Sensitivity of 510(k) Medical Device Filings to Government Shutdowns: A Brief Communication

Sensitivity of 510(k) Medical Device Filings to Government Shutdowns: A Brief Communication | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Short Report Sensitivity of 510(k) Medical Device Filings to Government Shutdowns: A Brief Communication Karl L. Schumacher, Sindura Penubarthi, Prashanth Asuri This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8718260/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 9 You are reading this latest preprint version Abstract Government shutdowns may impose indirect regulatory costs on medical device manufacturers by disrupting FDA review processes. This study examines changes in 510(k) review durations surrounding the 2013 and 2018 U.S. government shutdowns. We identify significant increases in post-shutdown review times and distinct timing-dependent effects across shutdowns, highlighting the sensitivity of regulatory review timelines to operational disruptions and suggest that even partial shutdowns impede medical device review timelines. Health sciences/Health care Health sciences/Medical research Figures Figure 1 Figure 2 Introduction As government shutdowns become increasingly common, it is important to understand how they affect different levels of the health system. As shown in Table 1 , shutdowns have grown both more frequent and longer in duration, with the most recent October 2025 shutdown lasting 43 days and becoming the longest in U.S. history. [ 1 ] Discussion of shutdown impacts has largely focused on the specific policies at the center of appropriations debates and the direct costs associated with government employee furloughs, however in the context of health systems the indirect costs dominate. [ 2 , 3 , 4 , 5 , 6 , 7 , 8 ] Table 1 Dates, Duration, and Presidential Administration for All Federal Funding Gaps Occurring Since January 1st, 2000 through December 31st, 2025 Start Date End Date Presidential Administration Duration (days) Dept. of HHS Furlough Oct 1, 2013 Oct 17, 2013 Obama 17 Yes Jan 20, 2018 Jan 22, 2018 Trump 3 Yes Feb 9, 2018 N/A Trump 1 No Dec 22, 2018 Jan 25, 2019 Trump 35 No Oct 1, 2020 N/A Trump 1 No Dec 22, 2020 N/A Trump 1 No Mar 23, 2024 N/A Biden 1 No Dec 21, 2024 N/A Biden 1 No Oct 1, 2025 Nov 12, 2025 Trump 43 Yes Medical device and pharmaceutical manufacturers are uniquely dependent on close and continuous interaction with regulators during the development of their products. [ 9 , 10 ] As a result, they are particularly sensitive to regulatory barriers or incentives, and may incur substantial indirect costs when shutdowns disrupt these relationships. Government shutdowns can create unexpected interruptions in the dialogue between manufacturers and regulators during filing review processes, leading to delays in otherwise standard review cycles and potentially material setbacks for manufacturers seeking to introduce novel medical technologies, despite assurances otherwise. [ 11 ] At the level of individual firms, these costs are largely unknown and highly case-specific, as manufacturers have distinct interactions with reviewers and cannot predict when or how shutdown-related delays may arise. Examining the industry as a whole provides a way to assess the aggregate impact of shutdowns on the medical device sector, particularly around the most consequential events. The FDA’s policies on public disclosure of filing documentation and correspondence for cleared medical device filings make this type of analysis feasible. The agency provides a reliable historical record of manufacturer and regulator behavior spanning the past two decades [ 12 ]. Applying analytical methods to this dataset and interpreting the resulting trends can inform both policymakers and manufacturers about the expected impacts of future shutdowns. This analysis focuses exclusively on 510(k) premarket notification filings, which represent approximately 99% of all medical device submissions and encompass roughly 53% of classified medical technologies. [ 13 , 14 ] Although medical devices span a wide range of product classes and clinical specialties, review durations across 510(k) filings are comparatively consistent and provide the largest available sample size among FDA regulatory pathways and are one of the most standardized filing pathways. [ 15 ] As such, this filing type captures the majority of routine regulatory interactions between manufacturers and the FDA, making it well suited for evaluating shutdown-related disruptions at the industry level. This study examines the implications of government shutdowns for medical device filings by analyzing changes in FDA review durations for 510(k) submissions under review around the October 2013 and December 2019 shutdowns. These events represent the fourth and second-longest government shutdowns, respectively, and both are surrounded by sufficiently robust FDA filing data. They also differ meaningfully in structure: the October 2013 shutdown during the second Obama administration was a full shutdown, with all HHS and FDA employees furloughed, whereas the December 2018 shutdown during the first Trump administration was partial. [ 16 , 17 , 18 ] Minibus appropriations bills maintained some HHS funding, resulting in an approximate 41% furlough at FDA, maintaining essential functions through the shutdown. [ 19 , 20 , 21 ] Funds from applicant fees submitted with clearance applications were intended to maintain product review progress. However, user fees only accounted for less than 35% of FDA CDRH budget at the time. [ 22 , 23 , 24 ] This analysis addresses two key questions regarding the impact of extended government shutdowns on the medical device filing process. (1) Does the timing of a filing submission relative to a shutdown significantly affect its review duration? We hypothesize that filings overlapping the period immediately following a shutdown experience longer median review durations than those overlapping the pre-shutdown period, due to the accumulation of delayed actions and FDA recovery. (2) Is there a specific portion of the review cycle that is particularly vulnerable to delay when it coincides with a shutdown? We hypothesize that filings whose second half of their review periods overlaps with the shutdown itself are especially susceptible to increased review times, due to the potential impact on the additional information request and interactive review stages of a filing, as they require the most correspondence between the applicant and FDA. [ 25 , 26 ] Results Figure 1 a) presents the results of the windowed sampling analysis for the October 2013 and December 2018 government shutdowns. For the October 2013 shutdown, the median review duration of 510(k) filings overlapping the post-shutdown period increased significantly by 18 days, from 206 days in the pre-shutdown window to 224 days in the post-shutdown window. Across the three windows, the interquartile range (IQR) of review durations decreased slightly, declining from 167 days in the pre-shutdown window to 163 days during the shutdown window, and further to 160.2 days in the post-shutdown window. A similar pattern is observed for the December 2018 shutdown. The median review duration for post-shutdown 510(k) filings increased significantly by 20 days, rising from 197 days in the pre-shutdown window to 217 days in the post-shutdown window. As with the 2013 shutdown, the IQR of filing review durations decreased across successive windows, progressing from 154 days prior to the shutdown, to 149 days during the shutdown, and to 147 days in the post-shutdown period. Supplemental figure S1 ) presents the same windowed sampling analysis applied to all federal funding gaps from Oct 2013 through Dec 2020. Figure 1 b) summarizes the quarter overlap analysis for both shutdowns. For the October 2013 shutdown, the Kruskal–Wallis test indicates that at least one sample differs significantly from the others. The fourth-quarter overlap sample exhibits the largest difference in median review duration relative to the other quarters, with a median of 182 days compared to 206, 209, and 210 days for the first, second, and third quarter samples, respectively. The third-quarter overlap sample has the highest median review duration among all quarters and is significantly greater than the other medians based on the Mann–Whitney U test. The IQR of review durations increased across the first three quarters, from 160.5 days to 166.78 days and then to 170.8 days, before decreasing to 152.5 days in the fourth quarter. For the December 2018 shutdown, the Kruskal–Wallis test similarly indicates that at least one quarter differs significantly from the others. Median review durations decrease sequentially across the four quarter-overlap samples, from 193 days in the first quarter to 191, 175, and 171 days in the second, third, and fourth quarters, respectively. The first-quarter overlap sample has the highest median review duration and is significantly greater than the other quarter medians according to the Mann–Whitney U test. The IQR of review durations generally increases across quarters, from 157.5 days in the first quarter to 164, 162.5, and 167 days in the