Influence of hospital-level practices on readmission after ischemic stroke

A novel risk score predicting 30-day hospital re-admission of patients with acute stroke by machine learning model

BACKGROUND

The 30-day hospital re-admission rate is a quality measure of hospital care to monitor the efficiency of the healthcare system. The hospital re-admission of acute stroke (AS) patients is often associated with higher mortality rates, greater levels of disability and increased healthcare costs. The aim of our study was to identify predictors of unplanned 30-day hospital re-admissions after discharge of AS patients and define an early re-admission risk score (RRS).

METHODS

This observational, retrospective study was performed on AS patients who were discharged between 2014 and 2019. Early re-admission predictors were identified by machine learning models. The performances of these models were assessed by receiver operating characteristic curve analysis.

RESULTS

Of 7599 patients with AS, 3699 patients met the inclusion criteria, and 304 patients (8.22%) were re-admitted within 30 days from discharge. After identifying the predictors of early re-admission by logistic regression analysis, RRS was obtained and consisted of seven variables: hemoglobin level, atrial fibrillation, brain hemorrhage, discharge home, chronic obstructive pulmonary disease, one and more than one hospitalization in the previous year. The cohort of patients was then stratified into three risk categories: low (RRS = 0-1), medium (RRS = 2-3) and high (RRS >3) with re-admission rates of 5%, 8% and 14%, respectively.

CONCLUSIONS

The identification of risk factors for early re-admission after AS and the elaboration of a score to stratify at discharge time the risk of re-admission can provide a tool for clinicians to plan a personalized follow-up and contain healthcare costs.

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.

Causes and Predictors of 30-Day Readmission in Patients With Stroke Undergoing Mechanical Thrombectomy: A Large Single-Center Experience

BACKGROUND AND OBJECTIVES

The 30-day readmission rate has emerged as a metric of quality care and is associated with increased health care expenditure. We aim to identify the rate and causes of 30-day readmission after mechanical thrombectomy and provide the risk factors of readmission to highlight high-risk patients who may require closer care.

METHODS

This is a retrospective study from a prospectively maintained database of 703 patients presenting for mechanical thrombectomy between 2017 and 2023. All patients who presented with a stroke and underwent a mechanical thrombectomy were included in this study. Patients who were deceased on discharge were excluded from this study.

RESULTS

Our study comprised 703 patients, mostly female (n = 402, 57.2%) with a mean age of 70.2 years ±15.4. The most common causes of readmission were cerebrovascular events (stroke [n = 21, 36.2%], intracranial hemorrhage [n = 9, 15.5%], and transient ischemic attack [n = 1, 1.7%]).Other causes of readmission included cardiovascular events (cardiac arrest [n = 4, 6.9%] and bradycardia [n = 1, 1.7%]), infection (wound infection postcraniectomy [n = 3, 5.2%], and pneumonia [n = 1, 1.7%]). On multivariate analysis, independent predictors of 30-day readmission were history of smoking (odds ratio [OR]: 2.2, 95% CI: 1.1-4.2) P = .01), distal embolization (OR: 3.2, 95% CI: 1.1-8.7, P = .03), decompressive hemicraniectomy (OR: 9.3, 95% CI: 3.2-27.6, P < .01), and intracranial stent placement (OR: 4.6, 95% CI: 2.4-8.7) P < .01).

CONCLUSION

In our study, the rate of 30-day readmission was 8.3%, and the most common cause of readmission was recurrent strokes. We identified a history of smoking, distal embolization, decompressive hemicraniectomy, and intracranial stenting as independent predictors of 30-day readmission in patients with stroke undergoing mechanical thrombectomy.

Effect of Variation in Early Rehabilitation on Hospital Readmission After Hip Fracture

OBJECTIVE

Provision of early rehabilitation services during acute hospitalization after a hip fracture is vital for improving patient outcomes. The purpose of this study was to examine the association between the amount of rehabilitation services received during the acute care stay and hospital readmission in older patients after a hip fracture.

METHODS

Medicare claims data (2016-2017) for older adults admitted to acute hospitals for a hip fracture (n = 131,127) were used. Hospital-based rehabilitation (physical therapy, occupational therapy, or both) was categorized into tertiles by minutes per day as low (median = 17.5), middle (median = 30.0), and high (median = 48.8). The study outcome was risk-adjusted 7-day and 30-day all-cause hospital readmission.

RESULTS

The median hospital stay was 5 days (interquartile range [IQR] = 4-6 days). The median rehabilitation minutes per day was 30 (IQR = 21-42.5 minutes), with 17 (IQR = 12.6-20.6 minutes) in the low tertile, 30 (IQR = 12.6-20.6 minutes) in the middle tertile, and 48.8 (IQR = 42.8-60.0 minutes) in the high tertile. Compared with high therapy minutes groups, those in the low and middle tertiles had higher odds of a 30-day readmission (low tertile: odds ratio [OR] = 1.11, 95% CI = 1.06-1.17; middle tertile: OR = 1.07, 95% CI = 1.02-1.12). In addition, patients who received low rehabilitation volume had higher odds of a 7-day readmission (OR = 1.20; 95% CI = 1.10-1.30) compared with high volume.

CONCLUSION

Elderly patients with hip fractures who received less rehabilitation were at higher risk of readmission within 7 and 30 days.

IMPACT

These findings confirm the need to update clinical guidelines in the provision of early rehabilitation services to improve patient outcomes during acute hospital stays for individuals with hip fracture.

LAY SUMMARY

There is significant individual- and hospital-level variation in the amount of hospital-based rehabilitation delivered to older adults during hip fracture hospitalization. Higher intensity of hospital-based rehabilitation care was associated with a lower risk of hospital readmission within 7 and 30 days.

Effectiveness of active occupational therapy in patients with acute stroke: A propensity score-weighted retrospective study

Background and purpose

The effects of therapy and patient characteristics on rehabilitation outcomes in patients with acute stroke are unclear. We investigated the effects of intensive occupational therapy (OT) on patients with acute stroke.

Methods

We performed a retrospective cohort study using the 2005-2016 Japan Rehabilitation Database, from which we identified patients with stroke (n = 10,270) who were admitted to acute care hospitals (n = 37). We defined active OT (AOT) and non-AOT as OT intervention times (total intervention time/length of hospital stay) longer or shorter than the daily physical therapy intervention time, respectively. The outcomes assessed were the Functional Independence Measure (FIM) and National Institutes of Health Stroke Scale (NIHSS) scores, duration of hospitalization, and rate of discharge. Propensity scores and inverse probability of treatment weighting analyses adjusted for patient characteristics were performed to investigate the effects of AOT on patient outcomes.

