Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2019 Jul 29;9(7):e028302.
doi: 10.1136/bmjopen-2018-028302.

Risk scores identifying elderly inpatients at risk of 30-day unplanned readmission and accident and emergency department visit: a systematic review

Camille Schwab  1   2 , Patrick Hindlet  2 , Brigitte Sabatier  1   3   4 , Christine Fernandez  2   5 , Virginie Korb-Savoldelli  1   6
Affiliations

Risk scores identifying elderly inpatients at risk of 30-day unplanned readmission and accident and emergency department visit: a systematic review

Camille Schwab et al. BMJ Open. .

Abstract

Objectives: The aim of this systematic review was to describe and analyse the performance statistics of validated risk scores identifying elderly inpatients at risk of early unplanned readmission.

Data sources: We identified potentially eligible studies by searching MEDLINE, EMBASE, COCHRANE and Web of Science. Our search was restricted to original studies, between 1966 and 2018.

Eligibility criteria: Original studies, which internally or externally validated the clinical scores of hospital readmissions in elderly inpatients.

Data extraction and synthesis: A data extraction grid based on Strengthening the Reporting of Observational Studies in Epidemiology and Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis statements was developed and completed by two reviewers to collect general data. The same process was used to extract metrological data of the selected scores.

Quality assessment of the included studies: Assessment of the quality and risk of bias in individual studies was performed by two reviewers, using the validated Effective Public Health Practice Project quality assessment tool.

Participants: Elderly inpatients discharged to home from hospital or returning home after an accident and emergency department visit.

Results: A total of 12 studies and five different scores were included in the review. The five scores present area under the receiving operating characteristic curve between 0.445 and 0.69. Identification of Senior At Risk (ISAR) and Triage Risk Screening Tool (TRST) scores were the more frequently validated scores with ISAR being more sensitive and TRST more specific.

Conclusions: The TRST and ISAR scores have been extensively studied and validated. The choice of the most suitable score relies on available patient data, patient characteristics and the foreseen clinical care intervention. In order to pair the intervention with the appropriate clinical score, further studies of external validation of clinical scores, identifying elderly patients at risk of early unplanned readmission, are needed.

Prospero registration number: CRD42017054516.

Keywords: clinical risk scores; elderly; public health; readmission.

PubMed Disclaimer

Conflict of interest statement

Competing interests: None declared.

Figures

Figure 1
Figure 1
Categories of predictors included in risk scores.
Figure 2
Figure 2
c-Statistics and sample sizes of included studies.
Figure 3
Figure 3
Sensitivity, specificity and c-statistics of the scores Identification of Senior At Risk (ISAR), lengths of stay, admission, Charlson, emergency (LACE), Triage Risk Screening Tool (TRST) and variable  indicative of placement (VIP).
Figure 4
Figure 4
Risk of bias across studies.
See this image and copyright information in PMC

References

    1. Haute Autorité de Santé. Comment réduire le risque de réhospitalisations évitables des personnes âgées ? 2013.
    1. Fischer C, Lingsma HF, Marang-van de Mheen PJ, et al. . Is the Readmission Rate a Valid Quality Indicator? A Review of the Evidence. PLoS ONE [Internet]. 2014;9 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4224424/. - PMC - PubMed
    1. Barnett ML, Hsu J, McWilliams JM. Patient Characteristics and Differences in Hospital Readmission Rates. JAMA Intern Med 2015;175:1803–12. 10.1001/jamainternmed.2015.4660 - DOI - PMC - PubMed
    1. Legrain S, Tubach F, Bonnet-Zamponi D, et al. . A new multimodal geriatric discharge-planning intervention to prevent emergency visits and rehospitalizations of older adults: the optimization of medication in AGEd multicenter randomized controlled trial. J Am Geriatr Soc 2011;59:2017–28. 10.1111/j.1532-5415.2011.03628.x - DOI - PubMed
    1. McIlvennan CK, Eapen ZJ, Allen LA. Hospital readmissions reduction program. Circulation 2015;131:1796–803. 10.1161/CIRCULATIONAHA.114.010270 - DOI - PMC - PubMed

Publication types