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. 2023 May 27;6(2):ooad036.
doi: 10.1093/jamiaopen/ooad036. eCollection 2023 Jul.

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

Matthew P Smeltzer  1 , Sarah L Reeves  2 , William O Cooper  3   4 , Brandon K Attell  5 , John J Strouse  6 , Clifford M Takemoto  7 , Julie Kanter  8 , Krista Latta  2 , Allison P Plaxco  1 , Robert L Davis  9 , Daniel Hatch  10 , Camila Reyes  11 , Kevin Dombkowski  2 , Angela Snyder  5 , Susan Paulukonis  12 , Ashima Singh  13 , Mariam Kayle  10
Affiliations

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

Matthew P Smeltzer et al. JAMIA Open. .

Abstract

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.

Keywords: data model; sickle cell; surveillance.

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Conflict of interest statement

Dr Matthew Smeltzer has worked as a paid research consultant for the Association of Community Cancer Centers. The findings and conclusions in this publication are those of the authors and do not necessarily represent the views of the North Carolina Department of Health and Human Services, Division of Public Health. No other authors have competing interests to declare.

Figures

Figure 1.
Figure 1.
Process of data compilation, construction of analytic datasets, analysis, and reporting (single- and multi-state projects).
Figure 2.
Figure 2.
Variable groupings (instruments) for SCDC common data model.
See this image and copyright information in PMC

References

    1. Hassell KL. Population estimates of sickle cell disease in the U.S. Am J Prev Med 2010; 38 (4 Suppl): S512–21. - PubMed
    1. Data & Statistics on Sickle Cell Disease | CDC. https://www.cdc.gov/ncbddd/sicklecell/data.html. Accessed May 20, 2022.
    1. Brown JS, Mendelsohn AB, Nam YH, et al.The US Food and Drug Administration Sentinel System: a national resource for a learning health system. J Am Med Inform Assoc 2022; 29 (12): 2191–200. - PMC - PubMed
    1. Brown JS, Holmes JH, Shah K, Hall K, Lazarus R, Platt R.. Distributed health data networks: a practical and preferred approach to multi-institutional evaluations of comparative effectiveness, safety, and quality of care. Med Care 2010; 48 (6 Suppl): S45–51. - PubMed
    1. Kent S, Dawoud D, Jonsson P, et al.Common problems, common data model solutions: evidence generation for health technology assessment. Pharmacoeconomics 2021; 39 (3): 275–85. - PMC - PubMed

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