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Background and objectivesThere is a limited appreciation of the epidemiology of dialysis-receiving AKI in children. The primary objective of the study was to evaluate changes in the incidence of dialysis-receiving AKI among children over a period of 20 years in Ontario, Canada. The secondary objectives were to assess temporal trends in the utilization of various dialysis modalities and 30-day mortality among children with dialysis-receiving AKI.Design, setting, participants, & measurementsAll children (29 days to 18 years) who received their first dialysis for AKI between 1996 and 2015 were identified from healthcare administrative databases. Those who received dialysis for ESKD, inborn errors of metabolism, and poisonings were excluded. The incidence rates of dialysis-receiving AKI were reported annually. The Cochran—Armitage test was used to assess trends in the incidence and short-term mortality after dialysis-receiving AKI.ResultsWe identified 1394 children treated with dialysis for AKI during a hospital stay. There was a significant increase in the incidence of dialysis-receiving AKI among hospitalized children from 1996 (0.58 per 1000 person-years) to 2015 (0.65 per 1000 person-years) (P=0.01). The use of continuous kidney replacement therapy and intermittent hemodialysis increased whereas the relative use of peritoneal dialysis declined over time. Thirty-day mortality rates after dialysis-receiving AKI increased from 14% to 25% between 1996 and 2009 and reduced to 19% in the more recent years (P=0.03).ConclusionsIn Ontario, the incidence of dialysis-receiving AKI among children has increased between 1996 and 2015. The use of peritoneal dialysis for AKI has declined and the short-term mortality after dialysis-receiving AKI has increased.

Introduction: Changes in physician reimbursement policies may hinder the collection of billing claims in administrative data; this can result in biased estimates of disease prevalence and incidence. However, the magnitude of data loss is largely unknown. The purpose of this study was to estimate completeness of capture of disease cases for Manitoba physicians paid by fee-for-service (FFS) and non-fee-for-service (NFFS) methods.

ObjectivesElectronic physician claims databases are widely used for chronic disease research and surveillance, but quality of the data may vary with a number of physician characteristics, including payment method. The objectives were to develop a prediction model for the number of prevalent diabetes cases in fee-for-service (FFS) electronic physician claims databases and apply it to estimate cases among non-FFS (NFFS) physicians, for whom claims data are often incomplete.DesignA retrospective observational cohort design was adopted.SettingData from the Canadian province of Newfoundland and Labrador were used to construct the prediction model and data from the province of Manitoba were used to externally validate the model.ParticipantsA cohort of diagnosed diabetes cases was ascertained from physician claims, insured resident registry and hospitalisation records. A cohort of FFS physicians who were responsible for the diagnosis was ascertained from physician claims and registry data.Primary and secondary outcome measuresA generalised linear model with a γ distribution was used to model the number of diabetes cases per FFS physician as a function of physician characteristics. The expected number of diabetes cases per NFFS physician was estimated.ResultsThe diabetes case cohort consisted of 31 714 individuals; the mean cases per FFS physician was 75.5 (median=49.0). Sex and years since specialty licensure were significantly associated (p<0.05) with the number of cases per physician. Applying the prediction model to NFFS physician registry data resulted in an estimate of 18 546 cases; only 411 were observed in claims data. The model demonstrated face validity in an independent data set.ConclusionsComparing observed and predicted disease cases is a useful and generalisable approach to assess the quality of electronic databases for population-based research and surveillance.

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Introduction Patterns of multimorbidity, the co-occurrence of two or more chronic diseases, may not be constant across populations. Our study objectives were to compare prevalence estimates of multimorbidity in the Aboriginal population in Canada and a matched non-Aboriginal Caucasian population and identify the chronic diseases that cluster in these groups. Methods We used data from the 2005 Canadian Community Health Survey (CCHS) to identify adult (≥ 18 years) respondents who self-identified as Aboriginal or non-Aboriginal Caucasian origin and reported having 2 or more of the 15 most prevalent chronic conditions measured in the CCHS. Aboriginal respondents who met these criteria were matched on sex and age to non-Aboriginal Caucasian respondents. Analyses were stratified by age (18–54 years and ≥ 55 years). Prevalence was estimated using survey weights. Latent class analysis (LCA) was used to identify disease clusters. Results A total of 1642 Aboriginal respondents were matched to the same number of non-Aboriginal Caucasian respondents. Overall, 38.9% (95% CI: 36.5%–41.3%) of Aboriginal respondents had two or more chronic conditions compared to 30.7% (95% CI: 28.9%–32.6%) of non-Aboriginal respondents. Comparisons of LCA results revealed that three or four clusters provided the best fit to the data. There were similarities in the diseases that tended to co-occur amongst older groups in both populations, but differences existed between the populations amongst the younger groups. Conclusion We found a small group of younger Aboriginal respondents who had complex co-occurring chronic diseases; these individuals may especially benefit from disease management programs.

Healthcare pathways are important to measure because they are expected to affect outcomes. However, they are challenging to define because patients exhibit heterogeneity in their use of healthcare services. The objective of this study was to identify and describe healthcare pathways during episodes of chronic obstructive pulmonary disease (COPD) exacerbations.Linked administrative databases from Saskatchewan, Canada were used to identify a cohort of newly diagnosed COPD patients and their episodes of healthcare use for disease exacerbations. Latent class analysis (LCA) was used to classify the cohort into homogeneous pathways using indicators of respiratory-related hospitalizations, emergency department (ED) visits, general and specialist physician visits, and outpatient prescription drug dispensations. Multinomial logistic regression models tested patients’ demographic and disease characteristics associated with pathway group membership. The most frequent healthcare contact sequences in each pathway were described. Tests of mean costs across groups were conducted using a model-based approach with χ2 statistics.LCA identified 3 distinct pathways for patients with hospital- (n = 963) and ED-initiated (n = 364) episodes. For the former, pathway group 1 members followed complex pathways in which multiple healthcare services were repeatedly used and incurred substantially higher costs than patients in the other pathway groups. For patients with an ED-initiated episode, pathway group 1 members also had higher costs than other groups. Pathway groups differed with respect to patient demographic and disease characteristics. A minority of patients were discharged from ED or hospital, but did not have any follow-up care during the remainder of their episode.Patients who followed complex pathways could benefit from case management interventions to streamline their journeys through the healthcare system. The minority of patients whose pathways were not consistent with recommended follow-up care should be further investigated to fully align COPD treatment in the province with recommended care practices.