second, third, and fourth quarters, respectively. Supplemental figure S2) presents the same quarter overlap analysis applied to all federal funding gaps from Oct 2013 through Dec 2020. Discussion and Conclusions The windowed sampling analysis indicates that for both government shutdowns examined, filings overlapping either the shutdown itself or the immediate post-shutdown period experienced increased FDA review durations. For the October 2013 shutdown, the increase observed in the post-shutdown window corresponds to approximately 105.8% of the shutdown’s implied effect, with an 18-day increase in median review duration relative to a 17-day shutdown. When compared to the median review duration in the pre-shutdown window, this represents an approximate 8% increase in filing review time. For the December 2018 shutdown, the post-shutdown increase in median review duration corresponds to approximately 57.1% of the shutdown’s implied effect, with a 20-day increase in median review duration following a 35-day shutdown. Relative to the pre-shutdown median, this represents an approximately 10% increase in review time. The smaller proportional effect observed for this shutdown suggests a dilution of the shutdown’s impact, preventing the median delay from approaching the full length of the shutdown itself. The discrepancy between the magnitude of these effects across the two shutdowns appears closely linked to differences in federal employee furlough policies. During the October 2013 shutdown, HHS employees—including FDA staff—were fully furloughed, consistent with the near one-to-one correspondence between shutdown duration and median review delay. In contrast, during the December 2018 shutdown, HHS employees were not completely furloughed, and FDA review operations were expected to continue uninterrupted, funded by already submitted user fees. Despite this, filing review durations increased substantially, indicating that there are bottlenecks in the filing review process that were not supported by the temporary appropriations, for instance external consultants, or other federal offices that were not exempted from furlough, or otherwise more directly impacted. Additionally, applicant behavior changes could be contributing to this difference, as shown in supplemental figures S4a-b) highlighting differences in FDA submission frequency between the two shutdowns. The quarter overlap analysis further highlights distinct differences in filing behavior across the two shutdowns. For the October 2013 shutdown, filings overlapping the shutdown during their third quarter of review exhibit both the highest median review duration and the greatest variability. This pattern suggests heightened vulnerability to shutdown effects during the third quarter of the review process, a phase that typically corresponds to active interaction between applicants and the FDA through additional information requests and responses. The sharp decline in both median review duration and variance for filings overlapping the shutdown in their fourth quarter suggests that applications which had largely completed substantive correspondence were less affected, and potentially only awaiting final regulatory decisions. In contrast, filings overlapping the December 2018 shutdown show a general decrease in review duration for later quarter overlaps. This pattern suggests a different mechanism underlying the shutdown’s impact on review timelines, wherein filings further along in the review process were largely insulated from delay. Together, these findings indicate that the timing of a filing within the review lifecycle plays a critical role in determining its susceptibility to shutdown-related disruption, and that the operational characteristics of a shutdown meaningfully shape its downstream effects on regulatory review. Methods Data Sources and Screening Data for this analysis is entirely derived from the FDA downloadable datasets for medical device filings. [ 27 ]. Filing Type and Date Filtering Only 510(k) filings with a recorded FDA decision date between January 2000 and December 2025 were included. The lower bound reflects limitations in data completeness and reliability prior to widespread digitization and online submission of FDA filings. The upper bound reflects structural constraints of the FDA filing database, which suppresses records for submissions that have not yet reached a final decision, resulting in incomplete reporting for more recent filings. Sampling Methods Figure 2 ) visually represents the two sampling methods used for the windowed sampling analysis and quarter overlap analysis on a sample of representative filings. For the windowed sampling analysis, to minimize sampling bias, an independent and temporally symmetric sampling framework was applied. For each government shutdown, three sampling periods were defined: Prior, Spanning, and Post. Each period was equal in duration to the shutdown itself. The Prior and Post periods were offset from the shutdown start and end by a fixed 90 day interval, preserving symmetry across samples. Filings were assigned to one or more sampling periods based on temporal overlap, with filings spanning multiple periods contributing to each relevant distribution. This design intentionally oversamples filings that span multiple sampling periods. Because such filings are duplicated across distributions, their relative influence within any single period is diluted. Consequently, differences observed between periods are driven primarily by filings that uniquely intersect a given sampling window, rather than by long-running filings that dominate multiple windows. A three-month window before and after each shutdown was chosen to balance statistical power with temporal specificity. The Prior period captures baseline FDA review behavior, the Spanning period represents filings directly exposed to the shutdown, and the Post period includes filings that did not overlap the shutdown but may reflect residual or recovery effects within the FDA review process. This offset-window approach is well suited for identifying aggregate shifts in review duration associated with shutdown timing but is less sensitive to short-lived disruptions within longer filing timelines. Supplemental figures S3a-b) indicate the longer term application of this sampling method for the year before and after the subject shutdown period. For the quarter overlap analysis each filing overlapping a shutdown was divided into four equal-length quarters representing stages of review progress, to examine more acute shutdown effects coinciding with the development phases of clearance filings. Each quarter was evaluated independently for overlap with the shutdown period, and the full filing review duration was attributed to each overlapping quarter bin. As with the windowed analysis, filings overlapping multiple quarters are similarly oversampled, which tends to deflate median review durations for longer shutdowns that intersect more quarters of shorter filings. This method also introduces an inherent limitation: for filing reviews extended by a shutdown, the equal quarter divisions all absorb some of this delay, slightly impacting the overlap positioning of each quarter. Statistical Analysis All processing of this dataset was performed in Python using the Pandas, Numpy and Scipy data structure and statistical analysis libraries. [ 28 , 29 , 30 , 31 ] The Mann–Whitney U test was used to assess whether the distribution of values in one population differs from that of another population and to evaluate the significance of that difference. [ 32 ] The null hypothesis assumes that the two populations have identical distributions, while the alternative hypothesis posits that the median of the post-shutdown (or later-stage) population is greater than that of the pre-shutdown (or earlier-stage) population. This directional alternative hypothesis was selected to test whether later populations exhibit a higher central tendency in review duration than earlier populations. To assess differences between review-duration distributions across multiple filing populations defined by their timing relative to a government shutdown, the Kruskal–Wallis test was applied. [ 33 ] This non-parametric omnibus test evaluates whether at least one sample originates from a different distribution than the others and does not assume normality of the underlying data, making it well suited for comparing review durations across independent groups. The Kruskal–Wallis test was used to identify the presence of statistically significant differences across the quarter-overlap samples, without presupposing the location of those differences. When the Kruskal–Wallis test indicated a statistically significant result, 1-vs-all comparisons were conducted using the MWU test to identify the specific populations driving the observed differences. For each MWU comparison, the following statistical information is reported in the figure annotations: the sample sizes of the populations being compared; the Mann–Whitney U statistic (U), which quantifies the degree of separation between the two distributions; and the associated p-value (p MWU ). For each KW test, the associated p-value (p KW ) was reported