The Hospital Frailty Risk Score—outcomes in specialised services

Imam, Towhid; Konstant-Hambling, Rob; Fluck, Richard; Hall, Nathan; Palmer, James; Conroy, Simon

doi:10.1093/ageing/afaa156

Cited by 22 publications

(21 citation statements)

References 15 publications

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“…Despite higher HFRS being associated with increased 30-day mortality, longer LOS and 30-day readmission ( 8 , 10 ), this was not seen in patients under geriatrician care, where despite higher prevalence of patients with high HFRS, LOS was significantly lower with no significant increase in 30-day readmission. In total, thirty-day mortality was increased for patients under geriatrician-led care team which could be attributed to the higher mean age and HFRS for patients under geriatrician care.…”

Section: Discussionmentioning

confidence: 95%

“…Hospital Frailty Risk Score was initially described by Gilbert et al and utilizes ICD-10 codes to generate a frailty risk score ( 10 ). HFRS has been validated in multiple patient populations and is predictive of LOS, inpatient mortality, adverse events, and cost ( 8 , 19 ). Age-adjusted Charlson Comorbidity Index is a constitute of weighted index of age, number, and seriousness of comorbid disease, and originally validated to predict mortality ( 20 ).…”

Section: Methodsmentioning

confidence: 99%

“…However, performing this assessment for all the hospitalized older patients can be resource-intensive. In this regard, healthcare systems worldwide are studying the use of frailty score derived from electronic health records such as electronic frailty index (FI) or Hospital Frailty Risk Score (HFRS) to guide resource allocation ( 8 – 10 ).…”

Section: Introductionmentioning

confidence: 99%

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Outcomes of Care by Geriatricians and Non-geriatricians in an Academic Hospital

Merchant

Chen

et al. 2022

Front. Med.

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IntroductionWhile hospitalist and internist inpatient care models dominate the landscape in many countries, geriatricians and internists are at the frontlines managing hospitalized older adults in countries such as Singapore and the United Kingdom. The primary aim of this study was to determine outcomes for older patients cared for by geriatricians compared with non-geriatrician-led care teams.Materials and MethodsA retrospective cohort study of 1,486 Internal Medicine patients aged ≥75 years admitted between April and September 2021 was conducted. They were either under geriatrician or non-geriatrician (internists or specialty physicians) care. Data on demographics, primary diagnosis, comorbidities, mortality, readmission rate, Hospital Frailty Risk Score (HFRS), Age-adjusted Charlson Comorbidity Index, Length of Stay (LOS), and cost of hospital stay were obtained from the hospital database and analyzed.ResultsThe mean age of patients was 84.0 ± 6.3 years, 860 (57.9%) females, 1,183 (79.6%) of Chinese ethnicity, and 902 (60.7%) under the care of geriatricians. Patients under geriatrician were significantly older and had a higher prevalence of frailty, dementia, and stroke, whereas patients under non-geriatrician had a higher prevalence of diabetes and hypertension. Delirium as the primary diagnosis was significantly higher among patients under geriatrician care. Geriatrician-led care model was associated with shorter LOS, lower cost, similar inpatient mortality, and 30-day readmission rates. LOS and cost were lower for patients under geriatrician care regardless of frailty status but significant only for low and intermediate frailty groups. Geriatrician-led care was associated with significantly lower extended hospital stay (OR 0.73; 95% CI 0.56–0.95) and extended cost (OR 0.69; 95% CI 0.54–0.95).ConclusionGeriatrician-led care model showed shorter LOS, lower cost, and was associated with lower odds of extended LOS and cost.

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Section: Discussionmentioning

confidence: 95%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Outcomes of Care by Geriatricians and Non-geriatricians in an Academic Hospital

Merchant

Chen

et al. 2022

Front. Med.

