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.

Lack of Regulations and Conflict of Interest Transparency of New Hernia Surgery Technologies.

BACKGROUND: Medical devices introduced to market through the 510K process often have limited research of low quality and substantial conflict of interest (COI). By the time high-quality safety and effectiveness research is performed, thousands of patients may have already been treated by the device. Our aim was to systematically review the trends of outcomes, research quality, and financial relationships of published studies related to de-adopted meshes for ventral hernia repair. MATERIALS AND METHODS: Literature was systematically reviewed using PubMed to obtain all published studies related to three de-adopted meshes: C-QUR, Physiomesh, and meshes with polytetrafluoroethylene. Primary outcome was change in cumulative percentage of subjects with positive published outcomes. Secondary outcome was percentage of published manuscript with COI. RESULTS: A total of 723 articles were screened, of which, 129 were analyzed and included a total of 8081 subjects. Percentage of subjects with positive outcomes decreased over time for all groups: (1) C-QUR from 100% in 2009 to 22% in 2018, (2) Physiomesh from 100% in 2011 to 20% in 2018, and (3) polytetrafluoroethylene from 100% in 1979 to 49% in 2018. Authors of only 20% of articles self-reported no COI, most representing later publications and were more likely to show neutral or negative results. CONCLUSIONS: Among three de-adopted meshes, early publications demonstrated overly optimistic results followed by disappointing outcomes. Skepticism over newly introduced, poorly proven therapies is essential to prevent adoption of misleading practices and products. Devices currently approved under the 510K processes should undergo blinded, randomized controlled trials before introduction to the market.

Evaluation of the Implementation of CDC's Health Alert Related to the FDA LeadCare Recall From the State Health Department Perspective.

On May 17, 2017, the Food and Drug Administration (FDA) issued a safety recall for the Magellan Diagnostics' LeadCare Testing Systems due to the potential for inaccurately low blood lead test results when used with venous blood samples. The Centers for Disease Control and Prevention (CDC) announced a health alert with retesting recommendations because those with a blood lead level of concern may have been missed and not connected to the appropriate follow-up services. A qualitative evaluation of 9 state childhood lead poisoning prevention programs' experiences is presented in this report. Interviewees reported using a variety of media and notification methods to inform key stakeholders about the recall and recommendations. Challenges experienced by programs in responding to retesting recommendations include incomplete and out-of-date lists of LeadCare users; missing or inaccurate information in their surveillance database; not having large laboratories and hospitals consider contacting persons for retesting to be within their purview; and having limited staff members to conduct emergency response activities. Two of the 9 states report subsequent challenges with their retesting rates. The retesting recommendations were generally viewed positively. The interviewees' comments provide insight into steps CDC might take to better serve state and local lead programs. Programs' experiences have led to a better understanding of the roles of their program when emergency events occur, their relationship with stakeholders as related to the blood lead testing and reporting process, and areas of improvement in surveillance databases. Public health agencies at all levels have important roles to play in preventing lead exposures and providing needed services when exposures occur. Programs may achieve long-term benefits by improving surveillance systems and having a better understanding of laboratory practices. CDC will continue to provide timely information and recommendations to state and local public health agencies to inform both routine and emergency response activities.

Assessment of Obstetric and Gynecologic Food and Drug Administration Device Approvals and Recalls.

STUDY OBJECTIVE: To evaluate and compare the recall rates of obstetric and gynecologic devices approved via the Food and Drug Administration's 510(k) and premarket approval (PMA) processes. DESIGN: A retrospective observational study (Canadian Task Force classification II-2). SETTING: Clinical settings in the United States that use obstetric and gynecologic devices. SUBJECTS: Two thousand two hundred forty-nine Food and Drug Administration-approved obstetric and gynecologic devices that were recalled between November 1, 2002, and December 31, 2017. MEASUREMENTS AND MAIN RESULTS: The class of device, class of recall, date of recall, and original approval process were obtained for each device. These were compared against the total number of approved devices during this time period in the PMA and 510(k) processes. Recall proportions of each process were calculated and compared. A total of 685 devices were approved via the PMA process, and 1564 devices were approved via the 510(k) process in the observed time period. Of these, 1.17% of the PMA-approved devices and 15.98% of the 510(k)-approved devices were recalled (p < .001). There was an overall increase in absolute device recall numbers over time in the 510(k) process, whereas the number of recalls in the PMA process did not change with time. CONCLUSION: The recall event rate for the 510(k) approval process is 13.6 times the rate for the PMA approval process for obstetric and gynecologic devices. Analysis of the results suggests improper device risk classification, inappropriate assignment of the approval process, increased device malfunctions, recalls by the 510(k) process and, therefore, increased risk to patients by these devices. This warrants a call for improvement and increased scrutiny in the 510(k) approval process for devices used in obstetrics and gynecology.

