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Discharge planning from hospital

Overview of attention for article published in Cochrane database of systematic reviews, January 2016
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

blogs
1 blog
policy
1 policy source
twitter
57 tweeters
facebook
4 Facebook pages
wikipedia
2 Wikipedia pages

Readers on

mendeley
605 Mendeley
citeulike
1 CiteULike
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Title
Discharge planning from hospital
Published in
Cochrane database of systematic reviews, January 2016
DOI 10.1002/14651858.cd000313.pub5
Pubmed ID
Authors

Daniela C. Gonçalves-Bradley, Natasha A Lannin, Lindy M Clemson, Ian D Cameron, Sasha Shepperd

Abstract

Discharge planning is a routine feature of health systems in many countries. The aim of discharge planning is to reduce hospital length of stay and unplanned readmission to hospital, and to improve the co-ordination of services following discharge from hospital.This is the third update of the original review. To assess the effectiveness of planning the discharge of individual patients moving from hospital. We updated the review using the Cochrane Central Register of Controlled Trials (CENTRAL) (2015, Issue 9), MEDLINE, EMBASE, CINAHL, the Social Science Citation Index (last searched in October 2015), and the US National Institutes of Health trial register (ClinicalTrials.gov). Randomised controlled trials (RCTs) that compared an individualised discharge plan with routine discharge care that was not tailored to individual participants. Participants were hospital inpatients. Two authors independently undertook data analysis and quality assessment using a pre-designed data extraction sheet. We grouped studies according to patient groups (elderly medical patients, patients recovering from surgery, and those with a mix of conditions) and by outcome. We performed our statistical analysis according to the intention-to-treat principle, calculating risk ratios (RRs) for dichotomous outcomes and mean differences (MDs) for continuous data using fixed-effect meta-analysis. When combining outcome data was not possible because of differences in the reporting of outcomes, we summarised the reported data in the text. We included 30 trials (11,964 participants), including six identified in this update. Twenty-one trials recruited older participants with a medical condition, five recruited participants with a mix of medical and surgical conditions, one recruited participants from a psychiatric hospital, one from both a psychiatric hospital and from a general hospital, and two trials recruited participants admitted to hospital following a fall. Hospital length of stay and readmissions to hospital were reduced for participants admitted to hospital with a medical diagnosis and who were allocated to discharge planning (length of stay MD - 0.73, 95% CI - 1.33 to - 0.12, 12 trials, moderate certainty evidence; readmission rates RR 0.87, 95% CI 0.79 to 0.97, 15 trials, moderate certainty evidence). It is uncertain whether discharge planning reduces readmission rates for patients admitted to hospital following a fall (RR 1.36, 95% CI 0.46 to 4.01, 2 trials, very low certainty evidence). For elderly patients with a medical condition, there was little or no difference between groups for mortality (RR 0.99, 95% CI 0.79 to 1.24, moderate certainty). There was also little evidence regarding mortality for participants recovering from surgery or who had a mix of medical and surgical conditions. Discharge planning may lead to increased satisfaction for patients and healthcare professionals (low certainty evidence, six trials). It is uncertain whether there is any difference in the cost of care when discharge planning is implemented with patients who have a medical condition (very low certainty evidence, five trials). A discharge plan tailored to the individual patient probably brings about a small reduction in hospital length of stay and reduces the risk of readmission to hospital at three months follow-up for older people with a medical condition. Discharge planning may lead to increased satisfaction with healthcare for patients and professionals. There is little evidence that discharge planning reduces costs to the health service.

Twitter Demographics

The data shown below were collected from the profiles of 57 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 605 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 6 <1%
United States 3 <1%
Canada 3 <1%
Italy 2 <1%
Colombia 1 <1%
Unknown 590 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 127 21%
Student > Ph. D. Student 75 12%
Student > Bachelor 72 12%
Researcher 69 11%
Student > Doctoral Student 39 6%
Other 123 20%
Unknown 100 17%
Readers by discipline Count As %
Medicine and Dentistry 188 31%
Nursing and Health Professions 158 26%
Social Sciences 44 7%
Psychology 23 4%
Pharmacology, Toxicology and Pharmaceutical Science 18 3%
Other 59 10%
Unknown 115 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 47. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 October 2019.
All research outputs
#420,793
of 14,574,683 outputs
Outputs from Cochrane database of systematic reviews
#1,128
of 11,002 outputs
Outputs of similar age
#12,734
of 339,220 outputs
Outputs of similar age from Cochrane database of systematic reviews
#33
of 204 outputs
Altmetric has tracked 14,574,683 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,002 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 22.3. This one has done well, scoring higher than 89% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 339,220 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 204 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.