Results

We enrolled 3,501 patients (1,938 and 1,563 patients in the AOT and non-AOT groups, respectively) in the study. After inverse probability of treatment weighting, the AOT group had a shorter length of hospitalization (95% confidence interval: -3.7, -1.3, p < 0.001), and the FIM (95% confidence interval: 2.0, 5.7, p < 0.001) and NIHSS (95% confidence interval; 0.3, 1.1, p < 0.001) scores improved significantly. Subgroup analysis showed that lower NHISS scores for aphasia, gaze, and neglect and lower overall NIHSS and FIM scores on admission led to a greater increase in FIM scores in the AOT group.

Conclusions

AOT improved the limitations in performing activities of daily living (ADL) and physical function in patients with acute stroke and reduced the length of hospitalization. Additionally, subgroup analysis suggested that the increase in FIM score was greater in patients with severe limitations in performing ADLs and worse cognitive impairment, such as neglect, on admission.

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.

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.

Occupational Therapy and the IMPACT Act: Part 1. A Systematic Review of Evidence for Fall Prevention and Reduction, Community Discharge and Reintegration, and Readmission Prevention Interventions

IMPORTANCE

Interventions that prevent falls, facilitate discharge after hospitalization, and reduce hospital readmissions assist occupational therapy practitioners in demonstrating professional value, improving quality, and reducing costs.

OBJECTIVE

In this systematic review, we address three outcome areas of the Improving Medicare Post-Acute Care Transformation (IMPACT) Act of 2014: prevention and reduction of falls, facilitation of community discharge and reintegration, and prevention of hospital readmission.

DATA SOURCES

We conducted a search of the literature published between 2009 and 2019. Study Selection and Data Collection: We developed operational definitions to help us identify articles that answered the search question for each outcome area. This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

FINDINGS

We found 53 articles that address the three outcome areas. Regarding the prevention and reduction of falls, low strength of evidence is available for interventions focusing on a single fall risk and for customized interventions addressing multiple risks. Moderate strength of evidence supports structured community fall risk prevention interventions. Low strength of evidence was found for community discharge and reintegration interventions that include physical activity and educational programming. Low to moderate strength of evidence was found for readmission prevention interventions for patients with four types of condition. Conclusion and Relevance: Several intervention themes in the three outcome areas of interest are supported by few studies or by studies with a moderate risk of bias. Additional research is needed that supports the value of occupational therapy interventions in these outcome areas. What This Article Adds: Our study provides important insights into the state of the evidence related to occupational therapy interventions to address three outcome areas of the IMPACT Act.

Occupational Therapy and the IMPACT Act: Part 1. A Systematic Review of Evidence for Fall Prevention and Reduction, Community Discharge and Reintegration, and Readmission Prevention Interventions

IMPORTANCE

Interventions that prevent falls, facilitate discharge after hospitalization, and reduce hospital readmissions assist occupational therapy practitioners in demonstrating professional value, improving quality, and reducing costs.

OBJECTIVE

In this systematic review, we address three outcome areas of the Improving Medicare Post-Acute Care Transformation (IMPACT) Act of 2014: prevention and reduction of falls, facilitation of community discharge and reintegration, and prevention of hospital readmission.

DATA SOURCES

We conducted a search of the literature published between 2009 and 2019. Study Selection and Data Collection: We developed operational definitions to help us identify articles that answered the search question for each outcome area. This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

FINDINGS

We found 53 articles that address the three outcome areas. Regarding the prevention and reduction of falls, low strength of evidence is available for interventions focusing on a single fall risk and for customized interventions addressing multiple risks. Moderate strength of evidence supports structured community fall risk prevention interventions. Low strength of evidence was found for community discharge and reintegration interventions that include physical activity and educational programming. Low to moderate strength of evidence was found for readmission prevention interventions for patients with four types of condition. Conclusion and Relevance: Several intervention themes in the three outcome areas of interest are supported by few studies or by studies with a moderate risk of bias. Additional research is needed that supports the value of occupational therapy interventions in these outcome areas. What This Article Adds: Our study provides important insights into the state of the evidence related to occupational therapy interventions to address three outcome areas of the IMPACT Act.

Higher Frequency of Acute Occupational Therapy Services Is Associated With Reduced Hospital Readmissions

IMPORTANCE

Hospital readmissions are associated with poor patient outcomes, including higher risk for mortality, nutritional concerns, deconditioning, and higher costs.

OBJECTIVE

To evaluate how acute occupational therapy service delivery factors affect readmission risk.

DESIGN

Cross-sectional, retrospective study.

SETTING

Single academic medical center.

PARTICIPANTS

Medicare inpatients with a diagnosis included in the Hospital Readmissions Reduction Program (HRRP; N = 17,618). Data were collected from medical records at a large urban hospital in southeastern Wisconsin. Outcomes and Measures: Logistic regression models were estimated to examine the association between acute occupational therapy service delivery factors and odds of readmission. In addition, the types of acute occupational therapy services for readmitted versus not-readmitted patients were compared.

RESULTS

Patients had significantly higher odds of readmission if they received occupational therapy services while hospitalized (odds ratio [OR] = 1.18, 95% confidence interval [CI] [1.07, 1.31]). However, patshients who received acute occupational therapy services had significantly lower odds of readmission if they received a higher frequency (OR = 0.99, 95% CI [0.99,1.00]) of acute occupational therapy services. A significantly higher proportion of patients who were not readmitted, compared with patients who were readmitted, received activities of daily living (ADL) or self-care training (p < .01).

CONCLUSIONS AND RELEVANCE

For patients with HRRP-qualifying diagnoses who received acute occupational therapy services, higher frequency of acute occupational therapy services was linked with lower odds of readmission. Readmitted patients were less likely to have received ADL or self-care training while hospitalized. What This Article Adds: Identifying factors of acute occupational therapy services that reduce the odds of readmission for Medicare patients may help to improve patient outcomes and further define occupational therapy's role in the U.S. quality-focused health care system.

Effectiveness of Hospital-Based Interventions by Occupational Therapy Practitioners on Reducing Readmissions: A Systematic Review With Meta-Analyses

IMPORTANCE

Readmission to the hospital can lead to poorer patient outcomes and increased health care costs. The effect of occupational therapy interventions for adult hospitalized patients on readmission rates has not been previously evaluated.

OBJECTIVE

To systematically examine the published literature to determine the effects of occupational therapy interventions for adult hospitalized patients on readmission rates.

