ArticleAmerican journal of surgery2017
Discharge decision-making after complex surgery: Surgeon behaviors compared to predictive modeling to reduce surgical readmissions.
Article in American journal of surgery, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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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.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- ERAS following spine surgery in the elderly: a systematic review and meta-analysis.Journal of orthopaedic surgery and research · 2025Pooled it
- Predicting Colorectal Surgery Readmission Risk: a Surgery-Specific Predictive Model.IISE transactions on healthcare systems engineering · 2023Article
- Healthcare Warranty Policies Optimization for Chronic Diseases Based on Delay Time Concept.Healthcare (Basel, Switzerland) · 2021Article
- Effects of patients' hospital discharge preferences on uptake of clinical decision support.PloS one · 2021Article
- Article
- Analysing repeated hospital readmissions using data mining techniques.Health systems (Basingstoke, England) · 2018Article
- Analysing repeated hospital readmissions using data mining techniques.Health systems (Basingstoke, England) · 2018Article
- The independent effect of cancer on outcomes: a potential limitation of surgical risk prediction.The Journal of surgical research · 2017Article
- Higher Quality and Lower Cost from Improving Hospital Discharge Decision Making.Journal of economic behavior & organization · 2016Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
backgroundLittle is known about how information available at discharge affects decision-making and its effect on readmission. We sought to define the association between information used for discharge and patients' subsequent risk of readmission.
methods2009-2014 patients from a tertiary academic medical center's surgical services were analyzed using a time-to-event model to identify criteria that statistically explained the timing of discharges. The data were subsequently used to develop a time-varying prediction model of unplanned hospital readmissions. These models were validated and statistically compared.
resultsThe predictive discharge and readmission regression models were generated from a database of 20,970 patients totaling 115,976 patient-days with 1,565 readmissions (7.5%). 22 daily clinical measures were significant in both regression models. Both models demonstrated good discrimination (C statistic = 0.8 for all models). Comparison of discharge behaviors versus the predictive readmission model suggested important discordance with certain clinical measures (e.g., demographics, laboratory values) not being accounted for to optimize discharges.
conclusionsDecision-support tools for discharge may utilize variables that are not routinely considered by healthcare providers. How providers will then respond to these atypical findings may affect implementation.
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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.