Predictors of hospital readmission after stroke: a systematic review

Females with diabetes have a higher risk of ischemic stroke readmission: a retrospective cohort study

BACKGROUND

There are significant sex differences in the incidence of stroke or diabetes mellitus. However, little is known about sex differences in stroke rehospitalization among diabetic patients.

OBJECT

To explore the sex differences in short-term and long-term rehospitalization of ischemic stroke patients with Type 2 diabetes mellitus.

METHODS

A retrospective cohort study was conducted from 2017 to 2021. The rehospitalization events of ischemic stroke patients with diabetes mellitus were identified by the national unified Electronic Health Record. Propensity score matching was applied to adjust for multiple covariates, and LASSO regression was used to screen for independent variables. Cox proportional hazards model was utilized to analyze the different sex in short-term (90 days, 1 year) and long-term (5 years) rehospitalization in ischemic stroke patients with type 2 diabetes mellitus.

RESULT

A total of 10,724 ischemic stroke patients were included in this study, of whom 5,952 (55.5%) were males. After a 1:1 propensity score matching, there were 3,460 males and 2,772 females. After adjusting for confounding factors, female patients with type 2 diabetes had an increased risk of ischemic stroke rehospitalization at 90 days (HR: 1.94, 95%CI: 1.13-3.33, P < 0.05), 1 year (HR: 1.65, 95%CI:1.22-2.23, P = 0.001), and 5 years (HR: 1.58, 95%CI: 1.26-1.97, P < 0.001). However, there was no significant relationship between male patients with type 2 diabetes and the risk of ischemic stroke rehospitalization, either in the short or long term.

CONCLUSION

Females with type 2 diabetes mellitus have a higher risk of ischemic stroke rehospitalization in both the short-term and long-term.

Community Participation Transition After Stroke (COMPASS) Randomized Controlled Trial: Effect on Adverse Health Events

OBJECTIVE

To compare adverse health events in intervention versus control group participants in the Community Participation Transition After Stroke trial to reduce barriers to independent living for community-dwelling stroke survivors.

DESIGN

Randomized controlled trial.

SETTING

Inpatient rehabilitation (IR) to home and community transition.

PARTICIPANTS

Stroke survivors aged ≥50 years being discharged from IR who had been independent in activities of daily living prestroke (N=183).

INTERVENTIONS

Participants randomized to intervention group (n=85) received home modifications and self-management training from an occupational therapist over 4 visits in the home. Participants randomized to control group (n=98) received the same number of visits consisting of stroke education.

MAIN OUTCOME MEASURES

Death, skilled nursing facility (SNF) admission, 30-day rehospitalization, and fall rates after discharge from IR.

RESULTS

Time-to-event analysis revealed that the intervention reduced SNF admission (cumulative survival, 87.8%; 95% confidence interval [CI], 78.6%-96.6%) and death (cumulative survival, 100%) compared with the control group (SNF cumulative survival, 78.9%; 95% CI, 70.4%-87.4%; P=.039; death cumulative survival, 87.3%; 95% CI, 79.9%-94.7%; P=.001). Thirty-day rehospitalization also appeared to be lower among intervention participants (cumulative survival, 95.1%; 95% CI, 90.5%-99.8%) than among control participants (cumulative survival, 86.3%; 95% CI, 79.4%-93.2%; P=.050) but was not statistically significant. Fall rates did not significantly differ between the intervention group (5.6 falls per 1000 participant-days; 95% CI, 4.7-6.5) and the control group (7.2 falls per 1000 participant-days; 95% CI, 6.2-8.3; incidence rate ratio, 0.78; 95% CI, 0.46-1.33; P=.361).

CONCLUSIONS

A home-based occupational therapist-led intervention that helps stroke survivors transition to home by reducing barriers in the home and improving self-management could decrease the risk of mortality and SNF admission after discharge from rehabilitation.

Association between repeat imaging and readmission in patients with acute ischaemic stroke: a 16-year nationwide population-based study

OBJECTIVES

This study aims to evaluate such usage patterns and identify factors that may contribute to the need for repeat imaging in acute ischaemic stroke patients and determine the association between repeat imaging and readmission in Taiwan.

METHODS

We searched and analysed data from the Taiwan National Health Insurance Research Database for patients admitted for acute ischaemic stroke between 2002 and 2017. Cases where repeat brain imaging during the initial hospital admission occurred and where patients were readmitted within 30 days following discharge were documented.

RESULTS

Of a total of 195 016 patients with new onset ischaemic stroke, 51 798 (26.6%) underwent repeat imaging during their initial admission. Factors associated with repeat brain imaging included younger age, longer hospital stay, use of recombinant tissue plasminogen activator (rt-PA) therapy (odds ratio = 2.10 [95% CI, 1.98-2.22]), more recent year of diagnosis, higher National Institutes of Health Stroke Scale (NIHSS) score, and admission to a hospital offering a higher level of care. Repeat imaging was also associated with an increased risk of ischaemic stroke and all types of stroke readmission.

CONCLUSIONS

Repeat brain imaging of patients with stroke has increased in recent years, and it is associated with certain factors including age, length of stay, use of rt-PA, hospital level of care, and NIHSS score. It is also associated with increased readmission.

ADVANCES IN KNOWLEDGE

Knowledge of the associations of repeat imaging may help clinicians use repeat imaging more carefully and efficaciously.

Association of Posttraumatic Stress Disorder and Race on Readmissions After Stroke

BACKGROUND

There is limited research on outcomes of patients with posttraumatic stress disorder (PTSD) who also develop stroke, particularly regarding racial disparities. Our goal was to determine whether PTSD is associated with the risk of hospital readmission after stroke and whether racial disparities existed.

METHODS

The analytical sample consisted of all veterans receiving care in the Veterans Health Administration who were identified as having a new stroke requiring inpatient admission based on the International Classification of Diseases codes. PTSD and comorbidities were identified using the International Classification of Diseases codes and given the date of first occurrence. The retrospective cohort data were obtained from the Veterans Affairs Corporate Data Warehouse. The main outcome was any readmission to Veterans Health Administration with a stroke diagnosis. The hypothesis that PTSD is associated with readmission after stroke was tested using Cox regression adjusted for patient characteristics including age, sex, race, PTSD, smoking status, alcohol use, and comorbidities treated as time-varying covariates.

RESULTS

Our final cohort consisted of 93 651 patients with inpatient stroke diagnosis and no prior Veterans Health Administration codes for stroke starting from 1999 with follow-up through August 6, 2022. Of these patients, 12 916 (13.8%) had comorbid PTSD. Of the final cohort, 16 896 patients (18.0%) with stroke were readmitted. Our fully adjusted model for readmission found an interaction between African American veterans and PTSD with a hazard ratio of 1.09 ([95% CI, 1.00-1.20] P=0.047). In stratified models, PTSD has a significant hazard ratio of 1.10 ([95% CI, 1.02-1.18] P=0.01) for African American but not White veterans (1.05 [95% CI, 0.99-1.11]; P=0.10).

CONCLUSIONS

Among African American veterans who experienced stroke, preexisting PTSD was associated with increased risk of readmission, which was not significant among White veterans. This study highlights the need to focus on high-risk groups to reduce readmissions after stroke.

Rapid systematic review of readmissions costs after stroke

BACKGROUND

Stroke readmissions are considered a marker of health quality and may pose a burden to healthcare systems. However, information on the costs of post-stroke readmissions has not been systematically reviewed.

OBJECTIVES

To systematically review information about the costs of hospital readmissions of patients whose primary diagnosis in the index admission was a stroke.

METHODS

A rapid systematic review was performed on studies reporting post-stroke readmission costs in EMBASE, MEDLINE, and Web of Science up to June 2021. Relevant data were extracted and presented by readmission and stroke type. The original study's currency values were converted to 2021 US dollars based on the purchasing power parity for gross domestic product. The reporting quality of each of the included studies was assessed using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist.

RESULTS

Forty-four studies were identified. Considerable variability in readmission costs was observed among countries, readmissions, stroke types, and durations of the follow-up period. The UK and the USA were the countries reporting the highest readmission costs. In the first year of follow-up, stroke readmission costs accounted for 2.1-23.4%, of direct costs and 3.3-21% of total costs. Among the included studies, only one identified predictors of readmission costs.

CONCLUSION

Our review showed great variability in readmission costs, mainly due to differences in study design, countries and health services, follow-up duration, and reported readmission data. The results of this study can be used to inform policymakers and healthcare providers about the burden of stroke readmissions. Future studies should not solely focus on improving data standardization but should also prioritize the identification of stroke readmission cost predictors.

An overview of reviews and synthesis across 440 studies examines the importance of hospital readmission predictors across various patient populations

OBJECTIVES

The scientific literature contains an abundance of prediction models for hospital readmissions. However, no review has yet synthesized their predictors across various patient populations. Therefore, our aim was to examine predictors of hospital readmissions across 13 patient populations.

STUDY DESIGN AND SETTING

An overview of systematic reviews was combined with a meta-analytical approach. Two thousand five hundred four different predictors were categorized using common ontologies to pool and examine their odds ratios and frequencies of use in prediction models across and within different patient populations.

RESULTS

Twenty-eight systematic reviews with 440 primary studies were included. Numerous predictors related to prior use of healthcare services (odds ratio; 95% confidence interval: 1.64; 1.42-1.89), diagnoses (1.41; 1.31-1.51), health status (1.35; 1.20-1.52), medications (1.28; 1.13-1.44), administrative information about the index hospitalization (1.23; 1.14-1.33), clinical procedures (1.20; 1.07-1.35), laboratory results (1.18; 1.11-1.25), demographic information (1.10; 1.06-1.14), and socioeconomic status (1.07; 1.02-1.11) were analyzed. Diagnoses were frequently used (in 37.38%) and displayed large effect sizes across all populations. Prior use of healthcare services showed the largest effect sizes but were seldomly used (in 2.57%), whereas demographic information (in 13.18%) was frequently used but displayed small effect sizes.

CONCLUSION

Diagnoses and patients' prior use of healthcare services showed large effects both across and within different populations. These results can serve as a foundation for future prediction modeling.