A p-value less than 0.05 was considered statistically significant for all tests. Declarations Acknowledgements This work was supported through institutional resources provided by the School of Engineering at Santa Clara University; no external funding or monetary support was received. No specific grant number. Author Contributions KS conceived and designed the study, performed the data analysis, and interpreted the regulatory trends regarding FDA-Shutdown interactions. PA and SP contributed to the interpretation of the results. PA and SP were involved in planning and contributed to the overall direction. KS wrote the manuscript with input from PA and SP. All authors read and approved the final manuscript. Competing Interests The authors declare the following potential conflicts of interest: author SP is employed by Masimo, a global medical technology company, and KS is employed by BioIntelliSense, a medical device company. These affiliations had no involvement in the design, analysis, interpretation, or publication of this analysis. PA declares no competing interests. Data Availability All data used in this analysis are publicly available through the U.S. Food and Drug Administration (FDA) databases. [27] Code Availability The code supporting this analysis is available upon request from the corresponding author References History, Art & Archives, U.S. House of Representatives. (2026, January 1). Funding gaps and shutdowns in the federal government . https://history.house.gov/Institution/Shutdown/Government-Shutdowns/ Joint Economic Committee. (2024, December 19). Update: The economic costs of a GOP shutdown (Fact sheet) . https://www.jec.senate.gov/public/index.cfm/democrats/2024/12/update-the-economic-costs-of-a-gop-shutdown Joint Economic Committee Brass, C. T., Brudnick, I. A., McMillion, B. J., Paris, N., Rollins, J. W., & Yeh, B. T. (2018, December 10). Shutdown of the federal government: Causes, processes, and effects (CRS Report No. RL34680). Congressional Research Service. https://www.congress.gov/crs-product/RL34680 Labonte, M., & Weinstock, L. R. (2023, September 22). Economic effects of government shutdowns (CRS Insight No. IN12248). Congressional Research Service. https://crsreports.congress.gov Morello, L., Guglielmi, G., Ledford, H., Reardon, S., Tollefson, J., & Witze, A. (2018, January 20). Science in limbo as US government shuts down: Grants are set to dry up, space launches could be delayed and some experiments could be ruined . Nature. https://www.nature.com/articles/d41586-018- 01016-2 Morello, L., Maxmen, A., Reardon, S., & Witze, A. (2019, January 4). Scientists despair as US government shutdown drags on: Space missions can continue to collect data, but thousands of federal researchers are forced to stay at home without pay . Nature, 565, 141–142. https://doi.org/10.1038/d41586-019-00008-0 Executive Office of the President. (2013, November). Impacts and costs of the October 2013 federal government shutdown (Report). https://obamawhitehouse.archives.gov/sites/default/files/omb/reports/impacts-and-costs-of-october-2013-federal-government-shutdown-report.pdf Wamsley, L. (2019, January 9). How is the shutdown affecting America? Let us count the ways . NPR. https://www.npr.org/2019/01/09/683642605/how-is-the-shutdown-affecting-america-let-us-count-the-ways U.S. Food and Drug Administration. (2014, April 4). Types of communication during the review of medical device submissions: Guidance for industry and Food and Drug Administration staff. U.S. Department of Health and Human Services . https://www.fda.gov/media/85200/download U.S. Food and Drug Administration. (2022, October 3). 510(k) submission process . https://www.fda.gov/medical-devices/premarket-notification-510k/510k-submission-process U.S. Department of Health and Human Services. (2025, September 25). FY 2026 HHS contingency staffing plan for operations in the absence of enacted annual appropriations. https://www.hhs.gov/about/budget/fy-2026-hhs-contingency-staffing-plan/index.html U.S. Food and Drug Administration. (2025, December 29). 510(k) premarket notification. https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm Aboy, M., Crespo, C., & Stern, A. (2024). Beyond the 510(k): The regulation of novel moderate-risk medical devices, intellectual property considerations, and innovation incentives in the FDA’s De Novo pathway . npj Digital Medicine, 7, Article 29. https://doi.org/10.1038/s41746-024-01021-y Piermatteo, K. (2020, December 15). How is my medical device classified? U.S. Food and Drug Administration. https://www.fda.gov/media/131270/download U.S. Food and Drug Administration. (2014, July 28). The 510(k) program: Evaluating substantial equivalence in premarket notifications [510(k)]: Guidance for industry and Food and Drug Administration staff. U.S. Department of Health and Human Services. https://www.fda.gov/media/82395/download Beasley, S. (2013, October 11). Postponed FDA advisory meetings, workshops spark concerns. FDA Week, 19(41), 1, 4–5. https://www.jstor.org/stable/10.2307/26692518 Morello, L. (2013, October 1). US government shuts down . Nature, 502, 13–14. https://doi.org/10.1038/502013a Murray, J., & Wilson, C. (2025, September 30). Past government shutdowns: Key resources (CRS Report No. R41759). Congressional Research Service. https://crsreports.congress.gov Department of Defense and Labor, Health and Human Services, and Education Appropriations Act, 2019 and Continuing Appropriations Act , 2019, Pub. L. No. 115–245, 132 Stat. 2981 (2018). https://www.congress.gov/115/plaws/publ245/PLAW-115publ245.pdf Roza, D. (2019, January 4). FDA expert foresees long-term planning damage due to shutdown . FDA Week, 25(1), 1, 4–5. https://www.jstor.org/stable/10.2307/27045307 House Committee on Appropriations. (2025, December 20). Cole, Collins deliver bicameral agreement on FY26 funding allocations [Press release]. U.S. House Committee on Appropriations. https://appropriations.house.gov/news/press-releases/cole-collins-deliver-bicameral-agreement-fy26-funding-allocations Morello, L. (2018, January 18). What a US government shutdown would mean for science . Nature. https://www.nature.com/articles/d41586-018-00928-3 Klock, S. M., & Werner, M. J. (2019, January 25). The government shutdown and its effects on the FDA . Holland & Knight Healthcare Blog. https://www.hklaw.com/en/insights/publications/2019/01/the-government-shutdown-and-its-effects-on-the-fda Parasrampuria, S., & Beleche, T. (2023, March). FDA user fees: Examining changes in medical product development and economic benefits (Issue Brief). Office of the Assistant Secretary for Planning and Evaluation, U.S. Department of Health and Human Services. https://www.ncbi.nlm.nih.gov/books/NBK603243/ U.S. Food and Drug Administration. (2022, October). Information requests and discipline review letters under the Generic Drug User Fee Amendments (GDUFA): Guidance for industry (Revision 1). U.S. Department of Health and Human Services. https://www.fda.gov/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/default.htm U.S. Food and Drug Administration. (2022, October 26). Developing and responding to deficiencies in accordance with the least burdensome provisions: Guidance for industry and Food and Drug Administration staff (Final Level 2 guidance). U.S. Department of Health and Human Services. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/developing-and-responding-deficiencies-accordance-least-burdensome-provisions U.S. Food and Drug Administration. (2021, November 23). Downloadable 510(k) files . U.S. Department of Health and Human Services. https://www.fda.gov/medical-devices/510k-clearances/downloadable-510k-files The pandas development team. (2020). pandas-dev/pandas: Pandas (latest) [Software]. Zenodo. https://doi.org/10.5281/zenodo.3509134 Harris, C.R., Millman, K.J., van der Walt, S.J. et al (2020). Array programming with NumPy . Nature 585, 357–362. https://doi.org/10.1038/s41586-020-2649-2 . Pauli Virtanen, Ralf Gommers, Travis E. Oliphant, and SciPy 1.0 Contributors (2020). SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python . Nat. Methods, 17(3), 261–272. https://doi.org/10.1038/s41592-019-0686-2 . Krzywinski, M., Altman, N (2014). Nonparametric tests . Nat. Methods 11, 467–468. https://doi.org/10.1038/nmeth.2937 Mann, Henry B.; Whitney, Donald R. (1947). On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other . Annals of Mathematical Statistics. 18 (1): 50–60. doi: 10.1214/aoms/1177730491 Kruskal; Wallis (1952). Use of ranks in one-criterion variance analysis . Journal of the American Statistical Association. 