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/

Zendy Plus

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

Zendy Tools

Zendy Open

Using patient-level data from 35 hospitals for 6 cardiovascular surgeries in New York, we provide empirical evidence that outcome differences between health care providers are heterogeneous across different groups of patients. We then use a causal tree approach to identify patient groups that exhibit significant differences in outcome. By quantifying these differences, we demonstrate that a large majority of patients can achieve better expected outcomes by selecting providers based on patient-centric outcome information. We also show how patient-centric outcome information can help providers to improve their processes and payers to design effective pay-for-performance programs.

A Causal Tree Approach for Personalized Health Care Outcome Analysis