FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2999189714> ?p ?o ?g. }

• W2999189714 endingPage "e15917" @default.
• W2999189714 startingPage "e15917" @default.
• W2999189714 abstract "Background Many public health departments use record linkage between surveillance data and external data sources to inform public health interventions. However, little guidance is available to inform these activities, and many health departments rely on deterministic algorithms that may miss many true matches. In the context of public health action, these missed matches lead to missed opportunities to deliver interventions and may exacerbate existing health inequities. Objective This study aimed to compare the performance of record linkage algorithms commonly used in public health practice. Methods We compared five deterministic (exact, Stenger, Ocampo 1, Ocampo 2, and Bosh) and two probabilistic record linkage algorithms (fastLink and beta record linkage [BRL]) using simulations and a real-world scenario. We simulated pairs of datasets with varying numbers of errors per record and the number of matching records between the two datasets (ie, overlap). We matched the datasets using each algorithm and calculated their recall (ie, sensitivity, the proportion of true matches identified by the algorithm) and precision (ie, positive predictive value, the proportion of matches identified by the algorithm that were true matches). We estimated the average computation time by performing a match with each algorithm 20 times while varying the size of the datasets being matched. In a real-world scenario, HIV and sexually transmitted disease surveillance data from King County, Washington, were matched to identify people living with HIV who had a syphilis diagnosis in 2017. We calculated the recall and precision of each algorithm compared with a composite standard based on the agreement in matching decisions across all the algorithms and manual review. Results In simulations, BRL and fastLink maintained a high recall at nearly all data quality levels, while being comparable with deterministic algorithms in terms of precision. Deterministic algorithms typically failed to identify matches in scenarios with low data quality. All the deterministic algorithms had a shorter average computation time than the probabilistic algorithms. BRL had the slowest overall computation time (14 min when both datasets contained 2000 records). In the real-world scenario, BRL had the lowest trade-off between recall (309/309, 100.0%) and precision (309/312, 99.0%). Conclusions Probabilistic record linkage algorithms maximize the number of true matches identified, reducing gaps in the coverage of interventions and maximizing the reach of public health action." @default.
• W2999189714 created "2020-01-23" @default.
• W2999189714 creator A5004811457 @default.
• W2999189714 creator A5038833573 @default.
• W2999189714 creator A5040963030 @default.
• W2999189714 creator A5042837659 @default.
• W2999189714 creator A5049883527 @default.
• W2999189714 creator A5062021767 @default.
• W2999189714 creator A5076566436 @default.
• W2999189714 date "2020-04-30" @default.
• W2999189714 modified "2023-10-01" @default.
• W2999189714 title "Comparing Methods for Record Linkage for Public Health Action: Matching Algorithm Validation Study" @default.
• W2999189714 cites W1965346830 @default.
• W2999189714 cites W1975356361 @default.
• W2999189714 cites W1984737236 @default.
• W2999189714 cites W2044280769 @default.
• W2999189714 cites W2046507636 @default.
• W2999189714 cites W2048354844 @default.
• W2999189714 cites W2073471108 @default.
• W2999189714 cites W2114253654 @default.
• W2999189714 cites W2165202360 @default.
• W2999189714 cites W2259332251 @default.
• W2999189714 cites W2272596129 @default.
• W2999189714 cites W2322661047 @default.
• W2999189714 cites W2323184922 @default.
• W2999189714 cites W2324357129 @default.
• W2999189714 cites W2326456351 @default.
• W2999189714 cites W2410948424 @default.
• W2999189714 cites W2558291781 @default.
• W2999189714 cites W2573352467 @default.
• W2999189714 cites W2766573726 @default.
• W2999189714 cites W2887875390 @default.
• W2999189714 cites W2967126995 @default.
• W2999189714 cites W3121361745 @default.
• W2999189714 cites W3146259567 @default.
• W2999189714 cites W4242744113 @default.
• W2999189714 doi "https://doi.org/10.2196/15917" @default.
• W2999189714 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7226047" @default.
• W2999189714 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/32352389" @default.
• W2999189714 hasPublicationYear "2020" @default.
• W2999189714 type Work @default.
• W2999189714 sameAs 2999189714 @default.
• W2999189714 citedByCount "7" @default.
• W2999189714 countsByYear W29991897142021 @default.
• W2999189714 countsByYear W29991897142022 @default.
• W2999189714 countsByYear W29991897142023 @default.
• W2999189714 crossrefType "journal-article" @default.
• W2999189714 hasAuthorship W2999189714A5004811457 @default.
• W2999189714 hasAuthorship W2999189714A5038833573 @default.
• W2999189714 hasAuthorship W2999189714A5040963030 @default.
• W2999189714 hasAuthorship W2999189714A5042837659 @default.
• W2999189714 hasAuthorship W2999189714A5049883527 @default.
• W2999189714 hasAuthorship W2999189714A5062021767 @default.
• W2999189714 hasAuthorship W2999189714A5076566436 @default.
• W2999189714 hasBestOaLocation W29991897141 @default.
• W2999189714 hasConcept C104317684 @default.
• W2999189714 hasConcept C105795698 @default.
• W2999189714 hasConcept C11413529 @default.
• W2999189714 hasConcept C118552586 @default.
• W2999189714 hasConcept C119857082 @default.
• W2999189714 hasConcept C124101348 @default.
• W2999189714 hasConcept C138816342 @default.
• W2999189714 hasConcept C142210648 @default.
• W2999189714 hasConcept C159110408 @default.
• W2999189714 hasConcept C165064840 @default.
• W2999189714 hasConcept C166957645 @default.
• W2999189714 hasConcept C185592680 @default.
• W2999189714 hasConcept C205649164 @default.
• W2999189714 hasConcept C27415008 @default.
• W2999189714 hasConcept C2776361769 @default.
• W2999189714 hasConcept C2779343474 @default.
• W2999189714 hasConcept C2908647359 @default.
• W2999189714 hasConcept C31266012 @default.
• W2999189714 hasConcept C33923547 @default.
• W2999189714 hasConcept C41008148 @default.
• W2999189714 hasConcept C55493867 @default.
• W2999189714 hasConcept C71924100 @default.
• W2999189714 hasConcept C81669768 @default.
• W2999189714 hasConcept C99454951 @default.
• W2999189714 hasConceptScore W2999189714C104317684 @default.
• W2999189714 hasConceptScore W2999189714C105795698 @default.
• W2999189714 hasConceptScore W2999189714C11413529 @default.
• W2999189714 hasConceptScore W2999189714C118552586 @default.
• W2999189714 hasConceptScore W2999189714C119857082 @default.
• W2999189714 hasConceptScore W2999189714C124101348 @default.
• W2999189714 hasConceptScore W2999189714C138816342 @default.
• W2999189714 hasConceptScore W2999189714C142210648 @default.
• W2999189714 hasConceptScore W2999189714C159110408 @default.
• W2999189714 hasConceptScore W2999189714C165064840 @default.
• W2999189714 hasConceptScore W2999189714C166957645 @default.
• W2999189714 hasConceptScore W2999189714C185592680 @default.
• W2999189714 hasConceptScore W2999189714C205649164 @default.
• W2999189714 hasConceptScore W2999189714C27415008 @default.
• W2999189714 hasConceptScore W2999189714C2776361769 @default.
• W2999189714 hasConceptScore W2999189714C2779343474 @default.
• W2999189714 hasConceptScore W2999189714C2908647359 @default.
• W2999189714 hasConceptScore W2999189714C31266012 @default.
• W2999189714 hasConceptScore W2999189714C33923547 @default.

• next