47 (260): 583–621. doi: 10.1080/01621459.1952.10483441 . Additional Declarations Competing interest reported. The authors declare the following potential conflicts of interest: author SP is employed by Masimo, a global medical technology company, and KS is employed by BioIntelliSense, a medical device company. These affiliations had no involvement in the design, analysis, interpretation, or publication of this analysis. PA declares no competing interests. Supplementary Files 510kSensitivitytoGovtShutdownsSupplemental.pdf Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 08 Apr, 2026 Reviews received at journal 05 Apr, 2026 Reviews received at journal 15 Mar, 2026 Reviewers agreed at journal 13 Feb, 2026 Reviewers agreed at journal 11 Feb, 2026 Reviewers invited by journal 11 Feb, 2026 Editor assigned by journal 05 Feb, 2026 Submission checks completed at journal 02 Feb, 2026 First submitted to journal 28 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8718260","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Short Report","associatedPublications":[],"authors":[{"id":591052167,"identity":"2b2bd224-d3bb-4d58-9e65-34ddeadf5f6e","order_by":0,"name":"Karl L. Schumacher","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4UlEQVRIiWNgGAWjYBACCQYGNjDDgIGB8cEHBhibSC3MhjNI1cImzUOMFsn+w88e8+bYyZuz9z6Qtvljl9jA3rxNAp8WaYk0c2PebcmGO3uOGxjntiUnNvAcK8OrRU6Ch02adxtzgsGNNIbk3IYDiQ0SOWb4tfCfAWmpTzC4/4zhsMUfoBb5N/i1SDPkgLQcBtrCxtjMwAayhQe/FskZaWaSc7cdN9xwJo2Zsbct2biNJ63YAp8WifOHn0m83VYtb3D8GPuPH3/sZPvZD2+8gU8LJmAjTfkoGAWjYBSMAmwAAH1FQnRFKc4XAAAAAElFTkSuQmCC","orcid":"","institution":"Santa Clara University","correspondingAuthor":true,"prefix":"","firstName":"Karl","middleName":"L.","lastName":"Schumacher","suffix":""},{"id":591052168,"identity":"833097e5-26cd-4199-8edd-c321b4c75410","order_by":1,"name":"Sindura Penubarthi","email":"","orcid":"","institution":"Regulatory Affairs Professional","correspondingAuthor":false,"prefix":"","firstName":"Sindura","middleName":"","lastName":"Penubarthi","suffix":""},{"id":591052169,"identity":"953ade7b-b99e-4484-b04a-3daf81f18a51","order_by":2,"name":"Prashanth Asuri","email":"","orcid":"","institution":"Santa Clara University","correspondingAuthor":false,"prefix":"","firstName":"Prashanth","middleName":"","lastName":"Asuri","suffix":""}],"badges":[],"createdAt":"2026-01-28 09:08:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8718260/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8718260/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102842448,"identity":"c0c189e1-6316-4864-b59f-4791132a9e3a","added_by":"auto","created_at":"2026-02-17 12:29:10","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":429754,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003ea-b: Windowed Sampling Analysis and Quarter Overlap Analysis of 510(k) Review Duration Distributions for Oct 2013 and Dec 2018 Federal Shutdowns. \u003c/em\u003e1a) Distributions of FDA review durations for 510(k) medical device filings overlapping the prior, spanning, and post-shutdown windows of each shutdown. Summary statistics beneath each boxplot report Mann–Whitney U tests comparing Post and Prior windows under the alternative hypothesis that the Post-window median exceeds the Prior-window median. U statistics and corresponding p-values are shown. Sample sizes for each window are indicated. 1b) Distributions of FDA review durations for 510(k) medical device filings whose first through fourth review quarters overlap with a government shutdown. Quarter-overlap groups are first evaluated using a Kruskal–Wallis test to assess whether at least one group differs from the others. Conditional on a significant omnibus result, all quarters are independently compared against the remaining quarters using one-sided Mann–Whitney U tests under the alternative hypothesis that the quarter’s median review duration exceeds that of the others. Among quarters with statistically significant results, the quarter with the greatest median review duration is reported; the corresponding U statistic and adjusted p-value are shown. Sample sizes for each quarter-overlap group per shutdown are indicated.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-8718260/v1/f9d409f30a4e86a5d710d705.png"},{"id":102842447,"identity":"30f27476-a1e5-4da7-8eb9-86cc42765b3b","added_by":"auto","created_at":"2026-02-17 12:29:10","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":146825,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eTimeline Representation of Offset Window Sampling Scheme and Quarter Overlap Analysis Sampling\u003c/em\u003e. Depicting seven example 510(k) filings which interact with the 3 sampling windows around the Dec 2018 federal government shutdown. The Prior and Post windows are the same 35 day duration as the shutdown and spaced 90 days before and after the shutdown respectively to observe the effect on review duration of filings which overlap each period. Each of the 7 example filings are annotated with their respective period overlap labels. For example: Filing K182451 only overlaps the prior window; K183496 only overlaps the shutdown window; K191004 only overlaps the post window; K181126 overlaps both the prior and shutdown windows; K183567 overlaps the shutdown and post windows; K173590 overlaps all 3 sampling windows; K190412 overlaps none of the sampling windows. Each filing review period is divided into quarters which define labels for each filing by which quarter overlaps the shutdown window. Filings which have multiple quarters overlapping the shutdown window will contribute to both labels in analysis. For example: Filing K183496 overlaps the shutdown in both its first and second quarter; K181126 overlaps the shutdown in its 4th quarter; K183567 overlaps in its first quarter; K173590 overlaps in its second and third quarters; Filings K182451, K191004, and K190412 do not have any quarter overlap with the shutdown window.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-8718260/v1/d06e07b89bef327e5db61e41.png"},{"id":104779091,"identity":"1bc97e5c-8c29-4388-a31b-a81b639442dd","added_by":"auto","created_at":"2026-03-17 07:34:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1030667,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8718260/v1/93d2b9ef-c6a4-4b00-a4d9-6974bde14a65.pdf"},{"id":102963752,"identity":"b22bbe57-dba6-46c0-8687-167f932e2f2b","added_by":"auto","created_at":"2026-02-19 04:20:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":1075267,"visible":true,"origin":"","legend":"","description":"","filename":"510kSensitivitytoGovtShutdownsSupplemental.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8718260/v1/be4477b20129475c7667334d.pdf"}],"financialInterests":"Competing interest reported. The authors declare the following potential conflicts of interest: author SP is employed by Masimo, a global medical technology company, and KS is employed by BioIntelliSense, a medical device company. These affiliations had no involvement in the design, analysis, interpretation, or publication of this analysis. PA declares no competing interests.","formattedTitle":"Sensitivity of 510(k) Medical Device Filings to Government Shutdowns: A Brief Communication","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAs government shutdowns become increasingly common, it is important to understand how they affect different levels of the health system. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, shutdowns have grown both more frequent and longer in duration, with the most recent October 2025 shutdown lasting 43 days and becoming the longest in U.S. history. [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] Discussion of shutdown impacts has largely focused on the specific policies at the center of appropriations debates and the direct costs associated with government employee furloughs, however in the context of health systems the indirect costs dominate. [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDates, Duration, and Presidential Administration for All Federal Funding Gaps Occurring Since January 1st, 2000 through December 31st, 2025\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStart Date\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEnd Date\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePresidential Administration\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDuration\u003c/p\u003e \u003cp\u003e(days)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDept. of HHS Furlough\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOct 1, 2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOct 17, 2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eObama\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJan 20, 2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJan 22, 2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTrump\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFeb 9, 2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTrump\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDec 22, 2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJan 25, 2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTrump\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOct 1, 2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTrump\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDec 22, 2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTrump\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMar 23, 2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBiden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDec 21, 2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBiden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOct 1, 2025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNov 12, 2025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTrump\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMedical device and pharmaceutical manufacturers are uniquely dependent on close and continuous interaction with regulators during the development of their products. [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] As a result, they are particularly sensitive to regulatory barriers or incentives, and may incur substantial indirect costs when shutdowns disrupt these relationships. Government shutdowns can create unexpected interruptions in the dialogue between manufacturers and regulators during filing review processes, leading to delays in otherwise standard review cycles and potentially material setbacks for manufacturers seeking to introduce novel medical technologies, despite assurances otherwise. [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eAt the level of individual firms, these costs are largely unknown and highly case-specific, as manufacturers have distinct interactions with reviewers and cannot predict when or how shutdown-related delays may arise. Examining the industry as a whole provides a way to assess the aggregate impact of shutdowns on the medical device sector, particularly around the most consequential events.