Probabilistic Return-on-Investment Analysis of Single-Family Versus Open-Bay Rooms in Neonatal Intensive Care Units—Synthesis and Evaluation of Early Evidence on Nosocomial Infections, Length of Stay, and Direct Cost of Care
Bibliographic record
Abstract
BACKGROUND:: There is increasing evidence that the physical environment of neonatal intensive care units (NICUs), including single-family rooms (SFRs) versus open-bay rooms (OPBYs), has tangible effects on vulnerable patients. The objective of this study was to illustrate the financial implications of SFR versus OPBY units by synthesizing and evaluating the evidence regarding the benefits and costs of each unit from a hospital perspective. METHODS:: We assumed a hypothetical NICU with 40 beds in OPBY rooms, to be replaced with a new NICU with 32 SFRs and 8 OPBYs. We synthesized evidence regarding the comparative benefit of each option on 3 outcomes-nosocomial infections, length of stay, and direct costs. We calculated incremental benefit-cost ratio separately considering each outcome over an analysis period of 5 years. A ratio of more than 1 indicates that the investment is worthwhile. Input parameters were assigned probability distributions representing the degree of uncertainty around their true values. Monte Carlo simulation with 5000 iterations was used to quantify the distribution of benefits and costs. RESULTS:: The mean value of the incremental benefit-cost ratio was 0.730 (95% credible interval: 0.724-0.735) when nosocomial infections were considered, 1.298 (1.282-1.315) when reduced length of stay was considered, and 1.794 (1.783-1.804) when direct costs of care were compared. The probability of a benefit-cost ratio of lower than 1 was about 91%, 31%, and 2% in each case, respectively. CONCLUSION:: Cost savings associated with SFR units would justify additional construction and operation costs compared to OPBY units only when evidence on inclusive outcomes such as length of stay or direct costs of care is considered. A specific outcome such as infection rate potentially fails to capture all benefits of SFRs. As more evidence becomes available on full benefits and hazards of SFRs versus OPBYs, future studies should investigate the broader return-on-investment outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".