Software-Related Recalls of Health Information Technology and Other Medical Devices: Implications for FDA Regulation of Digital Health.

Policy Points: Medical software has become an increasingly critical component of health care, yet the regulation of these devices is inconsistent and controversial. No studies of medical devices and software assess the impact on patient safety of the FDA's current regulatory safeguards and new legislative changes to those standards. Our analysis quantifies the impact of software problems in regulated medical devices and indicates that current regulations are necessary but not sufficient for ensuring patient safety by identifying and eliminating dangerous defects in software currently on the market. New legislative changes will further deregulate health IT, reducing safeguards that facilitate the reporting and timely recall of flawed medical software that could harm patients. CONTEXT: Medical software has become an increasingly critical component of health care, yet the regulatory landscape for digital health is inconsistent and controversial. To understand which policies might best protect patients, we examined the impact of the US Food and Drug Administration's (FDA's) regulatory safeguards on software-related technologies in recent years and the implications for newly passed legislative changes in regulatory policy. METHODS: Using FDA databases, we identified all medical devices that were recalled from 2011 through 2015 primarily because of software defects. We counted all software-related recalls for each FDA risk category and evaluated each high-risk and moderate-risk recall of electronic medical records to determine the manufacturer, device classification, submission type, number of units, and product details. FINDINGS: A total of 627 software devices (1.4 million units) were subject to recalls, with 12 of these devices (190,596 units) subject to the highest-risk recalls. Eleven of the devices recalled as high risk had entered the market through the FDA review process that does not require evidence of safety or effectiveness, and one device was completely exempt from regulatory review. The largest high-risk recall categories were anesthesiology and general hospital, with one each in cardiovascular and neurology. Five electronic medical record systems (9,347 units) were recalled for software defects classified as posing a moderate risk to patient safety. CONCLUSIONS: Software problems in medical devices are not rare and have the potential to negatively influence medical care. Premarket regulation has not captured all the software issues that could harm patients, evidenced by the potentially large number of patients exposed to software products later subject to high-risk and moderate-risk recalls. Provisions of the 21st Century Cures Act that became law in late 2016 will reduce safeguards further. Absent stronger regulations and implementation to create robust risk assessment and adverse event reporting, physicians and their patients are likely to be at risk from medical errors caused by software-related problems in medical devices.

Ability of patients to recall habitual contact lens products and enhancement of recall using photographic aids.

PURPOSE: To determine the proportion of soft contact lens (CL) wearers who are able to recall their habitual products (lenses and care system) correctly from memory, and to evaluate the value of using photographic aids (PAs) to improve recall. METHODS: 103 soft lens wearers attended 2 visits to investigate their habitual CL product use. At the first visit they were asked to recall which products they were using and then to identify their products from PAs. They returned for a second visit with their products for confirmation. RESULTS: 51% correctly reported their lens brands from memory alone, which improved to 87% with the use of the PAs (p<0.001). 41% correctly reported their habitual care system from memory alone, which improved to 80% with the use of PAs (p<0.001). Females were better at recalling care system brand names than males (49% versus 27% correct, p=0.040) and wearers with more than 1 year experience with their habitual CLs had better recall than those with up to 1 year experience (63% versus 27%, p=0.014). CONCLUSION: Less than 50% of contact lens wearers were able to recall the names of their habitual lens and lens care products correctly from memory. PAs improved this recall significantly for both contact lenses and contact lens care systems.