Observational studyBMC health services research2018
Prediction of post-acute care demand in medical and neurological inpatients: diagnostic assessment of the post-acute discharge score - a prospective cohort study.
Observational study in BMC health services research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01768494 (Optimizing Triage and Hospitalisation In Adult General Medical Emergency Patients), which is not on this 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.
Optimizing Triage and Hospitalisation In Adult General Medical Emergency Patients: the TRIAGE Study
Who cites it
5 citing papers in PubMed, 12 citations in OpenAlex.
- Prediction of In-Hospital Falls Using NRS, PACD Score and FallRS: A Retrospective Cohort Study.Geriatrics (Basel, Switzerland) · 2023Article
- Self-Care Index and Post-Acute Care Discharge Score to Predict Discharge Destination of Adult Medical Inpatients: Protocol for a Multicenter Validation Study.JMIR research protocols · 2021Article
- Integrative hospital treatment in older patients to benchmark and improve outcome and length of stay - the In-HospiTOOL study.BMC health services research · 2019Article
- Improving the post-acute care discharge score (PACD) by adding patients' self-care abilities: A prospective cohort study.PloS one · 2019Observational
- Behavioral Health Services with Short-Stay Residents in Skilled Nursing Facilities: A Qualitative Study of Clinicians and Administrators.Clinical gerontologistArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
23 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEarly 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").
methodsIn 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.
resultsMedical 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%.
conclusionPACD 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.
trial registrationClinialTrials.gov Identifier, NCT01768494 .
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