\u003c/p\u003e \u003cp\u003eThe FDA\u0026rsquo;s policies on public disclosure of filing documentation and correspondence for cleared medical device filings make this type of analysis feasible. The agency provides a reliable historical record of manufacturer and regulator behavior spanning the past two decades [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Applying analytical methods to this dataset and interpreting the resulting trends can inform both policymakers and manufacturers about the expected impacts of future shutdowns.\u003c/p\u003e \u003cp\u003eThis analysis focuses exclusively on 510(k) premarket notification filings, which represent approximately 99% of all medical device submissions and encompass roughly 53% of classified medical technologies. [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] Although medical devices span a wide range of product classes and clinical specialties, review durations across 510(k) filings are comparatively consistent and provide the largest available sample size among FDA regulatory pathways and are one of the most standardized filing pathways. [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] As such, this filing type captures the majority of routine regulatory interactions between manufacturers and the FDA, making it well suited for evaluating shutdown-related disruptions at the industry level.\u003c/p\u003e \u003cp\u003eThis study examines the implications of government shutdowns for medical device filings by analyzing changes in FDA review durations for 510(k) submissions under review around the October 2013 and December 2019 shutdowns. These events represent the fourth and second-longest government shutdowns, respectively, and both are surrounded by sufficiently robust FDA filing data. They also differ meaningfully in structure: the October 2013 shutdown during the second Obama administration was a full shutdown, with all HHS and FDA employees furloughed, whereas the December 2018 shutdown during the first Trump administration was partial. [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] Minibus appropriations bills maintained some HHS funding, resulting in an approximate 41% furlough at FDA, maintaining essential functions through the shutdown. [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] Funds from applicant fees submitted with clearance applications were intended to maintain product review progress. However, user fees only accounted for less than 35% of FDA CDRH budget at the time. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eThis analysis addresses two key questions regarding the impact of extended government shutdowns on the medical device filing process. (1) Does the timing of a filing submission relative to a shutdown significantly affect its review duration? We hypothesize that filings overlapping the period immediately following a shutdown experience longer median review durations than those overlapping the pre-shutdown period, due to the accumulation of delayed actions and FDA recovery. (2) Is there a specific portion of the review cycle that is particularly vulnerable to delay when it coincides with a shutdown? We hypothesize that filings whose second half of their review periods overlaps with the shutdown itself are especially susceptible to increased review times, due to the potential impact on the additional information request and interactive review stages of a filing, as they require the most correspondence between the applicant and FDA. [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea) presents the results of the windowed sampling analysis for the October 2013 and December 2018 government shutdowns. For the October 2013 shutdown, the median review duration of 510(k) filings overlapping the post-shutdown period increased significantly by 18 days, from 206 days in the pre-shutdown window to 224 days in the post-shutdown window. Across the three windows, the interquartile range (IQR) of review durations decreased slightly, declining from 167 days in the pre-shutdown window to 163 days during the shutdown window, and further to 160.2 days in the post-shutdown window.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eA similar pattern is observed for the December 2018 shutdown. The median review duration for post-shutdown 510(k) filings increased significantly by 20 days, rising from 197 days in the pre-shutdown window to 217 days in the post-shutdown window. As with the 2013 shutdown, the IQR of filing review durations decreased across successive windows, progressing from 154 days prior to the shutdown, to 149 days during the shutdown, and to 147 days in the post-shutdown period. Supplemental figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) presents the same windowed sampling analysis applied to all federal funding gaps from Oct 2013 through Dec 2020.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb) summarizes the quarter overlap analysis for both shutdowns. For the October 2013 shutdown, the Kruskal\u0026ndash;Wallis test indicates that at least one sample differs significantly from the others. The fourth-quarter overlap sample exhibits the largest difference in median review duration relative to the other quarters, with a median of 182 days compared to 206, 209, and 210 days for the first, second, and third quarter samples, respectively. The third-quarter overlap sample has the highest median review duration among all quarters and is significantly greater than the other medians based on the Mann\u0026ndash;Whitney U test. The IQR of review durations increased across the first three quarters, from 160.5 days to 166.78 days and then to 170.8 days, before decreasing to 152.5 days in the fourth quarter.\u003c/p\u003e \u003cp\u003eFor the December 2018 shutdown, the Kruskal\u0026ndash;Wallis test similarly indicates that at least one quarter differs significantly from the others. Median review durations decrease sequentially across the four quarter-overlap samples, from 193 days in the first quarter to 191, 175, and 171 days in the second, third, and fourth quarters, respectively. The first-quarter overlap sample has the highest median review duration and is significantly greater than the other quarter medians according to the Mann\u0026ndash;Whitney U test. The IQR of review durations generally increases across quarters, from 157.5 days in the first quarter to 164, 162.5, and 167 days in the second, third, and fourth quarters, respectively. Supplemental figure S2) presents the same quarter overlap analysis applied to all federal funding gaps from Oct 2013 through Dec 2020.\u003c/p\u003e "},{"header":"Discussion and Conclusions","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003cp\u003eThe windowed sampling analysis indicates that for both government shutdowns examined, filings overlapping either the shutdown itself or the immediate post-shutdown period experienced increased FDA review durations.\u003c/p\u003e \u003cp\u003eFor the October 2013 shutdown, the increase observed in the post-shutdown window corresponds to approximately 105.8% of the shutdown\u0026rsquo;s implied effect, with an 18-day increase in median review duration relative to a 17-day shutdown. When compared to the median review duration in the pre-shutdown window, this represents an approximate 8% increase in filing review time.\u003c/p\u003e \u003cp\u003eFor the December 2018 shutdown, the post-shutdown increase in median review duration corresponds to approximately 57.1% of the shutdown\u0026rsquo;s implied effect, with a 20-day increase in median review duration following a 35-day shutdown. Relative to the pre-shutdown median, this represents an approximately 10% increase in review time. The smaller proportional effect observed for this shutdown suggests a dilution of the shutdown\u0026rsquo;s impact, preventing the median delay from approaching the full length of the shutdown itself.