DATA SOURCES

Systematic search of five electronic databases was performed from database inception until May 2020, supplemented by citation and reference list searches. Study Selection and Data Collection: This review is reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and was registered prospectively; methodological quality of the included studies was assessed using the Downs and Black checklist. Meta-analyses were conducted with clinically homogeneous data; the overall body of evidence was graded for quality.

FINDINGS

Meta-analysis of 7 studies with 16,718 participants provided low-quality evidence that 1-mo readmission rates were reduced when adult patients hospitalized for general medical and surgical care received additional occupational therapy interventions compared with standard care. Subgroup analysis of 4 studies provided moderate-quality evidence that interventions focusing on the transition from hospital to the community were effective in reducing 1-mo readmissions to hospitals compared with standard care.

CONCLUSIONS AND RELEVANCE

Occupational therapy interventions can be effective in reducing readmissions among some adult hospitalized patient populations, including those admitted for surgery or management of acute medical conditions, with stronger evidence to support transitional care interventions. What This Article Adds: Occupational therapy interventions can be effective in reducing readmissions among adult hospitalized patients. There is a continued need for occupational therapy practitioners to understand their value and contribution to reducing avoidable readmissions to hospitals.

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.

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.

Prediction of 30-Day Readmission After Stroke Using Machine Learning and Natural Language Processing

Background and Purpose: This study aims to determine whether machine learning (ML) and natural language processing (NLP) from electronic health records (EHR) improve the prediction of 30-day readmission after stroke.

Methods: Among index stroke admissions between 2011 and 2016 at an academic medical center, we abstracted discrete data from the EHR on demographics, risk factors, medications, hospital complications, and discharge destination and unstructured textual data from clinician notes. Readmission was defined as any unplanned hospital admission within 30 days of discharge. We developed models to predict two separate outcomes, as follows: (1) 30-day all-cause readmission and (2) 30-day stroke readmission. We compared the performance of logistic regression with advanced ML algorithms. We used several NLP methods to generate additional features from unstructured textual reports. We evaluated the performance of prediction models using a five-fold validation and tested the best model in a held-out test dataset. Areas under the curve (AUCs) were used to compare discrimination of each model.

Results: In a held-out test dataset, advanced ML methods along with NLP features out performed logistic regression for all-cause readmission (AUC, 0.64 vs. 0.58; p < 0.001) and stroke readmission prediction (AUC, 0.62 vs. 0.52; p < 0.001).

Conclusion: NLP-enhanced machine learning models potentially advance our ability to predict readmission after stroke. However, further improvement is necessary before being implemented in clinical practice given the weak discrimination.

Association Between Use of Rehabilitation in the Acute Care Hospital and Hospital Readmission or Mortality in Patients With Stroke

OBJECTIVE

To examine the association between the number of physical and occupational therapist visits received in the acute care hospital and the risk of hospital readmission or death.

DESIGN

Retrospective cohort study of electronic health records and administrative claims data collected for 2.25 years (January 1, 2016-March 30, 2018).

SETTING

Twelve acute care hospitals in a large health care system in western Pennsylvania.

PARTICIPANTS

Adults (N=8279) discharged with a primary stroke diagnosis.

INTERVENTIONS

The exposure was number of physical and occupational therapist visits during the acute care stay.

MAIN OUTCOME MEASURES

Generalized linear mixed models were estimated to examine the relationship between therapy use and 30- and 7-day hospital readmission or death (outcome), controlling for patient demographic and clinical characteristics.

RESULTS

The 30- and 7-day readmission or death rates were 16.0% and 5.7%, respectively. The number of therapist visits was inversely related to the risk of 30-day readmission or death. Relative to no therapist visits, the odds of readmission or death were 0.70 (95% confidence interval [CI], 0.54-0.90) for individuals who received 1-2 visits, 0.59 (95% CI, 0.43-0.81) for 3-5 visits, and 0.57 (95% CI, 0.39-0.81) for >5 visits. A similar pattern was seen for the 7-day outcome, with slightly larger effect sizes. Effects were also greater in individuals with more mobility limitations on admission and for those discharged to a postacute care facility vs home.

CONCLUSIONS

There was an inverse relationship between the number of therapist visits and risk for readmission or death for patients with stroke discharged from an acute care hospital. Effects differed by time to the event (30d vs 7d), discharge location, and mobility limitations on admission.

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.

Remote Longitudinal Inpatient Acute Stroke Care Via Telestroke

OBJECTIVES

While telestroke 'hub-and-spoke' systems are a well-established model for improving acute stroke care at spoke facilities, utility beyond the hyperacute phase is unknown. In patients receiving intravenous thrombolysis via telemedicine, care at spoke facilities has been shown to be associated with longer length of stay and worse outcomes. We sought to explore the impact of ongoing stroke care by a vascular neurologist via telemedicine compared to care provided by local neurologists.

METHODS

A network spoke facility protocol was revised to pilot telestroke consultation with a hub vascular neurologist for all patients presenting to the emergency department with ischemic stroke or transient ischemic attack regardless of time since onset or severity. Subsequent telestroke rounds were performed for patients who received initial telestroke consultation. Key outcome measures were length of stay, 30-day readmission and mortality and 90-day mRS. Results during the pilot (post-cohort) were compared to the same hospital's previous outcomes (pre-cohort).

RESULTS

Of 257 enrolled patients, 67% were in the post-cohort. Forty percent (69) of the post-cohort received an initial telestroke consult. In spoke-retained patients followed by telestroke rounds (55), median length of stay decreased by 0.8 days (P = 0.01). Readmission and mortality rates did not differ significantly between groups (19.5 vs. 9.1%, P = 0.14 and 3.9 vs. 3.6%, P = 1, respectively). The favorable functional outcome rate was similar between groups (47.3% vs 65.9%, P = 0.50).

CONCLUSIONS

Longitudinal stroke care via telestroke may be economically viable through length of stay reduction. Randomized prospective studies are needed to confirm our findings and further investigate this model's potential benefits.

Investigating the geographic disparity in quality of care: the case of hospital readmission after acute myocardial infarction in Italy

Unwarranted variation in the quality of care challenges the sustainability of healthcare systems. Especially in decentralised healthcare systems, it is crucial to understand the drivers behind regional differences in hospital qualities such as unplanned readmissions. This paper examines the factors that influence the risk of unplanned hospital readmission and the geographic disparity of readmission rate in Italy. We use hospital discharge data from 2010 to 2015 for patients above 65 years old admitted with Acute Myocardial Infarction. Employing hierarchical models, we identified the patient and hospital-level determinants for unplanned readmission. In line with the literature, the risk of readmission increases with age and being male, while hospitals with higher patient volume and capacity tend to have lower unplanned readmission. In particular, we find that after patient risk-adjustments, there are differential effects of hospitalisation length-of-stay on the probability of readmission across the hospitals that are governed by different payment systems. For hospitals under a prospective payment system, the effect of length-of-stay in reducing the probability of readmission is weaker than hospitals under an ex-post global budget, but the overall readmission rates are the lowest. Moreover, there are substantial geographic variations in readmission rate across Local Health Authority and regions, and these variations of unplanned readmission are explained by differences in hospital length-of-stay and surgical procedures used. Our results demonstrate that differential hospital behaviours can be one of the potential mechanisms that drive geographic quality disparities.