Stroke Subtype and Risk of Subsequent Hospitalization: The Atherosclerosis Risk in Communities Study

BACKGROUND AND OBJECTIVES

Risk of readmission after stroke differs by stroke (sub)type and etiology, with higher risks reported for hemorrhagic stroke and cardioembolic stroke. We examined the risk and cause of first readmission by stroke subtype over the years post incident stroke.

METHODS

Atherosclerosis Risk in Communities (ARIC) study participants (n = 1,412) with first-ever stroke were followed up for all-cause readmission after incident stroke. Risk of first readmission was examined by stroke subtypes (cardioembolic, thrombotic/lacunar, and hemorrhagic [intracerebral and subarachnoid]) using Cox and Fine-Gray proportional hazards models, adjusting for sociodemographic and cardiometabolic risk factors.

RESULTS

Among 1,412 participants (mean [SD] age 72.4 [9.3] years, 52.1% women, 35.3% Black), 1,143 hospitalizations occurred over 41,849 person-months. Overall, 81% of participants were hospitalized over a maximum of 26.6 years of follow-up (83% of participants with thrombotic/lacunar stroke, 77% of participants with cardioembolic stroke, and 78% of participants with hemorrhagic stroke). Primary cardiovascular and cerebrovascular diagnoses were reported for half of readmissions. Over the entire follow-up period, compared with cardioembolic stroke, readmission risk was lower for thrombotic/lacunar stroke (hazard ratio [HR] 0.82, 95% CI 0.71-0.95) and hemorrhagic stroke (HR 0.74, 95% CI 0.58-0.93) in adjusted Cox proportional hazards models. By contrast, there was no statistically significant difference among subtypes when adjusting for atrial fibrillation and competing risk of death. Compared with cardioembolic stroke, thrombotic/lacunar stroke was associated with lower readmission risk within 1 month (HR 0.66, 95% CI 0.46-0.93) and during 1 month-1 year (HR 0.78, 95% CI 0.62-0.97), and hemorrhagic stroke was associated with lower risk during 1 month-1 year (HR 0.60, 95% CI 0.41-0.87). There was no significant difference between subtypes in readmission risk during later periods.

DISCUSSION

Over 26 years of follow-up, 81% of stroke participants experienced a readmission. Cardiovascular and cerebrovascular diagnoses at readmission were most common across stroke subtypes. Though cardioembolic stroke has previously been reported to confer higher risk of readmission, in this study, the readmission risk was not statistically significantly different between stroke subtypes or over different periods when accounting for the competing risk of death.

Prediction of Early and Long-Term Hospital Readmission in Patients with Severe Obesity: A Retrospective Cohort Study

Adults with obesity have a higher risk of hospitalization and high hospitalization-related healthcare costs. However, a predictive model for the risk of readmission in patients with severe obesity is lacking. We conducted a retrospective cohort study enrolling all patients admitted for severe obesity (BMI ≥ 40 kg/m2) between 2009 and 2018 to the Istituto Auxologico Italiano in Piancavallo. For each patient, all subsequent hospitalizations were identified from the regional database by a deterministic record-linkage procedure. A total of 1136 patients were enrolled and followed up for a median of 5.7 years (IQR: 3.1-8.2). The predictive factors associated with hospital readmission were age (HR = 1.02, 95%CI: 1.01-1.03, p < 0.001), BMI (HR = 1.02, 95%CI: 1.01-1.03, p = 0.001), smoking habit (HR = 1.17, 95%CI: 0.99-1.38, p = 0.060), serum creatinine (HR = 1.22, 95%CI: 1.04-1.44, p = 0.016), diabetes (HR = 1.17, 95%CI: 1.00-1.36, p = 0.045), and number of admissions in the previous two years (HR = 1.15, 95%CI: 1.07-1.23, p < 0.001). BMI lost its predictive role when restricting the analysis to readmissions within 90 days. BMI and diabetes lost their predictive roles when further restricting the analysis to readmissions within 30 days. In conclusion, in this study, we identified predictive variables associated with early and long-term hospital readmission in patients with severe obesity. Whether addressing modifiable risk factors could improve the outcome remains to be established.

Common procedures and conditions leading to inpatient hospital admissions in adults with and without diabetes from 2015 to 2019 in Germany : A comparison of frequency, length of hospital stay and complications

OBJECTIVE

To evaluate common surgical procedures and admission causes in inpatient cases with diabetes in Germany between 2015 and 2019 and compare them to inpatient cases without diabetes.

METHODS

Based on the German diagnosis-related groups (G-DRG) statistics, regression models stratified by age groups and gender were used to calculate hospital admissions/100,000 individuals, hospital days as well as the proportion of complications and mortality in inpatient cases ≥ 40 years with or without a documented diagnosis of diabetes (type 1 or type 2).

RESULTS

A total of 14,222,326 (21%) of all inpatient cases aged ≥ 40 years had a diagnosis of diabetes. More middle-aged females with vs. without diabetes/100,000 individuals [95% CI] were observed, most pronounced in cases aged 40-< 50 years with myocardial infarction (305 [293-319] vs. 36 [36-37], p < 0.001). Higher proportions of complications and longer hospital stays were found for all procedures and morbidities in cases with diabetes.

CONCLUSION

Earlier hospitalizations, longer hospital stays and more complications in inpatient cases with diabetes together with the predicted future increase in diabetes prevalence depict huge challenges for the German healthcare system. There is an urgent need for developing strategies to adequately care for patients with diabetes in hospital.

Cumulative rehospitalizations and implications for subsequent mortality after first-ever ischemic stroke

INTRODUCTION

Clinical implications of readmission following initial hospitalization for acute ischemic stroke (AIS) are not known. We examined predictors of readmissions and impact of readmissions on subsequent mortality after first-ever AIS.

MATERIALS AND METHODS

Adults aged ≥18 years who survived to discharge after hospitalization for first-ever AIS from 2003 to 2019 were included in the study. For each patient, the overall burden of hospitalizations was measured as total number of hospitalizations and aggregate days spent hospitalized during follow-up. We used Poisson regression to estimate incident rate ratios (IRR) for predictors of re-hospitalization and time-dependent Cox regression to estimate hazard ratios (HR) for mortality.

RESULTS

Of 908 AIS survivors, 537 died, 669 had 2,645 readmissions over 4,535 person-years follow-up. Adjusted independent predictors of cumulative readmission inlcuded being white (IRR 1.21, 95% CI 1.03-1.42), dependency on discharge (IRR 1.27, 95% CI 1.17-1.38), cardio-embolism (IRR 1.35, 95% CI 1.18-1.45), smoking (IRR 1.21, 95% CI 1.08-1.35), anemia (IRR 1.40, 95% CI 1.24-1.57), arthritis (IRR 1.20, 95% CI 1.10-1.31), coronary artery disease (IRR 1.34, 95% CI 1.23-1.47), cancer (IRR 1.96, 95% CI 1.64-2.30), chronic kidney disease (IRR 1.36, 95% CI 1.21-1.57), COPD (IRR 1.18, 95% CI 1.04-1.34), depression (IRR 1.50, 95% CI 1.37-1.66), diabetes mellitus (IRR 1.48, 95% CI 1.36-1.48), and heart failure (IRR 1.17, 95% CI 1.03-1.34). Conversely, hyperlipidemia was associated with a lower risk of readmission (IRR 0.79, 95% CI 0.71-0.88). Mortality was significantly increased with each hospitalization and cumulative days spent in hospital.

CONCLUSIONS

Among survivors of AIS hospitalization, certain sociodemographic indicators, stroke-specific features, and several key comorbid conditions were associated with increased risk of readmissions, which in turn correlated with increased mortality. Therefore, lifestyle modification and optimal treatment of comorbidities are likely to improve the outcome after AIS.

Factors Associated with Receiving a Discharge Care Plan After Stroke in Australia: A Linked Registry Study

Background

Discharge planning is recommended to optimise the transition from acute care to home for patients admitted with stroke. Despite this guideline recommendation, many patients do not receive a discharge care plan. Also, there is limited evidence on factors influencing the provision of discharge care plan post-stroke. We evaluated patient, clinical and system factors associated with receiving a care plan on discharge from hospital back to the community after stroke.

Methods

This was an observational cohort study of patients with acute stroke who were discharged to the community between 2009-2013, using data from the Australian Stroke Clinical Registry linked to hospital administrative data. For this analysis, we used merged dataset containing information on patient demographics, clinical characteristics, and receipt of acute care processes. Multivariable logistic regression models were used to determine factors associated with receiving a discharge care plan.

Results

Among 7812 eligible patients (39 hospitals, median age 73 years, 44.7% female, 56.9% ischaemic stroke), 47% received a care plan at discharge. The odds of receiving a discharge care plan increased over time (odds ratio [OR] 1.39 per year, 95% CI 1.37-1.48), and varied between hospitals. Factors associated with receiving a discharge care plan included greater socioeconomic position (OR 1.18, 95% CI 1.02-1.38), diagnosis of ischaemic stroke (OR 1.18, 95% CI 1.05-1.33), greater stroke severity (OR 1.15, 95% CI 1.01-1.31), or being discharged on antihypertensive medication (OR 3.07, 95% CI 2.69-3.50). In contrast, factors associated with a reduced odds of receiving a discharge care plan included being aged 85+ years (vs < 85 years; OR 0.79, 95% CI 0.64-0.96), discharged on a weekend (OR 0.56, 95% CI 0.46-0.67), discharged to residential aged care (OR 0.48, 95% CI 0.39-0.60), or being treated in a large hospital ( > 300 beds; OR 0.30, 95% CI 0.10-0.92).

Conclusions

Implementing practices to target people who are older, discharged to residential aged care, or discharged on a weekend may improve discharge planning and post-discharge care after stroke.

Combined Functional Assessment for Predicting Clinical Outcomes in Stroke Patients After Post-acute Care: A Retrospective Multi-Center Cohort in Central Taiwan

Background and Objective

In 2014, Taiwan’s National Health Insurance administration launched a post-acute care (PAC) program for patients to improve their functions after acute stroke. The present study was aimed to determine PAC assessment parameters, either alone or in combination, for predicting clinical outcomes.