\u003c/p\u003e \u003cp\u003eThe discrepancy between the magnitude of these effects across the two shutdowns appears closely linked to differences in federal employee furlough policies. During the October 2013 shutdown, HHS employees\u0026mdash;including FDA staff\u0026mdash;were fully furloughed, consistent with the near one-to-one correspondence between shutdown duration and median review delay. In contrast, during the December 2018 shutdown, HHS employees were not completely furloughed, and FDA review operations were expected to continue uninterrupted, funded by already submitted user fees. Despite this, filing review durations increased substantially, indicating that there are bottlenecks in the filing review process that were not supported by the temporary appropriations, for instance external consultants, or other federal offices that were not exempted from furlough, or otherwise more directly impacted. Additionally, applicant behavior changes could be contributing to this difference, as shown in supplemental figures S4a-b) highlighting differences in FDA submission frequency between the two shutdowns.\u003c/p\u003e \u003cp\u003eThe quarter overlap analysis further highlights distinct differences in filing behavior across the two shutdowns. For the October 2013 shutdown, filings overlapping the shutdown during their third quarter of review exhibit both the highest median review duration and the greatest variability. This pattern suggests heightened vulnerability to shutdown effects during the third quarter of the review process, a phase that typically corresponds to active interaction between applicants and the FDA through additional information requests and responses. The sharp decline in both median review duration and variance for filings overlapping the shutdown in their fourth quarter suggests that applications which had largely completed substantive correspondence were less affected, and potentially only awaiting final regulatory decisions.\u003c/p\u003e \u003cp\u003eIn contrast, filings overlapping the December 2018 shutdown show a general decrease in review duration for later quarter overlaps. This pattern suggests a different mechanism underlying the shutdown\u0026rsquo;s impact on review timelines, wherein filings further along in the review process were largely insulated from delay. Together, these findings indicate that the timing of a filing within the review lifecycle plays a critical role in determining its susceptibility to shutdown-related disruption, and that the operational characteristics of a shutdown meaningfully shape its downstream effects on regulatory review.\u003c/p\u003e \u003c/div\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eData Sources and Screening\u003c/h2\u003e \u003cp\u003eData for this analysis is entirely derived from the FDA downloadable datasets for medical device filings. [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eFiling Type and Date Filtering\u003c/h3\u003e\n\u003cp\u003eOnly 510(k) filings with a recorded FDA decision date between January 2000 and December 2025 were included. The lower bound reflects limitations in data completeness and reliability prior to widespread digitization and online submission of FDA filings. The upper bound reflects structural constraints of the FDA filing database, which suppresses records for submissions that have not yet reached a final decision, resulting in incomplete reporting for more recent filings.\u003c/p\u003e\n\u003ch3\u003eSampling Methods\u003c/h3\u003e\n\u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) visually represents the two sampling methods used for the windowed sampling analysis and quarter overlap analysis on a sample of representative filings.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFor the windowed sampling analysis, to minimize sampling bias, an independent and temporally symmetric sampling framework was applied. For each government shutdown, three sampling periods were defined: Prior, Spanning, and Post. Each period was equal in duration to the shutdown itself. The Prior and Post periods were offset from the shutdown start and end by a fixed 90 day interval, preserving symmetry across samples. Filings were assigned to one or more sampling periods based on temporal overlap, with filings spanning multiple periods contributing to each relevant distribution.\u003c/p\u003e \u003cp\u003eThis design intentionally oversamples filings that span multiple sampling periods. Because such filings are duplicated across distributions, their relative influence within any single period is diluted. Consequently, differences observed between periods are driven primarily by filings that uniquely intersect a given sampling window, rather than by long-running filings that dominate multiple windows.\u003c/p\u003e \u003cp\u003eA three-month window before and after each shutdown was chosen to balance statistical power with temporal specificity. The Prior period captures baseline FDA review behavior, the Spanning period represents filings directly exposed to the shutdown, and the Post period includes filings that did not overlap the shutdown but may reflect residual or recovery effects within the FDA review process. This offset-window approach is well suited for identifying aggregate shifts in review duration associated with shutdown timing but is less sensitive to short-lived disruptions within longer filing timelines. Supplemental figures S3a-b) indicate the longer term application of this sampling method for the year before and after the subject shutdown period.\u003c/p\u003e \u003cp\u003eFor the quarter overlap analysis each filing overlapping a shutdown was divided into four equal-length quarters representing stages of review progress, to examine more acute shutdown effects coinciding with the development phases of clearance filings. Each quarter was evaluated independently for overlap with the shutdown period, and the full filing review duration was attributed to each overlapping quarter bin.\u003c/p\u003e \u003cp\u003eAs with the windowed analysis, filings overlapping multiple quarters are similarly oversampled, which tends to deflate median review durations for longer shutdowns that intersect more quarters of shorter filings. This method also introduces an inherent limitation: for filing reviews extended by a shutdown, the equal quarter divisions all absorb some of this delay, slightly impacting the overlap positioning of each quarter.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eAll processing of this dataset was performed in Python using the Pandas, Numpy and Scipy data structure and statistical analysis libraries. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eThe Mann\u0026ndash;Whitney U test was used to assess whether the distribution of values in one population differs from that of another population and to evaluate the significance of that difference. [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] The null hypothesis assumes that the two populations have identical distributions, while the alternative hypothesis posits that the median of the post-shutdown (or later-stage) population is greater than that of the pre-shutdown (or earlier-stage) population. This directional alternative hypothesis was selected to test whether later populations exhibit a higher central tendency in review duration than earlier populations.\u003c/p\u003e \u003cp\u003eTo assess differences between review-duration distributions across multiple filing populations defined by their timing relative to a government shutdown, the Kruskal\u0026ndash;Wallis test was applied. [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] This non-parametric omnibus test evaluates whether at least one sample originates from a different distribution than the others and does not assume normality of the underlying data, making it well suited for comparing review durations across independent groups. The Kruskal\u0026ndash;Wallis test was used to identify the presence of statistically significant differences across the quarter-overlap samples, without presupposing the location of those differences. When the Kruskal\u0026ndash;Wallis test indicated a statistically significant result, 1-vs-all comparisons were conducted using the MWU test to identify the specific populations driving the observed differences.\u003c/p\u003e \u003cp\u003eFor each MWU comparison, the following statistical information is reported in the figure annotations: the sample sizes of the populations being compared; the Mann\u0026ndash;Whitney U statistic (U), which quantifies the degree of separation between the two distributions; and the associated p-value (p\u003csub\u003eMWU\u003c/sub\u003e). For each KW test, the associated p-value (p\u003csub\u003eKW\u003c/sub\u003e) was reported\u003c/p\u003e \u003cp\u003eA p-value less than 0.05 was considered statistically significant for all tests.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eThis work was supported through institutional resources provided by the School of Engineering at Santa Clara University; no external funding or monetary support was received. No specific grant number.\u003c/p\u003e\n\u003ch2\u003eAuthor Contributions\u003c/h2\u003e\n\u003cp\u003eKS conceived and designed the study, performed the data analysis, and interpreted the regulatory trends regarding FDA-Shutdown interactions. PA and SP contributed to the interpretation of the results. PA and SP were involved in planning and contributed to the overall direction. KS wrote the manuscript with input from PA and SP. