Geographic variation in preventable hospitalisations across Canada: a cross-sectional study

• Published in: BMJ Open
• Main Authors: Wilk, Piotr, Ali, Shehzad, Anderson, Kelly K, Clark, Andrew F, Cooke, Martin, Frisbee, Stephanie J, Gilliland, Jason, Haan, Michael, Harris, Stewart, Kiarasi, Soushyant, Maltby, Alana, Norozi, Kambiz, Petrella, Robert, Sarma, Sisira, Singh, Sarah S, Stranges, Saverio, Thind, Amardeep
• Format: Text
• Language: English
• Published: BMJ Publishing Group Ltd 2020
• Subjects: Epidemiology; Canada; Nunavut
• Online Access: http://bmjopen.bmj.com/cgi/content/short/10/5/e037195; https://doi.org/10.1136/bmjopen-2020-037195

Objective The objective of this study is to examine the magnitude and pattern of small-area geographic variation in rates of preventable hospitalisations for ambulatory care-sensitive conditions (ACSC) across Canada (excluding Qu e ´ bec). Design and setting A cross-sectional study conducted in Canada (excluding Qu e ´ bec) using data from the 2006 Canadian Census Health and Environment Cohort (CanCHEC) linked prospectively to hospitalisation records from the Discharge Abstract Database (DAD) for the three fiscal years: 2006–2007, 2007–2008 and 2008–2009. Primary outcome measure Preventable hospitalisations (ACSC). Participants The 2006 CanCHEC represents a population of 22 562 120 individuals in Canada (excluding Qu e ´ bec). Of this number, 2 940 150 (13.03%) individuals were estimated to be hospitalised at least once during the 2006–2009 fiscal years. Methods Age-standardised annualised ACSC hospitalisation rates per 100 000 population were computed for each of the 190 Census Divisions. To assess the magnitude of Census Division-level geographic variation in rates of preventable hospitalisations, the global Moran’s I statistic was computed. ‘Hot spot’ analysis was used to identify the pattern of geographic variation. Results Of all the hospitalisation events reported in Canada during the 2006–2009 fiscal years, 337 995 (7.10%) events were ACSC-related hospitalisations. The Moran’s I statistic (Moran’s I =0.355) suggests non-randomness in the spatial distribution of preventable hospitalisations. The findings from the ‘hot spot’ analysis indicate a cluster of Census Divisions located in predominantly rural and remote parts of Ontario, Manitoba and Saskatchewan and in eastern and northern parts of Nunavut with significantly higher than average rates of preventable hospitalisation. Conclusion The knowledge generated on the small-area geographic variation in preventable hospitalisations can inform regional, provincial and national decision makers on planning, allocation of resources and monitoring performance of ...