Systematic Review of Hospital Readmissions in Stroke Patients

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.

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.

Post-stroke pneumonia: Factors associated with readmission within 90 days of stroke discharge

OBJECTIVE

The objective was to identify risk and protective factors associated with post-stroke pneumonia readmission.

METHOD

A retrospective chart review was conducted on 365 stroke patients who were admitted to Ascension Via Christi St. Francis Hospital in Wichita, Kansas from January 1, 2015 through January 30, 2020. This case control study used matching by age at a proportion of four control patients to one post-stroke pneumonia patient. Patients with and without post-stroke pneumonia readmission within 90 days of discharge were included in this study.

RESULTS

Of the 3,952 patients diagnosed with stroke, 1.8% (n=73) patients were readmitted with post-stroke pneumonia. Compared to patients who were not readmitted for post-stroke pneumonia, patients with post-stroke pneumonia readmission were more likely to: have used a nasogastric tube during index admission, have used mechanical ventilation during index admission, or have been placed on a nothing-by-mouth diet at discharge. Being placed on nothing-by-mouth for fluids was also a predictor of post-stroke pneumonia readmission. Lack of acquired infection during the index admission was a protective factor for post-stroke pneumonia readmission.

DISCUSSION

The pathophysiology of post-stroke pneumonia is multifactorial and includes consideration of dysphagia severity, bacterial colonization of the oropharynx and feeding tube, and an altered immune system.

CONCLUSION

During the index admission, patients on nothing-by-mouth were more likely to be readmitted, and infection-free patients were less likely to be readmitted with post-stroke pneumonia. By identifying at-risk patients, clinicians may be able to use this information to tailor future medical interventions to prevent post-stroke pneumonia readmissions.

The Combination of Sensor Digital Kariasa Early Detection Prototype and Health Education for Self-Management in Preventing Recurrent Ischemic Stroke

Introduction

Recurrent stroke is one of the concerns that not only causes functional disability but also economic and psychosocial problems. Self-management is one of the indicators to predict recurrent stroke. Field observations indicate there is currently no tool to increase the survivors' self-awareness.

Objective

The study aimed to investigate if an early detection tool and health education can improve patient self-awareness toward self-management in ischemic stroke patients in order to prevent recurrent ischemic stroke.

Methods

This study consisted of two stages. In the first stage, the study used research and development methods to develop a digital sensor tool named Sensor Digital Kariasa (SenDiKa). In the second stage, the study used a quasi-experimental design with a pretest-posttest control group involving 44 postischemic stroke patients who were selected by using consecutive sampling. The subjects were divided into intervention and control groups, and the length of the intervention was 12 weeks.

Results

This study found a significant difference between the two groups (P < .001). The intervention group who used the early detection tool and received health education showed better self-management compared to the control group. The use of SenDiKa early detection prototype and health education for self-management was perceived useful and gave positive effect to the improvement of self-management in poststroke patients to prevent recurrent stroke.

Conclusion

The combination of SenDiKa early detection prototype and health education for self-management can be used for patients to identify the major risk factors of recurrent stroke, such as blood pressure, blood sugar, and cholesterol.

Association between the LACE+ index and unplanned 30-day hospital readmissions in hospitalized patients with stroke

Background

The LACE+ index is used to predict unplanned 30-day hospital readmissions, but its utility to predict 30-day readmission in hospitalized patients with stroke is unknown.

Methods

We retrospectively analyzed 1,657 consecutive patients presenting with ischemic or hemorrhagic strokes, included in an institutional stroke registry between January 2018 and August 2020. The primary outcome of interest was unplanned 30-day readmission for any reason after index hospitalization for stroke. The 30-day readmission risk was categorized by LACE+ index to high risk (≥78), medium-to-high risk (59–77), medium risk (29–58), and low risk (≤ 28). Kaplan-Meier analysis, Log rank test, and multivariable Cox regression analysis (with backward elimination) were used to determine whether the LACE+ score was an independent predictor for 30-day unplanned readmission.