Movement Matters, and So Does Context: Lessons Learned From Multisite Implementation of the Movement Matters Activity Program for Stroke in the Comprehensive Postacute Stroke Services Study

The purpose of this Special Communication is to discuss the rationale and design of the Movement Matters Activity Program for Stroke (MMAP) and explore implementation successes and challenges in home health and outpatient therapy practices across the stroke belt state of North Carolina. MMAP is an interventional component of the Comprehensive Postacute Stroke Services Study, a randomized multicenter pragmatic trial of stroke transitional care. MMAP was designed to maximize survivor health, recovery, and functional independence in the community and to promote evidence-based rehabilitative care. MMAP provided training, tools, and resources to enable rehabilitation providers to (1) prescribe physical activity and exercise according to evidence-based guidelines and programs, (2) match service setting and parameters with survivor function and benefit coverage, and (3) align treatment with quality metric reporting to demonstrate value-based care. MMAP implementation strategies were aligned with the Expert Recommendations for Implementing Change project, and MMAP site champion and facilitator survey feedback were thematically organized into the Consolidated Framework for Implementation Research domains. MMAP implementation was challenging, required modification and was affected by provider- and system-level factors. Program and study participation were limited and affected by practice priorities, productivity standards, and stroke patient volume. Sites with successful implementation appeared to have empowered MMAP champions in vertically integrated systems that embraced innovation. Findings from this broad evaluation can serve as a road map for the design and implementation of other comprehensive, complex interventions that aim to bridge the currently disconnected realms of acute care, postacute care, and community resources.

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.

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.

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.

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.

Hospital admission and readmission among homeless patients with neurologic disease

OBJECTIVE

To characterize the most common neurologic diagnoses leading to hospitalization for homeless compared to housed individuals and to assess whether homelessness is an independent risk factor for 30-day readmission after an admission for a neurologic illness.

METHODS

We performed a retrospective serial cross-sectional study using data from the Healthcare Cost and Utilization Project California State Inpatient Database from 2006 to 2011. Adult patients with a primary neurologic discharge diagnosis were included. The primary outcome was 30-day readmission. We used multilevel logistic regression to examine the association between homelessness and readmission after adjustment for patient factors.

RESULTS

We identified 1,082,347 patients with a neurologic primary diagnosis. The rate of homelessness was 0.37%. The most common indications for hospitalization among homeless patients were seizure and traumatic brain injury, both of which were more common in the homeless compared to housed population (19.3% vs 8.1% and 31.9% vs 9.2%, respectively, p < 0.001). A multilevel mixed-effects model controlling for patient age, sex, race, insurance type, comorbid conditions, and clustering on the hospital level found that homelessness was associated with increased 30-day readmission (odds ratio 1.5, 95% confidence interval 1.4-1.6, p < 0.001). This association persisted after this analysis was repeated within specific diagnoses (patients with epilepsy, trauma, encephalopathy, and neuromuscular disease).

CONCLUSION

The most common neurologic reasons for admission among homeless patients are seizure and traumatic brain injury; these patients are at high risk for readmission. Future interventions should target the drivers of readmissions in this vulnerable population.

Participation, Fear of Falling, and Upper Limb Impairment are Associated with High Sitting Time in People with Stroke

The purpose of this cross-sectional, exploratory study was to explore associations between sitting time and (1) participation, (2) fear of falling, and (3) upper limb impairment after stroke. High sitting time was associated with less participation in meaningful activities involving standing or walking (ρ = -0.519, p = 0.023). A greater fear of falling (ρ = 0.579, p = 0.012) and having an impaired upper limb (mean difference 18.7%, 95% CI: 5.3-32.1, p = 0.012) were associated with greater sitting time. Providing support for stroke survivors to participate in meaningful activities while reducing sitting time is an important consideration when planning occupational therapy interventions, particularly for individuals with an arm impairment and/or those with a fear of falling.

Use of Hospital-Based Rehabilitation Services and Hospital Readmission Following Ischemic Stroke in the United States

OBJECTIVE

To examine the association between hospital-based rehabilitation service use and all-cause 30-day hospital readmission among patients with ischemic stroke.

DESIGN

Secondary analysis of inpatient Medicare claims data using Standard Analytical Files.

SETTING

Acute hospitals across the United States.

PARTICIPANTS

From nationwide data, Medicare fee-for-service beneficiaries (N=88,826) aged 66 years or older hospitalized for ischemic stroke between January to November 2010.

INTERVENTIONS

Hospital-based rehabilitation services were quantified using Medicare inpatient claims revenue center codes for evaluation (occupational therapy [OT] and physical therapy [PT]), as well as the number of therapy units delivered. Therapy minutes for both OT and PT services were categorized into none, low, medium, and high.

MAIN OUTCOME MEASURES

All-cause 30-day hospital readmission. A generalized linear mixed model was used to examine the effect of hospital-based rehabilitation services on 30-day hospital readmission, after adjusting for patient and hospital characteristics.

RESULTS

In fully adjusted models, compared to patients who received no PT, we observed a monotonic inverse relationship between the amount of PT and hospital readmission. For low PT (30 minutes), the odds ratio (OR) was 0.90 (95% confidence interval [CI], 0.83-0.96). For medium PT (>30 to ≤75 minutes), the OR was 0.89 (95% CI, 0.82-0.95). For high PT (>75 minutes), the OR was 0.86 (95% CI, 0.80-0.93).

CONCLUSION

Hospital-based PT services were associated with lower risk of 30-day hospital readmission in patients with ischemic stroke.

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.

To what degree can variations in readmission rates be explained on the level of the hospital? a multilevel study using a large Dutch database

BACKGROUND

It is not clear which part of the variation in hospital readmissions can be attributed to the standard of care hospitals provide. This is in spite of their widespread use as an indicator of a lower quality of care. The aim of this study is to assess the variation in readmissions on the hospital level after adjusting for case-mix factors.

