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Data silos undermine efforts to characterize, predict, and mitigate dementia-related missing person incidents
It is estimated that up to 60% of people living with dementia go missing at least once during the course of their disease. Databases on missing incidents involving people living with dementia are managed in silos with minimal or incomplete data. A national strategy for the collection of data on miss...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9615336/ https://www.ncbi.nlm.nih.gov/pubmed/35678379 http://dx.doi.org/10.1177/08404704221106156 |
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author | Miguel Cruz, Antonio Marshall, Samantha Daum, Christine Perez, Hector Hirdes, John Liu, Lili |
author_facet | Miguel Cruz, Antonio Marshall, Samantha Daum, Christine Perez, Hector Hirdes, John Liu, Lili |
author_sort | Miguel Cruz, Antonio |
collection | PubMed |
description | It is estimated that up to 60% of people living with dementia go missing at least once during the course of their disease. Databases on missing incidents involving people living with dementia are managed in silos with minimal or incomplete data. A national strategy for the collection of data on missing incidents of people living with dementia would optimize time and resources spent on police and search and rescue and enhance chances of saving lives of those who go missing. Such a strategy would be a first step toward developing strategies to prevent future missing person incidents among this population. The objectives of this manuscript are to: (1) describe the issues and challenges related to the lack of integrated data on people living with dementia at risk of going missing, and (2) propose directions to create a national database. |
format | Online Article Text |
id | pubmed-9615336 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-96153362022-10-29 Data silos undermine efforts to characterize, predict, and mitigate dementia-related missing person incidents Miguel Cruz, Antonio Marshall, Samantha Daum, Christine Perez, Hector Hirdes, John Liu, Lili Healthc Manage Forum Original Articles It is estimated that up to 60% of people living with dementia go missing at least once during the course of their disease. Databases on missing incidents involving people living with dementia are managed in silos with minimal or incomplete data. A national strategy for the collection of data on missing incidents of people living with dementia would optimize time and resources spent on police and search and rescue and enhance chances of saving lives of those who go missing. Such a strategy would be a first step toward developing strategies to prevent future missing person incidents among this population. The objectives of this manuscript are to: (1) describe the issues and challenges related to the lack of integrated data on people living with dementia at risk of going missing, and (2) propose directions to create a national database. SAGE Publications 2022-06-09 2022-11 /pmc/articles/PMC9615336/ /pubmed/35678379 http://dx.doi.org/10.1177/08404704221106156 Text en © 2022 The Canadian College of Health Leaders. All rights reserved. https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Original Articles Miguel Cruz, Antonio Marshall, Samantha Daum, Christine Perez, Hector Hirdes, John Liu, Lili Data silos undermine efforts to characterize, predict, and mitigate dementia-related missing person incidents |
title | Data silos undermine efforts to characterize, predict, and mitigate dementia-related missing person incidents |
title_full | Data silos undermine efforts to characterize, predict, and mitigate dementia-related missing person incidents |
title_fullStr | Data silos undermine efforts to characterize, predict, and mitigate dementia-related missing person incidents |
title_full_unstemmed | Data silos undermine efforts to characterize, predict, and mitigate dementia-related missing person incidents |
title_short | Data silos undermine efforts to characterize, predict, and mitigate dementia-related missing person incidents |
title_sort | data silos undermine efforts to characterize, predict, and mitigate dementia-related missing person incidents |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9615336/ https://www.ncbi.nlm.nih.gov/pubmed/35678379 http://dx.doi.org/10.1177/08404704221106156 |
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