Methods

We retrospectively enrolled stroke adult patients through one PAC network in central Taiwan between January 2014 and December 2020. We collected data on post-stroke patients’ functional ability at baseline and after PAC stay. The comprehensive assessment included the following: Modified Rankin Scale (MRS), Functional Oral Intake Scale (FOIS), Mini-Nutritional Assessment (MNA), Berg Balance Scale (BBS), Fugl-Meyer Assessment (FMA), Mini-Mental State Examination (MMSE), aphasia test, and quality of life. The above items were assessed first at baseline and again at discharge from PAC. Logistic regression was used to determine factors that were associated with PAC length of stay (LOS), 14-day hospital readmission, and 1-year mortality.

Results

A total of 267 adults (mean age 67.2 ± 14.7 years) with completed data were analyzed. MRS, activities of daily living (ADLs), instrumental activities of daily living (IADLs), BBS, and MMSE all had improved between disease onset and PAC discharge. Higher baseline and greater improvement of physical and cognitive functions between initial and final PAC assessments were significantly associated with less readmission, and lower mortality. Furthermore, the improved ADLs, FOIS, MNA, FMA-motor, and MMSE scores were related to LOS during PAC. Using logistic regression, we found that functional improvements ≥5 items [adjusted odds ratio (aOR) = 0.16; 95% confidence interval (CI) = 0.05–0.45] and improved MMSE (aOR = 0.19; 95% CI = 0.05–0.68) were significantly associated with reduced post-PAC mortality or readmission. Whereas, functional improvements ≥7 items, improved FOIS, and MNA significantly prolonged LOS during PAC.

Conclusion

Physical performance parameters of patients with acute stroke improved after PAC. PAC assessment with multiple parameters better predicted clinical outcomes. These parameters could provide information on rehabilitation therapy for acute stroke patients receiving PAC.

Spatial distribution of stroke readmission within 30 days and the influencing factors in Hunan Province

OBJECTIVES

Stroke readmission increases financial burden on the family and the consumption of medical resources, and 30-day readmission rate is an important indicator for quality evaluation on health services. The influential factors for readmission mainly include patient-related factors, hospital factors, and society-related factors, with regional differences. This study aims to explore the spatial distribution and its main relevant factors for 30-day readmission of stroke patients in Hunan Province, and to provide the useful information for the improvement of regional prevention and control of stroke readmission.

METHODS

Stroke patients in Hunan Province who were hospitalized in 2018 and readmitted within 30 days were included in the study. The vector map of the county boundary in Hunan Province was used as the basic map since county was the spatial analysis unit. SPSS 26.0 and ArcGIS 10.8 were used for statistical analysis that contains descriptive analysis of the general situation and the distribution map of readmission rate within 30 days of stroke patients. Spatial autocorrelation analysis and spatial regression analysis were further used to find the spatial clusters of the 30-day readmission rate of stroke and the local relationship between the readmission rate and main influential factors.

RESULTS

In 2018, a total of 172 800 stroke patients were hospitalized in Hunan Province, of which 6 953 patients were re-hospitalized within 30 days after discharging due to stroke. The 30-day readmission rate was 4.09% in Hunan Province. The clusters of stroke readmission rates were mainly concentrated in the northeast and western regions in Hunan Province. The geographically weighted regression revealed that proportion of patients with complications, number of hospitals per 10 000 population and number of primary medical and health care institution per 10 000 population were the main relevant factors for stroke readmission, and there were differences both in the direction and degree of the effect on readmission in different regions.

CONCLUSIONS

The 30-day readmission rate for stroke patients in Hunan province and its main influential factors had spatial heterogeneity. The key prevention and control areas were mainly concentrated in the northeast and western regions. It is recommended that the prevention and treatment of stroke complications and the construction of medical institutions need to be strengthened to improve the quality of medical services, particularly in the western region. The importance to the treatment of stroke complications should be attached in the northern region, and the primary health care should be reinforced in the northeast region. All counties should take prevention and control measures according to local conditions, so as to effectively control the readmission rate of stroke within 30 days.

Multicentre collection of uniform data on patients hospitalised for transient ischaemic attack or stroke in the Philippines: the Philippine Neurological Association One Database-Stroke (PNA1DB-Stroke) protocol

INTRODUCTION

For scientific advances to translate into improved patient outcomes, systems of care must be in place to facilitate delivery of care. There is scarce information on quality of care and clinical outcome in our stroke patients. We aim to collect uniform data from patients with first or recurrent transient ischaemic attack (TIA) or ischaemic or haemorrhagic stroke to determine in-patient caseload, patient profile, types of diagnostic and therapeutic procedures, outcomes and overall quality of care among patients hospitalised for acute stroke in the Philippines.

METHODS AND ANALYSIS

This multicentre observational study and standing database will include patients diagnosed with first or recurrent TIA, ischaemic or haemorrhagic stroke or cerebral venous thrombosis, ≥18 years old, and admitted in any of the country's 11 accredited adult neurology residency training institutions. Anonymised data on sociodemographics, medical history, stroke subtype, in-hospital management and discharge outcomes will be collected and entered in a database using a secure online data platform. Outcomes include in-hospital complications, functional, neurological and vital (alive or dead) status at discharge.We intend to capture data from all TIA and stroke cases in participating sites. Based on 2017-2019 census, approximately 10 000 cases each year may be included. Collective data spanning 3 years will be extracted, summarised and analysed every year.

ETHICS AND DISSEMINATION

Approval from ethics committees or institutional review boards (EC/IRB) was obtained from the Single Joint Research Ethics Board and all participating institutions. As this study involves no more than minimal risk to patients, waiver of informed consent was requested. Written information about the study will be provided to patients or legal representative. If site EC/IRB requires written consent, only approved consent forms will be used.To identify areas of improvement and guide public health policies, data on 'real-world' situation are needed. The Philippine Neurological Association One Database-Stroke initiative may become a model that can be implemented in other designated stroke-ready hospitals.

TRIAL REGISTRATION

NCT04972058; ClinicalTrials.gov.

Potentially preventable hospital readmissions after patients' first stroke in Taiwan

Readmission is an important indicator of the quality of care. The purpose of this study was to explore the probabilities and predictors of 30-day and 1-year potentially preventable hospital readmission (PPR) after a patient's first stroke. We used claims data from the National Health Insurance (NHI) from 2010 to 2018. Multinomial logistic regression was used to assess the predictors of 30-day and 1-year PPR. A total of 41,921 discharged stroke patients was identified. We found that hospital readmission rates were 15.48% within 30-days and 47.25% within 1-year. The PPR and non-PPR were 9.84% (4123) and 5.65% (2367) within 30-days, and 30.65% (12,849) and 16.60% (6959) within 1-year, respectively. The factors of older patients, type of stroke, shorter length of stay, higher Charlson Comorbidity Index (CCI), higher stroke severity index (SSI), regional hospital, public and private hospital, and hospital in the lower urbanized area were associated significantly with the 30-day PPR. In addition, the factors of male, hospitalization year, and monthly income were associated significantly with 1-year PPR. The ORs of long-term PPR showed a decreasing trend since implementing the national health insurance post-acute care (PAC) program in 2014 and a dramatic drop in 2018 after the government expanded the long-term care plan-LTC 2.0 in 2017. The results showed that better discharge planning, implementing post-acute care programs and long-term care plan-LTC 2.0 may benefit the care of stroke patients and help reduce long-term readmission in Taiwan.

Implementing a Neurohospitalist Program Improves Stroke Care Metrics and Patient Satisfaction Scores

Objective

Compare the differences in health outcomes and patient satisfaction between a neurohospitalist model of care and a community-based neurologists model at a single community-based teaching hospital among in-patients diagnosed with a cerebrovascular accident (CVA).

Methods

Data was collected from the Stamford Hospital’s electronic medical records system. An assessment of patient health outcomes and satisfaction scores was conducted, comparing both discrete and continuous variables between the two time periods. An omnibus P-value of 0.05 ( P < 0.05) was considered statistically significant.

Results

The sample consisted of 341 patients between the two periods, pre-period n = 168 (49.3%) post-period n = 173 (50.7%). Door to lab and door to tPA times decreased significantly between pre- and post-periods ( P = 0.003 and P = 0.002, respectively) as did the number of MRIs ( P < 0.001). In addition, statistically significant increases were found between pre-period and post-period percentages, all increasing over time: stroke education ( P < 0.001), discharged on anticoagulant medication ( P < 0.001), and discharged on anti-thrombolytic medication ( P = 0.019). Patient satisfaction scores demonstrated mean gain across both periods for five of six items. Two items “Doctor’s Concern of my Questions/Worries” and “Skill of Doctors” demonstrated statistical significance ( P = 0.020 and P = 0.029, respectively).

Conclusions

The introduction of a neurohospitalist service at a community-based teaching hospital improved patient health outcomes on time to intervention, stroke education, discharge medications as well as patient satisfaction. Therefore, it may be beneficial for hospitals to implement a neurohospitalist model of care for their patients presenting with CVA.

High Risk Features Contributing to 30-Day Readmission After Acute Ischemic Stroke: A Single Center Retrospective Case-Control Study

BACKGROUND AND PURPOSE

Risk of 30-day stroke readmission has been attributed to medical comorbidities, stroke severity, and hospitalization metrics. The leading etiologies appear to vary across institutions and remain a moving target. We hypothesized that patients with increased medical complexity have higher odds of 30-day readmission and the immediate time after discharge may be most vulnerable. We aimed to characterize patients with 30-day readmission after acute ischemic stroke (IS) and identify predictors of post-IS readmission.

METHODS

We performed a retrospective case-control study analyzing post-IS 30-day readmission between January 2016-December 2019 using data from Mount Sinai Hospital's Get With The Guidelines database. We performed chi square analyses and multivariate adjusted logistic regression model including age, sex, coronary artery disease (CAD), renal insufficiency (RI), history of prior stroke or TIA, length of stay (LOS) > 7, and NIHSS ≥ 5.