METHODS

We performed multilevel logistic regression analyses with a random intercept for the factor 'hospital' to estimate the variance on the hospital level after adjustment for case-mix variables. We used administrative data from 53 Dutch hospitals from 2010 to 2012 (58% of all Dutch hospitals; 2,577,053 admissions). We calculated models for the top ten diagnosis groups with the highest number of readmissions after an index admission for a surgical procedure. We calculated intraclass correlation coefficients (ICC) per diagnosis group in order to explore the variation in readmissions between hospitals. Furthermore, we determined C-statistics for the models with and without a random effect on the hospital level to determine the discriminative ability.

RESULTS

The ICCs on the hospital level ranged from 0.48 to 2.70% per diagnosis group. The C-statistics of the models with a random effect on the hospital level ranged from 0.58 to 0.65 for the different diagnosis groups. The C-statistics of the models that included the hospital level were higher compared to the models without this level.

CONCLUSIONS

For some diagnosis groups, a small part of the explained variation in readmissions was found on the hospital level, after adjusting for case-mix variables. However, the C-statistics of the prediction models are moderate, so the discriminative ability is limited. Readmission indicators might be useful for identifying areas for improving quality within hospitals on the level of diagnosis or specialty.

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.

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.

Hospital readmissions after spontaneous intracerebral hemorrhage in Southern Portugal

OBJECTIVES

Spontaneous intracerebral hemorrhage (SICH) survivors are at risk of hospital readmissions. Data on readmissions after SICH is scarce. We aimed to study the frequency and predictors of readmissions after SICH in Algarve, Portugal.

PATIENTS AND METHODS

Retrospective study of a community representative cohort of SICH survivors (2009-2015). The first unplanned readmission in the first year after discharge was the outcome. Cox regression analysis was performed to identify predictors of 1-year readmission.

RESULTS

Of the 357 SICH survivors followed, 116 (32.5%) were readmitted within the first-year. Sixty-seven (18.8%) of the survivors were early readmitted (<90 days), corresponding to 57.8% or all readmissions. Common causes were pneumonia, endocrine/nutritional/metabolic and cardiovascular complications. The risk of readmission was increased by prior to index SICH history of ≥ 3 previous emergency department visits (hazards ratio (HR) = 2.663 (1.770-4.007); P < 0.001), pneumonia during index hospitalization (HR = 2.910 (1.844-4.592); P < 0.001) and reduced in patients discharge home (HR = 0.681 (0.366-0.976); P = 0.048).

CONCLUSIONS

The rate of readmissions after SICH is high, predictors are identifiable and causes are potentially preventable. Improvement of care can potentially reduce this burden.

Association Between Early Outpatient Visits and Readmissions After Ischemic Stroke

BACKGROUND

Reducing hospital readmission is an important goal to optimize poststroke care and reduce costs. Early outpatient follow-up may represent one important strategy to reduce readmissions. We examined the association between time to first outpatient contact and readmission to inform postdischarge transitions.

METHODS AND RESULTS

We performed a retrospective cohort study of all Medicare fee-for-service patients discharged home after an acute ischemic stroke in 2012 identified by the InternationalClassification of Diseases, Ninth Revision, Clinical Modification codes. Our primary predictor variable was whether patients had a primary care or neurology visit within 30 days of discharge. Our primary outcome variable was all-cause 30-day hospital readmission. We used separate multivariable Cox models with primary care and neurology visits specified as time-dependent covariates, adjusted for numerous patient- and systems-level factors. The cohort included 78 345 patients. Sixty-one percent and 16% of patients, respectively, had a primary care and neurology visit within 30 days of discharge. Visits occurred a median (interquartile range) 7 (4-13) and 15 (5-22) days after discharge for primary care and neurology, respectively. Thirty-day readmission occurred in 9.4% of patients. Readmissions occurred a median 14 (interquartile range, 7-21) days after discharge. Patients who had a primary care visit within 30 days of discharge had a slightly lower adjusted hazard of readmission than those who did not (hazard ratio, 0.98; 95% confidence interval, 0.97-0.98). The association was nearly identical for 30-day neurology visits (hazard ratio, 0.98; 95% confidence interval, 0.97-0.98).

CONCLUSIONS

Thirty-day outpatient follow-up was associated with a small reduction in hospital readmission among elderly patients with stroke discharged home. Further work should assess how outpatient care may be improved to further reduce readmissions.

A propensity score analysis of the impact of surgical intervention on unexpected 30-day readmission following admission for subdural hematoma

OBJECTIVE

Subdural hematoma (SDH) is a common disease that is increasingly being managed nonoperatively. The all-cause readmission rate for SDH has not previously been described. This study seeks to describe the incidence of unexpected 30-day readmission in a cohort of patients admitted to an academic neurosurgical center. Additionally, the relationship between operative management, clinical outcome, and unexpected readmission is explored.

METHODS

This is an observational study of 200 consecutive adult patients with SDH admitted to the neurosurgical ICU of an academic medical center. Demographic information, clinical characteristics, and treatment strategies were compared between readmitted and nonreadmitted patients. Multivariable logistic regression, weighted by the inverse probability of receiving surgery using propensity scores, was used to evaluate the association between operative management and unexpected readmission.

RESULTS

Of 200 total patients, 18 (9%) died during hospitalization and were not included in the analysis. Overall, 48 patients (26%) were unexpectedly readmitted within 30 days. Sixteen patients (33.3%) underwent SDH evacuation during their readmission. Factors significantly associated with unexpected readmission were nonoperative management (72.9% vs 54.5%, p = 0.03) and female sex (50.0% vs 32.1%, p = 0.03). In logistic regression analysis weighted by the inverse probability of treatment and including likely confounders, surgical management was not associated with likelihood of a good outcome at hospital discharge, but was associated with significantly reduced odds of unexpected readmission (OR 0.19, 95% CI 0.08-0.49).

CONCLUSIONS

Over 25% of SDH patients admitted to an academic neurosurgical ICU were unexpectedly readmitted within 30 days. Nonoperative management does not affect outcome at hospital discharge but is significantly associated with readmission, even when accounting for the probability of treatment by propensity score weighted logistic regression. Additional research is needed to validate these results and to further characterize the impact of nonoperative management on long-term costs and clinical outcomes.

High Mortality among 30-Day Readmission after Stroke: Predictors and Etiologies of Readmission

BACKGROUND

Although some risk factors for stroke readmission have been reported, the mortality risk is unclear. We sought to evaluate etiologies and predictors of 30-day readmissions and determine the associated mortality risk.

