Screening Elders for Risk of Hospital Admission

Boult, Chad; Dowd, Bryan E; McCaffrey, David J.; Boult, Lisa; Hernández, Rafael; Krulewitch, Harry

doi:10.1111/j.1532-5415.1993.tb06175.x

Cited by 293 publications

(355 citation statements)

References 16 publications

(33 reference statements)

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“…Nonetheless, the following strata were statistically signifi cant: low risk (PRA<0.30), medium risk (PRA=0.30-0.49) and high risk (PRA≥0.500). 1,11,19 The observed predictive accuracy of the area under the ROC curve was 0. In our study, the PRA showed improved ability to identify elderly at risk of hospitalization within six months, when a cutoff value of 0.4 was used to defi ne the high risk population.…”

Section: Discussionmentioning

confidence: 99%

“…Based on these results, Boult et al 1 developed a Probability of Repeated Hospital Admissions (Predição de Risco de Admissão Hospitalar -PRA) questionnaire. 1,3,12,13 In accordance with the presence or not of risk factors, the logistic regression model applied to PRA generates a value from 0 to 1. Higher values correspond to increased risk of hospital admittance.…”

Section: Introductionmentioning

confidence: 99%

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Validade preditiva de instrumento para identificação do idoso em risco de hospitalização

Dutra

Moriguchi

Lampert³

et al. 2011

Rev. Saúde Pública

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OBJETIVO: Avaliar a validade de predição do Instrumento de Predição de Risco de Admissão Hospitalar Repetida da hospitalização de idosos. MÉTODOS: Estudo de coorte de base populacional com seguimento de seis meses com 515 idosos (> 60 anos de idade) não-institucionalizados, atendidos pela Estratégia Saúde da Família na cidade de Progresso, RS, em 2005. Os idosos responderam a oito perguntas objetivas, que foram reunidas em modelo de regressão logística para estimar seu risco de admissão hospitalar futura, por estratos de risco. Análise de sobrevida e a curva Receiver Operating Characteristics foram empregadas para aferir a validade do instrumento. RESULTADOS: Dos entrevistados, 56,1% eram mulheres e 10,1% foram hospitalizados. O grupo de risco alto teve freqüência de internação hospitalar 6,5 vezes superior em relação ao grupo de risco baixo. CONCLUSÕES: O instrumento é efetivo ao predizer o risco de hospitalização dos idosos atendidos pela Estratégia Saúde da Família do Sistema Único de Saúde.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Validade preditiva de instrumento para identificação do idoso em risco de hospitalização

Dutra

Moriguchi

Lampert³

et al. 2011

Rev. Saúde Pública

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“…These findings are close to those variables found in other studies on the general population and on elderly people. For instance, "Probability of Repeated Admission" (Pra) and "The Community Assessment Risk Screen" (CARS) tools (Boult et al, 1993;Shelton et al, 2000) include as relevant variables diagnosis of different chronic conditions (such as diabetes or heart diseases), as well as previous use of hospital resources (admissions or ED visits).…”

Section: Discussionmentioning

confidence: 99%

Development of a Predictive Model of Elderly Patients at Risk of Future Hospital Admission at Primary Care Centres in Valencia (Spain)

Doñate-Martínez¹,

Ródenas-Rigla²,

Garcés‐Ferrer³

2017

Eur. j. interdiscip. stud.

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This paper presents the development of a new predictive model of elders at risk of suffering hospital admissions in the subsequent year in Valencia (Spain), based on primary care experts' discussions and consensus. The study involves three main stages. Firstly, Focus Group methodology with six primary care experts to design the first set of variables of the model. Subsequently, two retrospective studies to analyse the performance of the selected variables in a pilot sample (n=107) and to design the predictive model in a development sample (n=343). Data was collected from electronic medical records and consulting the professional of reference. Logistic regression analysis identified five variables as predictors of hospital admissions during the subsequent year of the development cohort: diagnosis of chronic heart diseases, chronic respiratory diseases, diabetes, presence of palliative care and number of previous visits to the hospital emergency department. A risk scoring system was developed for each patient from 0 to 1, with a cut-off point of 0. 5. The model had a sensitivity of 42%, specificity of 96% and AUC of 0. 764. Our predictive model identifies with moderate efficiency elderly patients at risk of suffering future hospital admissions. Additionally, this first screening could be extended through a second phase aimed to assess social variables which are very relevant in the current economic context in Spain. Further research is needed to validate these results with larger samples, and to explore their applicability in other health and social care settings.

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“…16,17 Functional decline is associated with social isolation, reduced quality of life, and death. 3,5,7,8,14,[18][19][20][21][22] It is also an important predictor of hospitalization, 23,24 prolonged hospital stay, 25 repeat ED visits, 7,26 and the need for home care 25 . Moreover, functional decline is the most important predictor of admission to institutions and of disproportionate use of health services by the elderly population.…”

Section: Introductionmentioning

confidence: 99%

National Survey of Emergency Physicians to Define Functional Decline in Elderly Patients with Minor Trauma

Abdulaziz

Brehaut

Taljaard

et al. 2015

CJEM

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Background: There are a number of screening tools to predict return to the emergency department (ED) in elderly trauma patients, but none exist to specifically screen for functional decline after a minor injury. The objective of this study was to identify outcome measures for a possible future clinical decision rule to be used in the ED to identify previously independent patients at high risk of functional decline at six months post minor injury. Methods: After a rigorous development process, a survey instrument was administered to a random sample of 178 emergency physicians using the Dillman's Tailored Design Method. Results: Of 156 eligible surveys, we received 81 completed surveys (response rate 51.9%). Considering all 14 activities of daily living (ADL) items, 90% of physicians deemed a minimal clinically important difference (MCID) in function to be at least three points on the 28-point Older Americans Resources and Services (OARS) ADL Scale as clinically significant. A tool with a sensitivity of 93% to detect patients at risk of functional decline at six months post injury would meet or exceed the sensitivity deemed to be required by 90% of physicians. The majority of emergency physicians do not assess elderly injured patients for the majority of the tasks. Conclusions: A drop of three points on the 28-point OARS ADL Scale would be deemed clinically important by the vast majority of emergency physicians. Further, a sensitivity of 93% for a clinical decision tool would satisfy the MCID requirements of the vast majority of emergency physicians. There appears to be a gap between physician knowledge and actual practice. We intend to use these findings in the development of a clinical decision rule to identify high-risk elderly trauma patients.

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Screening Elders for Risk of Hospital Admission

Cited by 293 publications

References 16 publications

Validade preditiva de instrumento para identificação do idoso em risco de hospitalização

Validade preditiva de instrumento para identificação do idoso em risco de hospitalização

Development of a Predictive Model of Elderly Patients at Risk of Future Hospital Admission at Primary Care Centres in Valencia (Spain)

National Survey of Emergency Physicians to Define Functional Decline in Elderly Patients with Minor Trauma

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