RESULTS

6.7% (n = 115) of 1,706 IS encounters had 30-day readmission. The 115 cases were compared to 1,591 controls without 30-day readmission. In our adjusted model, CAD (OR = 1.7, p = 0.01), history of prior stroke or TIA (OR = 1.6, p = 0.01), LOS >7 (OR = 1.7, p = 0.02), and NIHSS ≥ 5 (OR = 4.5, p < 0.001) predicted 30-day readmission. 65% (n = 75) of readmitted patients had readmission within 14 days post-discharge.

CONCLUSIONS

Patients with post-IS 30-day readmission were more likely to have complex medical comorbidities and history of stroke or TIA compared to controls. Patients with more severe stroke and longer LOS may benefit from individualized transition of care plans and closer follow up during the vulnerable 30-day post-stroke period.

Transition of care in stroke patients discharged home: a single-center prospective cohort study

Introduction

Approximately two-thirds of the patients admitted to the hospital with an ischemic stroke are discharged directly home. Discontinuity of care may result in avoidable patient harm, re-admissions and even death. We hypothesized that the transfer of information is most essential in this patient group since any future care for these patients relies solely on the information that is available to the care provider responsible at that time.

Aim

The objective of this study was to evaluate the continuity of transmural care in ischemic stroke patients by assessing 1) the transfer of clinical information through discharge letters to general practitioners (GPs), 2) subsequent documentation of this information and early follow-up by GPs and 3) the documentation of medication-related information in discharge letters, at GPs and community pharmacies (CPs).

Methods

This prospective cohort study was conducted from September 2019 through March 2020 in OLVG, Amsterdam, the Netherlands, in patients with a first stroke discharged directly home. Outcome measures were derived from national guidelines and regional agreements. Results were analyzed using descriptive analysis.

Results

A total of 33 patients were included. Discharge letters (n = 33) and outpatient clinic letters (n = 24) to GPs contained most of the essential items, but 16% (n = 9) of the letters were sent in time. GPs (n = 31) infrequently adhered to guidelines since 10% (n = 3) of the diagnoses were registered using the correct code and 55% (n = 17) of the patients received follow-up shortly after discharge. Medication overviews were inaccurately communicated to GPs since 62% (n = 150) of all prescriptions (n = 243) were correctly noted in the discharge letter. Further loss of information was seen as only 39% (n = 95) of all prescriptions were documented correctly in GP overviews. We found that 59% (n = 144) of the prescriptions were documented correctly in CP overviews.

Conclusion

In this study, we found that discontinuity of care occurred to a varying extent throughout transmural care in patients with a first stroke who were discharged home.

Real-world outcomes associated with the use of the EmboTrap revascularization device for ischemic stroke in the United States

BACKGROUND

Mechanical thrombectomy (MT) has become the standard of care for the treatment of acute ischemic stroke (AIS). The EmboTrap revascularization device (CERENOVUS, Johnson & Johnson Medical Devices, Irvine, California, USA) has an innovative, dual layer feature designed to facilitate thrombus retrieval.

OBJECTIVE

To investigate the real-world clinical and economic outcomes among patients with AIS undergoing MT using the EmboTrap device in the United States (US).

METHODS

Adult patients (≥18 years) who underwent MT for AIS using the EmboTrap device between July 2018 and December 2020 were identified from the Premier Healthcare Database. Patient outcomes included discharge status (including in-hospital mortality), mean length of stay (LOS), intracranial hemorrhage (ICH), mean hospital costs, and 30-day readmissions (all-cause, cardiovascular (CV)-related, and AIS-related).

RESULTS

A total of 318 patients (mean age 68.5±14.6 years) with AIS treated with the EmboTrap device as the only stent retriever used were identified. Approximately 25% of patients were discharged to home/home health organization, and the in-hospital mortality rate was 10.7%. The rate of ICH was 16.7%. Mean hospital LOS was 9.9±11.3 days, and the mean hospital costs were US$47 367±30 297. The 30-day readmission rate was 9.6% for all-causes, 5.9% for CV-related causes, and 2.6% for AIS-related causes.

CONCLUSIONS

This is the first study in the US to report real-world outcomes sourced by retrospective database analysis among patients with AIS undergoing MT using the EmboTrap device. Further research is needed to better understand performance of the EmboTrap device in real-world settings.

Admission and Readmission/Death Patterns in Hospitalized and Non-hospitalized First-Ever-in-a-Lifetime Stroke Patients During the First Year: A Population-Based Incidence Study

Background: Hospitalization and readmission rates after a first-ever-in-a-lifetime stroke (FELS) are considered measures of quality of care and, importantly, may give valuable information to better allocate health-related resources. We aimed to investigate the hospitalization pattern and the unplanned readmissions or death of hospitalized (HospS) and non-hospitalized stroke (NHospS) patients 1 year after a FELS, based on a community register.

Methods: Data about hospitalization and unplanned readmissions and case fatality 1 year after a FELS were retrieved from the population-based register undertaken in Northern Portugal (ACIN2), comprising all FELS in 2009–2011. We used the Kaplan–Meier method to estimate 1-year readmission/death-free survival and Cox proportional hazard models to identify independent factors for readmission/death.

Results: Of the 720 FELS, 35.7% were not hospitalized. Unplanned readmission/death within 1 year occurred in 33.0 and 24.9% of HospS and NHospS patients, respectively. The leading causes of readmission were infections, recurrent stroke, and cardiovascular events. Stroke-related readmissions were observed in more than half of the patients in both groups. Male sex, age, pre- and post-stroke functional status, and diabetes were independent factors of readmission/death within 1 year.

Conclusion: About one-third of stroke patients were not hospitalized, and the readmission/death rate was higher in HospS patients. Still, that readmission/death rate difference was likely due to other factors than hospitalization itself. Our research provides novel information that may help implement targeted health-related policies to reduce the burden of stroke and its complications.

Utilization of Advanced Practice Providers in Advanced Practice Provider-Led Stroke Clinic to Expand Outpatient Stroke Follow-up Care

Stroke follow-up care with neurology specialty advanced practice providers is critical to focus on stroke prevention. The need for which is underscored by results of a recent study noting that many stroke survivors of first-ever strokes were not receiving stroke standard-of-care prevention measures including consistent antiplatelet therapies and regular exercise. Study findings further note the rates of usage for stroke prevention interventions (daily anti-platelet therapy, smoking cessation, regular exercise, hypertension control) were between 50% and 70%. Clinical nurse specialists along with nurse practitioner and physician assistant advanced practice providers are uniquely suited to manage outpatient ischemic stroke care to reduce the recurrence of stroke and improve patient outcomes.

Machine Learning-Enabled 30-Day Readmission Model for Stroke Patients

Background and Purpose: Hospital readmissions impose a substantial burden on the healthcare system. Reducing readmissions after stroke could lead to improved quality of care especially since stroke is associated with a high rate of readmission. The goal of this study is to enhance our understanding of the predictors of 30-day readmission after ischemic stroke and develop models to identify high-risk individuals for targeted interventions. Methods: We used patient-level data from electronic health records (EHR), five machine learning algorithms (random forest, gradient boosting machine, extreme gradient boosting-XGBoost, support vector machine, and logistic regression-LR), data-driven feature selection strategy, and adaptive sampling to develop 15 models of 30-day readmission after ischemic stroke. We further identified important clinical variables. Results: We included 3,184 patients with ischemic stroke (mean age: 71 ± 13.90 years, men: 51.06%). Among the 61 clinical variables included in the model, the National Institutes of Health Stroke Scale score above 24, insert indwelling urinary catheter, hypercoagulable state, and percutaneous gastrostomy had the highest importance score. The Model's AUC (area under the curve) for predicting 30-day readmission was 0.74 (95%CI: 0.64-0.78) with PPV of 0.43 when the XGBoost algorithm was used with ROSE-sampling. The balance between specificity and sensitivity improved through the sampling strategy. The best sensitivity was achieved with LR when optimized with feature selection and ROSE-sampling (AUC: 0.64, sensitivity: 0.53, specificity: 0.69). Conclusions: Machine learning-based models can be designed to predict 30-day readmission after stroke using structured data from EHR. Among the algorithms analyzed, XGBoost with ROSE-sampling had the best performance in terms of AUC while LR with ROSE-sampling and feature selection had the best sensitivity. Clinical variables highly associated with 30-day readmission could be targeted for personalized interventions. Depending on healthcare systems' resources and criteria, models with optimized performance metrics can be implemented to improve outcomes.

Care of the Patient With Acute Ischemic Stroke (Posthyperacute and Prehospital Discharge): Update to 2009 Comprehensive Nursing Care Scientific Statement: A Scientific Statement From the American Heart Association

In 2009, the American Heart Association/American Stroke Association published a comprehensive scientific statement detailing the nursing care of the patient with an acute ischemic stroke through all phases of hospitalization. The purpose of this statement is to provide an update to the 2009 document by summarizing and incorporating current best practice evidence relevant to the provision of nursing and interprofessional care to patients with ischemic stroke and their families during the acute (posthyperacute phase) inpatient admission phase of recovery. Many of the nursing care elements are informed by nurse-led research to embed best practices in the provision and standard of care for patients with stroke. The writing group comprised members of the Stroke Nursing Committee of the Council on Cardiovascular and Stroke Nursing and the Stroke Council. A literature review was undertaken to examine the best practices in the care of the patient with acute ischemic stroke. The drafts were circulated and reviewed by all committee members. This statement provides a summary of best practices based on available evidence to guide nurses caring for adult patients with acute ischemic stroke in the hospital posthyperacute/intensive care unit. In many instances, however, knowledge gaps exist, demonstrating the need for continued nurse-led research on care of the patient with acute ischemic stroke.

Hospital Presentations in Long-Term Survivors of Stroke: Causes and Associated Factors in a Linked Data Study

BACKGROUND AND PURPOSE

A comprehensive understanding of the long-term impact of stroke assists in health care planning. We aimed to determine changes in rates, causes, and associated factors for hospital presentations among long-term survivors of stroke.

