Preventable readmissions within 30 days of ischemic stroke among Medicare beneficiaries

Readmission to a different hospital following acute stroke is associated with worse outcomes

OBJECTIVE

There is a high risk of readmission within 30 days of index acute ischemic stroke (AIS), but effect of readmission to a different hospital is not known. We performed a retrospective cohort study to assess our hypothesis that 30-day readmission outcomes after AIS are worse for those readmitted to another hospital vs the discharging hospital.

METHODS

We utilized the 2013 Nationwide Readmissions Database to identify patients with index stroke admissions with ICD-9-CM codes. We identified all-cause readmissions with Clinical Classification Software. Outcomes included length of stay (LOS), total charges of hospitalization, and in-hospital mortality during 30-day readmission. Using linear and logistic regression, outcomes were compared in those readmitted to another hospital vs the discharging hospital.

RESULTS

There were 194,549 patients included, with an average age of 80.0 ± 14.0 years; 51.2% were female; 24,545 were readmitted within 30 days, and 7,274 (29.6%) to a different hospital. Readmission to a different hospital was associated with an increased LOS of 1.0 days (95% confidence interval [CI] 0.7-1.2, p < 0.0001) and $7,677.28 (95% CI $5,496-$9,858, p < 0.0001) greater total charges. The odds ratio for in-hospital mortality during readmission was 1.2 for readmission to another hospital (95% CI 1.0-1.3, p = 0.0079).

CONCLUSIONS

Readmission to another hospital within 30 days of AIS index admission was independently associated with longer LOS, increased total charges, and greater in-hospital mortality compared to readmission to the same hospital.

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

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

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Preventable Readmissions and Predictors of Readmission After Subarachnoid Hemorrhage

OBJECTIVE

To estimate rates of all-cause and potentially preventable readmissions up to 90 days after discharge for aneurysmal subarachnoid hemorrhage (SAH) and medical comorbidities associated with readmissions BACKGROUND: Readmission rate is a common metric linked to compensation and used as a proxy to quality of care. Prior studies in SAH have reported 30-day readmission rates of 7-17% with a higher readmission risk among those with the higher SAH severity, ≥ 3 comorbidities, and non-home discharge. Intermediate-term rates, up to 90-days, and the proportion of these readmissions that are potentially preventable are unknown. Furthermore, the specific medical comorbidities associated with readmissions are unknown.

METHODS

Index SAH admissions were identified from the 2013 Nationwide Readmissions Database. All-cause readmissions were defined as any readmission during the 30-, 60-, and 90-day post-discharge period. Potentially preventable readmissions were identified using Prevention Quality Indicators developed by the US Agency for Healthcare Research and Quality. Unadjusted and adjusted Poisson models were used to identify factors associated with increased readmission rates.

RESULTS

Out of 9987 index admissions for SAH, 7949 (79%) survived to discharge. The percentage of 30-, 60-, and 90-day all-cause readmissions were 7.8, 16.6, and 26%, respectively. Up to 14% of readmissions in the first 30 days were considered potentially preventable and acute conditions (dehydration, bacterial pneumonia, and urinary tract infections) accounted for over half, whereas acute cerebrovascular disease was the most common cause for neurological return. In multivariable analysis, significant predictors of a higher readmission rate included diabetes (rate ratio [RR] 1.09, 95% confidence interval [CI] 1.03-1.15), congestive heart failure (RR 1.09, 1.003-1.18), and renal impairment (RR 1.35, 1.13-1.61). Only discharge home was associated with a lower readmission rate (RR 0.89, 0.85-0.93).

CONCLUSIONS

SAH has a 30-day readmission rate of 7.8% which continues to rise into the intermediate-term. A low but constant proportion of readmissions are potentially preventable. Several chronic medical comorbidities were associated with readmissions. Prospective studies are warranted to clarify causal relationships.