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“…HFRS helps identification of patients with characteristics of frailty, and at risk of adverse healthcare outcomes including mortality, prolonged hospital stays and unplanned readmissions. The score has been validated in medical 10 , 11 and surgical 12 , 13 patients.…”

Section: Introductionmentioning

confidence: 99%

Interaction effects of multimorbidity and frailty on adverse health outcomes in elderly hospitalised patients

Lujic

Randall

Simpson

et al. 2022

Sci Rep

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We quantified the interaction of multimorbidity and frailty and their impact on adverse health outcomes in the hospital setting. Using aretrospective cohort study of persons aged ≥ 75 years, admitted to hospital during 2010–2012 in New South Wales, Australia, and linked with mortality data, we constructed multimorbidity, frailty risk and outcomes: prolonged length of stay (LOS), 30-day mortality and 30-day unplanned readmissions. Relative risks (RR) of outcomes were obtained using Poisson models with random intercept for hospital. Among 257,535 elderly inpatients, 33.6% had multimorbidity and elevated frailty risk, 14.7% had multimorbidity only, 19.9% had elevated frailty risk only and 31.8% had neither. Additive interactions were present for all outcomes, with a further multiplicative interaction for mortality and LOS. Mortality risk was 4.2 (95% CI 4.1–4.4), prolonged LOS 3.3 (95% CI 3.3–3.4) and readmission 1.8 (95% CI 1.7–1.9) times higher in patients with both factors present compared with patients with neither. In conclusion, multimorbidity and frailty coexist in older hospitalized patients and interact to increase the risk of adverse outcomes beyond the sum of their individual effects. Their joint effect should be considered in health outcomes research and when administering hospital resources.

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“…Given the need for additional training and time spent to applying these indices, this makes an automatable index such as HFRS an attractive alternative. Over the last few years the HFRS has been validated in numerous medical cohorts and has been used in studies to screen for frailty in medical populations 23‐28 . Less data exists for cohorts of surgical patients.…”

Section: Introductionmentioning

confidence: 99%

Validation of the Hospital Frailty Risk Score in older surgical patients: A population‐based retrospective cohort study

Gunnarsdottir

Helgadóttir

Einarsson

et al. 2021

Acta Anaesthesiol Scand

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Background There is a need for standardized and cost‐effective identification of frailty risk. The objective was to validate the Hospital Frailty Risk Score which utilizes International Classification Diagnoses in a cohort of older surgical patients, assess the score as an independent risk factor for adverse outcomes and compare discrimination properties of the frailty risk score with other risk stratification scores. Methods Data were analysed from all patients ≥65 years undergoing primary surgical procedures from 2006‐2018. Patients were categorized based on the frailty risk score. The primary outcomes were 30‐day mortality and 180‐day risk of readmission. Results Of 16 793 patients evaluated, 7480 (45%), 7605 (45%) and 1708 (10%) had a low, intermediate and high risk of frailty. There was a higher incidence of 30‐day mortality for individuals with intermediate (2.9%) and high (8.3%) compared with low (1.4%) risk of frailty (P < .001 for both comparisons). Similarly, the hazard of readmission within the first 180 days was higher for intermediate (HR 1.25; 95% CI: 1.16‐1.34) and high (HR 1.84; 95% CI: 1.66‐2.03) compared with low (HR 1.00, P < .001 for both comparisons) risk of frailty. The hazard of long‐term mortality was higher for intermediate (HR 1.70; 95% CI: 1.61‐1.80) and high (HR 4.16; 95% CI: 3.84‐4.49) compared with low (HR 1.00, P < .001 for both comparisons) risk of frailty. Finally, long length of primary hospitalization occurred for 9.3%, 15.0% and 27.3% of individuals with low, intermediate and high frailty risk (P < .001 for all comparisons). A model including age and ASA classification had the best discrimination for 30‐day mortality (AUC 0.862; 95% CI: 0.847‐0.877). Conclusion Our findings suggest that the Hospital Frailty Risk Score might be used to screen older surgical patients for risk of frailty. While only slightly improving prediction of 30‐day mortality using the ASA classification, the Hospital Frailty Risk Score can be used to independently classify older patients for the risk of important outcomes using pre‐existing readily available electronic data.

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The Hospital Frailty Risk Score—outcomes in specialised services

Cited by 22 publications

References 15 publications

Outcomes of Care by Geriatricians and Non-geriatricians in an Academic Hospital

Outcomes of Care by Geriatricians and Non-geriatricians in an Academic Hospital

Interaction effects of multimorbidity and frailty on adverse health outcomes in elderly hospitalised patients

Validation of the Hospital Frailty Risk Score in older surgical patients: A population‐based retrospective cohort study

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