METHODS

Person-level data from the AuSCR (Australian Stroke Clinical Registry) during 2009 to 2013 were linked with state-based health department emergency department and hospital admission data. The study cohort included adults with first-ever stroke who survived the first 6 months after discharge from hospital. Annualized rates of hospital presentations (nonadmitted emergency department or admission)/person/year were calculated for 1 to 12 months prior, and 7 to 12 months (inclusive) after hospitalization. Multilevel, negative binomial regression was used to identify associated factors after adjustment for prestroke hospital presentations and stratification for perceived impairment status. Perceived impairments to health were defined according to the subscales and visual analog health status scores on the 5-Dimension European Quality of Life Scale.

RESULTS

There were 7183 adults with acute stroke, 7-month survivors (median age 72 years; 56% male; 81% ischemic, and 42% with impairment at 90-180 days) from 39 hospitals included in this landmark analysis. Annualized presentations/person increased from 0.88 (95% CI, 0.86-0.91) to 1.25 (95% CI, 1.22-1.29) between the prestroke and poststroke periods, with greater rate increases in those with than without perceived impairment (55% versus 26%). Higher presentation rates were most strongly associated with older age (≥85 versus 65 years, incidence rate ratio, 1.52 [95% CI, 1.27-1.82]) and greater comorbidity score (incidence rate ratio, 1.06 [95% CI, 1.02-1.10]), whereas reduced rates were associated with greater social advantage (incidence rate ratio, 0.71 [95% CI, 0.60-0.84]). Poststroke hospital presentations (7-12 months) were most frequently related to recurrent cardiovascular and cerebrovascular events and sequelae of stroke.

CONCLUSIONS

A large increase in annualized hospital presentation rates after stroke indicates the potential for improved community management and support for this vulnerable patient group.

Predictors, causes and outcome of 30-day readmission among acute ischemic stroke

BACKGROUND AND PURPOSE

Readmission within 30 days of index acute ischemic stroke (AIS) after hospitalization increases the burden on patients and healthcare expense. The purpose of our study was to investigate predictors and causes of 30-day readmission after AIS and investigate hospitalization expenses, length of stay (LOS) and in-hospital mortality of 30-day readmission.

METHODS

This is a multicenter retrospective study. AIS were captured by International Classification of Diseases, Tenth Revision (ICD-10) diagnosis codes, patients with readmitted within 30 days after discharge were identified as readmission group. Multivariable logistic regression was used to identify independent predictors of 30-day readmissions. Hospitalization expenses, LOS and in-hospital mortality were compared for index admission and readmission.

RESULTS

We identified 2371 patients with AIS, 176 patients died before discharge, 504(23.0%) patients were admitted within 30 days. Older age, prior stroke, non-neurology floor during index admission, indwelling urinary catheter and diabetes were independently associated with increased risk of 30-day readmission (P<0.05). The most common causes for 30-day readmission were infection (28.8%) and recurrent stroke and TIA (22.8%). Patients with 30-day readmission have longer LOS and higher hospitalization expenses on readmission compared with the mean of these metrics on index admission (P<0.001). The in-hospital mortality after a within 30-day readmission was higher than index admission (13.1% vs 8.0%; OR 1.88, 95% CI 2.5-5.3; P<0.001).

CONCLUSIONS

Older age, stroke severity, prior stroke, diabetes, indwelling urinary catheter and admission to non-neurology floor during index admission were associated with 30-day readmission. 30-readmission after AIS increased hospitalization expenses, LOS and in-hospital mortality.

Type 2 Diabetes: A Risk Factor for Hospital Readmissions and Mortality in Australian Patients With Cirrhosis

Although there is evidence that type 2 diabetes mellitus (T2D) impacts adversely on liver-related mortality, its influence on hospital readmissions and development of complications in patients with cirrhosis, particularly in alcohol-related cirrhosis (the most common etiological factor among Australian hospital admissions for cirrhosis) has not been well studied. This study aimed to investigate the association between T2D and liver cirrhosis in a population-based cohort of patients admitted for cirrhosis in the state of Queensland, Australia. A retrospective cohort analysis was conducted using data from the Queensland Hospital Admitted Patient Data Collection, which contains information on all hospital episodes of care for patients with liver cirrhosis, and the Death Registry during 2008-2017. We used demographic, clinical data, and socioeconomic characteristics. A total of 8,631 patients were analyzed. A higher proportion of patients with T2D had cryptogenic cirrhosis (42.4% vs. 27.3%, respectively; P < 0.001) or nonalcoholic fatty liver disease/nonalcoholic steatohepatitis (13.8% vs. 3.4%, respectively; P < 0.001) and an admission for hepatocellular carcinoma (18.0% vs. 12.2%, respectively; P < 0.001) compared to patients without T2D. Patients with liver cirrhosis with T2D compared to those without T2D had a significantly increased median length of hospital stay (6 [range, 1-11] vs. 5 [range, 1-11] days, respectively; P < 0.001), double the rate of noncirrhosis-related admissions (incidence rate ratios [IRR], 2.03; 95% confidence interval [CI], 1.98-2.07), a 1.35-fold increased rate of cirrhosis-related admissions (IRR, 1.35; 95% CI, 1.30-1.41), and significantly lower survival (P < 0.001). Conclusion: Among hospitalized patients with cirrhosis, the cohort with T2D is at higher risk and may benefit from attention to comorbidities and additional support to reduce readmissions.

Is Referral to Home Health Rehabilitation After Inpatient Rehabilitation Facility Associated With 90-Day Hospital Readmission for Adult Patients With Stroke?

OBJECTIVE

We examined the association between home health rehabilitation referral and 90-day risk-adjusted hospital readmission after discharge from inpatient rehabilitation facilities among adult patients recovering from stroke (N = 1219).

DESIGN

A secondary data analysis of the 2005-2006 Stroke Recovery in Underserved Population database. A logistic regression model, multilevel model, and the propensity score inverse probability weighting model were used to evaluate the risk of 90-day rehospitalization between patients with stroke who received a referral for home health rehabilitation and those who did not receive a home health rehabilitation referral at inpatient rehabilitation facility discharge.

RESULTS

The regression, multilevel, and propensity score inverse probability weighting models indicated that inpatient rehabilitation facility patients with stroke who received home health rehabilitation referral had substantially lower odds of 90-day rehospitalization after inpatient rehabilitation facility discharge compared with those who were not referred to home health (odds ratio = 0.325, 95% confidence interval = 0.138-0.764; odds ratio = 0.340, 95% confidence interval = 0.139-0.832; odds ratio = 0.407, 95% confidence interval = 0.183-0.906, respectively).

CONCLUSIONS

Our findings suggest the importance of continuation of care (home health) after hospitalization and intense inpatient rehabilitation for stroke. Additional research is needed to establish appropriate use criteria and explore potential underuse of home health services as well as the benefits for follow-up outpatient services for those who do not qualify for home health at inpatient rehabilitation facility discharge.

Readmissions and Mortality During the First Year After Stroke-Data From a Population-Based Incidence Study

Background: After a first-ever-in-a-lifetime stroke (FELS), hospital readmissions are common and associated with increased mortality and morbidity of stroke survivors, thus, raising the overall health burden of stroke. Population-based stroke studies on hospital readmissions are scarce despite it being an important healthcare service quality indicator. We evaluated unplanned readmissions or death during the first year after a FELS and their potential factors, based on a Portuguese community register.

Methods: Data were retrieved from a population-based prospective register undertaken in Northern Portugal (ACIN2) in 2009–2011. Retrospective information about unplanned hospital readmissions and case fatality within 1 year after FELS index hospitalization (FELS-IH) was evaluated. Readmission/death-free survival 1 year after discharge was estimated using the Kaplan–Meyer method. Independent risk factors for readmission/death were identified using Cox proportional hazard models.

Results: Unplanned readmission/death within 1 year occurred in 120 (31.6%) of the 389 hospitalized FELS survivors. In 31.2% and 33.5% of the cases, it occurred after ischemic stroke or intracerebral hemorrhage, respectively. Infections and cerebrovascular and cardiovascular diseases were the main causes of readmission. Of the readmissions, 65.3% and 52.5% were potentially avoidable or stroke related, respectively. The main cause of potentially avoidable readmissions was the continuation/recurrence of the event responsible for the initial admission or a closely related condition (71.2%). Male sex, age, previous and post-stroke functional status, and FELS-IH length of stay were independent factors of readmission/death within 1 year.

Conclusions: Almost one-third of FELS survivors were readmitted/dead 1 year after their FELS-IH. This outcome persisted after the first months after stroke hospitalization in all stroke subtypes. More than half of readmissions were considered potentially avoidable or stroke related.

Relationship between early follow-up and readmission within 30 and 90 days after ischemic stroke

OBJECTIVE

To examine whether early follow-up with primary care or neurology is associated with lower all-cause readmissions within 30 and 90 days after acute ischemic stroke admission.

METHODS

We performed a retrospective cohort study of patients who were discharged home after acute ischemic stroke, identified by ICD-9 and ICD-10 codes, using PharMetrics, a nationally representative claims database of insured Americans from 2009 to 2015. The primary predictor was outpatient primary care or neurology follow-up within 30 and 90 days of discharge, and the primary outcome was all-cause 30- and 90-day readmissions. Multivariable Cox models were used with primary care and neurology visits specified as time-dependent covariates, with adjustment for patient demographics, comorbid conditions, and stroke severity measures.

RESULTS

The cohort included 14,630 patients. Readmissions within 30 days occurred in 7.3% of patients, and readmissions within 90 days occurred in 13.7% of patients. By 30 days, 59.3% had a primary care visit, and 24.4% had a neurology visit. Primary care follow-up was associated with reduced 30-day readmissions (hazard ratio [HR] 0.84, 95% confidence interval [CI] 0.72-0.98). Primary care follow-up before 90 days did not reach significance (HR 0.92, 95% CI 0.83-1.03). Neurology follow-up was not associated with reduced readmissions within 30 or 90 days (HR 1.05, 95% CI; HR 1.00, 95% CI, respectively).

CONCLUSION

Early outpatient follow-up with primary care is associated with a reduction in 30-day hospital readmissions. Early outpatient follow-up may represent an important opportunity for intervention after acute stroke admissions.

