Frailty Is Associated With Early Hospital Readmission in Older Medical Patients

Stillman, Gary; Stillman, Andrew N.; Beecher, Michael S

doi:10.1177/0733464819894926

Cited by 23 publications

(20 citation statements)

References 38 publications

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“…Furthermore, patients at risk are more frail and may have a higher degree of morbidity, which could have affected the risk of readmission. 40 Readmission rates prior to the study Preintervention readmission rates may mirror differences in impact between studies. It may be assumed that hospitals with low preintervention readmission rates may experience no reduction of postintervention readmission rates as the remaining readmissions may not be preventable.…”

Section: Study Populationmentioning

confidence: 99%

Impact of transitional care interventions on hospital readmissions in older medical patients: a systematic review

Rasmussen¹,

Grode²,

Lange³

et al. 2021

BMJ Open

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ObjectivesTo identify and synthesise available evidence on the impact of transitional care interventions with both predischarge and postdischarge elements on readmission rates in older medical patients.DesignA systematic review.MethodInclusion criteria were: medical patients ≥65 years or mean age in study population of ≥75 years; interventions were transitional care interventions between hospital and home with both predischarge and postdischarge components; outcome was hospital readmissions. Studies were excluded if they: included other patient groups than medical patients, included patients with only one diagnosis or patients with only psychiatric disorders. PubMed, The Cochrane Library, Embase, Cumulative Index to Nursing and Allied Health Literature (CINAHL) and Web of Science were searched from January 2008 to August 2019. Study selection at title level was undertaken by one author; the remaining selection process, data extraction and methodological quality assessment were undertaken by two authors independently. A narrative synthesis was performed, and effect sizes were estimated.ResultWe identified 1951 records and included 11 studies: five randomised trials, four non-randomised controlled trials and two pre–post cohort studies. The 11 studies represent 15 different interventions and 29 outcome results measuring readmission rates within 7–182 days after discharge. Twenty-two of the 29 outcome results showed a drop in readmission rates in the intervention groups compared with the control groups. The most significant impact was seen when interventions were of high intensity, lasted at least 1 month and targeted patients at risk. The methodological quality of the included studies was generally poor.ConclusionTransitional care interventions reduce readmission rates among older medical patients although the impact varies at different times of outcome assessment. High-quality studies examining the impact of interventions are needed, preferably complimented by a process evaluation to refine and improve future interventions.PROSPERO registration numberCRD42019121795.

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Section: Study Populationmentioning

confidence: 99%

Impact of transitional care interventions on hospital readmissions in older medical patients: a systematic review

Rasmussen¹,

Grode²,

Lange³

et al. 2021

BMJ Open

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“…It is possible that, in the absence of an objective assessment of frailty, clinicians rely on age as a proxy for frailty, so as to determine their potential suitability for receipt of heart failure specific pharmacotherapy, an assumption which has been proven to be wrong according to our study as well as others [3]. Since frail patients are at a high risk of adverse health outcomes, such as death or readmission [21,22], the potential absolute benefits of treatment may be greatest in this subgroup of patients [23].…”

Section: Discussionmentioning

confidence: 91%

Trends in Frailty and Use of Evidence-Based Pharmacotherapy for Heart Failure in Australian Hospitalised Patients: An Observational Study

Sharma

Horwood

Hakendorf

et al. 2021

JCM

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Frailty increases morbidity and mortality in heart failure (HF) patients. Current risk-adjustment models do not include frailty-status and the relationship between frailty and pharmacotherapy is unclear. This study explored trends in frailty over time and its relationship with prescription of heart failure specific pharmacotherapy in hospitalised HF patients. We used the Hospital Frailty Risk Score (HFRS) to determine frailty status of patients ≥18 years admitted between 2015–2019 at two tertiary hospitals in Australia. Patients with an HFRS ≥ 5 were classified as frail. In the 3706 patients with a mean (SD) age of 76.1 (14.4) years, 876 (23.6%) were classified as frail. HFRS was weakly correlated with age (r = 0.16) and Charlson-index (r = 0.35) (both p values < 0.001). Whilst frailty was more common in older HF patients (28.9% of patients ≥80 years), 15.1% of patients ≤65 years of age were also found to be frail. The proportion of frail patients increased from 19.4% in 2015 to 29.2% in 2019 despite no significant change in age during this period. The proportion of patients who received heart failure specific pharmacotherapy decreased from 86.7% in 2015 to 82.9% in 2019 (p value = 0.03) and frail patients were significantly less likely to be prescribed HF specific pharmacotherapy than non-frail patients (77.4% vs. 85.9%, p < 0.001).

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“…Frailty status of the patients was assessed by use of the Edmonton Frail Scale (EFS) within 48 hours of hospital admission ( Keenan et al, 2017 ). The EFS is a valid and reliable instrument for identification of frailty in hospitalised patients and predicts clinical outcomes ( Keenan et al, 2017 ; Stillman et al, 2021 ). The EFS contains nine components and is scored out of 17.…”

Section: Methodsmentioning

confidence: 99%

Validity of the Malnutrition Universal Screening Tool for Evaluation of Frailty Status in Older Hospitalised Patients

Sharma

Avina

Ross

et al. 2022

Gerontology and Geriatric Medicine

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The malnutrition-universal-screening-tool (MUST) is commonly used for screening malnutrition in hospitalised patients but its utility in the detection of frailty is unknown. This study determined the utility of MUST in detection of frailty in older hospitalised patients. This prospective-study enrolled 243 patients ⩾65 years in a tertiary-teaching hospital in Australia. Patients with a MUST score of ⩾1 were classified as at-risk of malnutrition. Frailty status was determined by the Edmonton-Frail-Scale (EFS) and patients with an EFS score of >8 were classified as frail. We validated the MUST against the EFS by plotting a receiver-operating-characteristic-curve (ROC) curve and area-under-the-curve (AUC) was determined. The mean (SD) age was 83.9 (6.5) years and 126 (51.8%) were females. The EFS determined 149 (61.3%) patients as frail, while 107 (44.1%) patients were at-risk of malnutrition according to the MUST. There was a positive linear but weak association between the MUST and the EFS scores (Pearson’s correlation coefficient= .22, 95% CI .12– .36, p < .001). The sensitivity, specificity, positive and negative predictive value of MUST in the detection of frailty was 51%, 67%, 78.5% and 37%, respectively and the AUC was .59 (95% CI .53–.65, p < .001). The MUST is moderately sensitive in detection of frailty in older-hospitalised patients.

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Frailty Is Associated With Early Hospital Readmission in Older Medical Patients

Cited by 23 publications

References 38 publications

Impact of transitional care interventions on hospital readmissions in older medical patients: a systematic review

Impact of transitional care interventions on hospital readmissions in older medical patients: a systematic review

Trends in Frailty and Use of Evidence-Based Pharmacotherapy for Heart Failure in Australian Hospitalised Patients: An Observational Study

Validity of the Malnutrition Universal Screening Tool for Evaluation of Frailty Status in Older Hospitalised Patients

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