Hospital-acquired functional decline in older patients cared for in acute medical wards and predictors: Findings from a multicentre longitudinal study

Palese, Alvisa; Gonella, Silvia; Moreale, Renzo; Guarnier, Annamaria; Barelli, Paolo; Zambiasi, Paola; Allegrini, Elisabetta; Bazoli, Letizia; Casson, Paola; Marin, Meri; Padovan, Marisa; Picogna, Michele; Taddia, Patrizia; Salmaso, Daniele; Chiari, Paolo; Frison, Tiziana; Marognolli, Oliva; Benaglio, Carla; Canzan, Federica; Ambrosi, Elisa; Saiani, Luisa

doi:10.1016/j.gerinurse.2016.01.001

Cited by 55 publications

(57 citation statements)

References 31 publications

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“…Older people are more likely to have multiple and complex presenting complaints, often compounded by polypharmacy, frailty, delirium and/or dementia . If admitted to hospital, they are susceptible to iatrogenic complications, such as deconditioning, hospital acquired infection, medication errors and weight loss . As such, tailored methods of assessment in the ED have been developed, implemented and/or evaluated to achieve the right care in the most appropriate location.…”

Section: Introductionmentioning

confidence: 99%

Predictors of a long length of stay in the emergency department for older people

Sweeny

Keijzers

O’Dwyer

et al. 2020

Internal Medicine Journal

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Background Dedicated geriatric models of care are becoming more prevalent due to the complexity of, and increase in, acute healthcare presentations for older patients. For older people, a long stay in the emergency department (ED) may reflect the complexity of their presentation, or deficiencies in systems that manage these complexities. Aims To identify predictors of a long ED length of stay (LLoS) for patients ≥65 years old. Methods Linked hospital information systems data from a large, public Australian ED were analysed in this retrospective cohort study. LLoS was defined as the 75th percentile (617 min). Multivariate regression identified LLoS predictors for admissions and discharges separately. Results Of 16 791 ED presentations made by older people, 4192 experienced a LLoS; 55% were admitted. Increasing age was associated with an increasing ED LoS. Factors most predictive of LLoS for both admitted and discharged patients included: investigations (both pathology and imaging), less urgent Australasian triage scale categories and after‐hours arrival. Ambulance arrival did not increase the risk of a LLoS for patients eventually admitted, but conferred nearly a twofold increased risk for a LLoS for discharged older persons (adjusted odds ratios = 1.9; 95% confidence interval 1.5–2.4). Conclusions This study assists clinicians and decision‐makers to identify reasons why older persons have a LLoS, whether admitted or discharged. Interventions to streamline care for older patients arriving after‐hours and who require imaging and pathology are required. LoS targets should consider age distribution. The use of ED LoS as a quality of care indicator should be assessed for admissions and discharges, separately.

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Section: Introductionmentioning

confidence: 99%

Predictors of a long length of stay in the emergency department for older people

Sweeny

Keijzers

O’Dwyer

et al. 2020

Internal Medicine Journal

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“…Functional decline is a dynamic process that occurs in up to 50% of older people hospitalised for acute illness [1][2][3]. It is associated with poor hospital outcomes, extremely poor long-term outcomes, greater service utilisation and higher societal costs [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

“…Besides the disabling effects of certain illnesses (such as stroke or metastatic cancer) and patient-related characteristics (such as age, frailty, impaired cognition, low albumin, low social activity, residence, and social and financial supports) [3,7], hospitalisation itself produces additional stressors. These include environmental hazards, reduced caloric intake, low physical activity and/ or impaired mobility, depressed mood, social isolation and iatrogenic factors, such as medication errors and continence care [1,8,19]. Organisational factors, such as staffing availability and skill set, may also impact on the likelihood of decline [1].…”

Section: Introductionmentioning

confidence: 99%

“…These include environmental hazards, reduced caloric intake, low physical activity and/ or impaired mobility, depressed mood, social isolation and iatrogenic factors, such as medication errors and continence care [1,8,19]. Organisational factors, such as staffing availability and skill set, may also impact on the likelihood of decline [1]. Furthermore, over time, patient populations, service delivery models, hospital occupancy rates, drug therapies, prevalence of multiresistant organisms, nursing numbers and mix may have changed.…”

Section: Introductionmentioning

confidence: 99%

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Predictors on admission of functional decline among older patients hospitalised for acute care: A prospective observational study

et al. 2017

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“…Unexpectedly, patients in the PNS® group depicted significantly higher odds of functional decline compared to patients in the fixed‐team nursing group. Palese et al () demonstrated that more care provided by nursing assistants instead of RNs doubles the risk of declining functional status, and thus, an increase in nurse assistant‐to‐patient ratio could be a possible explanation for functional decline in patients in the PNS® group. However, it is necessary to conduct further exploration on how an increase in the proportion of severe patients changes RNs' practices and how the implementation of PNS® influences nursing care for supporting patients' ADLs.…”

Section: Discussionmentioning

confidence: 99%

Association between nursing care delivery models and patients' health outcomes in a university hospital: A retrospective cohort study based on the Diagnostic Procedure Combination database

Higaonna

Morimoto

Ueda

2020

Japan Journal Nursing Sci

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Aim This study aims to examine the association between nursing delivery models (fixed‐team nursing model and Partnership Nursing System® [PNS®]) and patients' health outcomes (30‐day in‐hospital mortality and functional decline, indicated by a decline in Barthel Index or in‐hospital mortality). Methods This study used a retrospective cohort design based on the data from the Diagnostic Procedure Combination database, which included routinely collected health data for Japanese administrative claims. Participants were inpatients aged 20–99 years admitted between July 2010 and August 2012 (fixed‐team nursing period) and July 2014 and August 2017 (PNS® period) to an academic teaching hospital in Japan. Odds ratios and 95% confidence intervals were estimated using multivariable logistic models. Results We included 24,108 and 23,872 patients for the analyses of 30‐day in‐hospital mortality and functional decline, respectively (median age: 62 years; 52% women). The 30‐day mortalities in both fixed‐team nursing and PNS® groups were 0.5%. There was no significant association between the nursing delivery models and 30‐day in‐hospital mortality (adjusted odds ratio = 1.15, 95% confidence interval = 0.78–1.70). However, the PNS® group was found to have a higher proportion of patients with functional decline (2.7%) than the fixed‐team nursing group (2.2%; p = .030). The adjusted odds ratio of declined function in the PNS® group, compared to the fixed‐team nursing group, was 1.40 (95% confidence interval = 1.17–1.68, p < .001). Conclusions Further studies are needed to examine how the PNS® model influences patient outcomes, especially nurse‐sensitive patient outcomes.

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Hospital-acquired functional decline in older patients cared for in acute medical wards and predictors: Findings from a multicentre longitudinal study

Cited by 55 publications

References 31 publications

Predictors of a long length of stay in the emergency department for older people

Predictors of a long length of stay in the emergency department for older people

Predictors on admission of functional decline among older patients hospitalised for acute care: A prospective observational study

Association between nursing care delivery models and patients' health outcomes in a university hospital: A retrospective cohort study based on the Diagnostic Procedure Combination database

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