Factors Associated With 90-Day Readmission After Stroke or Transient Ischemic Attack

Background and Purpose—

Readmissions after stroke are common and appear to be associated with comorbidities or disability-related characteristics. In this study, we aimed to determine the patient and health-system level factors associated with all-cause and unplanned hospital readmission within 90 days after acute stroke or transient ischemic attack (TIA) in Australia.

Methods—

We used person-level linkages between data from the Australian Stroke Clinical Registry (2009–2013), hospital admissions data and national death registrations from 4 Australian states. Time to first readmission (all-cause or unplanned) for discharged patients was examined within 30, 90, and 365 days, using competing risks regression to account for deaths postdischarge. Covariates included age, stroke severity (ability to walk on admission), stroke type, admissions before stroke/TIA and the Charlson Comorbidity Index (derived from International Statistical Classification of Diseases and Related Health Problems, Tenth Revision , [Australian modified] coded hospital data in the preceding 5 years).

Results—

Among the 13 594 patients discharged following stroke/TIA (45% female; 65% ischemic stroke; 11% intracerebral hemorrhage; 4% undetermined stroke; and 20% TIA), 25% had an all-cause readmission and 15% had an unplanned readmission within 90 days. In multivariable analyses, the factors independently associated with a greater risk of unplanned readmission within 90 days were being female (subhazard ratio, 1.13 [95% CI, 1.03–1.24]), greater Charlson Comorbidity Index scores (subhazard ratio, 1.11 [95% CI, 1.09–1.12]) and having an admission ≤90 days before the index event (subhazard ratio, 1.85 [95% CI, 1.59–2.15]). Compared with being discharged to rehabilitation or aged care, those who were discharged directly home were more likely to have an unplanned readmission within 90 days (subhazard ratio, 1.44 [95% CI, 1.33–1.55]). These factors were similar for readmissions within 30 and 365 days.

Conclusions—

Apart from comorbidities and patient-level characteristics, readmissions after stroke/TIA were associated with discharge destination. Greater support for transition to home after stroke/TIA may be needed to reduce unplanned readmissions.

Association of Kidney Function With 30-Day and 1-Year Poststroke Mortality and Hospital Readmission

Background and Purpose- Kidney dysfunction is common among patients hospitalized for ischemic stroke. Understanding the association of kidney disease with poststroke outcomes is important to properly adjust for case mix in outcome studies, payment models and risk-standardized hospital readmission rates. Methods- In this cohort study of fee-for-service Medicare patients admitted with ischemic stroke to 1579 Get With The Guidelines-Stroke participating hospitals between 2009 and 2014, adjusted multivariable Cox proportional hazards models were used to determine the independent associations of estimated glomerular filtration rate (eGFR) and dialysis status with 30-day and 1-year postdischarge mortality and rehospitalizations. Results- Of 204 652 patients discharged alive (median age [25th-75th percentile] 80 years [73.0-86.0], 57.6% women, 79.8% white), 48.8% had an eGFR ≥60, 26.5% an eGFR 45 to 59, 16.3% an eGFR 30 to 44, 5.1% an eGFR 15 to 29, 0.6% an eGFR <15 without dialysis, and 2.8% were receiving dialysis. Compared with eGFR ≥60, and after adjusting for relevant variables, eGFR <45 was associated with increased 30-day mortality with the risk highest among those with eGFR <15 without dialysis (hazard ratio [HR], 2.09; 95% CI, 1.66-2.63). An eGFR <60 was associated with increased 1-year poststroke mortality that was highest among patients on dialysis (HR, 2.65; 95% CI, 2.49-2.81). Dialysis was also associated with the highest 30-day and 1-year rehospitalization rates (HR, 2.10; 95% CI, 1.95-2.26 and HR, 2.55; 95% CI, 2.44-2.66, respectively) and 30-day and 1-year composite of mortality and rehospitalization (HR, 2.04; 95% CI, 1.90-2.18 and HR, 2.46; 95% CI, 2.36-2.56, respectively). Conclusions- Within the first year after index hospitalization for ischemic stroke, eGFR and dialysis status on admission are associated with poststroke mortality and hospital readmissions. Kidney function should be included in risk-stratification models for poststroke outcomes.

Race-Ethnic Disparities in 30-Day Readmission After Stroke Among Medicare Beneficiaries in the Florida Stroke Registry

OBJECTIVE

To examine racial/ethnic disparities in 30-day all-cause readmission after stroke.

METHODS

Thirty-day all-cause readmission was compared by race/ethnicity among Medicare fee-for-service beneficiaries discharged for ischemic stroke from hospitals in the Florida Stroke Registry from 2010 to 2013. We fit a Cox proportional hazards model that censored for death and adjusted for age, sex, length of stay, discharge home, and comorbidities to assess racial/ethnic differences in readmission.

RESULTS

Among 16,952 stroke patients (54% women, 75% white, 8% black, and 15% Hispanic), 30-day all-cause readmission was 15% (17.2% for blacks, 16.7% for Hispanics, 14.4% for whites, and 14.7% for others; P = .003). There was a median of 11 days between discharge and first readmission. In adjusted analyses, there was no significant difference in readmission for blacks (hazard ratio 1.15, 95% confidence interval 0.99-1.33), Hispanics (1.00, .90-1.13), and those of other race/ethnicity (.91, .71-1.16) compared with whites. Nearly 1 in 4 readmissions were attributable to acute cerebrovascular events: 16.6% ischemic stroke or transient ischemic attack, 1.5% hemorrhagic stroke, and 5.2% cerebral artery interventions. Interventions were more common among whites and those of other race than blacks and Hispanics (P = .029). Readmission due to pneumonia or urinary tract infection was 8.2%.

CONCLUSIONS

Readmissions attributable to acute cerebrovascular events were common and generally occurred within 2 weeks of hospital discharge. Racial/ethnic disparities were present in readmissions for arterial interventions. Our results underscore the importance of postdischarge transitional care and the need for better secondary prevention strategies after ischemic stroke, particularly among minority populations.

Prediction Model of Early Return to Hospital after Discharge Following Acute Ischemic Stroke

BACKGROUND

Reducing hospital readmissions for stroke remains a significant challenge to improve outcomes and decrease healthcare costs.

METHODS

We analyzed 10,034 adult patients with ischemic stroke, presented within 24 hours of onset from a hospital-based stroke registry. The risk factors for early return to hospital after discharge were analyzed using multivariate logistic regression and classification and regression tree (CART) analyses.

RESULTS

Among the study population, 277 (2.8%) had 3-day Emergency Department (ED) reattendance, 534 (5.3%) had 14-day readmission, and 932 (9.3%) had 30-day readmission. Multivariate logistic regression revealed that age, nasogastric tube feeding, indwelling urinary catheter, healthcare utilization behaviour, and stroke severity were major and common risk factors for an early return to the hospital after discharge. CART analysis identified nasogastric tube feeding and length of stay for 72-hour ED reattendance, Barthel Index (BI) score, total length of stay in the Year Preceding the index admission (YLOS), indwelling urinary catheter, and age for 14-day readmission, and nasogastric tube feeding, BI score, YLOS, and number of inpatient visits in the year preceding the index admission for 30-day readmission as important factors to classify the patients into subgroups.

CONCLUSION

Although CART analysis did not improve the prediction of an early return to the hospital after stroke compared with logistic regression models, decision rules generated by CART can easily be interpreted and applied in clinical practice.

A quality improvement curriculum for the neurology clerkship: A practice-based approach to discharge education

In the Neurology Clerkship at our institution, we introduced a medical education curriculum to increase student competency in providing discharge education to patients with neurologic disease, and to increase knowledge of QI principles. The curriculum was peer-based, in that it was developed by medical students, experienced by medical student clerks, and modified over time with their feedback, which was tracked using exit surveys. Patients counseled were predominantly male (67%) and white (55%), with stroke or TIA together representing the most common diagnoses (58%). A high proportion of students (>85%) agreed that the clerkship project was effective in teaching discharge education, the risk factors for readmission, and increased confidence in providing discharge education. We conclude that medical students are poised to learn QI principals through practice-based curricula, and through practice may improve the quality and safety of care for patients with neurologic disease. This curriculum can be implemented within other services, and with different learners.

A Pilot Randomized Controlled Trial Testing the Feasibility and Acceptability of a SystemCHANGE Intervention to Improve Medication Adherence in Older Adult Stroke Survivors

BACKGROUND

Adhering to an antithrombotic medication regimen is essential to reducing recurrent stroke in adult stroke survivors. The purpose of this study was to evaluate the feasibility and acceptability of the SystemCHANGE (SC) and attention control (AC) intervention in older adult, nonadherent ischemic stroke patients.

METHODS

A pilot randomized controlled trial was conducted to determine the feasibility and acceptability of an SC versus AC intervention in older adult, nonadherent stroke survivors in the management of antithrombotic medication. Participants were masked to group assignment. Stroke survivors 50 years or older, taking at least 1 once-a-day antithrombotic medication, were recruited from a Midwest Comprehensive Stroke Center-affiliated neurology office. They were screened electronically using the Medication Event Monitoring System for 2 months to determine baseline medication adherence. Nonadherent stroke survivors (medication adherence < 0.97) were randomized to SC or AC intervention and monitored for 3 months. SC focused on redesigning the interpersonal environmental system and daily routines. The AC group was provided education materials on stroke that consisted of stroke risk factor reduction, stroke facts, rehabilitation, and nutrition with the primary investigator. Participation and intervention experience interviews were evaluated for themes.

RESULTS

Thirty participants were recruited: median age was 64 years, 46.7% of them were male, and they took an average of 7.77 (SD, 3.191; range, 3-15) prescribed medications. The number of over-the-counter medications taken (excluding aspirin) on a regular basis averaged 1.9 (SD, 0.8; range, 1-4). Two participants were nonadherent and were randomized to the 2 arms. Both participants had positive feedback and were not inconvenienced by their participation in the study. Neither participant voiced concerns about the intervention, survey demands, time requirement, or completing the surveys on the primary investigator's laptop.

