ArticleBMC research notes2012
Quantitative tools for addressing hospital readmissions.
Article in BMC research notes, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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.
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Who cites it
5 citing papers in PubMed.
- What is the impact on the readmission ratio of taking into account readmissions to other hospitals? A cross-sectional study.BMJ open · 2019Article
- To what degree can variations in readmission rates be explained on the level of the hospital? a multilevel study using a large Dutch database.BMC health services research · 2018Article
- The Quality of Surgical and Pneumonia Care in Minority-Serving and Racially Integrated Hospitals.Health services research · 2016Article
- Unexpectedly long hospital stays as an indicator of risk of unsafe care: an exploratory study.BMJ open · 2014Article
- Clinical identification of patients readmitted to hospitals: why patients return.BMC research notes · 2013Article
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
backgroundIncreased interest in health care cost containment is focusing attention on reduction of hospital readmissions. Major payors have already developed financial penalties for providers that generate excess readmissions. This subject has benefitted from the development of resources such as the Potentially Preventable Readmissions software. This process has encouraged hospitals to renew efforts to improve these outcomes. The aim of this study was to describe quantitative tools such as definitions, risk estimation, and tracking of patients for reducing hospital readmissions.
findingsThis study employed the Potentially Preventable Readmissions software to develop quantitative tools for addressing hospital readmissions. These tools included two definitions of readmissions that support identification and management of patients. They also included analytical approaches for estimation of the risk of readmission for individual patients by age, discharge status of the initial admission, and severity of illness. They also included patient specific spreadsheets for tracking of target populations and for evaluation of the impact of interventions.
conclusionsThe study demonstrated that quantitative tools including the development of definitions of readmissions, estimation of the risk of readmission, and patient specific spreadsheets could contribute to the improvement of patient outcomes in hospitals.
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Registered trials
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