{"title":"评估基于食品药品管理局制造商和用户设施设备经验数据的研究的可重复性。","authors":"Xinyu Li, Yubo Feng, Yang Gong, You Chen","doi":"10.1097/PTS.0000000000001220","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>This article aims to assess the reproducibility of Manufacturer and User Facility Device Experience (MAUDE) data-driven studies by analyzing the data queries used in their research processes.</p><p><strong>Methods: </strong>Studies using MAUDE data were sourced from PubMed by searching for \"MAUDE\" or \"Manufacturer and User Facility Device Experience\" in titles or abstracts. We manually chose articles with executable queries. The reproducibility of each query was assessed by replicating it in the MAUDE Application Programming Interface. The reproducibility of a query is determined by a reproducibility coefficient that ranges from 0.95 to 1.05. This coefficient is calculated by comparing the number of medical device reports (MDRs) returned by the reproduced queries to the number of reported MDRs in the original studies. We also computed the reproducibility ratio, which is the fraction of reproducible queries in subgroups divided by the query complexity, the device category, and the presence of a data processing flow.</p><p><strong>Results: </strong>As of August 8, 2022, we identified 523 articles from which 336 contained queries, and 60 of these were executable. Among these, 14 queries were reproducible. Queries using a single field like product code, product class, or brand name showed higher reproducibility (50%, 33.3%, 31.3%) compared with other fields (8.3%, P = 0.037). Single-category device queries exhibited a higher reproducibility ratio than multicategory ones, but without statistical significance (27.1% versus 8.3%, P = 0.321). Studies including a data processing flow had a higher reproducibility ratio than those without, although this difference was not statistically significant (42.9% versus 17.4%, P = 0.107).</p><p><strong>Conclusions: </strong>Our findings indicate that the reproducibility of queries in MAUDE data-driven studies is limited. Enhancing this requires the development of more effective MAUDE data query strategies and improved application programming interfaces.</p>","PeriodicalId":48901,"journal":{"name":"Journal of Patient Safety","volume":" ","pages":"e45-e58"},"PeriodicalIF":1.7000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Assessing the Reproducibility of Research Based on the Food and Drug Administration Manufacturer and User Facility Device Experience Data.\",\"authors\":\"Xinyu Li, Yubo Feng, Yang Gong, You Chen\",\"doi\":\"10.1097/PTS.0000000000001220\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>This article aims to assess the reproducibility of Manufacturer and User Facility Device Experience (MAUDE) data-driven studies by analyzing the data queries used in their research processes.</p><p><strong>Methods: </strong>Studies using MAUDE data were sourced from PubMed by searching for \\\"MAUDE\\\" or \\\"Manufacturer and User Facility Device Experience\\\" in titles or abstracts. We manually chose articles with executable queries. The reproducibility of each query was assessed by replicating it in the MAUDE Application Programming Interface. The reproducibility of a query is determined by a reproducibility coefficient that ranges from 0.95 to 1.05. This coefficient is calculated by comparing the number of medical device reports (MDRs) returned by the reproduced queries to the number of reported MDRs in the original studies. We also computed the reproducibility ratio, which is the fraction of reproducible queries in subgroups divided by the query complexity, the device category, and the presence of a data processing flow.</p><p><strong>Results: </strong>As of August 8, 2022, we identified 523 articles from which 336 contained queries, and 60 of these were executable. Among these, 14 queries were reproducible. Queries using a single field like product code, product class, or brand name showed higher reproducibility (50%, 33.3%, 31.3%) compared with other fields (8.3%, P = 0.037). Single-category device queries exhibited a higher reproducibility ratio than multicategory ones, but without statistical significance (27.1% versus 8.3%, P = 0.321). Studies including a data processing flow had a higher reproducibility ratio than those without, although this difference was not statistically significant (42.9% versus 17.4%, P = 0.107).</p><p><strong>Conclusions: </strong>Our findings indicate that the reproducibility of queries in MAUDE data-driven studies is limited. Enhancing this requires the development of more effective MAUDE data query strategies and improved application programming interfaces.</p>\",\"PeriodicalId\":48901,\"journal\":{\"name\":\"Journal of Patient Safety\",\"volume\":\" \",\"pages\":\"e45-e58\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2024-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Patient Safety\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1097/PTS.0000000000001220\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/3/12 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"HEALTH CARE SCIENCES & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Patient Safety","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/PTS.0000000000001220","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/3/12 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
Assessing the Reproducibility of Research Based on the Food and Drug Administration Manufacturer and User Facility Device Experience Data.
Objective: This article aims to assess the reproducibility of Manufacturer and User Facility Device Experience (MAUDE) data-driven studies by analyzing the data queries used in their research processes.
Methods: Studies using MAUDE data were sourced from PubMed by searching for "MAUDE" or "Manufacturer and User Facility Device Experience" in titles or abstracts. We manually chose articles with executable queries. The reproducibility of each query was assessed by replicating it in the MAUDE Application Programming Interface. The reproducibility of a query is determined by a reproducibility coefficient that ranges from 0.95 to 1.05. This coefficient is calculated by comparing the number of medical device reports (MDRs) returned by the reproduced queries to the number of reported MDRs in the original studies. We also computed the reproducibility ratio, which is the fraction of reproducible queries in subgroups divided by the query complexity, the device category, and the presence of a data processing flow.
Results: As of August 8, 2022, we identified 523 articles from which 336 contained queries, and 60 of these were executable. Among these, 14 queries were reproducible. Queries using a single field like product code, product class, or brand name showed higher reproducibility (50%, 33.3%, 31.3%) compared with other fields (8.3%, P = 0.037). Single-category device queries exhibited a higher reproducibility ratio than multicategory ones, but without statistical significance (27.1% versus 8.3%, P = 0.321). Studies including a data processing flow had a higher reproducibility ratio than those without, although this difference was not statistically significant (42.9% versus 17.4%, P = 0.107).
Conclusions: Our findings indicate that the reproducibility of queries in MAUDE data-driven studies is limited. Enhancing this requires the development of more effective MAUDE data query strategies and improved application programming interfaces.
期刊介绍:
Journal of Patient Safety (ISSN 1549-8417; online ISSN 1549-8425) is dedicated to presenting research advances and field applications in every area of patient safety. While Journal of Patient Safety has a research emphasis, it also publishes articles describing near-miss opportunities, system modifications that are barriers to error, and the impact of regulatory changes on healthcare delivery. This mix of research and real-world findings makes Journal of Patient Safety a valuable resource across the breadth of health professions and from bench to bedside.