Critical path planning for discharging older adults using a functional perspective
Bibliographic record
Abstract
Abstract This study aims to introduce an innovative method to schedule and analyze the discharge planning processes under uncertain individual activity completing times. Hospital care processes ending in discharging older adults represent a major challenge, as a number of interrelated tasks or activities are involved in the processes. The functional resonance analysis method (FRAM) is used to identify activities that constitute a descriptive model of the discharge planning processes and to assign the completion time to each task or activity. Then the critical path planning technique is utilized to identify the critical path of the discharge process. To this end, the Program Evaluation and Review Technique (PERT) is employed. Published data regarding six older patients are used to examine the potential utility of the introduced method to improve the discharge process of older adults. The results show that the integration of the FRAM and PERT is able to identify the critical activities that constitute the critical path of the discharge process. It also helps analyze the completion time assigned to each task/activity and calculate the completion time of the discharge process. The probability of completing the discharge process within a target completion time is also discussed. The results add further evidence showing the applicability of the FRAM and PERT to scheduling systems for the discharge planning processes. Health care professionals could use the findings of this study in designing a scheduling system to complete the discharge process of older adults in a reasonable time.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| 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".