Results

The overall 30-day unplanned readmission rate was 11.7% (194/1,657). The median LACE+ score was higher in the 30-day readmission group compared to subjects that had no unplanned 30-day readmission [74 (IQR 67–79) vs. 70 (IQR 62–75); p < 0.001]. On Kaplan-Meier analysis, the high-risk group had the shortest 30-day readmission free survival time as compared to medium and medium-to-high risk groups (p < 0.01, each; statistically significant). On fully adjusted multivariable Cox-regression, the highest LACE+ risk category was independently associated with the unplanned 30-day readmission risk (per point: HR 1.67 95%CI 1.23–2.26, p = 0.001).

Conclusion

Subjects in the high LACE+ index category had a significantly greater unplanned 30-day readmission risk after stroke as compared to lower LACE+ risk groups. This supports the validity of the LACE+ scoring system for predicting unplanned readmission in subjects with stroke. Future studies are warranted to determine whether LACE+ score-based risk stratification can be used to devise early interventions to mitigate the risk for unplanned readmission.

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.

Impact of NP follow-up calls on reducing 30-day readmissions in patients with stroke

ABSTRACT

Hospital readmissions are major contributors to increased healthcare costs and lower quality of life. Despite advanced stroke care, patients who have experienced a stroke require ongoing follow-up care to prevent complications and hospital readmissions. We evaluated the impact of NP follow-up calls, providing another level of expertise to promptly identify new symptoms and complications, on readmission rates in patients who have experienced stroke.

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.

Perioperative Stroke and Thirty-Day Hospital Readmission After Cardiac Surgeries: State Inpatient Database Study

BACKGROUND

Readmission rates are an important metric for evaluating healthcare quality. Stroke is a major complication following cardiac surgery. Our study aimed to evaluate the frequency and predictors of 30-day unplanned hospital readmission after cardiac surgeries and to evaluate the impact of perioperative stroke on readmission.

METHODS

Surgical discharge records spanning the years of 2008 through 2011 were analyzed utilizing California State Inpatient Database. International Classification of Diseases, ninth revision-Clinical Modification (ICD-9-CM) codes and Clinical Classification Software (CCS) codes were used to identify surgeries and variables of interest. Surgical records were then followed up for 30 days through linking admission records. Perioperative stroke was defined as brain infarction of ischemic or hemorrhagic etiology that occurred during or within 30 days after surgery.

RESULTS

Baseline characteristics associated with increased readmission rates were female gender, age above 65, non-white race, lower income, and increased number of comorbidities. Among 199,617 hospitalizations for cardiac surgeries, 1,817 (0.91%) patients developed perioperative stroke. The rate of readmission in perioperative stroke patients was 21.89%. They had a longer length of hospital stay and their discharge was vastly non-routine (84%). Our univariate analysis yielded significant association between stroke and readmission rates (odds ratio: 1.82, 95% confidence interval: 1.63 - 2.04). This association failed to remain significant upon controlling for other variables in our multivariate analysis.

CONCLUSION

Baseline patient characteristics and perioperative complications are significant predictors of readmission. More than one in five patients who develop a stroke after cardiac surgery are readmitted to the hospital within 30 days of discharge.

Use of health and aged care services in Australia following hospital admission for myocardial infarction, stroke or heart failure

BACKGROUND

Cardiovascular diseases (CVD), including myocardial infarction (MI), stroke and heart failure (HF) are the leading cause of death amongst the older population worldwide. The aim of this study is to investigate trajectories of use of health and aged care services after hospital admission for MI, stroke or HF among community-dwelling people not previously receiving aged care services.

