Validation of case definition algorithms for the ascertainment of congenital anomalies.

BACKGROUND: Congenital anomalies (CA) are one of the leading causes of infant mortality and long-term disability. Many jurisdictions rely on health administrative data to monitor these conditions. Case definition algorithms can be used to monitor CA; however, validation of these algorithms is needed to understand the strengths and limitations of the data. This study aimed to validate case definition algorithms used in a CA surveillance system in British Columbia (BC), Canada. METHODS: A cohort of births between March 2000 and April 2002 in BC was linked to the Health Status Registry (HSR) and the BC Congenital Anomalies Surveillance System (BCCASS) to identify cases and non-cases of specific anomalies within each surveillance system. Measures of algorithm performance were calculated for each CA using the HSR as the reference standard. Agreement between both databases was calculated using kappa coefficient. The modified Standards for Reporting Diagnostic Accuracy guidelines were used to enhance the quality of the study. RESULTS: Measures of algorithm performance varied by condition. Positive predictive value (PPV) ranged between approximately 73%-100%. Sensitivity was lower than PPV for most conditions. Internal congenital anomalies or conditions not easily identifiable at birth had the lowest sensitivity. Specificity and negative predictive value exceeded 99% for all algorithms. CONCLUSION: Case definition algorithms may be used to monitor CA at the population level. Accuracy of algorithms is higher for conditions that are easily identified at birth. Jurisdictions with similar administrative data may benefit from using validated case definitions for CA surveillance as this facilitates cross-jurisdictional comparison.

Implementation of the BC Congenital Anomalies Surveillance System (BCCASS).

SETTING: Congenital anomalies (CAs) can cause lifelong morbidity and accounted for 23.2% of infant deaths from 2003 to 2007. In British Columbia (BC), surveillance of CAs has been irregular since the early 2000s. To enhance CAs surveillance in BC, the Public Health Agency of Canada has provided funding for the implementation of the BC Congenital Anomalies Surveillance System (BCCASS). INTERVENTION: BCCASS is a population-based surveillance system. The system leverages existing administrative data sources that capture information regarding vital events, disease status, drug prescription, and healthcare utilization. The system uses a series of algorithms to capture specific CAs diagnoses, some of which are further validated with the support of the Provincial Advisory Committee. This Advisory Committee is a multi-stakeholder coalition that includes the BC Office of the Provincial Health Officer, subject matter experts, data partners, users, and academia, and acts to provide support, expertise, and strategic guidance to BCCASS. OUTCOMES: Through BCCASS, prevalence and historical trends for 35 CAs in BC are available. Information pertaining to maternal place of residence, risk, and protective factors can be used for association studies such as links to environmental hazards and cluster analysis. IMPLICATIONS: BCCASS is a cost-effective and sustainable system that leverages existing data sources necessary to understand the overall burden of CAs across the BC population. This is fundamental to support data-driven decisions around policy development, program planning, and evaluation of preventive measures. Strong coalitions with stakeholders are instrumental to ensure successful implementation and expansion in the future.

RéSUME: CONTEXTE: Les anomalies congénitales (AC) peuvent causer une morbidité à vie et ont représenté 23,2 % des décès infantiles de 2003 à 2007. En Colombie-Britannique, la surveillance des AC a été irrégulière depuis le début des années 2000. Afin d'améliorer la surveillance de l'AC en Colombie-Britannique, l'Agence de la santé publique du Canada a financé la mise en œuvre du BC Congenital Anomalies Surveillance System (BCCASS). INTERVENTION: Le BCCASS est un système de surveillance basé sur la population. Le système exploite les sources de données administratives existantes qui capturent des informations concernant les événements vitaux, les diagnostics médicaux, la prescription de médicaments et l'utilisation des soins de santé. Le système utilise une série d'algorithmes pour saisir des diagnostics d'AC spécifiques, dont certains sont ensuite validés avec le soutien du Comité consultatif provincial. Ce comité consultatif est une coalition multipartite entre le bureau de l'Agence de santé provincial de la Colombie-Britannique, des experts en la matière, des partenaires de données, des utilisateurs et des universitaires, qui agit pour fournir un soutien, une expertise et des conseils stratégiques au BCCASS. RéSULTATS: Par le BCCASS, la prévalence et les tendances historiques pour 35 AC en Colombie-Britannique sont disponibles. Les informations relatives au lieu de résidence de la mère, aux facteurs de risque et de protection peuvent être utilisées pour des études d'association telles que les liens avec les facteurs environnementaux et l'analyse typologique. INCIDENCES: Le BCCASS est un système rentable et durable qui tire parti des sources de données existantes nécessaires pour comprendre le fardeau global des CA dans l'ensemble de la population de la Colombie-Britannique. Ceci est fondamental pour soutenir les décisions fondées sur les données concernant l'élaboration de politiques, la planification de programmes et l'évaluation des mesures préventives. Des coalitions solides avec les parties prenantes sont essentielles pour assurer une mise en œuvre et une expansion réussie dans l'avenir.