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eCompeting Interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare the following potential conflicts of interest: author SP is employed by Masimo, a global medical technology company, and KS is employed by BioIntelliSense, a medical device company. These affiliations had no involvement in the design, analysis, interpretation, or publication of this analysis. PA declares no competing interests.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eAll data used in this analysis are publicly available through the U.S. Food and Drug Administration (FDA) databases. [27]\u003c/p\u003e\n\u003ch2\u003eCode Availability\u003c/h2\u003e\n\u003cp\u003eThe code supporting this analysis is available upon request from the corresponding author\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHistory, Art \u0026amp; Archives, U.S. House of Representatives. (2026, January 1). \u003cem\u003eFunding gaps and shutdowns in the federal government\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://history.house.gov/Institution/Shutdown/Government-Shutdowns/\u003c/span\u003e\u003cspan address=\"https://history.house.gov/Institution/Shutdown/Government-Shutdowns/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJoint Economic Committee. (2024, December 19). \u003cem\u003eUpdate: The economic costs of a GOP shutdown (Fact sheet)\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.jec.senate.gov/public/index.cfm/democrats/2024/12/update-the-economic-costs-of-a-gop-shutdown\u003c/span\u003e\u003cspan address=\"https://www.jec.senate.gov/public/index.cfm/democrats/2024/12/update-the-economic-costs-of-a-gop-shutdown\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e Joint Economic Committee\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrass, C. T., Brudnick, I. A., McMillion, B. J., Paris, N., Rollins, J. W., \u0026amp; Yeh, B. T. (2018, December 10). \u003cem\u003eShutdown of the federal government: Causes, processes, and effects\u003c/em\u003e (CRS Report No. RL34680). Congressional Research Service. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.congress.gov/crs-product/RL34680\u003c/span\u003e\u003cspan address=\"https://www.congress.gov/crs-product/RL34680\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLabonte, M., \u0026amp; Weinstock, L. R. (2023, September 22). \u003cem\u003eEconomic effects of government shutdowns\u003c/em\u003e (CRS Insight No. IN12248). Congressional Research Service. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://crsreports.congress.gov\u003c/span\u003e\u003cspan address=\"https://crsreports.congress.gov\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMorello, L., Guglielmi, G., Ledford, H., Reardon, S., Tollefson, J., \u0026amp; Witze, A. (2018, January 20). \u003cem\u003eScience in limbo as US government shuts down: Grants are set to dry up, space launches could be delayed and some experiments could be ruined\u003c/em\u003e. Nature. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.nature.com/articles/d41586-018-\u003c/span\u003e\u003cspan address=\"https://www.nature.com/articles/d41586-018-\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e01016-2\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMorello, L., Maxmen, A., Reardon, S., \u0026amp; Witze, A. (2019, January 4). \u003cem\u003eScientists despair as US government shutdown drags on: Space missions can continue to collect data, but thousands of federal researchers are forced to stay at home without pay\u003c/em\u003e. Nature, 565, 141\u0026ndash;142. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/d41586-019-00008-0\u003c/span\u003e\u003cspan address=\"10.1038/d41586-019-00008-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eExecutive Office of the President. (2013, November). \u003cem\u003eImpacts and costs of the October 2013 federal government shutdown\u003c/em\u003e (Report). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://obamawhitehouse.archives.gov/sites/default/files/omb/reports/impacts-and-costs-of-october-2013-federal-government-shutdown-report.pdf\u003c/span\u003e\u003cspan address=\"https://obamawhitehouse.archives.gov/sites/default/files/omb/reports/impacts-and-costs-of-october-2013-federal-government-shutdown-report.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWamsley, L. (2019, January 9). \u003cem\u003eHow is the shutdown affecting America? Let us count the ways\u003c/em\u003e. NPR. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.npr.org/2019/01/09/683642605/how-is-the-shutdown-affecting-america-let-us-count-the-ways\u003c/span\u003e\u003cspan address=\"https://www.npr.org/2019/01/09/683642605/how-is-the-shutdown-affecting-america-let-us-count-the-ways\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eU.S. Food and Drug Administration. (2014, April 4). \u003cem\u003eTypes of communication during the review of medical device submissions: Guidance for industry and Food and Drug Administration staff. U.S. Department of Health and Human Services\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.fda.gov/media/85200/download\u003c/span\u003e\u003cspan address=\"https://www.fda.gov/media/85200/download\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eU.S. Food and Drug Administration. (2022, October 3). \u003cem\u003e510(k) submission process\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.fda.gov/medical-devices/premarket-notification-510k/510k-submission-process\u003c/span\u003e\u003cspan address=\"https://www.fda.gov/medical-devices/premarket-notification-510k/510k-submission-process\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eU.S. Department of Health and Human Services. (2025, September 25). \u003cem\u003eFY 2026 HHS contingency staffing plan for operations in the absence of enacted annual appropriations.\u003c/em\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.hhs.gov/about/budget/fy-2026-hhs-contingency-staffing-plan/index.html\u003c/span\u003e\u003cspan address=\"https://www.hhs.gov/about/budget/fy-2026-hhs-contingency-staffing-plan/index.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eU.S. Food and Drug Administration. (2025, December 29). \u003cem\u003e510(k) premarket notification.\u003c/em\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm\u003c/span\u003e\u003cspan address=\"https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAboy, M., Crespo, C., \u0026amp; Stern, A. (2024). \u003cem\u003eBeyond the 510(k): The regulation of novel moderate-risk medical devices, intellectual property considerations, and innovation incentives in the FDA\u0026rsquo;s De Novo pathway\u003c/em\u003e. npj Digital Medicine, 7, Article 29. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41746-024-01021-y\u003c/span\u003e\u003cspan address=\"10.1038/s41746-024-01021-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePiermatteo, K. (2020, December 15). \u003cem\u003eHow is my medical device classified?\u003c/em\u003e U.S. Food and Drug Administration. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.fda.gov/media/131270/download\u003c/span\u003e\u003cspan address=\"https://www.fda.gov/media/131270/download\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eU.S. Food and Drug Administration. (2014, July 28). \u003cem\u003eThe 510(k) program: Evaluating substantial equivalence in premarket notifications [510(k)]: Guidance for industry and Food and Drug Administration staff.\u003c/em\u003e U.S. Department of Health and Human Services. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.fda.gov/media/82395/download\u003c/span\u003e\u003cspan address=\"https://www.fda.gov/media/82395/download\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBeasley, S. (2013, October 11). \u003cem\u003ePostponed FDA advisory meetings, workshops spark concerns.\u003c/em\u003e FDA Week, 19(41), 1, 4\u0026ndash;5. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.jstor.org/stable/10.2307/26692518\u003c/span\u003e\u003cspan address=\"https://www.jstor.org/stable/10.2307/26692518\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMorello, L. (2013, October 1). \u003cem\u003eUS government shuts down\u003c/em\u003e. Nature, 502, 13\u0026ndash;14. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/502013a\u003c/span\u003e\u003cspan address=\"10.1038/502013a\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMurray, J., \u0026amp; Wilson, C. (2025, September 30). \u003cem\u003ePast government shutdowns: Key resources\u003c/em\u003e (CRS Report No. R41759). Congressional Research Service. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://crsreports.congress.gov\u003c/span\u003e\u003cspan address=\"https://crsreports.congress.gov\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e\u003cem\u003eDepartment of Defense and Labor, Health and Human Services, and Education Appropriations Act, 2019 and Continuing Appropriations Act\u003c/em\u003e, 2019, Pub. L. No. 115\u0026ndash;245, 132 Stat. 2981 (2018). