Identifying directional properties of spatial point patterns an investigation of two methods

Analyses of spatial point patterns tend to focus on deviations from randomness by either clustering or regularity. One assumption of these analyses implies that the point generating process is equal in all directions. However, the association of the location of points with a process biased in one or more directions is widely neglected due to a lack of appropriate statistical procedures. This is surprising, since patterns generated by directional processes are important in Geography. The purpose of this thesis is to investigate the blunt-triangle method and the third moment method for their potential of identifying directionality in spatial point patterns. A point process model is presented that combines the properties of both clustering and directionality. Realizations of this model are used with the objective of evaluating the two spatial analytical procedures. The blunt-triangle method is based on the comparison of blunt angles between triplets of points to theoretical blunt-triangle statistics. The failure of these statistics to find the characteristics given in the model can be explained by the dependence of the blunt-triangle method on assumptions of randomness. The third moment method examines the distributions of distances and angles between points, and is thus expected to be sensitive to a directional bias in spatial point patterns. It is shown that if the parameters of the procedure are chosen properly, different levels of directionality can be identified. The third moment method can thus be recommended for empirical applications in Geography

The Canadian Chronic Disease Surveillance System: A model for collaborative surveillance

Chronic diseases have a major impact on populations and healthcare systems worldwide. Administrative health data are an ideal resource for chronic disease surveillance because they are population-based and routinely collected. For multi-jurisdictional surveillance, a distributed model is advantageous because it does not require individual-level data to be shared across jurisdictional boundaries. Our objective is to describe the process, structure, benefits, and challenges of a distributed model for chronic disease surveillance across all Canadian provinces and territories (P/Ts) using linked administrative data. The Public Health Agency of Canada (PHAC) established the Canadian Chronic Disease Surveillance System (CCDSS) in 2009 to facilitate standardized, national estimates of chronic disease prevalence, incidence, and outcomes. The CCDSS primarily relies on linked health insurance registration files, physician billing claims, and hospital discharge abstracts. Standardized case definitions and common analytic protocols are applied to the data for each P/T; aggregate data are shared with PHAC and summarized for reports and open access data initiatives. Advantages of this distributed model include: it uses the rich data resources available in all P/Ts; it supports chronic disease surveillance capacity building in all P/Ts; and changes in surveillance methodology can be easily developed by PHAC and implemented by the P/Ts. However, there are challenges: heterogeneity in administrative databases across jurisdictions and changes in data quality over time threaten the production of standardized disease estimates; a limited set of databases are common to all P/Ts, which hinders potential CCDSS expansion; and there is a need to balance comprehensive reporting with P/T disclosure requirements to protect privacy. The CCDSS distributed model for chronic disease surveillance has been successfully implemented and sustained by PHAC and its P/T partners. Many lessons have been learned about national surveillance involving jurisdictions that are heterogeneous with respect to healthcare databases, expertise and analytical capacity, population characteristics, and priorities

Estimation de l’exhaustivité des demandes de remboursement des médecins dans une optique de détermination des cas de diabète : étude menée dans plusieurs provinces

IntroductionDes recherches antérieures ont suggéré que le mode de rémunération des médecins peut avoir une influence sur l’exhaustivité des demandes de remboursement lors de l’estimation des maladies chroniques. Le but de cette étude est d’estimer l’exhaustivité des données sur la facturation des médecins dans l’optique de déterminer des cas de diabète. MéthodologieNous avons utilisé les données administratives de huit provinces canadiennes pour la période du 1er avril 2014 au 31 mars 2016. Nous avons divisé la cohorte de patients en deux groupes mutuellement exclusifs en fonction du mode de rémunération de leur médecin : médecins rémunérés à l’acte pour ceux payés uniquement de cette façon et médecins non rémunérés à l’acte pour les autres. À l’aide des données sur les ordonnances de médicaments hypoglycémiants (source de nos données de référence), nous avons évalué si les cas de maladie avaient été déterminés avec la même exactitude en fonction du mode de rémunération. Nous avons ensuite corrigé les taux d’incidence du diabète afin d’optimiser l’exhaustivité des cas déterminés. RésultatsLa cohorte comprenait 86 110 patients. Dans l’ensemble, des proportions égales de patients ont reçu leurs médicaments hypoglycémiants de la part de médecins rémunérés à l’acte et de médecins non rémunérés à l’acte. Globalement, le mode de rémunération des médecins a eu peu d’effet sur le pourcentage de cas de diabète omis (14,8 % chez les médecins rémunérés à l’acte contre 12,2 % chez les médecins non rémunérés à l’acte). Toutefois, la différence de cas omis entre les médecins rémunérés à l’acte et ceux non rémunérés à l’acte était très variable d’une province à l’autre, allant de -1,0 % en Nouvelle-Écosse à 29,9 % à Terre-Neuve-et-Labrador. La différence entre les taux observés d’incidence de la maladie et les taux corrigés était également variable d’une province à l’autre, allant de 22 % à l’Île-du-Prince-Édouard à 4 % en Nouvelle-Écosse. ConclusionLa différence entre le nombre de cas omis selon le mode de rémunération des médecins est variable d’une province à l’autre. Cette perte de données contribue probablement à une sous-estimation de l’incidence de la maladie. Il serait possible d’appliquer la méthode que nous avons utilisée à d’autres maladies chroniques pour lesquelles des données de traitement pharmacologique pourraient servir de données de référence

Estimating the completeness of physician billing claims for diabetes case ascertainment: a multiprovince investigation

IntroductionPrevious research has suggested that how physicians are paid may affect the completeness of billing claims for estimating chronic disease. The purpose of this study is to estimate the completeness of physician billings for diabetes case ascertainment. MethodsWe used administrative data from eight Canadian provinces covering the period 1 April 2014 to 31 March 2016. The patient cohort was stratified into two mutually exclusive groups based on their physician remuneration type: fee-for-service (FFS), for those paid only on that basis; and non-fee-for-service (NFFS). Using diabetes prescription drug data as our reference data source, we evaluated whether completeness of disease case ascertainment varied with payment type. Diabetes incidence rates were then adjusted for completeness of ascertainment. ResultsThe cohort comprised 86 110 patients. Overall, equal proportions received their diabetes medications from FFS and NFFS physicians. Overall, physician payment method had little impact upon the percentage of missed diabetes cases (FFS, 14.8%; NFFS, 12.2%). However, the difference in missed cases between FFS and NFFS varied widely by province, ranging from −1.0% in Nova Scotia to 29.9% in Newfoundland and Labrador. The difference between the observed and adjusted disease incidence rates also varied by province, ranging from 22% in Prince Edward Island to 4% in Nova Scotia. ConclusionThe difference in the loss of cases by physician remuneration method varied across jurisdictions. This loss may contribute to an underestimation of disease incidence. The method we used could be applied to other chronic diseases for which drug therapy could serve as reference data source