Scoping review: Social support impacts hospital readmission rates

Impact of time from discharge to readmission on outcomes: an observational study from the US National Readmission Database

BACKGROUND

The Hospital Readmission Reduction Programme (HRRP) was created to decrease the number of hospital readmissions for acute myocardial infarction (AMI), chronic obstructive pulmonary disease (COPD), heart failure (HF), pneumonia (PNA), coronary artery bypass graft (CABG), elective total hip arthroplasty (THA) and total knee arthroplasty.

OBJECTIVES

To analyse the impact of the HRRP on readmission rates from 2010 to 2019 and how time to readmission impacted outcomes.

DESIGN

Population-based retrospective study.

SETTING

All patients included in the US National Readmission database from 2010 to 2019.

PATIENTS

We recorded demographic and clinical variables.

MEASUREMENTS

Using linear regression models, we analysed the association between readmission status and timing with death and length of stay (LOS) outcomes. We transformed LOS and charges into log-LOS and log-charges to normalise the data.

RESULTS

There were 31 553 363 records included in the study. Of those, 4 593 228 (14.55%) were readmitted within 30 days. From 2010 to 2019, readmission rates for COPD (20.8%-19.8%), HF (24.9%-21.9%), PNA (16.4%-15.1%), AMI (15.6%-12.9%) and TKR (4.1%-3.4%) decreased whereas CABG (10.2%-10.6%) and THA (4.2%-5.8%) increased. Readmitted patients were at higher risk of mortality (6% vs 2.8%) and had higher LOS (3 (2-5) vs 4 (3-7)). Patients readmitted within 10 days had a mortality 6.4% higher than those readmitted in 11-20 days (5.4%) and 21-30 days (4.6%). Increased time from discharge to readmission was associated with a lower likelihood of mortality, like LOS.

CONCLUSION

Over the last 10 years, readmission rates decreased for most conditions included in the HRRP except CABG and THA. Patients readmitted shortly after discharge were at higher risk of death.

Using social risks to predict unplanned hospital readmission and emergency care among hospitalized Veterans

OBJECTIVES

(1) To estimate the association of social risk factors with unplanned readmission and emergency care after a hospital stay. (2) To create a social risk scoring index.

DATA SOURCES AND SETTING

We analyzed administrative data from the Department of Veterans Affairs (VA) Corporate Data Warehouse. Settings were VA medical centers that participated in a national social work staffing program.

STUDY DESIGN

We grouped socially relevant diagnoses, screenings, assessments, and procedure codes into nine social risk domains. We used logistic regression to examine the extent to which domains predicted unplanned hospital readmission and emergency department (ED) use in 30 days after hospital discharge. Covariates were age, sex, and medical readmission risk score. We used model estimates to create a percentile score signaling Veterans' health-related social risk.

DATA EXTRACTION

We included 156,690 Veterans' admissions to a VA hospital with discharged to home from 1 October, 2016 to 30 September, 2022.

PRINCIPAL FINDINGS

The 30-day rate of unplanned readmission was 0.074 and of ED use was 0.240. After adjustment, the social risks with greatest probability of readmission were food insecurity (adjusted probability = 0.091 [95% confidence interval: 0.082, 0.101]), legal need (0.090 [0.079, 0.102]), and neighborhood deprivation (0.081 [0.081, 0.108]); versus no social risk (0.052). The greatest adjusted probabilities of ED use were among those who had experienced food insecurity (adjusted probability 0.28 [0.26, 0.30]), legal problems (0.28 [0.26, 0.30]), and violence (0.27 [0.25, 0.29]), versus no social risk (0.21). Veterans with social risk scores in the 95th percentile had greater rates of unplanned care than those with 95th percentile Care Assessment Needs score, a clinical prediction tool used in the VA.

CONCLUSIONS

Veterans with social risks may need specialized interventions and targeted resources after a hospital stay. We propose a scoring method to rate social risk for use in clinical practice and future research.

Barriers and facilitators of readiness for hospital discharge in patients with myocardial infarction: a qualitative study: quality improvement study

Background

Readiness for hospital discharge (RHD) in patients with myocardial infarction (MI) is a key concept in the discharge process. This study was conducted to explain the barriers and facilitators of preparation for discharge in patients with MI.

Materials and methods

A qualitative study was conducted using conventional content analysis from April 2021 to 2022. Data collection was done in a targeted manner through semi-structured interviews until the data saturation stage. Nineteen participants (11 patients, 3 family members, and 5 healthcare team) were interviewed. Data analysis was done in eight steps according to the suggested steps of Graneheim and Lundman. MAXQDA18 software was used for coding.

Results

From the interviews, 348 primary codes, 11 sub-categories, and 5 categories were extracted. Finally, after continuous analysis and comparison of interviews, codes, and categories, two themes including "supporting platform" and "caring atmosphere" were extracted, which were the result of the participants' experience and understanding of the barriers and facilitators of RHD. The supporting platform included "family support" and "social support" and the caring atmosphere included "care gaps" and "professional healthcare team performance".

Conclusion

The results of this study indicate several factors affecting RHD in heart attack patients. According to the results of the study, the participation of the patient, family, healthcare team, and community in creating RHD is recommended. It is also suggested to pay attention to these factors in care and treatment planning to help improve health and control complications and prevent re-hospitalization in these patients.

