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The evolution of serious health-related suffering from 1990 to 2021: an update to The Lancet Commission on global access to palliative care and pain relief.

The Lancet. Global health2025-03-01PubMed
Total: 78.5Innovation: 7Impact: 9Rigor: 8Citation: 8

Summary

Applying the SHS 2.0 method to GBD data, the authors estimate that serious health-related suffering rose 74% from 1990 to 2021 to nearly 73.5 million individuals, with 80% occurring in LMICs and a growing share among non-decedents (63% by 2021). Drivers shifted toward non-communicable diseases, with marked sex- and age-specific patterns that inform targeted palliative care expansion.

Key Findings

  • Global SHS increased 74% from 1990 to 2021, reaching nearly 73.5 million individuals.
  • LMICs accounted for 80% of SHS; non-decedent SHS more than doubled to 63% by 2021.
  • Burden shifted toward non-communicable diseases; child SHS share fell from 25% to 14%; female 20–49 years in LICs and ≥70 years in HICs were most affected.

Clinical Implications

Encourages earlier integration of palliative care, prioritization of non-decedent populations, and targeted services for women in specific age bands across income settings. Supports national planning for essential palliative medicines and workforce.

Why It Matters

Provides the most comprehensive, methodologically updated global quantification of palliative care need, with actionable stratification by geography, sex, age, and condition. Likely to guide health policy, financing, and workforce planning.

Limitations

  • Model-based estimates rely on GBD inputs and assumptions, which may vary in quality across countries.
  • Lack of patient-level validation limits inference on service delivery effectiveness.

Future Directions

Link SHS estimates to health system capacity mapping, prospective monitoring of palliative care access, and evaluation of interventions reducing non-decedent suffering.

Study Information

Study Type
Cohort
Research Domain
Prognosis
Evidence Level
III - Observational, model-based global burden analysis using secondary data.
Study Design
OTHER