ArticleJournal of anesthesia2026
Implementing prospective probabilistic scheduling of surgical cases to yield more predictable utilisations.
Article in Journal of anesthesia, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We studied the impact of a prospective, probabilistic scheduling method to replace surgeon-led booking, balancing contradictory goals of maximizing theatre utilised time while minimizing risk of over-utilised time. Implemented in an NHS Scotland hospital, the study analyzed 2420 surgical lists across multiple specialties. The Infix Schedule tool used median and median absolute deviation (MAD) of historical case times to calculate probability of finishing within allocated times, targeting a range 80-90% for utilised time. Data were compared post hoc across three groups: prior surgeon-led scheduling, surgeon over-rides of the tool, and unadjusted Infix-generated schedules. In surgeon-led scheduling, realised utilised time was 78.8%: shadow Infix-generated schedules predicted median utilised time 77.8%, significantly closer to this reality (p = 0.18). Surgeon predictions overestimated utilization (median 87.7%; p < 0.001). Surgeon over-rides were associated with lower utilised time (76.5%) than actual (77.3%) or Infix predicted (78.0%; p < 0.015). Patient cancellation rates were lower for the Infix scheduled cohort (8.51% vs 10.96% for surgeon;(p = 0.0297). However, the tool's performance was dependent on accurate surgical coding. While the "pessimistic" mathematical buffer used to ensure reliability was associated with utilization < 80% target, iterative learning and reducing human overrides should refine efficiency and waiting list management.
Indexed as
Identifiers
42573745What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.