Infections Increase the Risk of 30-Day Readmissions Among Stroke Survivors

Background and Purpose- Hospitals are increasingly using 30-day readmission (30dRA) to define the quality of care and reimbursement. We hypothesized that common infections occurring during the stroke stay are associated with 30dRA. Methods- We conducted a weighted analysis of the federally managed 2013 National Readmission Database to assess the relationship between infection during a stroke hospitalization and 30dRA among ischemic stroke survivors. Ischemic stroke, common infections (defined as sepsis, pneumonia, and urinary tract infection), and comorbidities were identified using International Classification of Diseases Ninth Revision ( ICD-9) diagnosis codes, and intravenous tPA (tissue-type plasminogen activator) or intra-arterial therapy was identified using ICD-9 procedure codes. Survey design logistic regression models were fit to estimate crude and adjusted odds ratios and 95% CI for the association between infections and 30dRA. Results- Among 319 317 ischemic stroke patients, 12.1% were readmitted within 30 days, and 29% had an infection during their index hospitalization. Patients with infection during their stroke admission had a 21% higher odds of being readmitted than patients without any type of infection (adjusted odds ratio, 1.21; 95% CI, 1.16-1.26). The association between infection and unplanned readmission was similar with an increased odds of unplanned readmission (adjusted odds ratio, 1.23; 95% CI, 1.18-1.29). When assessing specific types of infections, only urinary tract infections were associated with 30dRA in adjusted models (odds ratio, 1.10; 95% CI, 1.04-1.16). Conclusions- In a nationally representative cohort, patients who had a common infection during their stroke hospitalization were at increased odds of being readmitted. Patients with infection may benefit from earlier poststroke follow-up or closer monitoring.

Prevalence, Reasons, and Predisposing Factors Associated with 30-day Hospital Readmissions in Poland

There is a growing interest in quality issues associated with hospital care, with readmissions (rehospitalizations) being one of the main areas of interest. Retrospective data from a 914-bed university hospital in Bydgoszcz, Poland, was used to identify 30-day readmissions in 2015. We developed a catalogue of reasons for rehospitalization and differentiated between planned and unplanned readmissions, as well as those related and unrelated to index (initial) hospitalization. Multilevel logistic regression was used to determine factors associated with readmission risk. A total of 12.5% of patients were readmitted within 30 days of being discharged. The highest readmission rates were identified in pediatric, transplantation, and urology patients. The highest share of readmissions was due to the specific nature of a disease and its routine treatment practice. Almost two-thirds of readmission cases were classified as unplanned and related to the index hospitalization. The following characteristics were associated with a higher risk of rehospitalization: female gender, residing >35 km from the hospital, longer than average and very short stays at index admission, higher comorbidity score, and admission to a high-volume hospital sector. Due to the importance of quality issues in health policy, the topic should be further pursued to identify evidence-based practices that would improve hospitals’ performance.

Variation in Hospital-Based Rehabilitation Services Among Patients With Ischemic Stroke in the United States

BACKGROUND

Little is known about variation in use of rehabilitation services provided in acute care hospitals for people who have had a stroke.

OBJECTIVE

The objective was to examine patient and hospital sources of variation in acute care rehabilitation services provided for stroke.

DESIGN

This was a retrospective, cohort design.

METHODS

The sample consisted of Medicare fee-for-service beneficiaries with ischemic stroke admitted to acute care hospitals in 2010. Medicare claims data were linked to the Provider of Services file to gather information on hospital characteristics and the American Community Survey for sociodemographic data. Chi-square tests compared patient and hospital characteristics stratified by any rehabilitation use. We used multilevel, multivariable random effect models to identify patient and hospital characteristics associated with the likelihood of receiving any rehabilitation and with the amount of therapy received in minutes.

