and Recalls of Medical Devices Receiving 510(k) Clearance.

Importance: Most regulated medical devices enter the US market via the 510(k) regulatory submission pathway, wherein manufacturers demonstrate that applicant devices are "substantially equivalent" to 1 or more "predicate" devices (legally marketed medical devices with similar intended use). Most recalled medical devices are 510(k) devices. Objective: To examine the association between characteristics of predicate medical devices and recall probability for 510(k) devices. Design, Setting, and Participants: In this exploratory cross-sectional analysis of medical devices cleared by the US Food and Drug Administration (FDA) between 2003 and 2018 via the 510(k) regulatory submission pathway, linear probability models were used to examine associations between a 510(k) device's recall status and characteristics of its predicate medical devices. Public documents for the 510(k) medical devices were collected using FDA databases. A text extraction algorithm was applied to identify predicate medical devices cited in 510(k) regulatory submissions. Algorithm-derived metadata were combined with 2003-2020 FDA recall data. Exposures: Citation of predicate medical devices with certain characteristics in 510(k) regulatory submissions, including the total number of predicate medical devices cited by the applicant device, the age of the predicate medical devices, the lack of similarity of the predicate medical devices to the applicant device, and the recall status of the predicate medical devices. Main Outcomes and Measures: Class I or class II recall of a 510(k) medical device between its FDA regulatory clearance date and December 31, 2020. Results: The sample included 35 176 medical devices, of which 4007 (11.4%) were recalled. The applicant devices cited a mean of 2.6 predicate medical devices, with mean ages of 3.6 years and 7.4 years for the newest and oldest, respectively, predicate medical devices. Of the applicant devices, 93.9% cited predicate medical devices with no ongoing recalls, 4.3% cited predicate medical devices with 1 ongoing class I or class II recall, 1.0% cited predicate medical devices with 2 ongoing recalls, and 0.8% cited predicate medical devices with 3 or more ongoing recalls. Applicant devices citing predicate medical devices with 3 or more ongoing recalls were significantly associated with a 9.31-percentage-point increase (95% CI, 2.84-15.77 percentage points) in recall probability compared with devices without ongoing recalls of predicate medical devices, or an 81.2% increase in recall probability relative to the mean recall probability. A 1-SD increase in the total number of predicate medical devices cited by the applicant device was significantly associated with a 1.25-percentage-point increase (95% CI, 0.62-1.87 percentage points) in recall probability, or an 11.0% increase in recall probability relative to the mean recall probability. A 1-SD increase in the newest age of a predicate medical device was significantly associated with a 0.78-percentage-point decrease (95% CI, 1.29-0.30 percentage points) in recall probability, or a 6.8% decrease in recall probability relative to the mean recall probability. Conclusions and Relevance: This exploratory cross-sectional study of 510(k) medical devices cleared by the FDA between 2003 and 2018 demonstrated significant associations between 510(k) submission characteristics and recalls of medical devices. Further research is needed to understand the implications of these associations.

Software-related recalls in computer-assisted hip and knee arthroplasty.

PURPOSE: Computer-assisted arthroplasty supports the surgeons in planning, simulating, and performing the replacement procedure, using robotic or navigation technologies. However, the safety of the technology has not been widely ascertained. Food and Drug Administration (FDA) database was interrogated about software-related recalls in computer-assisted arthroplasty, aiming to assess: (1) the incidence, (2) the root causes, and (3) the actions taken due to recalls. METHODS: The Medical Device Recalls database was investigated about software-related recalls in computer-assisted hip and knee arthroplasty surgery, between 2017 and 2022. The incidence of the software-related recalls, the root causes according to FDA and manufacturers, and the corrective actions taken by firms were determined. RESULTS: Eighteen recall numbers could be identified (1.6%), corresponding to 11 recall events. A total of 4634 units were involved. The FDA determined root causes were: software design (66.6%), design change (22.2%), manufacturing deployment (1, 5.6%), and design manufacturing process (5.6%). Among the manufacturers' reasons for recalls, a specific error was declared in 16 cases (88.9%). In seven cases (43.8%), a coding error about lower limb alignment assessment was identified. Seventeen software-related recalls (94.4%) were classified as class 2; only one case was class 3 (5.6%). Return of the device was the main action taken by firms (8, 44.4%), followed by software update (7, 38.9%). CONCLUSION: Software-related recalls in computer-assisted hip and knee arthroplasty were quite uncommon among all the recalls, deemed non-life threatening and usually due to software design errors. The main actions taken by manufacturers were the return of the device or the software update.

