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Prediction of post-acute care demand in medical and neurological inpatients: diagnostic assessment of the post-acute discharge score – a prospective cohort study

Overview of attention for article published in BMC Health Services Research, February 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (64th percentile)

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1 blog
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1 X user

Citations

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13 Dimensions

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43 Mendeley
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Title
Prediction of post-acute care demand in medical and neurological inpatients: diagnostic assessment of the post-acute discharge score – a prospective cohort study
Published in
BMC Health Services Research, February 2018
DOI 10.1186/s12913-018-2897-0
Pubmed ID
Authors

Antoinette Conca, Angela Gabele, Barbara Reutlinger, Philipp Schuetz, Alexander Kutz, Sebastian Haubitz, Lukas Faessler, Marcus Batschwaroff, Ursula Schild, Zeljka Caldara, Katharina Regez, Susanne Schirlo, Gabi Vossler, Timo Kahles, Krassen Nedeltchev, Anja Keller, Andreas Huber, Sabina De Geest, Ulrich Buergi, Petra Tobias, Martine Louis Simonet, Beat Mueller, Petra Schäfer-Keller

Abstract

Early identification of patients requiring transfer to post-acute care (PAC) facilities shortens hospital stays. With a focus on interprofessional assessment of biopsychosocial risk, this study's aim was to assess medical and neurological patients' post-acute care discharge (PACD) scores on days 1 and 3 after hospital admission regarding diagnostic accuracy and effectiveness as an early screening tool. The transfer to PAC facilities served as the outcome ("gold standard"). In this prospective cohort study, registered at ClinicalTrial.gov (NCT01768494) on January 2013, 1432 medical and 464 neurological patients (total n = 1896) were included consecutively between February and October 2013. PACD scores and other relevant data were extracted from electronic records of patient admissions, hospital stays, and interviews at day 30 post-hospital admission. To gauge the scores' accuracy, we plotted receiver operating characteristic (ROC) curves, calculated area under the curve (AUC), and determined sensitivity and specificity at various cut-off levels. Medical patients' day 1 and day 3 PACD scores accurately predicted discharge to PAC facilities, with respective discriminating powers (AUC) of 0.77 and 0.82. With a PACD cut-off of ≥8 points, day 1 and 3 sensitivities were respectively 72.6% and 83.6%, with respective specificities of 66.5% and 70.0%. Neurological patients' scores showed lower accuracy both days: using the same cut-off, respective day 1 and day 3 AUCs were 0.68 and 0.78, sensitivities 41.4% and 68.7% and specificities 81.4% and 83.4%. PACD scores at days 1 and 3 accurately predicted transfer to PAC facilities, especially in medical patients on day 3. To confirm and refine these results, PACD scores' value to guide discharge planning interventions and subsequent impact on hospital stay warrants further investigation. ClinialTrials.gov Identifier, NCT01768494 .

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 43 100%

Demographic breakdown

Readers by professional status Count As %
Other 7 16%
Student > Doctoral Student 4 9%
Student > Bachelor 4 9%
Student > Master 4 9%
Researcher 3 7%
Other 3 7%
Unknown 18 42%
Readers by discipline Count As %
Nursing and Health Professions 10 23%
Medicine and Dentistry 3 7%
Business, Management and Accounting 2 5%
Chemistry 2 5%
Agricultural and Biological Sciences 1 2%
Other 5 12%
Unknown 20 47%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 19 February 2018.
All research outputs
#4,030,226
of 23,023,224 outputs
Outputs from BMC Health Services Research
#1,828
of 7,707 outputs
Outputs of similar age
#92,583
of 446,078 outputs
Outputs of similar age from BMC Health Services Research
#64
of 187 outputs
Altmetric has tracked 23,023,224 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,707 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.8. This one has done well, scoring higher than 75% 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 446,078 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 79% of its contemporaries.
We're also able to compare this research output to 187 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.