CONCLUSION

The SC and AC intervention protocols were feasible and acceptable to the participants in this study. Additional pilot testing is needed to further evaluate the intervention and its effect on medication adherence in this population.

Perioperative stroke associated in-hospital morbidity and in-hospital mortality in common non-vascular non-neurological surgery

Perioperative stroke in non-vascular, non-neurological surgery is a potential cause of high levels of in-hospital morbidity and mortality. Although, perioperative stroke following non-vascular and non-neurological surgery is a relatively infrequent event; high surgical volume results in thousands of patients experiencing neurological deficits. We aim to determine if perioperative stroke is an independent risk factor for 30-day in-hospital morbidity and mortality following common non-vascular non-neurological surgery. This is a retrospective analysis of 4,264,963 surgical procedures identified in the Nationwide Inpatient Sample (NIS) from the years 2000 through 2011. The exposure of interest was stroke within 30 days of total knee arthroscopy, total hip arthroscopy, lung segmentation and resection, appendectomy, hemicolectomy, cholecystectomy, and lysis of peritoneal adhesions. Study outcomes were in-hospital mortality and in-hospital morbidity. Our study found an in-hospital morbidity, in-hospital mortality, and perioperative stroke rate of 5.5%, 0.8%, and 0.2%, respectively. Multivariable analysis revealed perioperative stroke to be a significant independent predictor (p < 0.001) of length of stay exceeding 14 days (OR = 4.55, 95% CI: 4.21-4.91), cardiovascular complications (OR = 1.96, 95% CI: 1.75-2.19), pulmonary complications (OR = 2.07, 95% CI: 1.89-2.27). The impact of perioperative stroke on in-hospital mortality was (OR = 8.53, 95% CI: 7.87-9.25), whereas cardiovascular complications impact on in-hospital mortality was (OR = 8.36, 95% CI = 7.67-9.10, p < 0.001). This study identified perioperative stroke as an independent predictor of 30-day in-hospital morbidity and mortality following non-vascular, non-neurological surgery.

Hospital readmission risk prediction based on claims data available at admission: a pilot study in Switzerland

OBJECTIVES

Evaluating whether future studies to develop prediction models for early readmissions based on health insurance claims data available at the time of a hospitalisation are worthwhile.

DESIGN

Retrospective cohort study of hospital admissions with discharge dates between 1 January 2014 and 31 December 2016.

SETTING

All-cause acute care hospital admissions in the general population of Switzerland, enrolled in the Helsana Group, a large provider of Swiss mandatory health insurance.

PARTICIPANTS

The mean age of 138 222 hospitalised adults included in the study was 60.5 years. Patients were included only with their first index hospitalisation. Patients who deceased during the follow-up period were excluded, as well as patients admitted from and/or discharged to nursing homes or rehabilitation clinics.

MEASURES

The primary outcome was 30-day readmission rate. Area under the receiver operating characteristic curve (AUC) was used to measure the discrimination of the developed logistic regression prediction model. Candidate variables were theory based and derived from a systematic literature search.

RESULTS

We observed a 30-day readmission rate of 7.5%. Fifty-five candidate variables were identified. The final model included pharmacy-based cost group (PCG) cancer, PCG cardiac disease, PCG pain, emergency index admission, number of emergency visits, costs specialists, costs hospital outpatient, costs laboratory, costs therapeutic devices, costs physiotherapy, number of outpatient visits, sex, age group and geographical region as predictors. The prediction model achieved an AUC of 0.60 (95% CI 0.60 to 0.61).

CONCLUSIONS

Based on the results of our study, it is not promising to invest resources in large-scale studies for the development of prediction tools for hospital readmissions based on health insurance claims data available at admission. The data proved appropriate to investigate the occurrence of hospitalisations and subsequent readmissions, but we did not find evidence for the potential of a clinically helpful prediction tool based on patient-sided variables alone.

The Advanced Practice Nurse Will See You Now: Impact of a Transitional Care Clinic on Hospital Readmissions in Stroke Survivors

BACKGROUND

There is a paucity of evidence-based, posthospital stroke care in the United States proven to reduce preventable hospital readmissions.

LOCAL PROBLEM

Follow-up with a provider after hospitalization for stroke or transient ischemic attack had low compliance rates. This may contribute to preventable readmissions.

METHODS

A retrospective, descriptive chart review to determine whether an advanced practice registered nurse (APRN)-led transitional care clinic for stroke survivors impacted 30- and 90-day hospital readmissions. Readmissions between clinic patients and nonclinic patients were compared.

INTERVENTIONS

The site implemented an APRN-led transitional care stroke clinic to improve patient transitions from hospital to home.

RESULTS

The 30-day readmission proportion was significantly higher in nonclinic patients (n = 335) than in clinic patients (n = 68) (13.4% vs 1.5%, respectively; P = .003). The 90-day readmission proportion was numerically higher in nonclinic patients (12.8% vs 4.4%, respectively; P = .058).

CONCLUSIONS

The results suggest the APRN-led clinic may impact 30-day hospital readmissions in stroke/transient ischemic attack survivors.

The Burden of Cerebrovascular Disease in the United States

INTRODUCTION

Little is known about trends in the overall combined burden of fatal and nonfatal cerebrovascular disease events in the United States. Our objective was to describe the combined burden by age, sex, and region from 2006 through 2014.

METHODS

We used data on adults aged 35 and older from 2006 through 2014 Nationwide Emergency Department Sample, National Inpatient Sample of the Healthcare Cost and Utilization Project, and the National Vital Statistics System. We calculated age-standardized cerebrovascular disease event rates by using the 2010 US Census population. Trends in rates were assessed by calculating the relative percentage change (RPC) between 2006 and 2014, and by using Joinpoint to obtain P values for overall trends.

RESULTS

The age-standardized rate increased significantly for total cerebrovascular disease events (primary plus comorbid events) from 1,050 per 100,000 in 2006 to 1,147 per 100,000 in 2014 (P < .05 for trend). Treat-and-release emergency department visits with comorbid cerebrovascular disease events increased significantly, from 114 per 100,000 in 2006 to 213 per 100,000 in 2014 (RPC of 87%, P < .05 for trend). Significant rate increases were identified among adults aged 35 to 64 with an RPC of 19% in primary cerebrovascular disease events, 48% in comorbid cerebrovascular disease events, and 36% in total events.

CONCLUSION

Our findings have important implications for the increasing cerebrovascular disease burden among adults aged 35 to 64. Focused prevention strategies should be implemented, especially among young adults who may be unaware of existing modifiable risk factors.

Geospatial, Clinical, and Social Determinants of Hospital Readmissions

Unnecessary hospital readmissions increase patient burden, decrease health care quality and efficiency, and raise overall costs. This retrospective cohort study sought to identify high-risk patients who may serve as targets for interventions aiming at reducing hospital readmissions. The authors compared geospatial, social demographic, and clinical characteristics of patients with or without a 90-day readmission. Electronic health records of 42 330 adult patients admitted to 2 Midwestern hospitals during 2013 to 2016 were used, and logistic regression was performed to determine risk factors for readmission. The 90-day readmission percentage was 14.9%. Two main groups of patients with significantly higher odds of a 90-day readmission included those with severe conditions, particularly those with a short length of stay at incident admission, and patients with Medicare but younger than age 65. These findings expand knowledge of potential risk factors related to readmissions. Future interventions to reduce hospital readmissions may focus on the aforementioned high-risk patient groups.

Recrudescence of Old Stroke Deficits Among Transient Neurological Attacks

Background

Recrudescence of old stroke deficits (ROSD) is a reported cause of transient neurological symptoms, but it is not well characterized.

Objective

We sought to determine the prevalence, potential triggers, and clinical outcome of ROSD in a cohort of patients presenting with acute transient neurological attack (TNA) and absent acute pathology on brain imaging.

Methods

We retrospectively analyzed 340 consecutive patients who presented with TNA and no acute pathology on brain imaging that were included in an institutional stroke registry between February 2013 and April 2015. The presumed TNA cause was categorized as transient ischemic attack (TIA), ROSD, and other cause. Baseline characteristics, triggers, cardiovascular complications within 90 days, and death were recorded.

Results

The prevalence of ROSD in the studied cohort was 10% (34/340). Infectious stressors and acute metabolite derangements were more common in ROSD compared to TIA (P < .05, each). Compared to TIA and the other TNA, ROSD was more likely to have more than 1 acute stressor (P < .001). Patients with ROSD had similar vascular risk factors compared to TIA (P > .05), including hypertension, diabetes mellitus, peripheral vascular disease, hyperlipidemia, and similarly used HMG-CoA reductase inhibitor, antihypertensive, and antiplatelet medications. Among the patients with an available 90-day follow-up (n = 233), cardiovascular events were more frequent in the TIA group as compared to other TNA (P < .05).

Conclusion

ROSD is common and distinct from TIA and is associated with a triggering physiologic reaction leading to transient reemergence of prior neurologic deficits. Further study of the mechanism of this phenomenon is needed to help better identify these patients.

How Leading Hospitals Operationalize Evidence-Based Readmission Reduction Strategies: A Mixed-Methods Comparative Study Using Systematic Review and Survey Design

Although various interventions targeted at reducing hospital readmissions have been identified in the literature, little is known about actual operationalization of such evidence-based interventions. This study conducted a systematic review and a survey of key informants in 2 leading hospitals, Houston Methodist (HM) and MD Anderson Cancer Center (MDACC), to compare and contrast the most cited evidence-based interventions in the current literature with interventions reported by those hospitals. The authors found that both hospitals followed evidence-based practices reported as successful in the literature. Both hospitals have implemented interventions for inpatient settings, and the timing of interventions was very similar. Major implementation differences observed for post-discharge interventions focused on collaboration. It also was found that HM was more likely than MDACC to use medication reconciliation in outpatient ( P = .018) and discharge planning for community/home patients ( P = .032). Results will provide hospital professionals with insights for implementing the most effective interventions to reduce readmissions.