RESULTS

Among 104,295 patients, 85.2% received rehabilitation (61.5% both physical therapy and occupational therapy; 22.0% physical therapy only; and 1.7% occupational therapy only). Patients received 123 therapy minutes on average (median [SD] = 90.0 [99.2] minutes) during an average length of stay of 4.8 [3.5] days. In multivariable analyses, male sex, dual enrollment in Medicare and Medicaid, prior hospitalization, ICU stay, and feeding tube were associated with lower odds of receiving any rehabilitation services. These same variables were generally associated with fewer minutes of therapy. Patients treated by tissue plasminogen activator, in limited-teaching and nonteaching hospitals, and in hospitals with inpatient rehabilitation units, were more likely to receive more therapy minutes.

LIMITATION

The findings are limited to patients with ischemic stroke.

CONCLUSION

Only 61% of patients with ischemic stroke received both physical therapy and occupational therapy services in the acute setting. We identified considerable variation in the use of rehabilitation services in the acute care setting following a stroke.

Uncovering differences in interoperability across hospital size

BACKGROUND

Small hospitals significantly lag behind large hospitals in interoperable health information exchange. This analysis identifies factors that explain differences in interoperability between these hospital types. We place a particular emphasis on such factors as number of functionalities within electronic health record system (EHR), participation in regional and national networks, and adoption of a dominant EHR.

METHODS

Using data from the 2017 American Hospital Association (AHA) Annual Survey Information Technology Supplement (n = 2789 hospitals), we applied a Blinder-Oaxaca decomposition technique to explain differences in each domain of interoperability. Interoperability is defined as a hospitals' ability to electronically send, receive, and integrate summary of care records into their EHR and electronically find patient health information from external sources.

RESULTS

The percentage of small and large hospitals engaged in each interoperability domain increased between 2015 and 2017; however, the gap between these hospital types remained mostly the same. Differences in characteristics explained most of the gap in integrating, finding and receiving the data while differences in characteristics and returns to characteristics were significant in explaining the differences in sending the data. The number of EHR functionalities and participation in national and regional networks were among largest contributors to the gap.

CONCLUSIONS

The lack of participation in multiple networks and the number of functionalities in EHRs among small hospitals are key factors that explain the difference in interoperability between small and large hospitals. Policies that incentivize these activities or simplify electronic exchange could reduce gaps in interoperability among hospitals of different sizes.

Telemedicine in Rehabilitation

Telerehabilitation refers to the virtual delivery of rehabilitation services into the patient's home. This methodology has shown to be advantageous when used to enhance or replace conventional therapy to overcome geographic, physical, and cognitive barriers. The exponential growth of technology has led to the development of new applications that enable health care providers to monitor, educate, treat, and support patients in their own environment. Best practices and well-designed Telerehabilitation studies are needed to build and sustain a strong Telerehabilitation system that is integrated in the current health care structure and is cost-effective.

Recrudescence of Old Stroke Deficits Among Transient Neurological Attacks

Background

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

Objective

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

Methods

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

Results

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

Conclusion

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

Readmissions following hospitalisations for cardiovascular disease: a scoping review of the Australian literature