METHODS

This is a retrospective case-control study evaluating 1,544 patients admitted for stroke (hemorrhagic, ischemic, or TIA) from January 2013 to December 2014. Of these, 134 patients readmitted within 30 days were identified as cases; 1,418 other patients, with no readmissions were identified as controls. Patients readmitted for hospice or elective surgery were excluded. An additional 248 patients deceased on index admission were included for only a comparison of mortality rates. Factors explored included socio-demographic characteristics, clinical comorbidities, stroke characteristics, and length of stay. Chi-square test of proportions and multivariable logistic regression were used to identify independent predictors of 30-day stroke readmissions. Mortality rates were compared for index admission and readmission and among readmission diagnoses.

RESULTS

Among the 1,544 patients in the main analysis, 67% of index stroke admissions were ischemic, 22% hemorrhagic, and 11% TIA. The 30-day readmission rate was 8.7%. The most common etiologies for readmission were infection (30%), recurrent stroke and TIA (20%), and cardiac complications (14%). Significantly higher proportion of those readmitted for recurrent strokes and TIAs presented within the first week (p = 0.039) and had a shorter index admission length of stay (p = 0.027). Risk factors for 30-day readmission included age >75 (p = 0.02), living in a facility prior to index stroke (p = 0.01), history of prior stroke (p = 0.03), diabetes (p = 0.03), chronic heart failure (p ≤ 0.001), atrial fibrillation (p = 0.03), index admission to non-neurology service (p < 0.01), and discharge to other than home (p < 0.01). On multivariate analysis, index admission to a non-neurology service was an independent predictor of 30-day readmission (p ≤ 0.01). The mortality after a within 30-day readmission after stroke was higher than index admission (36.6 vs. 13.8% p ≤ 0.001) (OR 3.6 95% CI 2.5-5.3). Among those readmitted, mortality was significantly higher for those admitted for a recurrent stroke (p = 0.006).

CONCLUSION

Approximately one-third of 30-day readmissions were infection related and one-fifth returned with recurrent stroke or TIA. Index admission to non-neurology service was an independent risk factor of 30-day readmissions. The mortality rate for 30-day readmission after stroke is more than 2.5 times greater than index admissions and highest among those readmitted for recurrent stroke. Identifying high-risk patients for readmission, ensuring appropriate level of service, and early outpatient follow-up may help reduce 30-day readmission and the high associated risk of mortality.

No Racial Difference in Rehabilitation Therapy Across All Post-Acute Care Settings in the Year Following a Stroke

BACKGROUND AND PURPOSE

Black stroke survivors experience greater poststroke disability than whites. Differences in post-acute rehabilitation may contribute to this disparity. Therefore, we estimated racial differences in rehabilitation therapy utilization, intensity, and the number of post-acute care settings in the first year after a stroke.

METHODS

We used national Medicare data to study 186 168 elderly black and white patients hospitalized with a primary diagnosis of stroke in 2011. We tabulated the proportion of stroke survivors receiving physical, occupational, and speech and language therapy in each post-acute care setting (inpatient rehabilitation facility, skilled nursing facility, and home health agency), minutes of therapy, and number of transitions between settings. We then used generalized linear models to determine whether racial differences in minutes of physical therapy were influenced by demographics, comorbidities, thrombolysis, and markers of stroke severity.

RESULTS

Black stroke patients were more likely to receive each type of therapy than white stroke patients. Compared with white stroke patients, black stroke patients received more minutes of physical therapy (897.8 versus 743.4; P<0.01), occupational therapy (752.7 versus 648.9; P<0.01), and speech and language therapy (865.7 versus 658.1; P<0.01). There were no clinically significant differences in physical therapy minutes after adjustment. Blacks had more transitions (median, 3; interquartile range, 1-5) than whites (median, 2; interquartile range, 1-5; P<0.01).

CONCLUSIONS

There are no clinically significant racial differences in rehabilitation therapy utilization or intensity after accounting for patient characteristics. It is unlikely that differences in rehabilitation utilization or intensity are important contributors to racial disparities in poststroke disability.

Community Use of Physical and Occupational Therapy After Stroke and Risk of Hospital Readmission

OBJECTIVES

To determine whether receipt of therapy and number and timing of therapy visits decreased hospital readmission risk in stroke survivors discharged home.

DESIGN

Retrospective cohort analysis of Medicare claims (2010-2013).

SETTING

Acute care hospital and community.

PARTICIPANTS

Patients hospitalized for stroke who were discharged home and survived the first 30 days (N=23,413; mean age ± SD, 77.6±7.5y).

INTERVENTIONS

Physical and occupational therapist use in the home and/or outpatient setting in the first 30 days after discharge (any use, number of visits, and days to first visit).

MAIN OUTCOME MEASURES

Hospital readmission 30 to 60 days after discharge. Covariates included demographic characteristics, proxy variables for functional status, hospitalization characteristics, comorbidities, and prior health care use. Multivariate logistic regression analyses were conducted to examine the relation between therapist use and readmission.

RESULTS

During the first 30 days after discharge, 31% of patients saw a therapist in the home, 11% saw a therapist in an outpatient setting, and 59% did not see a therapist. Relative to patients who had no therapist contact, those who saw an outpatient therapist were less likely to be readmitted to the hospital (odds ratio, 0.73; 95% confidence interval, 0.59-0.90). Although the point estimates did not reach statistical significance, there was some suggestion that the greater the number of therapist visits in the home and the sooner the visits started, the lower the risk of hospital readmission.

CONCLUSIONS

After controlling for observable demographic-, clinical-, and health-related differences, we found that individuals who received outpatient therapy in the first 30 days after discharge home after stroke were less likely to be readmitted to the hospital in the subsequent 30 days, relative to those who received no therapy.

Sequence Analysis of Long-Term Readmissions among High-Impact Users of Cerebrovascular Patients

Objective

Understanding the chronological order of the causes of readmissions may help us assess any repeated chain of events among high-impact users, those with high readmission rate. We aim to perform sequence analysis of administrative data to identify distinct sequences of emergency readmissions among the high-impact users.

Methods

A retrospective cohort of all cerebrovascular patients identified through national administrative data and followed for 4 years.

Results

Common discriminating subsequences in chronic high-impact users (n = 2863) of ischaemic stroke (n = 34208) were “urological conditions-chest infection,” “chest infection-urological conditions,” “injury-urological conditions,” “chest infection-ambulatory condition,” and “ambulatory condition-chest infection” (p < 0.01). Among TIA patients (n = 20549), common discriminating (p < 0.01) subsequences among chronic high-impact users were “injury-urological conditions,” “urological conditions-chest infection,” “urological conditions-injury,” “ambulatory condition-urological conditions,” and “ambulatory condition-chest infection.” Among the chronic high-impact group of intracranial haemorrhage (n = 2605) common discriminating subsequences (p < 0.01) were “dementia-injury,” “chest infection-dementia,” “dementia-dementia-injury,” “dementia-urine infection,” and “injury-urine infection.” Conclusion. Although common causes of readmission are the same in different subgroups, the high-impact users had a higher proportion of patients with distinct common sequences of multiple readmissions as identified by the sequence analysis. Most of these causes are potentially preventable and can be avoided in the community.