How Might We Have Known? Using Administrative Data to Predict 30-Day Hospital Readmission in Clients Receiving Home Care Services from 2018 to 2021

Background

Reducing hospital readmissions can improve individual health outcomes and lower system-level costs. This study aimed to understand the characteristics of home care Personal Support clients who experienced a hospital admission (ie, hospital hold) and to identify factors that predict hospital readmission within 30 days of resuming home care Personal Support services.

Methods

We conducted a retrospective cohort study using client administrative data from a home healthcare provider organization (2018-2021). The sample included clients (⩾18 years) who received publicly funded Personal Support services and experienced a hospital hold. Descriptive statistics and a binary logistic regression model analyzed the relationship between demographics, hospital service utilization, home care service utilization, and contextual factors on the outcome of 30-day hospital readmission.

Results

Approximately 17% (n = 662) of all clients with a hospital hold (n = 3992) were readmitted to hospital within 30 days. Compared with non-readmitted clients, those with greater home care Personal Support service intensity after the index hospital hold were less likely to experience a hospital 30-day readmission. In contrast, those with greater acuity, higher assessed care needs, more hospital holds overall, more extended hospital stays (⩾2 weeks), and lower social support had a higher likelihood of 30-day hospital readmission.

Conclusion

The findings from this study provide a greater understanding of factors associated with home care clients' risk of hospital readmission within 30 days and can be used to inform targeted, evidence-based support to reduce home care clients' hospital readmissions.

Instruments Measuring Self-Care and Self-Management of Chronic Conditions by Community-Dwelling Older Adults: A Scoping Review

Given the high prevalence of chronic conditions and multimorbidity in older adults, there is a need to better conceptualize and measure self-care and self-management to promote a person-centered approach. This scoping review aimed to identify and map instruments measuring self-care and self-management of chronic conditions by older adults. We searched six electronic databases, charted data from the studies and tools and reported the results in accordance with the PRISMA-ScR guidelines. A total of 107 articles (103 studies) containing 40 tools were included in the review. There was substantial variation in the tools in terms of their aims and scope, structure, theoretical foundations, how they were developed, and the settings in which they have been used. The quantity of tools demonstrates the importance of assessing self-care and self-management. Consideration of the purpose, scope, and theoretical foundation should guide decisions about tools suitable for use in research and clinical practice.

Social network and severe lower respiratory tract infections in older adults: findings from a Swedish longitudinal population-based study

OBJECTIVES

To investigate the association between social network and the risk and prognosis of severe lower respiratory tract infections (LRTIs) in older adults.

METHODS

Data from Swedish hospital records were matched with the Swedish National Study on Aging and Care in Kungsholmen (SNAC-K). Social network was operationalized as social connections and social support, based on different self-reported variables, and categorized as low, medium, and high. The risk of severe LRTI and related outcomes were assessed using Cox, Poisson, and logistic regression models where appropriate.

RESULTS

A total of 362 individuals experienced LRTI-related hospitalizations between 2001 and 2016 (479 total hospitalizations). High levels of social support decreased the hazard of incident LRTI by 29% (hazard ratio 0.71, 95% confidence interval [CI] 0.52-0.96), the hospital length of stay by 21% (incidence rate ratio 0.79, 95% CI 0.65-0.97), and the risk of 30-day mortality by 92% (odds ratio 0.08, 95% CI 0.01-0.68), but was a risk factor for 30-day readmission (odds ratio 3.16, 95% CI 1.38-7.24). High levels of social connections were associated with a higher risk of incident LRTI in women and those with dementia and/or slow walking speed (P_interaction <0.05).

CONCLUSION

Older individuals' quality of social support seems to be a stronger determinant of LRTI incidence and prognosis than the quantity of their social connections. These findings may inform evidence-based policies aimed at preventing LRTIs in older adults.

Development and validation of a social vulnerabilities survey for medical inpatients

OBJECTIVES

Our objective was to validate a Social Vulnerabilities Survey that was developed to identify patient barriers in the following domains: (1) salience or priority of health; (2) social support; (3) transportation; and (4) finances.

DESIGN

Cross-sectional psychometric study.Questions for one domain (health salience) were developed de novo while questions for the other domains were derived from national surveys and/or previously validated questionnaires. We tested construct (ie, convergent and discriminative) validity for these new questions through hypothesis testing of correlations between question responses and patient characteristics. Exploratory factor analysis was conducted to determine structural validity of the survey as a whole.

SETTING

Patients admitted to the inpatient internal medicine service at a tertiary care hospital in Calgary, Canada.

PARTICIPANTS

A total of 406 patients were included in the study.

RESULTS

The mean age of respondents was 55.5 (SD 18.6) years, with the majority being men (55.4%). In feasibility testing of the first 107 patients, the Social Vulnerabilities Survey was felt to be acceptable, comprehensive and met face validity. Hypothesis testing of the health salience questions revealed that the majority of observed correlations were exactly as predicted. Exploratory factor analysis of the global survey revealed the presence of five factors (eigenvalue >1): social support, health salience, drug insurance, transportation barriers and drug costs. All but four questions loaded to these five factors.

CONCLUSIONS

The Social Vulnerabilities Survey has face, construct and structural validity. It can be used to measure modifiable social vulnerabilities, such that their effects on health outcomes can be explored and understood.