Objective International studies suggest high rates of readmissions after cardiovascular hospitalisations, but the burden in Australia is uncertain. We summarised the characteristics, frequency, risk factors of readmissions and interventions to reduce readmissions following cardiovascular hospitalisation in Australia. Methods A scoping review of the published literature from 2000-2016 was performed using Medline, EMBASE and Cumulative Index to Nursing and Allied Health Literature (CINAHL) databases and relevant grey literature. Results We identified 35 studies (25 observational, 10 reporting outcomes of interventions). Observational studies were typically single-centre (11/25) and reported readmissions following hospitalisations for heart failure (HF; 10/25), acute coronary syndrome (7/25) and stroke (6/25), with other conditions infrequently reported. The definition of a readmission was heterogeneous and was assessed using diverse methods. Readmission rate, most commonly reported at 1 month (14/25), varied from 6.3% to 27%, with readmission rates of 10.1-27% for HF, 6.5-11% for stroke and 12.7-17% for acute myocardial infarction, with a high degree of heterogeneity among studies. Of the 10 studies of interventions to reduce readmissions, most (n=8) evaluated HF management programs and three reported a significant reduction in readmissions. We identified a lack of national studies of readmissions and those assessing the cost and resource impact of readmissions on the healthcare system as well as a paucity of successful interventions to lower readmissions. Conclusions High rates of readmissions are reported for cardiovascular conditions, although substantial methodological heterogeneity exists among studies. Nationally standardised definitions are required to accurately measure readmissions and further studies are needed to address knowledge gaps and test interventions to lower readmissions in Australia. What is known about the topic? International studies suggest readmissions are common following cardiovascular hospitalisations and are costly to the health system, yet little is known about the burden of readmission in the Australian setting or the effectiveness of intervention to reduce readmissions. What does this paper add? We found relatively high rates of readmissions following common cardiovascular conditions although studies differed in their methodology making it difficult to accurately gauge the readmission rate. We also found several knowledge gaps including lack of national studies, studies assessing the impact on the health system and few interventions proven to reduce readmissions in the Australian setting. What are the implications for practitioners? Practitioners should be cautious when interpreting studies of readmissions due the heterogeneity in definitions and methods used in Australian literature. Further studies are needed to test interventions to reduce readmissions in the Australians setting.

Evaluation of Hospital-wide Readmission Risk Calculator to Predict 30-Day Readmission in Neurocritical Care Patients

BACKGROUND AND PURPOSE

Thirty-day hospital readmissions have been shown to be a measure of quality and result in higher mortality and increased costs. Readmissions are a target for hospitals and payers; thus, several centers have developed predictive readmission scores to identify high-risk patients. The purpose of this study was to evaluate the current hospital-wide readmission risk calculator and the ability of this tool to predict 30-day readmissions in the neurocritical care population.

METHODS

A retrospective chart review was performed that included 340 consecutive patients admitted to our neuroscience critical care unit. Data including readmission scores, reason for admission, length of stay, and whether they were readmitted were recorded.

RESULTS

After removing patients without readmission scores or who died at the end of the original admission, the records of N = 279 patients were analyzed. Patients were more likely to be readmitted if they were initially emergently hospitalized or if there was a history of malignancy. Readmitted patients had a longer original hospital length of stay. Furthermore, 65.8% of the patients who were given a "low risk" for readmission were readmitted within 30 days.

CONCLUSIONS

This small set of data in a specific patient population found that the current risk prediction score was inaccurate in predicting readmission in the neuroscience intensive care unit population. Further evaluation is needed of a larger patient population to generalize these results for all neuroscience intensive care unit patients. To design an accurate readmission risk tool, centers should create unique readmission scores based on less heterogeneous patient populations.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

Background

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

Methods

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

Results

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

Conclusions

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

Differential Impact of Hospital and Community Factors on Medicare Readmission Penalties

OBJECTIVE

To identify hospital/county characteristics and sources of regional heterogeneity associated with readmission penalties.

DATA SOURCES/STUDY SETTING

Acute care hospitals under the Hospital Readmissions Reduction Program from fiscal years 2013 to 2018 were linked to data from the Annual Hospital Association, Centers for Medicare and Medicaid Services, Medicare claims, Hospital Compare, Nursing Home Compare, Area Resource File, Health Inequity Project, and Long-term Care Focus. The final sample contained 3,156 hospitals in 1,504 counties.

DATA COLLECTION/EXTRACTION METHODS

Data sources were combined using Medicare hospital identifiers or Federal Information Processing Standard codes.

STUDY DESIGN

A two-level hierarchical model with correlated random effects, also known as the Mundlak correction, was employed with hospitals nested within counties.

PRINCIPAL FINDINGS

Over a third of the variation in readmission penalties was attributed to the county level. Patient sociodemographics and the surrounding access to and quality of care were significantly associated with penalties. Hospital measures of Medicare volume, percentage dual-eligible and Black patients, and patient experience were correlated with unobserved area-level factors that also impact penalties.

