Per-Patient Illness Trajectory Analyses

Abstract

Background:

Summary statistics often hide individual patients’ suffering, thereby impeding quality improvement efforts.

Objectives:

We aimed to show the experience of a population with health care toward the end of life while preserving the experience of the individual.

Design:

We developed a data display method called per-patient illness trajectory analysis. We tested it using a demonstration cohort of 192 patients with cancer referred to a regional Swedish specialized home-based palliative care practice. Chart review provided detailed information about illness trajectory events with a focus on unplanned hospitalization.

Results:

We created per-patient timelines spanning from cancer diagnosis until death and using a logarithmic scale: Compared with a conventional, linear timescale, this scale expands the time resolution toward the end of life. The method fosters the assessment of unmet palliative care need and care quality for individuals, small high-need groups, and populations.

Conclusion:

In populations of up to 200 people, per-patient illness trajectory analysis is feasible and promising. Using random sampling, it could be extended to larger populations.