[Development and Application of Medical Device Recall Event Tracking System].

A medical device recall event tracking system was designed, which can enable the users to obtain the recall, early warning and other information related to medical devices in time. The tracking system can timely obtain and release the recall information of medical devices, effectively improve the quality control of hospital medical devices, reduce the use risk of medical devices, and ensure the life safety of patients.

Investigation and analysis of four countries' recalls of osteosynthesis implants and joint replacement implants from 2011 to 2021.

BACKGROUND: Medical devices are used in almost all orthopedic surgical subspecialties, and the frequency of adverse events is increasing, which should not be ignored. To provide suggestions on how to avoid implant recalls from the perspective of manufacturers, medical institutions and supervisions, as well as how to respond promptly to adverse events. METHODS: The research extracted recalls of osteosynthesis implants and joint replacement implants from January 1, 2011, to June 30, 2021, in the CNMPA, FDA, HC and ATGA websites and collected the information on device name, recall time, recall class, recall manufacturer, device classification and affected areas. Moreover, the McKinsey 7S model and fishbone diagram were used to analyze recall reasons. RESULTS: A total of 315 cases of osteosynthesis implants and 286 cases of joint replacement implants were reported in China, the USA, Canada and Australia. The recalls number from 2016 to 2021 was more than that from 2011 to 2015 for osteosynthesis implant (p = 0.012) and joint replacement implant (p = 0.002), and both mainly focused on class II (76.19% and 78.32%). There were statistical differences in the four countries for both implants (p = 0.000), especially osteosynthesis implant between China and the USA (p = 0.000), China and Canada (p = 0.001), the USA and Australia (p = 0.002), and joint replacement implant between China and Australia (p = 0.000). CONCLUSIONS: To avoid the recalls of such implants, manufacturers should strictly select implant materials and components, develop detailed labels and instructions, severely control the packaging process and establish the integrity of medical device data. Medical institutions should standardize procurement procedures, use qualified equipment and train medical workers. It also requires supervisions to conduct premarket safety assessments. In addition, regulators should strengthen supervision and establish reporting systems to deal with the occurrence of adverse events promptly.

Recalls of Moderate- and High-Risk Otolaryngologic Devices Approved by the US Food and Drug Administration, 2003-2019.

OBJECTIVE: The US Food and Drug Administration (FDA) regulates the marketing of medical devices based on the premarket approval (PMA) or 510(k) pathway. We investigated the relationship among the regulatory pathway of otolaryngologic devices, the number of recalls, and the recall characteristics. STUDY DESIGN: Retrospective cross-sectional analysis. SETTING: Publicly available FDA databases. METHODS: The FDA Ear, Nose, and Throat Devices Panel database was queried for 510(k) clearances and PMA approvals from 1976 to 2019. Device recalls from 2003 to 2019 were reviewed. Devices were then categorized by subspecialty, type, supporting evidence, and PMA supplement type. Logistic regression characterized the odds of recall for each device type and subspeciality. RESULTS: A total of 1061 (57.8%) 510(k) and 778 (42.3%) PMA device applications and modifications were approved. There were 120 (11.3%) recall events associated with 42 unique otolaryngologic devices cleared via the 510(k) pathway, as compared with 25 (3.2%) recall events for 5 unique PMA devices. 510(k) device approvals were more likely to be recalled than PMA device approvals (odds ratio, 3.67; 95% CI, 2.38-5.88; P < .0001). 510(k) surgical devices (odds ratio, 2.1; 95% CI, 1.1-4.4; P = .03) were more likely to be recalled than diagnostic devices. Devices designated for laryngology (70.0%) and general otolaryngology (25.0%) composed the majority of recalls. CONCLUSION: Otolaryngologic devices approved by the FDA via the 510(k) pathway exhibit a higher number of recalls than the PMA pathway. Given the balance between regulation and facilitating innovation, postmarket surveillance and ongoing regulatory improvements are critical to ensure optimal safety of medical devices.

