Observational studySupportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer2018
Utility of Mayo Clinic's early screen for discharge planning tool for predicting patient length of stay, discharge destination, and readmission risk in an inpatient oncology cohort.
Observational study in Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.
- A systematic literature review of predicting patient discharges using statistical methods and machine learning.Health care management science · 2024Pooled it
- Predicting emergency department disposition using machine learning and large language models to support proactive capacity management: a multicenter retrospective study.BMC emergency medicine · 2026Article
- Psychosocial factors influencing the outcomes after major anatomical lung resections: a retrospective analysis of prospectively collected data.Journal of thoracic disease · 2025Article
- Research progress on discharge readiness service practices for patients undergoing endometrial cancer surgery.Frontiers in oncology · 2025Review
- Factors Associated with Transfer from an Acute Geriatric Unit to a Post-Acute Care Facility among Community-Dwelling Patients: Results from the DAMAGE Cohort.Clinical interventions in aging · 2022Article
- Explainable Tree-Based Predictions for Unplanned 30-Day Readmission of Patients With Cancer Using Clinical Embeddings.JCO clinical cancer informatics · 2021Article
- An Early Screening Tool for Discharge Planning Shortened Length of Hospital Stay for Elderly Patients with Community-Acquired Pneumonia.Clinical interventions in aging · 2021Observational
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo examine the feasibility of using the Mayo Clinic's Early Screen for Discharge Planning (ESDP) tool in determining its predictive ability in an inpatient oncology hospital setting for variables including length of stay (LOS), discharge destination, and readmission risk.
methodsA prospective observational study was conducted at a metropolitan tertiary cancer centre in Melbourne, Australia. The ESDP score, along with patient outcomes and characteristics, were collected to examine the relationships between positive and negative ESDP scores and patient outcomes.
resultsA total of 136 participants met inclusion criteria for this study. The proportion with positive ESDP scores was greater in those with unplanned hospital admissions compared with planned admissions (χ
conclusionThe findings from this study suggest that the ESDP tool could be useful in an adult inpatient oncology population in a hospital with defined specialised hospital discharge planning services (SHDCPS). The ESDP may be beneficial for early identification of service types likely to be required in care and likely discharge destination, both of which can assist discharge planning (DP); however, the ESDP was not useful for predicting LOS or readmission risk in the adult inpatient oncology population without a SHDCPS model in place.
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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.