METHODS

The study population comprised people aged 65+ years from the 45 and Up Study with linked records for hospital stays, aged care services and deaths for the period 2006-14. Among those with an index hospital admission for MI, stroke or HF, we developed Sankey plots to describe and visualize sequences and trajectories of service use (none, re-hospitalization, community care, residential care, death) in the 12 months following discharge. We used Cox proportional hazards models to estimate hazard ratios (HRs), for commencing community care and entering residential care (and the other outcomes) within 3, 6 and 12 months, compared to a matched group without MI, stroke or HF.

RESULTS

Two thousand six hundred thirty-nine, two thousand five hundred and two thousand eight hundred seventy-three people had an index hospitalization for MI, stroke and HF, respectively. Within 3 months of hospital discharge, 16, 32 and 29%, respectively, commenced community care (multivariable-adjusted HRs: 1.26 (95%CI:1.18-1.35), 1.53 (95%CI:1.44-1.64) and 1.39 (95%CI:1.32-1.48)); and 7, 18 and 14%, respectively, entered residential care (HRs: 1.25 (95%CI:1.12-1.41), 2.65 (95%CI:2.42-2.91) and 1.50 (95%CI:1.37-1.65)). Likewise, 26, 15 and 28%, respectively, were rehospitalized within 3 months following discharge (multivariable-adjusted HRs: 4.78 (95%CI:4.31-5.32), 3.26 (95%CI:2.91-3.65) and 4.94 (95%CI:4.47-5.46)).

CONCLUSIONS

Older people hospitalized for major CVD may be vulnerable to transition-related risks and have poor health trajectories, thus emphasizing the value of preventing such events and care strategies targeted towards this at-risk group.

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.

Developing a Predictive Tool for Hospital Discharge Disposition of Patients Poststroke with 30-Day Readmission Validation

After short-term, acute-care hospitalization for stroke, patients may be discharged home or other facilities for continued medical or rehabilitative management. The site of postacute care affects overall mortality and functional outcomes. Determining discharge disposition is a complex decision by the healthcare team. Early prediction of discharge destination can optimize poststroke care and improve outcomes. Previous attempts to predict discharge disposition outcome after stroke have limited clinical validations. In this study, readmission status was used as a measure of the clinical significance and effectiveness of a discharge disposition prediction. Low readmission rates indicate proper and thorough care with appropriate discharge disposition. We used Medicare beneficiary data taken from a subset of base claims in the years of 2014 and 2015 in our analyses. A predictive tool was created to determine discharge disposition based on risk scores derived from the coefficients of multivariable logistic regression related to an adjusted odds ratio. The top five risk scores were admission from a skilled nursing facility, acute heart attack, intracerebral hemorrhage, admission from "other" source, and an age of 75 or older. Validation of the predictive tool was accomplished using the readmission rates. A 75% probability for facility discharge corresponded with a risk score of greater than 9. The prediction was then compared to actual discharge disposition. Each cohort was further analyzed to determine how many readmissions occurred in each group. Of the actual home discharges, 95.7% were predicted to be there. However, only 47.8% of predictions for home discharge were actually discharged home. Predicted discharge to facility had 15.9% match to the actual facility discharge. The scenario of actual discharge home and predicted discharge to facility showed that 186 patients were readmitted. Following the algorithm in this scenario would have recommended continued medical management of these patients, potentially preventing these readmissions.

Effects of respiratory muscle training on cough function in neurological disorders: A systematic review with meta-analysis

BACKGROUND

Patients with neurological disorders can present the weakness of respiratory muscle and impaired cough function. Previous studies have shown that respiratory muscle strength training (RMT) is an effective method of improving the strength of respiratory muscle. The effects of RMT on cough function remain controversial.

OBJECTIVE

We aimed to analyze randomized controlled trials (RCTs) that investigated the effects of RMT on cough function of patients with neurological disorders.

METHODS

Pubmed, Medline, Embase, and the Cochrane Library were searched electronically for RCTs. Two reviewers independently performed data extraction and quality assessment. Data were analyzed by using RevMan 5.3 software of The Cochrane Collaboration.

