Health-Related Quality-of-Life and Cost Utility Analyses in Critical Care: A Systematic Review*
Bibliographic record
Abstract
OBJECTIVES: Cost utility analyses compare the costs and health outcome of interventions, with a denominator of quality-adjusted life year, a generic health utility measure combining both quality and quantity of life. Cost utility analyses are difficult to compare when methods are not standardized. It is unclear how cost utility analyses are measured/reported in critical care and what methodologic challenges cost utility analyses pose in this setting. This may lead to differences precluding cost utility analyses comparisons. Therefore, we performed a systematic review of cost utility analyses conducted in critical care. Our objectives were to understand: 1) methodologic characteristics, 2) how health-related quality-of-life was measured/reported, and 3) what costs were reported/measured. DESIGN: Systematic review. DATA SOURCES: We systematically searched for cost utility analyses in critical care in MEDLINE, Embase, American College of Physicians Journal Club, CENTRAL, Evidence-Based Medicine Reviews' selected subset of archived versions of UK National Health Service Economic Evaluation Database, Database of Abstracts of Reviews of Effects, and American Economic Association electronic databases from inception to April 30, 2020. SETTING: Adult ICUs. PATIENTS: Adult critically ill patients. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Of 8,926 citations, 80 cost utility analyse studies were eligible. The time horizon most commonly reported was lifetime (59%). For health utility reporting, health-related quality-of-life was infrequently measured (29% reported), with only 5% of studies reporting baseline health-related quality-of-life. Indirect utility measures (generic, preference-based health utility measurement tools) were reported in 85% of studies (majority Euro-quality-of-life-5 Domains, 52%). Methods of estimating health-related quality-of-life were seldom used when the patient was incapacitated: imputation (19%), assigning fixed utilities for incapacitation (19%), and surrogates reporting on behalf of incapacitated patients (5%). For cost utility reporting transparency, separate incremental costs and quality-adjusted life years were both reported in only 76% of studies. Disaggregated quality-adjusted life years (reporting separate health utility and life years) were described in only 34% of studies. CONCLUSIONS: We identified deficiencies which warrant recommendations (standardized measurement/reporting of resource use/unit costs/health-related quality-of-life/methodological preferences) for improved design, conduct, and reporting of future cost utility analyses in critical care.
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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 | 0.025 | 0.128 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.013 |
| Bibliometrics | 0.016 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".