Matthew P Smeltzer, Sarah L Reeves, William O Cooper, Brandon K Attell, John J Strouse, Clifford M Takemoto, Julie Kanter, Krista Latta, Allison P Plaxco, Robert L Davis, Daniel Hatch, Camila Reyes, Kevin Dombkowski, Angela Snyder, Susan Paulukonis, Ashima Singh, Mariam Kayle
{"title":"镰状细胞病监测的通用数据模型:考虑和影响。","authors":"Matthew P Smeltzer, Sarah L Reeves, William O Cooper, Brandon K Attell, John J Strouse, Clifford M Takemoto, Julie Kanter, Krista Latta, Allison P Plaxco, Robert L Davis, Daniel Hatch, Camila Reyes, Kevin Dombkowski, Angela Snyder, Susan Paulukonis, Ashima Singh, Mariam Kayle","doi":"10.1093/jamiaopen/ooad036","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>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.</p><p><strong>Materials and methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Discussion and conclusion: </strong>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.</p>","PeriodicalId":36278,"journal":{"name":"JAMIA Open","volume":"6 2","pages":"ooad036"},"PeriodicalIF":2.5000,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/dc/b2/ooad036.PMC10224800.pdf","citationCount":"1","resultStr":"{\"title\":\"Common data model for sickle cell disease surveillance: considerations and implications.\",\"authors\":\"Matthew P Smeltzer, Sarah L Reeves, William O Cooper, Brandon K Attell, John J Strouse, Clifford M Takemoto, Julie Kanter, Krista Latta, Allison P Plaxco, Robert L Davis, Daniel Hatch, Camila Reyes, Kevin Dombkowski, Angela Snyder, Susan Paulukonis, Ashima Singh, Mariam Kayle\",\"doi\":\"10.1093/jamiaopen/ooad036\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>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.</p><p><strong>Materials and methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Discussion and conclusion: </strong>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.</p>\",\"PeriodicalId\":36278,\"journal\":{\"name\":\"JAMIA Open\",\"volume\":\"6 2\",\"pages\":\"ooad036\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2023-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/dc/b2/ooad036.PMC10224800.pdf\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JAMIA Open\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1093/jamiaopen/ooad036\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"HEALTH CARE SCIENCES & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JAMIA Open","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/jamiaopen/ooad036","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
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 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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