Conclusion

Although common causes of readmission are the same in different subgroups, the high-impact users had a higher proportion of patients with distinct common sequences of multiple readmissions as identified by the sequence analysis. Most of these causes are potentially preventable and can be avoided in the community.

Cost effectiveness of the occupation-based approach for subacute stroke patients: result of a randomized controlled trial

BACKGROUND AND PURPOSE

The cost effectiveness of occupational therapy for subacute stroke patients is unclear in the extant literature. Consequently, this study determined the cost effectiveness of the occupation-based approach using Aid for Decision-Making in Occupation Choice (ADOC) for subacute stroke patients compared with an impairment-based approach.

METHODS

We conducted an economic evaluation from a societal perspective alongside a pilot randomized controlled trial, with a single blind assessor for participants in 10 subacute rehabilitation units in Japan. The intervention group received occupation-based goal setting using ADOC, with interventions focused on meaningful occupations. The control group received an impairment-based approach focused on restoring capacities. For both groups, occupational-therapy intervention was administered more than five times per week, for over 40 min each time, and they received physical and speech therapy prior to discharge. The main outcomes were quality-adjusted life years (QALYs) and total costs. Further, sensitivity analyses were performed to examine the influence of parameter uncertainty on the base case results.

RESULTS

The final number of participants was 24 in each of the two groups. In terms of QALYs, the intervention group is significantly higher than the control group (p = 0.001, difference 95% CI: 0.002-0.008) and total costs are not statistically significant. Applying a willingness-to-pay threshold of JPY 5 million/QALY, the probability of the occupation-based approach using ADOC being cost effective was estimated to be 65.3%.

CONCLUSIONS

The results show that the occupation-based approach is associated with significantly improved QALYs and has potential cost effectiveness, compared with the impairment-based approach.

Predictors of hospital readmission 1 year after ischemic stroke

Predictors of short-term readmission after ischemic stroke have been previously identified, but few studies analyzed predictors of long-term readmission, namely early imaging findings and treatment with intravenous thrombolysis (IVT). To characterize predictors of hospital readmission during the first year after hospitalization for ischemic stroke. The study consists of a retrospective cohort of consecutive ischemic stroke patients admitted in a Portuguese university hospital during 2013, who survived index hospitalization. We collected clinical and imaging information using the electronical clinical record. Information concerning 1-year unplanned hospital readmissions was assessed using the Portuguese electronic Health Data Platform. Descriptive and univariate analyses, Kaplan-Meier survival curve and multivariate survival analysis with Cox regression model were used. We included 480 patients, 50.6 % women, median age 79 years (interquartile range = 68-85). One-year hospital readmissions occurred in 165 patients [34.4 %, 95 % confidence interval (95 % CI) 30.2-38.7]. The main causes for readmission were infectious diseases (43.8 %), ischemic stroke or transient ischemic attack recurrence (13.2 %) and cardiac diseases (6.4 %). In-hospital mortality associated with readmission was 23.0 %. The independent predictors of 1-year hospital readmission after ischemic stroke were admission mini-National Institute of Health Stoke Scale [hazards ratio (HR) 1.05, 95 % CI 1.02-1.08, p = 0.002], and mild or absent early signs of ischemia on admission computed tomography (CT) (HR 0.54, 95 % CI 0.32-0.91, p = 0.021) and IVT (HR 0.11, 95 % CI 0.01-0.80, p = 0.029). Hospital readmission during the first year after ischemic stroke occurs in 1/3 of patients and is associated with high in-hospital mortality. Clinical stroke severity, early signs of ischemia on admission CT, and treatment with IVT are independent predictors of 1-year hospital readmission.

Impact of Neurological Follow-Up on Early Hospital Readmission Rates for Acute Ischemic Stroke

INTRODUCTION

Despite advances in stroke care, readmission rates for patients with ischemic stroke remain high. Although factors such as age, diabetes, and continuous use of antiplatelet agents have been found to predict readmission rates, the impact of after-hospital care has not been examined.

METHODS

The present study reviewed the charts of 416 patients with acute ischemic stroke and recorded stroke-related comorbidities, neurology follow-up within 21 days, readmission at 0 to 30 days, readmission at 31 to 90 days, and any reasons for readmission.

RESULTS

For those readmitted within 0 to 30 days, reasons for readmission were other medical conditions (62.5%), recurrent stroke (30.4%), and elective procedure (7.1%). For those readmitted within 31 to 90 days, reasons for readmission were other medical conditions (62.3%), recurrent stroke (15.1%), and elective procedure (22.6%). There was no significant relationship between being evaluated within 21 days and readmission at 0 to 30 or 31 to 90 days. However, those who did have a neurology follow-up at any point in time had a lower readmission rate of 10.6% compared to those who never came back (19.2%, P = .017). Patients with coronary artery disease and diabetes had a significantly higher likelihood of readmission within 0 to 30 days.

CONCLUSION

The present study suggests that neurology follow-up at any point in time for patients with acute ischemic stroke may reduce short-term readmissions, but special attention to optimizing management of other underlying medical conditions, coronary artery disease, or diabetes may also help reduce overall readmissions. Patients with stroke, therefore, may benefit from a follow-up with both the primary care and neurology in a coordinated fashion to prevent early readmissions at 30 days.

Stroke severity may predict causes of readmission within one year in patients with first ischemic stroke event

INTRODUCTION

Readmissions after stroke are costly. Risk assessment using information available upon admission could identify high-risk patients for potential interventions to reduce readmissions. Baseline stroke severity has been suspected to be a factor in readmission; however, the exact nature of the impact has not been adequately understood.

METHODS

Hospitalized adult patients with first-ever ischemic stroke were identified from a nationwide administrative database. Stroke severity was assessed using a validated claims-based stroke severity index. Cox proportional hazards models were used to investigate the relationship between stroke severity and first readmission within one year.

RESULTS

Of the 10,877 patients, 4295 (39.5%) were readmitted in one year. The cumulative risk of readmission was 34.1%, 44.7%, and 62.9% in patients with mild, moderate, and severe stroke, respectively. Patients with greater stroke severity had a significantly higher adjusted risk of first readmission for infection, metabolic disorders, neurological sequelae, and pulmonary diseases, whereas those with lesser stroke severity were prone to first readmission due to accidents. Stroke severity did not affect the risk of first readmission for recurrent stroke/transient ischemic attack, other cardiovascular events, malignancy, ulcers/upper gastrointestinal bleeding, kidney diseases, and others.