RESULTS

Five studies with 185 participants were included. The mean PEDro score was 6.2 (range 5 to 7), showing moderate methodological quality. Random-effects meta-analyses showed that respiratory muscle training improved peak expiratory cough flow of voluntary cough by 2.16 (95% CI 1.16 to 3.17) and involuntary cough by 2.84 (95% CI 1.29 to 4.39), with statistical significance (P < 0.0001, P = 0.0003). The experimental group had an improvement of 0.19 cmH2O (95% CI -0.12 to 0.5) on the maximal inspiratory pressure, 0.09 cmH2O (95% CI -0.23 to 0.42) on the maximal expiratory pressure, but with no statistical significance (P = 0.23, P = 0.58) between groups.

CONCLUSION

Respiratory muscle training was considered as an effective method for improving cough function. However, this review was insufficient to conclude whether respiratory muscle training was effective in improving inspiratory and expiratory muscle strength, this was opposite with previous meta-analysis. These effects might due to the small samples and different diseases.

Pre-stroke disability and stroke severity as predictors of discharge destination from an acute stroke ward

BACKGROUND AND RATIONALE

Reliable prediction of discharge destination in acute stroke informs discharge planning and can determine the expectations of patients and carers. There is no existing model that does this using routinely collected indices of pre-morbid disability and stroke severity.

METHODS

Age, gender, pre-morbid modified Rankin Scale (mRS) and National Institutes of Health Stroke Scale (NIHSS) were gathered prospectively on an acute stroke unit from 1,142 consecutive patients. A multiclass random forest classifier was used to train and validate a model to predict discharge destination.

RESULTS

Used alone, the mRS is the strongest predictor of discharge destination. The NIHSS is only predictive when combined with our other variables. The accuracy of the final model was 70.4% overall with a positive predictive value (PPV) and sensitivity of 0.88 and 0.78 for home as the destination, 0.68 and 0.88 for continued inpatient care, 0.7 and 0.53 for community hospital, and 0.5 and 0.18 for death, respectively.

CONCLUSION

Pre-stroke disability rather than stroke severity is the strongest predictor of discharge destination, but in combination with other routinely collected data, both can be used as an adjunct by the multidisciplinary team to predict discharge destination in patients with acute stroke.

Risk of 28-day readmissions among stroke patients in Malaysia (2008-2015): Trends, causes and its associated factors

BACKGROUND AND OBJECTIVES

Risk of readmissions is an important quality indicator for stroke care. Such information is limited among low- and middle-income countries. We assessed the trends for 28-day readmissions after a stroke in Malaysia from 2008 to 2015 and evaluated the causes and factors associated with readmissions in 2015.

METHODS

Using the national hospital admission records database, we included all stroke patients who were discharged alive between 2008 and 2015 for this secondary data analysis. The risk of readmissions was described in proportion and trends. Reasons were coded according to the International Classification of Diseases, 10th Edition. Multivariable logistic regression was performed to identify factors associated with readmissions.

RESULTS

Among 151729 patients, 11 to 13% were readmitted within 28 days post-discharge from their stroke events each year. The trend was constant for ischemic stroke but decreasing for hemorrhagic stroke. The leading causes for readmissions were recurrent stroke (32.1%), pneumonia (13.0%) and sepsis (4.8%). The risk of 28-day readmission was higher among those with stroke of hemorrhagic (adjusted odds ratio (AOR): 1.52) and subarachnoid hemorrhage (AOR: 2.56) subtypes, and length of index admission >3 days (AOR: 1.48), but lower among younger age groups of 35-64 (AORs: 0.61-0.75), p values <0.001.

CONCLUSION

The risk of 28-day readmission remained constant from 2008 to 2015, where one in eight stroke patients required readmission, mainly attributable to preventable causes. Age, ethnicity, stroke subtypes and duration of the index admission influenced the risk of readmission. Efforts should focus on minimizing potentially preventable admissions, especially among those at higher risk.

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.