CONCLUSIONS

As the readmission risk adjustment does not include any community-level characteristics or geographic controls, the resulting endogeneity bias has the potential to disparately penalize certain hospitals.

Risk Factors Associated With Major Cardiovascular Events 1 Year After Acute Myocardial Infarction

IMPORTANCE

Patients who survive acute myocardial infarction (AMI) have a high risk of subsequent major cardiovascular events. Efforts to identify risk factors for recurrence have primarily focused on the period immediately following AMI admission.

OBJECTIVES

To identify risk factors and develop and evaluate a risk model that predicts 1-year cardiovascular events after AMI.

DESIGN, SETTING, AND PARTICIPANTS

Prospective cohort study. Patients with AMI (n = 4227), aged 18 years or older, discharged alive from 53 acute-care hospitals across China from January 1, 2013, to July 17, 2014. Patients were randomly divided into samples: training (50% [2113 patients]), test (25% [1057 patients]), and validation (25% [1057 patients]). Risk factors were identified by a Cox model with Markov chain Monte Carlo simulation and further evaluated by latent class analysis. Analyses were conducted from May 1, 2017, to January 21, 2018.

MAIN OUTCOMES AND MEASURES

Major cardiovascular events, including recurrent AMI, stroke, heart failure, and death, within 1 year after discharge for the index AMI hospitalization.

RESULTS

The mean (SD) age of the cohort was 60.8 (11.8) years and 994 of 4227 patients (23.5%) were female. Common comorbidities included hypertension (2358 patients [55.8%]), coronary heart disease (1798 patients [42.5%]), and dyslipidemia (1290 patients [30.5%]). One-year event rates were 8.1% (95% CI, 6.91%-9.24%), 9.0% (95% CI, 7.22%-10.70%), and 6.4% (95% CI, 4.89%-7.85%) for the training, test, and validation samples, respectively. Nineteen risk factors comprising 15 unique variables (age, education, prior AMI, prior ventricular tachycardia or fibrillation, hypertension, angina, prearrival medical assistance, >4 hours from onset of symptoms to admission, ejection fraction, renal dysfunction, heart rate, systolic blood pressure, white blood cell count, blood glucose, and in-hospital complications) were identified. In the training, test, and validation samples, respectively, the risk model had C statistics of 0.79 (95% CI, 0.75-0.83), 0.73 (95% CI, 0.68-0.78), and 0.77 (95% CI, 0.70-0.83) and a predictive range of 1.2% to 33.9%, 1.2% to 37.9%, and 1.3% to 34.3%. The C statistic was 0.69 (95% CI, 0.65-0.74) for the latent class model in the training data. The risk model stratified 11.3%, 81.0%, and 7.7% of patients to high-, average-, and low-risk groups, with respective probabilities of 0.32, 0.06, and 0.01 for 1-year events.

CONCLUSIONS AND RELEVANCE

Nineteen risk factors were identified, and a model was developed and evaluated to predict risk of 1-year cardiovascular events after AMI. This may aid clinicians in identifying high-risk patients who would benefit most from intensive follow-up and aggressive risk factor reduction.

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

IMPORTANCE

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

OBJECTIVES

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

DESIGN, SETTING, AND PARTICIPANTS

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

MAIN OUTCOMES AND MEASURES

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

RESULTS

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

CONCLUSIONS AND RELEVANCE

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

Regional Variation in 30-Day Ischemic Stroke Outcomes for Medicare Beneficiaries Treated in Get With The Guidelines-Stroke Hospitals

BACKGROUND

We explored regional variation in 30-day ischemic stroke mortality and readmission rates and the extent to which regional differences in patients, hospitals, healthcare resources, and a quality of care composite care measure explain the observed variation.