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.congress.gov/115/plaws/publ245/PLAW-115publ245.pdf\u003c/span\u003e\u003cspan address=\"https://www.congress.gov/115/plaws/publ245/PLAW-115publ245.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoza, D. (2019, January 4). \u003cem\u003eFDA expert foresees long-term planning damage due to shutdown\u003c/em\u003e. FDA Week, 25(1), 1, 4\u0026ndash;5. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.jstor.org/stable/10.2307/27045307\u003c/span\u003e\u003cspan address=\"https://www.jstor.org/stable/10.2307/27045307\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHouse Committee on Appropriations. (2025, December 20). \u003cem\u003eCole, Collins deliver bicameral agreement on FY26 funding allocations\u003c/em\u003e [Press release]. U.S. House Committee on Appropriations. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://appropriations.house.gov/news/press-releases/cole-collins-deliver-bicameral-agreement-fy26-funding-allocations\u003c/span\u003e\u003cspan address=\"https://appropriations.house.gov/news/press-releases/cole-collins-deliver-bicameral-agreement-fy26-funding-allocations\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMorello, L. (2018, January 18). \u003cem\u003eWhat a US government shutdown would mean for science\u003c/em\u003e. Nature. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.nature.com/articles/d41586-018-00928-3\u003c/span\u003e\u003cspan address=\"https://www.nature.com/articles/d41586-018-00928-3\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKlock, S. M., \u0026amp; Werner, M. J. (2019, January 25). \u003cem\u003eThe government shutdown and its effects on the FDA\u003c/em\u003e. Holland \u0026amp; Knight Healthcare Blog. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.hklaw.com/en/insights/publications/2019/01/the-government-shutdown-and-its-effects-on-the-fda\u003c/span\u003e\u003cspan address=\"https://www.hklaw.com/en/insights/publications/2019/01/the-government-shutdown-and-its-effects-on-the-fda\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eParasrampuria, S., \u0026amp; Beleche, T. (2023, March). \u003cem\u003eFDA user fees: Examining changes in medical product development and economic benefits\u003c/em\u003e (Issue Brief). Office of the Assistant Secretary for Planning and Evaluation, U.S. Department of Health and Human Services. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/books/NBK603243/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/books/NBK603243/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eU.S. Food and Drug Administration. (2022, October). \u003cem\u003eInformation requests and discipline review letters under the Generic Drug User Fee Amendments (GDUFA): Guidance for industry\u003c/em\u003e (Revision 1). U.S. Department of Health and Human Services. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.fda.gov/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/default.htm\u003c/span\u003e\u003cspan address=\"https://www.fda.gov/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/default.htm\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eU.S. Food and Drug Administration. (2022, October 26). \u003cem\u003eDeveloping and responding to deficiencies in accordance with the least burdensome provisions: Guidance for industry and Food and Drug Administration staff\u003c/em\u003e (Final Level 2 guidance). U.S. Department of Health and Human Services. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.fda.gov/regulatory-information/search-fda-guidance-documents/developing-and-responding-deficiencies-accordance-least-burdensome-provisions\u003c/span\u003e\u003cspan address=\"https://www.fda.gov/regulatory-information/search-fda-guidance-documents/developing-and-responding-deficiencies-accordance-least-burdensome-provisions\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eU.S. Food and Drug Administration. (2021, November 23). \u003cem\u003eDownloadable 510(k) files\u003c/em\u003e. U.S. Department of Health and Human Services. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.fda.gov/medical-devices/510k-clearances/downloadable-510k-files\u003c/span\u003e\u003cspan address=\"https://www.fda.gov/medical-devices/510k-clearances/downloadable-510k-files\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThe pandas development team. (2020). pandas-dev/pandas: \u003cem\u003ePandas (latest)\u003c/em\u003e [Software]. Zenodo. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5281/zenodo.3509134\u003c/span\u003e\u003cspan address=\"10.5281/zenodo.3509134\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHarris, C.R., Millman, K.J., van der Walt, S.J. et al (2020). \u003cem\u003eArray programming with NumPy\u003c/em\u003e. Nature 585, 357\u0026ndash;362. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41586-020-2649-2\u003c/span\u003e\u003cspan address=\"10.1038/s41586-020-2649-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePauli Virtanen, Ralf Gommers, Travis E. Oliphant, and SciPy 1.0 Contributors (2020). \u003cem\u003eSciPy 1.0: Fundamental Algorithms for Scientific Computing in Python\u003c/em\u003e. Nat. Methods, 17(3), 261\u0026ndash;272. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41592-019-0686-2\u003c/span\u003e\u003cspan address=\"10.1038/s41592-019-0686-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKrzywinski, M., Altman, N (2014). \u003cem\u003eNonparametric tests\u003c/em\u003e. Nat. Methods 11, 467\u0026ndash;468. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/nmeth.2937\u003c/span\u003e\u003cspan address=\"10.1038/nmeth.2937\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMann, Henry B.; Whitney, Donald R. (1947). \u003cem\u003eOn a Test of Whether one of Two Random Variables is Stochastically Larger than the Other\u003c/em\u003e. Annals of Mathematical Statistics. 18 (1): 50\u0026ndash;60. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1214/aoms/1177730491\u003c/span\u003e\u003cspan address=\"10.1214/aoms/1177730491\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKruskal; Wallis (1952). \u003cem\u003eUse of ranks in one-criterion variance analysis\u003c/em\u003e. Journal of the American Statistical Association. 47 (260): 583\u0026ndash;621. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/01621459.1952.10483441\u003c/span\u003e\u003cspan address=\"10.1080/01621459.1952.10483441\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"npj-health-systems","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [npj Health Systems](https://www.nature.com/npjhealthsyst/)","snPcode":"44401","submissionUrl":"https://submission.springernature.com/new-submission/44401/3","title":"npj Health Systems","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8718260/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8718260/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Government shutdowns may impose indirect regulatory costs on medical device manufacturers by disrupting FDA review processes. This study examines changes in 510(k) review durations surrounding the 2013 and 2018 U.S. government shutdowns. We identify significant increases in post-shutdown review times and distinct timing-dependent effects across shutdowns, highlighting the sensitivity of regulatory review timelines to operational disruptions and suggest that even partial shutdowns impede medical device review timelines.","manuscriptTitle":"Sensitivity of 510(k) Medical Device Filings to Government Shutdowns: A Brief Communication","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-17 12:29:05","doi":"10.21203/rs.3.rs-8718260/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-08T15:59:51+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-05T19:47:34+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-15T15:07:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"297318918408817265808974047789498635359","date":"2026-02-13T17:15:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"38667823723401149379772023834903009016","date":"2026-02-11T17:23:57+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-11T17:10:57+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-06T04:14:11+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-03T04:08:35+00:00","index":"","fulltext":""},{"type":"submitted","content":"npj Health Systems","date":"2026-01-28T07:24:27+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"npj-health-systems","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [npj Health Systems](https://www.nature.com/npjhealthsyst/)","snPcode":"44401","submissionUrl":"https://submission.springernature.com/new-submission/44401/3","title":"npj Health Systems","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"5b69b578-f468-4170-875e-af1689808e37","owner":[],"postedDate":"February 17th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[{"id":62901959,"name":"Health sciences/Health care"},{"id":62901960,"name":"Health sciences/Medical research"}],"tags":[],"updatedAt":"2026-04-08T16:11:07+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-17 12:29:05","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8718260","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8718260","identity":"rs-8718260","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}