Comparison of Rates and Outcomes of Readmission to Index vs Non-index Hospitals After Intravenous Thrombolysis in Acute Stroke Patients

National and regional systems of stroke care are designed to provide patients with widespread access to hospitals with thrombolytic capabilities. However, such triaging systems may contribute to fragmentation of care. This study aims to compare rates of readmission and outcomes between index and non-index hospitals for stroke patients following intravenous thrombolytic therapy (IVT). This study utilized a nationally representative sample of stroke patients with IVT from the Nationwide Readmissions Database from 2010 to 2014. Descriptive and regression analyses were performed for patient and hospital level factors that influenced 90-day readmissions and regression models were used to identify differences in mortality, complications, and repeat readmissions between patients readmitted to index (facility where IVT was administered) and non-index hospitals. In the study, 49415 stroke patients were treated with IVT, of whom 21.7% were readmitted within 90 days. Among readmissions, 79.4% of patients were readmitted to index hospitals and 20.6% to non-index hospitals. On multivariate logistic regression analysis, index hospital readmission was independently associated with lower frequency of second readmissions (non-index OR 1.09, 95%CI 1.07-1.11, p<0.0001) but not with increased mortality or major complications (p=ns). Approximately one-fifth of stroke patients treated with thrombolysis were readmitted within 90 days, one-fifth of whom were readmitted to non-index hospitals. Although readmission to index hospital was associated with lower frequency of subsequent readmissions, readmission to non-index hospital was not associated with increased mortality or major complications. This difference may be due to standardized algorithms, mature systems of care, and demanding metrics required of stroke centers.

Patterns in hospital readmissions after ischaemic stroke - An observational study from the Swedish stroke register (Riksstroke)

Introduction

While acute treatment and secondary prevention in stroke have undergone major improvements, hospital readmission after index stroke remains high. However, there are few reports on long-term readmission patterns.

Patients and methods

For this prospective observational study, data on demographics, functional status and living conditions were obtained from the Swedish Stroke Register (Riksstroke). Data on comorbidity and hospital readmissions up to five years post-index stroke were obtained from the Swedish National Patient Register. Patients were grouped based on number of readmissions: low (0–1) intermediate (2–4), high (5–9) or very high (≥10).

Results

Of the 10,092 patients included, 43.7% had been readmitted within 12 months and 74.0% within 5 years. There was an average of three readmissions per individual during the five-year interval. A small group of patients with a high-comorbidity burden accounted for the majority of readmissions: approximately 20% of patients accounted for 60% of readmissions, and 5% of patients accounted for 25%. Circulatory conditions were the most common cause followed by infectious disease, stroke, trauma and diseases of the nervous system other than stroke. The proportion of readmissions due to stroke decreased sharply in the first six months.

Conclusion

A small number of patients with a high degree of comorbidity accounted for the majority of hospital readmissions after index stroke. Our results highlight the need for further development of strategies to support high-risk comorbid stroke patients in the community setting. Further research describing characteristics and healthcare utilisation patterns in this group is warranted.

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.

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.

Structural Equation Model (SEM) of Stroke Mortality in Spanish Inpatient Hospital Settings: The Role of Individual and Contextual Factors