Rapid response to medical device recalls: an organized patient-centered team effort.

As more patients depend upon mechanical or electronic technologies for treatment, medical device recalls-like the recent recall of common positive airway pressure treatment devices-impact millions of patients, often causing significant anxiety, extra costs, and interruption of care for patients. When recalls require health care and/durable medical equipment providers to be part of the solution, the burden on practices and businesses can be significant, creating strains on access for new patients and on limited medical supplies. We have observed that having an established and well-organized medical device recall plan in place allows for a rapid response, decreased practice burden, and reduced provider stress. Coupling the organized response with proactive, empathic, and clear communication with patients reduces their anxiety, provides clear directions for how to address the issue constructively, and reduces reactive communications. We share what we believe are key components of a medical device and produce recall procedure as we describe our institutions response in hopes that others can build on these basics as they design their own response plans. CITATION: Morgenthaler TI, Linginfelter EA, Gay PC, et al. Rapid response to medical device recalls: an organized patient-centered team effort. J Clin Sleep Med. 2022;18(2):663-667.

Mapping the genealogy of medical device predicates in the United States.

BACKGROUND: In the United States, medical devices are regulated and subject to review by the Food and Drug Administration (FDA) before they can be marketed. Low-to-medium risk novel medical devices can be reviewed under the De Novo umbrella before they can proceed to market, and this process can be fairly cumbersome, expensive, and time-consuming. An alternate faster and less-expensive pathway to going to market is the 510(k) pathway. In this approach, if the device can be shown to be substantially equivalent in safety and effectiveness to a pre-existing FDA-approved marketed device (or "predicates"), it can be cleared to market. Due to the possibility of daisy-chaining predicate devices, it can very quickly be difficult to unravel the logic and justification of how a particular medical device's equivalence was established. From patients' perspective, this minimizes transparency in the process. From a vendor perspective, it can be difficult to determine the right predicate that applies to their device. METHODS: We map the connectivity of various predicates in the medical device field by applying text mining and natural language processing (NLP) techniques on data publicly made available by the FDA 78000 device summaries were scraped from the US FDA 510(k) database, and a total of 2,721 devices cleared by the 510(k) regulatory pathway in 2020 were used as a specific case study to map the genealogy of medical devices cleared by the FDA. Cosine similarity was used to gauge the degree of substantial equivalence between two medical devices by evaluating their device descriptions and indications for use. Recalls and complaints for predicate devices were extracted from the FDA's Total Product Life Cycle database using html scraping and web page optical character recognition to determine the similarity between class 1 recalled devices (the most severe form of device recall) and other substantially equivalent devices. A specific product code was used to illustrate the mapping of the genealogy from a De Novo device. RESULTS AND DISCUSSION: The ancestral tree for the medical devices cleared in 2020 is vast and sparse, with a large number of devices having only 1-2 predicates. Evaluation of substantial equivalence data from 2003-2020 shows that the standard for substantial equivalence has not changed significantly. Studying the recalls and complaints, shows that the insulin infusion pump had the highest number of complaints, yet none of the recalled devices bore significant degree of text similarity to currently marketed devices. The mapping from the De Novo device case study was used to develop an ancestry map from the recalled predicate (recalled due to design flaws) to current substantially equivalent products in the market. CONCLUSIONS: Besides enabling a better understanding of the risks and benefits of the 510(k) process, mapping of connectivity of various predicates could help increase consumer confidence in the medical devices that are currently in the marketplace.

