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Can we predict your future? Using scores to predict length of stay and discharge destination
Sarah Mc Nally, Roisin Howlin, Annette Kehoe, Sarah A. Murphy. International Journal of Integrated Care, 2017-10-17
Topic: Risk, prevention and care in population studies
120 patients were included in the audit with a confirmed stroke on CTB/MRI. The average age was 73. There were 52 males and 68 females and the average length of stay was 44 days.Of the 49 patients that scored within mild-no cognitive impairment, 90% (n=44) went home from SVUH, 2% to further rehab, 6% to LTC and 2% died . The average length of stay for this cohort is 17 days.Of those that scored within the mild- moderate cognitive impairment (n=37) 30% went home, 40% went for further rehab, 27% went to LTC and 3% died. The average length of stay for this group was 49 days (more than twice the first group).Of those that scored within moderate – severe cognitive impairment, 12% went for further rehab, 63% to long term care and 25% died and 0% went home.Their average length of stay was 90days, nearly five times longer than the first cohort.Not every patient was able to complete a standardised cognitive assessment.42% of these patients went to long-term care and 35% died. This cohorts average length of stay was 82 days, with a the number of deaths shortly after admissionLessons Learnt: The results of this audit confirm that early cognitive screening can help predict discharge destination and length of stay. Early cognitive screening (as recommended in the Royal College Of Physicians Stroke guidelines) are completed within 24 hours of admission to SVUH. Therefore the multidisciplinary has a strong indicator of discharge destination and length of stay early in the course of the patient’s hospital stay. With an increasing emphasis on the delivery of appropriate allocation of resources and constant pressures on delivering cost effective care it is estimated this knowledge will have significant cost saving benefits. This information is also imperative in early planning to reduce the number of delayed discharges.Effects of changes: As a multidisciplinary team we now use these early cognitive scores prospectively, to inform discharge arrangements and the timeliness of interventions for newly diagnosed stroke patients. Family meetings are now arranged within two weeks of admissions as standard, meaning families/NOK are also informed and involved in effective early discharge planning, allowing for a more seamless discharge.We anticipate that this focus on early scores might assist in the better distribution of healthcare resources in the hospital setting.
Key findings
- 120 patients were included in the audit with a confirmed stroke on CTB/MRI.
- There were 52 males and 68 females and the average length of stay was 44 days.Of the 49 patients that scored within mild-no cognitive impairment, 90% (n=44) went home from SVUH, 2% to further rehab, 6% to LTC and 2% died .
- The average length of stay for this cohort is 17 days.Of those that scored within the mild- moderate cognitive impairment (n=37) 30% went home, 40% went for further rehab, 27% went to LTC and 3% died.
- The average length of stay for this group was 49 days (more than twice the first group).Of those that scored within moderate – severe cognitive impairment, 12% went for further rehab, 63% to long term care and 25% died and 0% went home.Their average length of stay was 90days, nearly five times longer than the first cohort.Not every patient was able to complete a standardised cognitive assessment.42% of these patients went to long-term care and 35% died.
- This cohorts average length of stay was 82 days, with a the number of deaths shortly after admissionLessons Learnt: The results of this audit confirm that early cognitive screening can help predict discharge destination and length of stay.
Why it matters
In this audit of 120 stroke patients, early cognitive screening helped predict discharge destination and length of stay, with more severe cognitive impairment linked to longer stays and lower likelihood of going home. The findings support using early cognitive screening to plan care after stroke.
Study details
- Participants44
- Evidence strengthModerate
How this study scored 32/100
Published in a peer-reviewed journal. Scored zero for study design, effect reported and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (International Journal of Integrated Care) |
| Journal's citation record | 1 / 4 | International Journal of Integrated Care: journal h-index 75 (OpenAlex, 2026-10-29) |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 3 / 5 | Rated “moderate” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 2 / 5 | 2017 — within 10 year(s) of the newest study here |
| Sample size | 1 / 4 | 44 participants |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 3 / 3 | Studied in people (participant count stated) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 0 / 7 | Cited 0 times (OpenAlex, 2026-10-10) |
| Citations per year | 0 / 5 | 0.0 citations a year over 11 year(s) since 2017 |
| Impact for its field and year | 0 / 6 | Cited 0.0× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 0 / 6 | No other study in this library cites it |
| Still being cited | 0 / 4 | Cited 0 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 2 / 4 | Last-listed author Sarah A. Murphy: h-index 26 (OpenAlex, whole career) |
| Institution's track record | 0 / 3 | St. Vincent's University Hospital: institution h-index 349 (OpenAlex) |
| Multi-centre collaboration | 0 / 3 | OpenAlex lists 1 institution(s) in 1 country — scores zero (affiliation lists can be incomplete) |
| Indexed in PubMed | 1 / 2 | Not in PubMed, but has a DOI |
| Free to read | 2 / 2 | Free to read |
| Total | 32 / 100 | — |
What each of these 20 components measures, and what this score is not →
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Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. Check the citation against the original before you use it.
APA 7th
Nally, S. M., Howlin, R., Kehoe, A., & Murphy, S. A. (2017). Can we predict your future? Using scores to predict length of stay and discharge destination. International Journal of Integrated Care. https://doi.org/10.5334/ijic.3678
Vancouver
Nally SM, Howlin R, Kehoe A, Murphy SA. Can we predict your future? Using scores to predict length of stay and discharge destination. International Journal of Integrated Care. 2017. doi:10.5334/ijic.3678.
BibTeX
@article{nally2017-4780401f,
author = {Nally, Sarah Mc and Howlin, Roisin and Kehoe, Annette and Murphy, Sarah A.},
title = {{Can we predict your future? Using scores to predict length of stay and discharge destination}},
journal = {International Journal of Integrated Care},
year = {2017},
doi = {10.5334/ijic.3678},
url = {https://doi.org/10.5334/ijic.3678}
}
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