Introduction: Traditionally, predictive models of in-hospital mortality in ischemic stroke have focused on individual patient variables, to the neglect of in-hospital contextual variables. In addition, frequently used scores are betters predictors of risk of sequelae than mortality, and, to date, the use of structural equations in elaborating such measures has only been anecdotal. Aims: The aim of this paper was to analyze the joint predictive weight of the following: (1) individual factors (age, gender, obesity, and epilepsy) on the mediating factors (arrhythmias, dyslipidemia, hypertension), and ultimately death (exitus); (2) contextual in-hospital factors (year and existence of a stroke unit) on the mediating factors (number of diagnoses, procedures and length of stay, and re-admission), as determinants of death; and (3) certain factors in predicting others. Material and Methods: Retrospective cohort study through observational analysis of all hospital stays of Diagnosis Related Group (DRG) 14, non-lysed ischemic stroke, during the time period 2008-2012. The sample consisted of a total of 186,245 hospital stays, taken from the Minimum Basic Data Set (MBDS) upon discharge from Spanish hospitals. MANOVAs were carried out to establish the linear effect of certain variables on others. These formed the basis for building the Structural Equation Model (SEM), with the corresponding parameters and restrictive indicators. Results: A consistent model of causal predictive relationships between the postulated variables was obtained. One of the most interesting effects was the predictive value of contextual variables on individual variables, especially the indirect effect of the existence of stroke units on reducing number of procedures, readmission and in-hospital mortality. Conclusion: Contextual variables, and specifically the availability of stroke units, made a positive impact on individual variables that affect prognosis and mortality in ischemic stroke. Moreover, it is feasible to determine this impact through the use of structural equation methodology. We analyze the methodological and clinical implications of this type of study for hospital policies.

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.

Risk factors associated with 31-day unplanned readmission in 50,912 discharged patients after stroke in China

BACKGROUND

Unplanned readmission within 31 days of discharge after stroke is a useful indicator for monitoring quality of hospital care. We evaluated the risk factors associated with 31-day unplanned readmission of stroke patients in China.

METHODS

We identified 50,912 patients from 375 hospitals in 29 provinces, municipalities or autonomous districts across China who experienced an unplanned readmission after stroke between 2015 and 2016, and extracted data from the inpatients' cover sheet data from the Medical Record Monitoring Database. Patients were grouped into readmission within 31 days or beyond for analysis. Chi-squared test was used to analyze demographic information, health system and clinical process-related factors according to the data type. Multilevel logistic modeling was used to examine the effects of patient (level 1) and hospital (level 2) characteristics on an unplanned readmission ≤31 days.

RESULTS

Among 50,912 patients, 14,664 (28.8%) were readmitted within 31 days after discharge. The commonest cause of readmissions were recurrent stroke (34.8%), hypertension (22.94%), cardio/cerebrovascular disease (13.26%) and diabetes/diabetic complications (7.34%). Higher risks of unplanned readmissions were associated with diabetes (OR = 1.089, P = 0.001), use of clinical pathways (OR = 1.174, P < 0.001), and being discharged without doctor's advice (OR = 1.485, P < 0.001). Lower risks were associated with basic medical insurances (OR ranging from 0.225 to 0.716, P < 0.001) and commercial medical insurance (OR = 0.636, P = 0.021), compared to self-paying for medical services. And patients aged 50 years old and above (OR ranging from 0.650 to 0.985, P < 0.05), with haemorrhagic stroke (OR = 0.467, P < 0.001), with length of stay more than 7 days in hospital (OR ranging from 0.082 to 0.566, P < 0.001), also had lower risks.

CONCLUSIONS

Age, type of stroke, medical insurance status, type of discharge, use of clinical pathways, length of hospital stay and comorbidities were the most influential factors for readmission within 31 days.

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.

Mechanical Thrombectomy by a Direct Aspiration First Pass Technique (ADAPT) in Ischemic Stroke: Results of Monocentric Study Based on Multimodal CT Patient Selection

Introduction

Mechanical thrombectomy with ADAP-technique of ischemic stroke has been reported as fast and effective. Aim of this study is to evaluate imaging criteria as possible predictors of stroke severity, therapeutic success, and outcome.

Materials and Methods

Patients (30) presenting from October 2015 to April 2017 with Emergent Large Vessel Occlusion of the anterior circulation were treated with ADAP-technique. 22 received also IV tPA; 8 underwent endovascular treatment only. Every patient was evaluated with noncontrast CT, multiphase angiography-CT, and perfusion CT. Clinical and radiological characteristics were measured. Good clinical outcome was an improvement of 8 points on NIHSS at discharge or a modified Rankin Scale ≤2 at discharge and at 90 days.

