Risk factors for acute care hospital readmission in older persons in Western countries: a systematic review

Abstract

EXECUTIVE SUMMARY Background Hospital readmission in older persons is common and reported as a post-discharge adverse outcome from hospitalization. Readmission relates to a mix of factors associated with increasing age, living conditions, progression of disease as well as factors related to the processes of care. To allow health professionals to focus more intensively on patients at risk of readmission, there is a need to identify the characteristics of those patients. Objectives To identify and synthesize the best available evidence on risk factors for acute care hospital readmission within one month of discharge in older persons in Western countries. Inclusion criteria Types of participants Participants were older persons from Western countries, hospitalized and discharged home or to residential care facilities. Types of intervention(s)/phenomena of interest The factors of interest considered generic factors related to socio-demographics, health characteristics and clinical and organizational factors related to the care pathway. Types of studies The current review considered analytical and descriptive epidemiological study designs that evaluated risk factors for acute care hospital readmission. Outcomes The outcome was readmission to an acute care hospital within one month of discharge. Search strategy A three-step search was utilized to find published and unpublished studies in English, French, German, Norwegian, Swedish or Danish. Five electronic databases were searched from 2004 to 2013, followed by a manual search for additional studies. Methodological quality Methodological quality was assessed independently by two reviewers, using the standardized Joanna Briggs Institute Meta-Analysis of Statistics Assessment and Review Instrument (JBI-MAStARI) critical appraisal tool. Data extraction Data were extracted verbatim using a data extraction form, which identified the components from the standardized JBI data extraction tool from JBI-MAStARI and was adapted to the needs of the present review. Data synthesis Due to the clinical and methodological heterogeneity of the studies included, a narrative summary and metasynthesis of the quantitative findings was conducted. Results Based on a review of nine studies from ten Western countries, we found several significant risk factors pertaining to readmission to an acute care hospital within one month of discharge in persons aged 65 years and over. Factors associated with higher risk of hospital readmission covered socio-demographics such as higher age, male gender, ethnicity, living conditions, health characteristics such as poor overall condition and functional disability as well as prior admissions. Organizational factors including length of hospital stay, method of referral and discharge destination were associated with increased risk of acute care hospital readmission. Conclusion We found several significant, but inconsistent, associations between readmission to an acute care hospital within one month of discharge in persons aged 65 years and over. These associations involved a mix of socio-demographic factors, factors related to health and illness, previous hospitalizations, length of stay as well as clinical and organizational determinants related to the index admission. Although more studies concluded that certain diagnoses or comorbid conditions affected the risk of readmission, they did not agree on any disease in particular. Due to the breadth and diversity of variables examined and the lack of comparability of findings, the impact of these varying factors and their value as risk adjusters and application in different settings and populations are limited.

Social and clinical predictors of short- and long-term readmission after a severe exacerbation of copd

“…https://doi.org/10.1371/journal.pone.0229257.t001 Only the patients' dependence to perform BADLs measured by means of a questionnaire not specifically designed for patients with respiratory pathologies and previous history of admissions were identified as predictors over any of the analysed time periods. Thus far, the available references regarding this topic are scarce and heterogeneous, as they were obtained from very diverse studies (from small case series to large databases of insurance companies) and centres forming part of health systems with varying forms of health care services and very disparate patient populations [7,8,10,14,31]. In contrast to the findings of other studies [7,8,10], in our research, the patients' economic income, a low level of education, or poor family support (all determining factors of social and family risk) were not predictors of readmission, although it is true that most of our patients received some sort of economic compensation, had a place to live, and there were practically no cases of serious social isolation.…”

“…In contrast to the findings of other studies [7,8,10], in our research, the patients' economic income, a low level of education, or poor family support (all determining factors of social and family risk) were not predictors of readmission, although it is true that most of our patients received some sort of economic compensation, had a place to live, and there were practically no cases of serious social isolation. It should also be noted that the Spanish Health System is universally accessible and free of charge at all levels of care, an aspect that could have influenced these results [31]. Expressed as a mean ± standard deviation.…”

Development of a prediction model for 30-day acute readmissions among older medical patients: the influence of social factors along with other patient-specific and organisational factors

“…Studies have highlighted that readmission risk is influenced by both comorbidities treated outside hospital in the primary healthcare sector and organisational factors 8 42 43. To our knowledge, prediction studies have not previously included chronic condition information from non-hospital data sources.…”

“…One study has shown that the ability to manage disease is associated with socioeconomic factors such as income, wealth and educational level,6 and numerous studies on the association of specific risk factors with 30-day readmission have showed that both health-related and social factors are risk factors for acute readmissions among older patients 7 8. For older patients, readmission diagnosis often differs from the previous admission, indicating a high level of comorbidities, vulnerability related to transfer of care and to the fact that the majority of older patients do not fit into a single disease category 5 9.…”

Facilitating holistic continuity of care for older patients: Home care nurses’ experiences using checklists

“…With high rates of chronic conditions and often complex medical treatment, older patients often receive care from many healthcare providers and move frequently within different healthcare settings. Older patients are, therefore, particularly vulnerable to poor outcomes during care transitions (Naylor & Keating, 2008;Pedersen, Meyer, & Uhrenfeldt, 2017;Tingle, 2016). In addition, these problems contribute to increased rates of readmission and economic costs (Chapin, Chandran, Sergeant, & Koenig, 2014) and affect the patients' lives and personal transition processes (Coffey & McCarthy, 2012;Rustad, Cronfalk, Furnes, & Dysvik, 2016).…”