The Impact of Ischaemic Stroke Subtype on 30-day Hospital Readmissions

Background

Stroke aetiology may affect the risk and causes of readmission after ischaemic stroke (IS) and transient ischaemic attack (TIA) due to differences in risk factors, functional outcome, and treatment. We aimed to examine frequencies, causes, and risk of 30-day readmission by stroke subtype, determine predictors of 30-day readmission, and study the impact of 30-day readmissions on one-year mortality.

Methods

All surviving patients admitted with IS or TIA from July 2007 to December 2013 were followed by review of medical records for all unplanned readmissions within 30 days after discharge. Stroke subtype was classified as large-artery atherosclerosis (LAA), cardioembolism (CE), small vessel occlusion (SVO), stroke of other determined aetiology (SOE), or stroke of undetermined aetiology (SUE). Cox regression analyses were performed to assess the risk of 30-day readmission for the stroke subtypes and identify predictors of 30-day readmission, and its impact on one-year mortality.

Results

Of 1874 patients, 200 (10.7%) were readmitted within 30 days [LAA 42/244 (17.2%), CE 75/605 (12.4%), SVO 12/205 (5.9%), SOE 6/32 (18.8%), SUE 65/788 (8.3%)]. The most frequent causes of readmissions were stroke-related event, infection, recurrent stroke/ TIA, and cardiac disease. After adjusting for age, sex, functional outcome, length of stay, and the risk factor burden, patients with LAA and SOE subtype had significantly higher risks of readmission for any cause, recurrent stroke or TIA, and stroke-related events. Predictors of 30-day readmission were higher age, peripheral arterial disease, enteral feeding, and LAA subtype. Thirty-day readmission was an independent predictor of one-year mortality.

Conclusions

Patients with LAA or SOE have a high risk of 30-day readmission, possibly caused by an increased risk of recurrent stroke and stroke-related events. Awareness of the risk of readmission for different causes and appropriate handling according to stroke subtype may be useful for preventing some readmissions after stroke.

Comparisons of readmissions and mortality based on post-discharge ambulatory follow-up services received by stroke patients discharged home: a register-based study

BACKGROUND

Few studies have focused on post-discharge ambulatory care for stroke patients and subsequent differences in readmission and mortality rates. Identifying groups at higher risk according to services received is important when planning post-discharge follow-up in ambulatory care. According to a recent Whitepaper by the Norwegian Government, patients receiving ambulatory care should have follow-up with a general practitioner (GP) within 14 days of hospital discharge.

METHODS

All home discharged stroke cases occurring in Oslo from 2009 to 2014 were included. 90- and 365-day all-cause readmissions and mortality were compared separately for patients categorized based on services received (no services, home nursing, ambulatory rehabilitation and home nursing with ambulatory rehabilitation) and early GP follow-up within 14 days following discharge. Variables used to adjust for differences in health status and demographics at admission included inpatient days and comorbidities the year prior to admission, calendar year, sex, age, income, education and functional score. Cox regression reporting hazard ratios (HR) was used.

RESULTS

There were no significant differences in readmission rates for early GP follow-up. Patients receiving home nursing and/or rehabilitation had higher unadjusted 90- and 365-day readmission rates than those without services (HR from 1.87 to 2.63 depending on analysis, p < 0.001), but the 90-day differences disappeared after risk adjustment, except for patients receiving only rehabilitation. There were no significant differences in mortality rates according to GP follow-up after risk adjustment. Patients receiving rehabilitation had higher mortality than those without services, even after adjustment (HR from 2.20 to 2.69, p < 0.001), whereas the mortality of patients receiving only home nursing did not differ from those without services.

CONCLUSIONS

Our results indicate that the observed differences in unadjusted readmission and mortality rates according to GP follow-up and home nursing were largely due to differences in health status at admission, likely unrelated to the stroke. On the other hand, mortality for patients receiving ambulatory rehabilitation was twice as high compared to those without, even after adjustment and irrespective of also receiving home nursing. Hence, assessing the needs of these patients during discharge planning and providing careful follow-up after discharge seems important.

Healthcare utilization and cost trajectories post-stroke: role of caregiver and stroke factors

BACKGROUND

It is essential to study post-stroke healthcare utilization trajectories from a stroke patient caregiver dyadic perspective to improve healthcare delivery, practices and eventually improve long-term outcomes for stroke patients. However, literature addressing this area is currently limited. Addressing this gap, our study described the trajectory of healthcare service utilization by stroke patients and associated costs over 1-year post-stroke and examined the association with caregiver identity and clinical stroke factors.

METHODS

Patient and caregiver variables were obtained from a prospective cohort, while healthcare data was obtained from the national claims database. Generalized estimating equation approach was used to get the population average estimates of healthcare utilization and cost trend across 4 quarters post-stroke.

RESULTS

Five hundred ninety-two stroke patient and caregiver dyads were available for current analysis. The highest utilization occurred in the first quarter post-stroke across all service types and decreased with time. The incidence rate ratio (IRR) of hospitalization decreased by 51, 40, 11 and 1% for patients having spouse, sibling, child and others as caregivers respectively when compared with not having a caregiver (p = 0.017). Disability level modified the specialist outpatient clinic usage trajectory with increasing difference between mildly and severely disabled sub-groups across quarters. Stroke type and severity modified the primary care cost trajectory with expected cost estimates differing across second to fourth quarters for moderately-severe ischemic (IRR: 1.67, 1.74, 1.64; p = 0.003), moderately-severe non-ischemic (IRR: 1.61, 3.15, 2.44; p = 0.001) and severe non-ischemic (IRR: 2.18, 4.92, 4.77; p = 0.032) subgroups respectively, compared to first quarter.

CONCLUSION

Highlighting the quarterly variations, we reported distinct utilization trajectories across subgroups based on clinical characteristics. Caregiver availability reducing hospitalization supports revisiting caregiver's role as potential hidden workforce, incentivizing their efforts by designing socially inclusive bundled payment models for post-acute stroke care and adopting family-centered clinical care practices.

Association between medication-related adverse events and non-elective readmission in acute ischemic stroke

Background

There is limited data on the effects of medication-related adverse events occurring during inpatient stays for stroke. The objectives of our study were to characterize reasons for acute readmission after acute ischemic stroke (AIS) and determine if medication-related adverse events occuring during AIS hospitalization were associated with 30-day readmission. Secondary objectives examined whether demographic, clinical, and hospital characterisitcs were associated with post-AIS readmission.

Methods

We used the Nationwide Readmission Database to identify index AIS hospitalizations in the United States between January and November 2014. Inpatient records were screened for diagnostic and external causes of injury codes indicative of medication-related adverse events, including adverse effects of prescribed drugs, unintentional overdosing, and medication errors. Nationally representative estimates of AIS hospitalizations, medication-related adverse events, and acute non-elective readmissions were computed using survey weighting methods. Adjusted odds of readmission for medication-related adverse events and select characteristics were estimated using unconditional logistic regression.

Results

We identified 439,682 individuals who were hospitalized with AIS, 4.7% of whom experienced a medication-related adverse event. Overall, 10.7% of hospitalized individuals with AIS were readmitted within 30 days of discharge. Reasons for readmission were consistent with those observed among older adults. Inpatients who experienced medication-related adverse events had significantly greater odds of being readmitted within 30 days (adjusted odds ratio (AOR): 1.22; 95% CI: 1.14–1.30). Medication-related adverse events were associated with readmission for non-AIS conditions (AOR, 1.26; 95% CI: 1.17–1.35), but not with readmission for AIS (AOR, 0.91; 95% CI: 0.75–1.10). Several factors, including but not limited to being younger than 40 years (AOR, 1.12; 95% CI: 1.00–1.26), Medicare insurance coverage (AOR, 1.33; 95% CI: 1.26–1.40), length of stay greater than 1 week (AOR, 1.38; 95% CI: 1.33–1.42), having 7 or more comorbidites (AOR, 2.20; 95% CI: 2.08–2.34), and receiving care at a for-profit hospital (AOR, 1.20; 95% CI: 1.12–1.29), were identified as being associated with all-cause 30-day readmission.

Conclusions

In this nationally representative sample of AIS hospitalizations, medication-related adverse events were positively associated with 30-day readmission for non-AIS causes. Future studies are necessary to determine whether medication-related adverse events and readmissions in AIS are avoidable.

Trajectory Modelling to Assess Trends in Long-Term Readmission Rate among Abdominal Aortic Aneurysm Patients

Introduction

The aim of the study was to use trajectory analysis to categorise high-impact users based on their long-term readmission rate and identify their predictors following AAA (abdominal aortic aneurysm) repair. Methods. In this retrospective cohort study, group-based trajectory modelling (GBTM) was performed on the patient cohort (2006-2009) identified through national administrative data from all NHS English hospitals. Proc Traj software was used in SAS program to conduct GBTM, which classified patient population into groups based on their annual readmission rates during a 5-year period following primary AAA repair. Based on the trends of readmission rates, patients were classified into low- and high-impact users. The high-impact group had a higher annual readmission rate throughout 5-year follow-up. Short-term high-impact users had initial high readmission rate followed by rapid decline, whereas chronic high-impact users continued to have high readmission rate.

Results

Based on the trends in readmission rates, GBTM classified elective AAA repair (n=16,973) patients into 2 groups: low impact (82.0%) and high impact (18.0%). High-impact users were significantly associated with female sex (P=0.001) undergoing other vascular procedures (P=0.003), poor socioeconomic status index (P < 0.001), older age (P < 0.001), and higher comorbidity score (P < 0.001). The AUC for c-statistics was 0.84. Patients with ruptured AAA repair (n=4144) had 3 groups: low impact (82.7%), short-term high impact (7.2%), and chronic high impact (10.1%). Chronic high impact users were significantly associated with renal failure (P < 0.001), heart failure (P = 0.01), peripheral vascular disease (P < 0.001), female sex (P = 0.02), open repair (P < 0.001), and undergoing other related procedures (P=0.05). The AUC for c-statistics was 0.71.

Conclusion

Patients with persistent high readmission rates exist among AAA population; however, their readmissions and mortality are not related to AAA repair. They may benefit from optimization of their medical management of comorbidities perioperatively and during their follow-up.