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Common data model for sickle cell disease surveillance: considerations and implications

OBJECTIVE: Population-level data on sickle cell disease (SCD) are sparse in the United States. The Centers for Disease Control and Prevention (CDC) is addressing the need for SCD surveillance through state-level Sickle Cell Data Collection Programs (SCDC). The SCDC developed a pilot common informati...

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Autores principales: Smeltzer, Matthew P, Reeves, Sarah L, Cooper, William O, Attell, Brandon K, Strouse, John J, Takemoto, Clifford M, Kanter, Julie, Latta, Krista, Plaxco, Allison P, Davis, Robert L, Hatch, Daniel, Reyes, Camila, Dombkowski, Kevin, Snyder, Angela, Paulukonis, Susan, Singh, Ashima, Kayle, Mariam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10224800/
https://www.ncbi.nlm.nih.gov/pubmed/37252051
http://dx.doi.org/10.1093/jamiaopen/ooad036
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author Smeltzer, Matthew P
Reeves, Sarah L
Cooper, William O
Attell, Brandon K
Strouse, John J
Takemoto, Clifford M
Kanter, Julie
Latta, Krista
Plaxco, Allison P
Davis, Robert L
Hatch, Daniel
Reyes, Camila
Dombkowski, Kevin
Snyder, Angela
Paulukonis, Susan
Singh, Ashima
Kayle, Mariam
author_facet Smeltzer, Matthew P
Reeves, Sarah L
Cooper, William O
Attell, Brandon K
Strouse, John J
Takemoto, Clifford M
Kanter, Julie
Latta, Krista
Plaxco, Allison P
Davis, Robert L
Hatch, Daniel
Reyes, Camila
Dombkowski, Kevin
Snyder, Angela
Paulukonis, Susan
Singh, Ashima
Kayle, Mariam
author_sort Smeltzer, Matthew P
collection PubMed
description OBJECTIVE: Population-level data on sickle cell disease (SCD) are sparse in the United States. The Centers for Disease Control and Prevention (CDC) is addressing the need for SCD surveillance through state-level Sickle Cell Data Collection Programs (SCDC). The SCDC developed a pilot common informatics infrastructure to standardize processes across states. MATERIALS AND METHODS: We describe the process for establishing and maintaining the proposed common informatics infrastructure for a rare disease, starting with a common data model and identify key data elements for public health SCD reporting. RESULTS: The proposed model is constructed to allow pooling of table shells across states for comparison. Core Surveillance Data reports are compiled based on aggregate data provided by states to CDC annually. DISCUSSION AND CONCLUSION: We successfully implemented a pilot SCDC common informatics infrastructure to strengthen our distributed data network and provide a blueprint for similar initiatives in other rare diseases.
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spelling pubmed-102248002023-05-29 Common data model for sickle cell disease surveillance: considerations and implications Smeltzer, Matthew P Reeves, Sarah L Cooper, William O Attell, Brandon K Strouse, John J Takemoto, Clifford M Kanter, Julie Latta, Krista Plaxco, Allison P Davis, Robert L Hatch, Daniel Reyes, Camila Dombkowski, Kevin Snyder, Angela Paulukonis, Susan Singh, Ashima Kayle, Mariam JAMIA Open Brief Communications OBJECTIVE: Population-level data on sickle cell disease (SCD) are sparse in the United States. The Centers for Disease Control and Prevention (CDC) is addressing the need for SCD surveillance through state-level Sickle Cell Data Collection Programs (SCDC). The SCDC developed a pilot common informatics infrastructure to standardize processes across states. MATERIALS AND METHODS: We describe the process for establishing and maintaining the proposed common informatics infrastructure for a rare disease, starting with a common data model and identify key data elements for public health SCD reporting. RESULTS: The proposed model is constructed to allow pooling of table shells across states for comparison. Core Surveillance Data reports are compiled based on aggregate data provided by states to CDC annually. DISCUSSION AND CONCLUSION: We successfully implemented a pilot SCDC common informatics infrastructure to strengthen our distributed data network and provide a blueprint for similar initiatives in other rare diseases. Oxford University Press 2023-05-27 /pmc/articles/PMC10224800/ /pubmed/37252051 http://dx.doi.org/10.1093/jamiaopen/ooad036 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Brief Communications
Smeltzer, Matthew P
Reeves, Sarah L
Cooper, William O
Attell, Brandon K
Strouse, John J
Takemoto, Clifford M
Kanter, Julie
Latta, Krista
Plaxco, Allison P
Davis, Robert L
Hatch, Daniel
Reyes, Camila
Dombkowski, Kevin
Snyder, Angela
Paulukonis, Susan
Singh, Ashima
Kayle, Mariam
Common data model for sickle cell disease surveillance: considerations and implications
title Common data model for sickle cell disease surveillance: considerations and implications
title_full Common data model for sickle cell disease surveillance: considerations and implications
title_fullStr Common data model for sickle cell disease surveillance: considerations and implications
title_full_unstemmed Common data model for sickle cell disease surveillance: considerations and implications
title_short Common data model for sickle cell disease surveillance: considerations and implications
title_sort common data model for sickle cell disease surveillance: considerations and implications
topic Brief Communications
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10224800/
https://www.ncbi.nlm.nih.gov/pubmed/37252051
http://dx.doi.org/10.1093/jamiaopen/ooad036
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