P51 Surviving intensive care: a systematic review of health care resource use after hospital discharge
Bibliographic record
Abstract
Background Intensive care units (ICUs) are an expensive resource. However, this expense does not end at hospital discharge. ICU survivors continue to experience significant morbidity. As the demand for ICU is likely to increase substantially, there is a need to establish how much health care resource survivors consume following discharge from hospital. This will enable appropriate service planning and policy development to meet the needs of these patients, and will improve the precision of economic evaluations relating to ICU. Aims We conducted a systematic review to determine the reported use of major health care resource by ICU survivors following discharge from hospital and to identify factors associated with increased resource use. Methods Studies were included if the study population derived from an adult, general ICU population, health care resource use was reported at the patient level and the publication was in the English language. Two reviewers independently screened abstracts, rejecting those clearly not meeting inclusion criteria. A single reviewer then retrieved the full texts and assessed them for inclusion. Costs were inflated to 2009 using the consumer price index and converted to US dollars using the purchasing power parity method. Results From 3522 articles, nine fulfilled criteria for inclusion. Two studies were conducted in the UK; three in Canada and four in the USA. Six studies used a cohort design; the remaining three collected data as part of a trial. The number of patients for which resource use was reported ranged from 66 to 963. Mean age ranged from 40 to 66. There was substantial variation in the cost categories included in each study. Following standardisation to a common currency and year, variation in resource use was apparent (range $1610–$45 173). Studies undertaken within the USA reported the highest costs; those in the UK reported substantially lower costs. The larger proportion of resource was consumed in secondary care (range 53–96%). Factors associated with increased resource use included increasing age, co-morbidities and organ dysfunction score. Conclusion This review is the first to bring together the literature relating to post-hospital discharge health care resource use for survivors of ICU. There was substantial variation in the cost of resource use between studies. Given the paucity of identified studies and their relatively short time horizons, there is a clear need for longer term studies to investigate resource use of ICU survivors. Our findings should help to inform the design and reporting of such studies.
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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 | 0.015 | 0.097 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.011 |
| Bibliometrics | 0.015 | 0.021 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".