Enabling Fast and Accurate Record Linkage of Large-Scale Health-Related Administrative Databases Through a DNA-Encoded Approach.
Objective Public health research frequently requires the integration of information from different data sources. However, errors in the records and the high computational costs involved make linking large administrative databases using record linkage (RL) methodologies a major challenge. We present...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Swansea University
2022-08-01
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| Series: | International Journal of Population Data Science |
| Subjects: | |
| Online Access: | https://ijpds.org/article/view/1774 |
| _version_ | 1797430656798556160 |
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| author | José Araújo Juan Silva André Costa-Martins Vanderson Sampaio Daniel Castro Robson Souza Jeevan Giddaluru Pablo Ramos Robespierre Pita Maurício Barreto Manoel Netto Helder Nakaya |
| author_facet | José Araújo Juan Silva André Costa-Martins Vanderson Sampaio Daniel Castro Robson Souza Jeevan Giddaluru Pablo Ramos Robespierre Pita Maurício Barreto Manoel Netto Helder Nakaya |
| author_sort | José Araújo |
| collection | DOAJ |
| description | Objective
Public health research frequently requires the integration of information from different data sources. However, errors in the records and the high computational costs involved make linking large administrative databases using record linkage (RL) methodologies a major challenge. We present Tucuxi-BLAST, a versatile tool for probabilistic RL that utilizes a DNA-encoded approach to encrypt, analyze and link massive administrative databases.
Materials and Methods
Tucuxi-BLAST encodes the identification records into DNA. BLASTn algorithm is then used to align the sequences between databases. We tested and benchmarked on a simulated database containing records for 300 million individuals and also on four large administrative databases containing real data on Brazilian patients.
Results
Our method was able to overcome misspellings and typographical errors in administrative databases. In processing the RL of the largest simulated dataset (200k records), the state-of-the art method took 5 days and 7 hours to perform the RL, while Tucuxi-BLAST only took 23 hours. When compared with five existing RL tools applied to a gold-standard dataset from real health-related databases, Tucuxi-BLAST had the highest accuracy and speed.
Discussion
By repurposing genomic tools, researchers are able to perform subject tracing across multiple large epidemiological databases using a regular laptop.
Conclusion
Tucuxi-BLAST can improve data-driven medical research and provide a fast and accurate way to link individual information across several administrative databases.
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| first_indexed | 2024-03-09T09:30:43Z |
| format | Article |
| id | doaj.art-325e6af5426b4105976e9cc40b416d1a |
| institution | Directory Open Access Journal |
| issn | 2399-4908 |
| language | English |
| last_indexed | 2024-03-09T09:30:43Z |
| publishDate | 2022-08-01 |
| publisher | Swansea University |
| record_format | Article |
| series | International Journal of Population Data Science |
| spelling | doaj.art-325e6af5426b4105976e9cc40b416d1a2023-12-02T03:51:50ZengSwansea UniversityInternational Journal of Population Data Science2399-49082022-08-017310.23889/ijpds.v7i3.1774Enabling Fast and Accurate Record Linkage of Large-Scale Health-Related Administrative Databases Through a DNA-Encoded Approach.José Araújo0Juan Silva1André Costa-Martins2Vanderson Sampaio3Daniel Castro4Robson Souza5Jeevan Giddaluru6Pablo Ramos7Robespierre Pita8Maurício Barreto9Manoel Netto10Helder Nakaya11Universidade de São PauloUniversidade de São PauloUniversidade de São PauloFundação de Medicina Tropical Dr. Heitor Vieira DouradoFundação de Vigilância em Saúde do AmazonasUniversidade de São PauloUniversidade de São PauloOswaldo Cruz FoundationOswaldo Cruz FoundationOswaldo Cruz FoundationOswaldo Cruz FoundationUniversity of São PauloObjective Public health research frequently requires the integration of information from different data sources. However, errors in the records and the high computational costs involved make linking large administrative databases using record linkage (RL) methodologies a major challenge. We present Tucuxi-BLAST, a versatile tool for probabilistic RL that utilizes a DNA-encoded approach to encrypt, analyze and link massive administrative databases. Materials and Methods Tucuxi-BLAST encodes the identification records into DNA. BLASTn algorithm is then used to align the sequences between databases. We tested and benchmarked on a simulated database containing records for 300 million individuals and also on four large administrative databases containing real data on Brazilian patients. Results Our method was able to overcome misspellings and typographical errors in administrative databases. In processing the RL of the largest simulated dataset (200k records), the state-of-the art method took 5 days and 7 hours to perform the RL, while Tucuxi-BLAST only took 23 hours. When compared with five existing RL tools applied to a gold-standard dataset from real health-related databases, Tucuxi-BLAST had the highest accuracy and speed. Discussion By repurposing genomic tools, researchers are able to perform subject tracing across multiple large epidemiological databases using a regular laptop. Conclusion Tucuxi-BLAST can improve data-driven medical research and provide a fast and accurate way to link individual information across several administrative databases. https://ijpds.org/article/view/1774DNA-encoded methodrecord linkagegenomic toolsepidemiologyBLAST |
| spellingShingle | José Araújo Juan Silva André Costa-Martins Vanderson Sampaio Daniel Castro Robson Souza Jeevan Giddaluru Pablo Ramos Robespierre Pita Maurício Barreto Manoel Netto Helder Nakaya Enabling Fast and Accurate Record Linkage of Large-Scale Health-Related Administrative Databases Through a DNA-Encoded Approach. International Journal of Population Data Science DNA-encoded method record linkage genomic tools epidemiology BLAST |
| title | Enabling Fast and Accurate Record Linkage of Large-Scale Health-Related Administrative Databases Through a DNA-Encoded Approach. |
| title_full | Enabling Fast and Accurate Record Linkage of Large-Scale Health-Related Administrative Databases Through a DNA-Encoded Approach. |
| title_fullStr | Enabling Fast and Accurate Record Linkage of Large-Scale Health-Related Administrative Databases Through a DNA-Encoded Approach. |
| title_full_unstemmed | Enabling Fast and Accurate Record Linkage of Large-Scale Health-Related Administrative Databases Through a DNA-Encoded Approach. |
| title_short | Enabling Fast and Accurate Record Linkage of Large-Scale Health-Related Administrative Databases Through a DNA-Encoded Approach. |
| title_sort | enabling fast and accurate record linkage of large scale health related administrative databases through a dna encoded approach |
| topic | DNA-encoded method record linkage genomic tools epidemiology BLAST |
| url | https://ijpds.org/article/view/1774 |
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