CONCLUSIONS

Stroke severity in patients with first-ever ischemic stroke not only predicts readmission but also relates to the cause of readmission. Our results might provide important information for tailoring discharge planning to prevent readmissions.

Many Neurology Readmissions Are Nonpreventable

INTRODUCTION

Reducing unplanned hospital readmissions has become a national focus due to the Centers for Medicare and Medicaid Services' (CMS) penalties for hospitals with high rates. A first step in reducing unplanned readmission is to understand which patients are at high risk for readmission, which readmissions are planned, and how well planned readmissions are currently captured in comparison to patient-level chart review.

METHODS

We examined all 5455 inpatient neurology admissions over a 2-year period to University of California San Francisco Medical Center and Johns Hopkins Hospital via chart review. We collected information such as patient age, procedure codes, diagnosis codes, all-payer diagnosis-related group, observed length of stay (oLOS), and expected length of stay. We performed multivariate logistic modeling to determine predictors of readmission. Discharge summaries were reviewed for evidence that a subsequent readmission was planned.

RESULTS

A total of 353 (6.5%) discharges were readmitted within 30 days. Fifty-five (15.6%) of the 353 readmissions were planned, most often for a neurosurgical procedure (41.8%) or immunotherapy (23.6%). Only 8 of these readmissions would have been classified as planned using current CMS methodology. Patient age (odds ratio [OR] = 1.01 for each 10-year increase, P < .001) and estimated length of stay (OR = 1.04, P = .002) were associated with a greater likelihood of readmission, whereas index admission oLOS was not.

CONCLUSIONS

Many neurologic readmissions are planned; however, these are often classified by current CMS methodology as unplanned and penalized accordingly. Modifications of the CMS lists for potentially planned neurological and neurosurgical procedures and for acute discharge neurologic diagnoses should be considered.

Hospital Variation in Home-Time After Acute Ischemic Stroke

Background and Purpose—

Stroke survivors identify home-time as a high-priority outcome; there are limited data on factors influencing home-time and home-time variability among discharging hospitals.

Methods—

We ascertained home-time (ie, time alive out of a hospital, inpatient rehabilitation facility, or skilled nursing facility) at 90 days and 1-year post discharge by linking data from Get With The Guidelines-Stroke Registry patients (≥65 years) to Medicare claims. Using generalized linear mixed models, we estimated adjusted mean home-time for each hospital. Using linear regression, we examined associations between hospital characteristics and risk-adjusted home-time.

Results—

We linked 156 887 patients with ischemic stroke at 989 hospitals to Medicare claims (2007–2011). Hospital mean home-time varied with an overall unadjusted median of 59.5 days over the first 90 days and 270.2 days over the first year. Hospital factors associated with more home-time over 90 days included higher annual stroke admission volume (number of ischemic stroke admissions per year); South, West, or Midwest geographic regions (versus Northeast); and rural location; 1-year patterns were similar. Lowest home-time quartile patients (versus highest) were more likely to be older, black, women, and have more comorbidities and severe strokes. Home-time variation decreased after risk adjustment (interquartile range, 57.4–61.4 days over 90 days; 266.3–274.2 days over 1 year). In adjusted analyses, increasing annual stroke volume and rural location were associated with significantly more home-time.

Conclusions—

In older ischemic stroke survivors, home-time post discharge varies by hospital annual stroke volume, severity of case-mix, and region. In adjusted analyses, annual ischemic stroke admission volume and rural location were associated with more home-time post stroke.

Systematic Review of Hospital Readmissions in Stroke Patients

Background. Previous evidence on factors and causes of readmissions associated with high-impact users of stroke is scanty. The aim of the study was to investigate common causes and pattern of short- and long-term readmissions stroke patients by conducting a systematic review of studies using hospital administrative data. Common risk factors associated with the change of readmission rate were also examined. Methods. The literature search was conducted from 15 February to 15 March 2016 using various databases, such as Medline, Embase, and Web of Science. Results. There were a total of 24 studies (n = 2,126,617) included in the review. Only 4 studies assessed causes of readmissions in stroke patients with the follow-up duration from 30 days to 5 years. Common causes of readmissions in majority of the studies were recurrent stroke, infections, and cardiac conditions. Common patient-related risk factors associated with increased readmission rate were age and history of coronary heart disease, heart failure, renal disease, respiratory disease, peripheral arterial disease, and diabetes. Among stroke-related factors, length of stay of index stroke admission was associated with increased readmission rate, followed by bowel incontinence, feeding tube, and urinary catheter. Conclusion. Although risk factors and common causes of readmission were identified, none of the previous studies investigated causes and their sequence of readmissions among high-impact stroke users.

Higher Hospital Spending on Occupational Therapy Is Associated With Lower Readmission Rates

Hospital executives are under continual pressure to control spending and improve quality. While prior studies have focused on the relationship between overall hospital spending and quality, the relationship between spending on specific services and quality has received minimal attention. The literature thus provides executives limited guidance regarding how they should allocate scarce resources. Using Medicare claims and cost report data, we examined the association between hospital spending for specific services and 30-day readmission rates for heart failure, pneumonia, and acute myocardial infarction. We found that occupational therapy is the only spending category where additional spending has a statistically significant association with lower readmission rates for all three medical conditions. One possible explanation is that occupational therapy places a unique and immediate focus on patients’ functional and social needs, which can be important drivers of readmission if left unaddressed.

Adaptation of neurological practice and policy to a changing US health-care landscape

Health care in the USA is undergoing a drastic transformation under the Patient Protection and Affordable Care Act. The Patient Protection and Affordable Care Act is driving major health-care policy changes by connecting payment for traditional health-care services to value-based care initiatives and emphasising population health and innovative mechanisms to deliver care. Under the Patient Protection and Affordable Care Act, neurological practice will need to adapt and transform. Therefore, neurological policy should consider employing a new framework for neurological residency training, developing interdisciplinary team approaches to neurological subspecialty care, and strengthening the primary care-neurological specialty care interface to avoid redundancies and other medical waste. Additionally, neurological policy will need to support a more robust review of diagnostic and care pathway use to reduce avoidable expenditures, and test and implement bundled payments for key neurological diagnoses. In view of an anticipated 19% shortage of US neurologists in the next 10 years, development of new neurological policy under the Patient Protection and Affordable Care Act is paramount.