Pediatr Blood Cancer. 2014 Aug 30. doi: 10.1002/pbc.25208. [Epub ahead of print]
Population based surveillance in sickle cell disease: Methods, findings and implications from the California registry and surveillance system in hemoglobinopathies project (RuSH).
Abstract
BACKGROUND:
There are no population-based surveillance systems to determine prevalence, impact or outcomes in sickle cell disease (SCD). Estimates of the SCD population in California range broadly from 4,500 to 7,000, and little is known about their health status, health care utilization or health outcomes. A surveillance strategy was implemented using diverse data sources to develop a multi-dimensional, state-based surveillance system for SCD that includes adults and children and describes utilization, treatment and outcomes.
PROCEDURE:
Data from California newborn screening, inpatient and emergency room records, Medi-Cal/Medicaid claims and two SCD special care centers were collected for 2004-2008. A multi-step, iterative linkage process was used to link and de-duplicate these data sources, and case definitions were used to categorize cases.
RESULTS:
After linking and de-duplicating, there were 1,975 confirmed cases of SCD, 3,159 probable cases as well as 8,024 possible cases. Among individual data sources, newborn screening and data from clinics contributed the greatest number of unique cases to the total. Select analyses of utilization and treatments for the population are described.
CONCLUSIONS:
Using linked existing data sources, an estimate of the statewide count of the SCD population is possible. The approach can be used to create an in-depth health status profile of the affected population by aggregating utilization, treatment, and outcomes data including mortality and morbidity information. This effort sets the stage for development of an on-going, state-based surveillance system. Pediatr Blood Cancer © 2014 Wiley Periodicals, Inc.
© 2014 Wiley Periodicals, Inc.
KEYWORDS:
California; data linkage; public health surveillance; sickle cell disease
- PMID:
- 25176145
- [PubMed - as supplied by publisher]
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