The Interconnected Ancestral Network of Hip Arthroplasty Device Approval.

BACKGROUND: In the United States, the most overwhelming medical devices, including hip arthroplasty devices, are cleared for human use by demonstration of "substantial equivalence" to a predicate, previously approved marketed device. This study examined the predicate approval lineages of modern hip arthroplasty devices. METHODS: The FDA 510(k) and premarket approval databases were searched to identify all approved hip arthroplasty devices since the database's inception in May 28, 1976. Ancestral predicate lineages were created using approval documentation, and FDA recall data were used to identify recalled devices. RESULTS: Evaluating 2,118 hip arthroplasty devices approved from 1976 to 2020, we found that the number of descendant devices for each approved device varied from 0 to 242. Many descendant devices served as predicates for other devices, leading to frequent indirect connections of equivalency across a wide range of implants. Two hundred forty-six (11.6%) devices were recalled for various reasons, with 34 (1.6%) related to implant design. Evaluating the predicate lineage of 51 hip arthroplasty devices approved between May 1, 2019, and May 1, 2020, 32 of 51 (62.7%) devices were linked, directly or indirectly, to predicates which were recalled for design issues. CONCLUSIONS: The lineage of hip arthroplasty device predicates reflects a complex ancestral web of equivalency across a wide range of implants, although their material and design properties may be different. Several currently approved devices were approved on substantial equivalence claims to products that were subsequently recalled from the market for implant design issues. These findings present several policy considerations for regulators, physicians, and the medical device industry.

An Algorithm for Management of Cosmetic and Reconstructive Patients with Textured Implants: An Institutional Experience.

SUMMARY: Textured anatomic silicone gel breast implants have advantages of gel cohesivity and a natural slope between the upper and lower poles of the breast; however, they have fallen out of favor secondary to their risk of breast implant-associated anaplastic large cell lymphoma. For patients who choose to keep their textured devices, there remains controversy over the best long-term follow-up. This article presents an algorithm from plastic surgery, surgical oncology, and radiology at the Massachusetts General Hospital for management of these patients.

Management of Symptomatic Patients with Textured Implants.

SUMMARY: Proper management of symptomatic textured implant patients is critical to identify and treat associated oncologic disease. Textured surface breast implants were first introduced more than 50 years ago in an effort to decrease high rates of capsular contracture and implant malposition observed with first-generation smooth surface breast implants. Textured implants were dominant over smooth devices in the United States in the late 1990s, but they fell out of favor for newer-generation smooth implants, while texture remained the dominant selling implants worldwide until recently. A class I device recall by the US Food and Drug Administration in 2019 precipitated a removal of the highest selling implant worldwide, Allergan Biocell, due to a disproportionately increased risk of breast implant-associated anaplastic large cell lymphoma (BIA-ALCL). Operative strategies, such as bacterial control at the time of textured implant insertion, have not been credibly shown to affect or prevent the future development of BIA-ALCL. BIA-ALCL patients require complete surgical excision of their disease, whereas textured implant patients who are otherwise asymptomatic do not require surgical removal. For suspicious cases, diagnostic testing with CD30 immunohistochemistry should be performed before any surgical intervention. Capsules are evaluated with 12 strategic regional biopsies in a standardized approach. If surgeons are revising or exchanging textured implants, they may reasonably consider a total capsulectomy, though this is not advocated by the Food and Drug Administration or national societies, and has not been shown to mitigate future risk of BIA-ALCL. The purpose of this article is to review data on and outcomes for textured surface implants, disease-associated risk, and the management strategy for revisionary surgery and device surveillance.