Results

Successful revascularization was obtained in 57% of patients, no procedural complications were witnessed, and only two hemorrhages were reported. Good outcome at discharge was obtained in 11 patients (37%) and predicted by NCCT ASPECT and TICI; outcome at 90 days was predicted by NCCT ASPECT, clot length, and premorbid mRS. Mortality was 23% at discharge and 30% at 90 days.

Conclusion

ADAPT is an effective endovascular method of stroke treatment with fast procedural times. Multimodal CT evaluation is effective in assessing stroke severity, providing important prognostic information, which is able to select patients for the appropriate treatment.

Causes and correlates of 30 day and 180 day readmission following discharge from a Medicine for the Elderly Rehabilitation unit

Background

Recently hospitalized patients experience a period of generalized risk of adverse health events. This study examined reasons for, and predictors of, readmission to acute care facilities within 30 and 180 days of discharge from an inpatient rehabilitation unit for older people.

Methods

Routinely collected, linked clinical data on admissions to a single inpatient rehabilitation facility over a 13-year period were analysed. Data were available regarding demographics, comorbid disease, admission and discharge Barthel scores, length of hospital stay, and number of medications on discharge. Discharge diagnoses for the index admission and readmissions were available from hospital episode statistics. Univariate and multivariate Cox regression analyses were performed to identify baseline factors that predicted 30 and 180-day readmission.

Results

A total of 3984 patients were included in the analysis. The cohort had a mean age of 84.1 years (SD 7.4), and 39.7% were male. Overall, 5.6% (n = 222) and 23.2% (n = 926) of the patients were readmitted within 30 days and 180 days of discharge respectively. For patients readmitted to hospital, 26.6% and 21.1% of patients were readmitted with the same condition as their initial admission at 30 days and 180 respectively. For patients readmitted within 30 days, 13.5% (n = 30) were readmitted with the same condition with the most common diagnoses associated with readmission being chest infection, falls/immobility and stroke. For patients readmitted within 180 days, 12.4% (n = 115) of patients were readmitted with the same condition as the index condition with the most common diagnoses associated with readmission being falls/immobility, cancer and chest infections. In multivariable Cox regression analyses, older age, male sex, length of stay and heart failure predicted 30 or 180-day readmission. In addition, discharge from hospital to patients own home predicted 30-day readmission, whereas diagnoses of cancer, previous myocardial infarction or chronic obstructive pulmonary disease predicted 180-day readmission.

Conclusion

Most readmissions of older people after discharge from inpatient rehabilitation occurred for different reasons to the original hospital admission. Patterns of predictors for early and late readmission differed, suggesting the need for different mitigation strategies.

Estimates and Temporal Trend for US Nationwide 30-Day Hospital Readmission Among Patients With Ischemic and Hemorrhagic Stroke

IMPORTANCE

Readmission reduction is linked to improved quality of care, saves cost, and is a desirable patient-centered outcome. Nationally representative readmission metrics for patients with stroke are unavailable to date. Such estimates are necessary for benchmarking performance.

OBJECTIVES

To provide US nationwide estimates and a temporal trend for overall, planned, and potentially preventable 30-day hospital readmission among patients with ischemic and hemorrhagic stroke; to investigate the association between hospitals' stroke discharge volume, teaching status, and 30-day readmission; and to highlight reasons for 30-day readmission and explore the association of 30-day readmission in terms of mortality, length of stay, and cost of care among patients with stroke.

DESIGN, SETTING, AND PARTICIPANTS

Cohort, year-wise analysis of the Nationwide Readmissions Database between January 1, 2010, and September 30, 2015. The setting was a population-based cohort study providing national estimates of 30-day readmission. The database represents 50% of all US hospitalizations from 22 geographically dispersed states. Participants were adult (≥18 years) patients with a primary discharge diagnosis of intracerebral hemorrhage, acute ischemic stroke, or subarachnoid hemorrhage. Hospitals were categorized by their annual stroke discharge volume and were classified as teaching hospitals if they had an American Medical Association-approved residency program or had a ratio of full-time equivalent interns and residents to beds of 0.25 or higher.

