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Cost trajectories from the final life year reveal intensity of end-of-life care and can help to guide palliative care interventions
  1. Viktor von Wyl1,2,
  2. Harry Telser3,
  3. Andreas Weber4,
  4. Barbara Fischer3,5 and
  5. Konstantin Beck2,6
  1. 1Institute for Epidemiology, Biostatistics & Prevention, University of Zürich, Zürich, Switzerland
  2. 2CSS-Institute for Empirical Health Economics, Luzern, Switzerland
  3. 3Polynomics AG, Olten, Switzerland
  4. 4Palliative Care Unit, Department of Internal Medicine, GZO Hospital Wetzikon, Wetzikon, Switzerland
  5. 5Department of Business Administration, University of Zürich, Zürich, Switzerland
  6. 6Department of Economics, University of Zürich, Zürich, Switzerland
  1. Correspondence to Dr Viktor von Wyl, Epidemiology, Biostatistics & Prevention Institute, University of Zürich, Hirschengraben 84, 8001 Zürich, Switzerland; viktor.vonwyl{at}uzh.ch

Abstract

Objective Exploration of healthcare utilisation patterns in the final life year to assess palliative care potential.

Methods Retrospective cluster analyses (k-means) of anonymised healthcare expenditure (HCE) trajectories, derived from health insurance claims of a representative sample of Swiss decedents who died between 2008 and 2010 (2 age classes: 4818 <66 years, 22 691 elderly).

Results 3 (<66 years) and 5 (elderly) trajectory groups were identified, whose shapes were dominated by HCE from inpatient care in hospitals and at nursing homes. In each age class, the most expensive group (average cumulative HCE for <66 years: SFr 84 295; elderly: SFr 84 941) also had the largest abundance of cancers (<66 years: 55%; elderly: 32%) and showed signs of continued treatment intensification until shortly before death. Although sizes of these high-cost groups were comparatively small (26% in younger; 6% in elderly), they contributed substantially to the end-of-life HCE in each age class (62% and 18%, respectively).

As age increased, these potential target groups for palliative care gained in share among <66-year olds (from 9% in children to 28% in 60–65-year olds), but decreased from 17% (66–70-year olds) to 1% (>90-year olds) among elderly.

Conclusions Cost trajectory clustering is well suited for first-pass population screenings of groups that warrant closer inspection to improve end-of-life healthcare allocation. The Swiss data suggest that many decedents undergo intensive medical treatment until shortly before death. Investigations into the clinical circumstances and motives of patients and physicians may help to guide palliative care.

  • Methodological research
  • Service evaluation
  • Terminal care
  • Clinical decisions

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