Back

Public but ineffective: Fatality inquiries into childhood deaths in Alberta.

Verbeke, M.-C.; Mitchell, I.

2023-09-29 public and global health
10.1101/2023.09.26.23296196 medRxiv
Show abstract

IntroductionChild Death Review (CDR) processes are public efforts to review a childs death to understand how and why children die, to improve child health and to prevent future deaths. In 2013, the Canadian Paediatric Society made specific recommendations to establish structured and comprehensive CDR systems in each province and territory. In Alberta, there is no comprehensive CDR process but there are some components. The most public and probably the most expensive component is the public fatality inquiry. A new notification policy adopted after in June 2017 appears to be of limited value for child death prevention. MethodsWe examined all Alberta fatality inquiry reports from January 1, 1995 to April 15, 2023 concerning children aged 0-17 years (n=133) to determine whether the fatality inquiry system might be effective in preventing future similar deaths. ResultsRecommendations made by judges in a fatality inquiry were not always followed by action, and hence inquiry recommendations have been largely ineffective. Fatality inquiry recommendations were sometimes untimely, and therefore had little chance of being effective. There is an increasing trend from 1995 (case 1) to 2023 (case 133) in the time taken to initiate a child fatality inquiry review. Discussion and ConclusionInformation and recommendations from fatality inquiries into Alberta childhood deaths tend to be delayed and not followed by action. A comprehensive CDR process is required in Alberta. With system changes, public fatality inquiries could be an effective part of the child death prevention process.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.