English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Interrupted time series designs are frequently employed to evaluate program impact. Analysis strategies to determine if shifts have occurred are not well known. The case where statistical fluctuations (errors) may be assumed independent is considered, and a segmented regression methodology presented. The method discussed ia applied to the assessment of changes in local and state perinatal postneonatal mortality to identify historical trends and will be used to evaluate the impact of the North Carolina Regionalized Perinatal Care Program when seven years of post-program mortality data become available. The perinatal program region is contrasted with a control region to provide a basis for interpretation of differences noted. Relevant segmented regression models provided good fits to the data and highlighted mortality trends over the last 30 years. Considerable racial differences in these trends were identified, particularly for postneonatal mortality. Segmented regression is considered relevant for the analysis of interrupted time series designs in other applications when errors can be taken to be independent. Thus, the methodology may be regarded as a general statistical tool for evaluation purposes.

Analysis of interrupted time series mortality trends: an example to evaluate regionalized perinatal care.