When Do Published Cost-Effectiveness Analyses Include Societal Costs? An Empirical Analysis, 2013–2023
Bibliographic record
Abstract
ObjectiveTo examine trends in the inclusion of societal costs in published cost-effectiveness analyses (CEAs), factors associated with their inclusion, and the impact of societal costs on incremental costs and incremental cost-effectiveness ratios (ICERs).MethodsWe analyzed 7,800 CEAs from 2013 to 2023 using the Tufts Medical Center CEA registry. The inclusion of societal costs in CEAs was evaluated across study characteristics. Associations between study characteristics and the inclusion of societal costs were analyzed using multivariate logistic regression. For studies reporting health care and societal perspectives, we assessed the impact of including societal costs on incremental costs and ICERs.ResultsFrom 2013 to 2023, CEAs including societal costs increased from 19% to 28%. Productivity was the most frequently reported component (12%), followed by transportation (8%), caregiver time (6%), patient time (5%), and consumption costs (1%). Compared with US-based analyses, studies from Scandinavian countries (adjusted odds ratio [OR]: 3.6) and the Netherlands (5.6) had higher odds of including societal costs, whereas studies from Canada (0.7), Australia (0.6), and the United Kingdom (0.4) had lower odds. Studies on mental health disorders (6.2) and immunization (4.1) had the highest odds of including societal costs. Compared with CEAs focused on adults, CEAs targeting pediatric populations had higher odds (OR: 1.6), while those targeting the elderly had lower odds (OR: 0.7). Upon inclusion of societal costs, incremental costs decreased in 72% and increased in 28% of studies; the ICER decreased in 74% and increased in 26% of studies.ConclusionDespite the increase in recent years, societal costs are infrequently included in CEAs, with substantial variation by country, disease, and population. Including societal costs can meaningfully improve value assessments and should be guided by relevance, evidence, and decision context.HighlightsBuilding on prior work by Kim et al. (2020), which analyzed approximately 6,900 cost-effectiveness analyses (CEAs), this study examined a larger and more recent sample of 7,800 CEAs from 2013 to 2023. In addition to updating the evidence base, we conducted new analyses to assess trends, associated factors, and the effect of including societal costs on incremental cost-effectiveness ratios (ICERs), thus providing insights that were not explored in prior work and addressing a key evidence gap in health economics.The inclusion of societal costs in CEAs rose modestly from 19% to 28% from 2013 to 2023, with substantial variation across countries, diseases, and intervention types. In some cases, the inclusion of societal costs affected incremental costs and ICERs enough to cross commonly used cost-effectiveness thresholds.The inclusion of societal costs can help improve value assessments in health care interventions, but it should be guided by relevance, available evidence, and the potential to influence decision making. Identifying when and where societal costs meaningfully affect outcomes can support more consistent and appropriate use.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.174 | 0.521 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.009 |
| Bibliometrics | 0.011 | 0.018 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".