Socio-environmental predictive factors for discharge destination after inpatient rehabilitation in patients with stroke: a systematic review and meta-analysis

Chevalley, Odile; Truijen, Steven; Saeys, Wim; Opsommer, Emmanuelle

doi:10.1080/09638288.2021.1923838

Cited by 11 publications

(16 citation statements)

References 65 publications

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“…In addition, further studies are required to consider socio-environmental factors such as the presence of support at home, living with others, and marital status. These factors were reported as crucial for the consideration of home discharge in a previous systematic review 27) and in another Japanese study. 28) The paragraphs below include suggestions for the selection of treatment regimens based on the latent ADL status and patient subgroups according to ADL status at admission.…”

Section: Discussionmentioning

confidence: 91%

Functional Independence Measure Subtypes among Inpatients with Subacute Stroke: Classification via Latent Class Analysis

Furuta

Mizuno

Unai

et al. 2022

PRM

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Objectives: Using Functional Independence Measure (FIM) records, this study used latent class analysis (LCA) to clarify the structure of activities of daily living (ADL) status in patients following stroke. Methods: In this retrospective, single-center study, we extracted the medical records of patients with stroke who were admitted to a rehabilitation hospital in Japan between April 2018 and March 2020. LCA was used to determine classes of ADL status based on response patterns in FIM items converted from the original seven levels to three levels: Complete Dependence, FIM1-2; Modified Dependence, FIM3-5; Independence, FIM6-7. We compared the length of stay and discharge destinations among subgroups of patients with different ADL status at admission. Results: From 373 patients, 1592 FIM records were analyzed. These were classified into six ADL status classes based on "Complete Dependence," "Modified Dependence," and "Independence" in the motor and cognitive domains. Significant differences were observed among the six admission ADL subgroups for the length of stay (median values in patient subgroups based on admission ADL status: 126, 146, 90, 65, 44, and 29 days in the Motor Complete/Cognitive Complete, Motor Complete/Cognitive Modified, Motor Modified/Cognitive Modified, Motor Modified/Cognitive Independent, Motor Independent/Cognitive Modified, and Motor Independent/Cognitive Independent groups, respectively) and discharge destinations (patients discharged home: 27%, 62%, 81%, 92%, 95%, and 98%, respectively, and to acute care hospitals: 18%, 14%, 8%, 8%, 2%, and 2%, respectively). Conclusions: LCA successfully stratified ADL status in patients with stroke undergoing rehabilitation and may aid in determining an appropriate treatment regimen.

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Section: Discussionmentioning

confidence: 91%

Functional Independence Measure Subtypes among Inpatients with Subacute Stroke: Classification via Latent Class Analysis

Furuta

Mizuno

Unai

et al. 2022

PRM

View full text Add to dashboard Cite

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“…Other studies have investigated the relationship between discharge home and the availability of a caring spouse or other person at home. 13,22,23 Similarly, the presence of a caregiver at home was associated with increased discharge to home, although Dutrieux et al 22 found this effect only in the patient group aged 70 years and above. Furthermore, living in an institution or at home with external help before stroke was a significant predictor of discharge to a residential facility.…”

Section: Discussionmentioning

confidence: 99%

“…In another review, support at home, living with others, being married, and living at home before stroke onset indicated a greater likelihood of a discharge home. 13 Moreover, while the impact of age and sex was less clear, a better pre-stroke functional and post-stroke cognitive status increased the likelihood of being discharged home. 14 In conclusion, different reviews recommend further research on age, sex, type of stroke, patient-specific biopsychosocial factors, other stroke-specific outcome measures, and global socioenvironmental determinants.…”

Section: Introductionmentioning

confidence: 99%

“…14 In conclusion, different reviews recommend further research on age, sex, type of stroke, patient-specific biopsychosocial factors, other stroke-specific outcome measures, and global socioenvironmental determinants. 11,[13][14][15] Therefore, we aimed to assess where stroke patients are discharged after acute treatment and to identify personal, pre-stroke, stroke-related, and clinical predictors of discharge destination.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Predictors of Discharge Destination After Stroke

Schrage

Thomalla

Härter

et al. 2023

Neurorehabil Neural Repair

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Background Determining the discharge destination after acute stroke care is important to prevent long-term disabilities and improve cost efficiency. Objective The aim of this study was to investigate where stroke patients are discharged to after acute treatment and to identify personal, social, stroke-related, and clinical predictors of discharge destination. Methods The present study included a secondary exploratory analysis of a prospective observational study. Patients with acute ischemic stroke, transient ischemic attack, or intracerebral hemorrhage were recruited consecutively over a 15-month period. A hierarchical multinomial logistic regression was performed to identify predictors of the primary outcome of discharge destination. Results We included 1026 stroke patients (48.7% female) with a mean age of 73.3 years (standard deviation 12.9 years) in the analysis. Overall, 55% of the patients were discharged home, 33% to a rehabilitation center, 3% to a residential facility, and 8% to another acute care hospital. Predictors that statistically significantly influenced the odds of the discharge destination were age, living situation pre-stroke, living location pre-stroke, stroke type, stroke severity, treatment type, and length of stay. Higher stroke severity was associated with discharge to all four inpatient facilities. Conclusions In line with previous research, predictors such as stroke severity and living situation pre-stroke significantly influenced the odds of the discharge destination. In contrast, pre-existing conditions and functional impairment pre-stroke had no significant impact on the primary outcome. This discrepancy could be due to a rather functional study sample before stroke and the use of clinical and patient-reported outcome measures.

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A systematic literature review of predicting patient discharges using statistical methods and machine learning

Pahlevani,

Taghavi,

Vanberkel

2024

Health Care Manag Sci

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Discharge planning is integral to patient flow as delays can lead to hospital-wide congestion. Because a structured discharge plan can reduce hospital length of stay while enhancing patient satisfaction, this topic has caught the interest of many healthcare professionals and researchers. Predicting discharge outcomes, such as destination and time, is crucial in discharge planning by helping healthcare providers anticipate patient needs and resource requirements. This article examines the literature on the prediction of various discharge outcomes. Our review discovered papers that explore the use of prediction models to forecast the time, volume, and destination of discharged patients. Of the 101 reviewed papers, 49.5% looked at the prediction with machine learning tools, and 50.5% focused on prediction with statistical methods. The fact that knowing discharge outcomes in advance affects operational, tactical, medical, and administrative aspects is a frequent theme in the papers studied. Furthermore, conducting system-wide optimization, predicting the time and destination of patients after discharge, and addressing the primary causes of discharge delay in the process are among the recommendations for further research in this field.

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Socio-environmental predictive factors for discharge destination after inpatient rehabilitation in patients with stroke: a systematic review and meta-analysis

Cited by 11 publications

References 65 publications

Functional Independence Measure Subtypes among Inpatients with Subacute Stroke: Classification via Latent Class Analysis

Functional Independence Measure Subtypes among Inpatients with Subacute Stroke: Classification via Latent Class Analysis

Predictors of Discharge Destination After Stroke

A systematic literature review of predicting patient discharges using statistical methods and machine learning

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