EOLinPLACE

Overview

Project Summary

Respecting preferences for place of death is important. The first step is to classify the dying places (home, hospital, among others) in a way that is meaningful for individuals. In this context, the EU-funded EOLinPLACE project will create a solid base for the first international classification tool to map preferred and actual places towards death. We will conduct a mixed-methods study in four countries covering existing target variation (Portugal, Netherlands, Uganda, USA) to explore nuances and commonalities in people’s end of life pathways. The findings will provide new insights into how to care for the dying.

Main Goals

We are driven by the vision of reforming the way dying places are classified and understood, refining and shifting the focus from the end-point (place of death) to the pathway that precedes it, as a way to discern diversity in the places people receive care and die and individual preferences in different parts of the world.

We want to develop a strong foundation for a pioneering international classification tool that maps preferred and actual places towards death grounded on what they mean for individuals (beyond a purely physical or medical view).

To achieve our aim, we will conduct an international comparative analysis of existing classifications systems and routinely collected death certificate/registration data on place of death. Alongside, we will conduct a novel mixed-methods study (ethnography followed by longitudinal study) in four countries covering existing target variation (Portugal, Netherlands, Uganda and USA), to explore nuances and commonalities in the experiences of patients with life-threatening conditions and their families. Based on the generated evidence,we will build a contemporary classification of dying places and assess its content validity in focus groups with patients, carers and other stakeholders. We will then test it in varied settings in a psychometric study to examine construct validity, reliability, responsiveness, data quality and interpretability. All data will be integrated to deepen understanding of different end of life pathways in caring environments and what influences them.

Project Details