MAIN OUTCOMES AND MEASURES

Readmission was defined as any admission within 30 days of index hospitalization discharge. Using Centers for Medicare & Medicaid Services-defined algorithms, events were classified as planned or unplanned and as potentially preventable.

RESULTS

Based on study criteria, 2 078 854 eligible patients were included (mean [SE] age, 70.02 [0.07] years; 51.9% female). Thirty-day readmission was highest for patients with intracerebral hemorrhage (13.70%; 95% CI, 13.40%-13.99%), followed by patients with acute ischemic stroke (12.44%; 95% CI, 12.33%-12.55%) and patients with subarachnoid hemorrhage (11.48%; 95% CI, 11.01%-11.96%). On average, there was a 3.3% annual decline in readmission between 2010 and 2014, which was statistically significant for the period of investigation (odds ratio, 0.96; 95% CI, 0.95-0.97). Patients discharged from nonteaching hospitals with high stroke discharge volume were at a significantly higher risk of 30-day readmission, and the top 2 reasons for readmission were acute cerebrovascular disease and septicemia.

CONCLUSIONS AND RELEVANCE

This study suggests that nationally representative readmission metrics can be used to benchmark hospitals' performance, and a temporal trend of 3.3% may be used to evaluate the effectiveness of readmission reduction strategies.

A retrospective cohort study of high-impact users among patients with cerebrovascular conditions

OBJECTIVE

To apply group-based trajectory modelling (GBTM) to the hospital administrative data to evaluate, model and visualise trends and changes in the frequency of long-term hospital care use of the subgroups of patients with cerebrovascular conditions.

DESIGN

A retrospective cohort study of patients with cerebrovascular conditions.

SETTINGS

Secondary care of all patients with cerebrovascular conditions admitted to English National Hospital Service hospitals.

PARTICIPANTS

All patients with cerebrovascular conditions identified through national administrative data (Hospital Episode Statistics) and subsequent emergency hospital admissions followed up for 4 years.

MAIN OUTCOME MEASURE

Annual number of emergency hospital readmissions.

RESULTS

GBTM model classified patients with intracranial haemorrhage (n=2605) into five subgroups, whereas ischaemic stroke (n=34 208) and transient ischaemic attack (TIA) (n=20 549) patients were shown to have two conventional groups, low and high impact. The covariates with significant association with high-impact users (17.1%) among ischaemic stroke were epilepsy (OR 2.29), previous stroke (OR 2.18), anxiety/depression (OR 1.63), procedural complication (OR 1.43), admission to intensive therapy unit (ITU) or high dependency unit (HDU) (OR 1.42), comorbidity score (OR 1.36), urinary tract infections (OR 1.32), vision loss (OR 1.32), chest infections (OR 1.25), living alone (OR 1.25), diabetes (OR 1.23), socioeconomic index (OR 1.20), older age (OR 1.03) and prolonged length of stay (OR 1.00). The covariates associated with high-impact users among TIA (20.0%) were thromboembolic event (OR 3.67), previous stroke (OR 2.51), epilepsy (OR 2.25), hypotension (OR 1.86), anxiety/depression (OR 1.63), amnesia (OR 1.62), diabetes (OR 1.58), anaemia (OR 1.55), comorbidity score (OR 1.39), atrial fibrillation (OR 1.27), living alone (OR 1.25), socioeconomic index (OR 1.13), older age (OR 1.04) and prolonged length of stay (OR 1.02). The high-impact users (0.5%) among intracranial haemorrhage were strongly associated with thromboembolic event (OR 20.3) and inversely related to older age (OR 0.58).

CONCLUSION

GBTM effectively assessed trends in the use of hospital care by the subgroups of patients with cerebrovascular conditions. High-impact users persistently had higher annual readmission during the follow-up period.