METHODS AND RESULTS

This ecological analysis aggregated patient and hospital characteristics from the Get With The Guidelines-Stroke registry (2007-2011), healthcare resource data from the Dartmouth Atlas of Health Care (2006), and Medicare fee-for-service data on 30-day mortality and readmissions (2007-2011) to the hospital referral region (HRR) level. We used linear regression to estimate adjusted HRR-level 30-day outcomes, to identify HRR-level characteristics associated with 30-day outcomes, and to describe which characteristics explained variation in 30-day outcomes. The mean adjusted HRR-level 30-day mortality and readmission rates were 10.3% (SD=1.1%) and 13.1% (SD=1.1%), respectively; a modest, negative correlation (r=-0.17; P=0.003) was found between one another. Demographics explained more variation in readmissions than mortality (25% versus 6%), but after accounting for demographics, comorbidities accounted for more variation in mortality compared with readmission rates (17% versus 7%). The combination of hospital characteristics and healthcare resources explained 11% and 16% of the variance in mortality and readmission rates, beyond patient characteristics. Most of the regional variation in mortality (65%) and readmission (50%) rates remained unexplained.

CONCLUSIONS

Thirty-day mortality and readmission rates vary substantially across HRRs and exhibit an inverse relationship. While regional variation in 30-day outcomes were explained by patient and hospital factors differently, much of the regional variation in both outcomes remains unexplained.

Age-related differences in the rate and diagnosis of 30-day readmission after hospitalization for acute ischemic stroke

Background Little is known about the association between age and readmission within 30 days after hospitalization for acute ischemic stroke. Aim To examine the age-related differences in rate and principal reason of 30-day readmissions in patients hospitalized for acute ischemic stroke. Methods In this retrospective, population-based cohort study using State Inpatient Databases from eight US states, we identified all adults hospitalized for acute ischemic stroke. We grouped the patients into four age categories: < 65, 65-74, 75-84, and ≥85 years. Outcomes were any-cause readmission within 30 days of discharge from the index hospitalization for acute ischemic stroke and the principal diagnosis of 30-day readmission. Results We identified 620,788 hospitalizations for acute ischemic stroke. The overall 30-day readmission rate was 16.6% with an increase with advanced age. Compared to patients aged <65 years, the readmission rate was significantly higher in age 65-74 years (OR 1.19; 95% CI 1.16-1.21), in age 75-84 years (OR 1.29; 95% CI 1.27-1.31), and in ≥ 85 years (OR 1.24; 95% CI 1.22-1.27; all P<0.001). There was heterogeneity in the age-readmission rate association between men and women (P_interaction < 0.001). Overall, 45.8% of readmissions were assigned stroke-related conditions or rehabilitation care. Compared to younger adults, older adults were more likely to present with non-stroke-related conditions (46.1% in < 65 years, 50.6% in 65-74 years, 57.1% in 75-84 years, and 62.9% in ≥ 85 years; P<0.001). Conclusions Advanced age was associated with a higher 30-day readmission rate after acute ischemic stroke. Compared with younger adults, older adults were more likely to be readmitted for non-stroke-related conditions.

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.

Care Coordination for Community Transitions for Individuals Post-stroke Returning to Low-Resource Rural Communities

High rates of hospital readmissions have been shown within 12 months post-discharge from inpatient rehabilitation following stroke. Multiple studies coupled with our previous work indicate a need for care support for stroke survivors' transitions to the community. The Kentucky Care Coordination for Community Transitions (KC³T) program was developed to provide access to medical, social, and environmental services to support community transitions for individuals with neurological conditions and their caregivers living in Kentucky. This program assessment was conducted to determine the effectiveness of using a specially trained community health worker to support community transitions. Thirty acute stroke survivors were enrolled in this program between July 2015 and May 2016. Data collection included: incidence of comorbidities; access to healthcare, insurance, medical equipment (DME), and medications; type of follow-up education provided; and number of 30-day rehospitalizations and Emergency Department (ED) visits. Participants required navigation in their home and community transition with support in: patient-provider communication; insurance support; accessing follow-up care; education on managing chronic health conditions, the stroke process, transfers and mobility; and accessing DME and essential medications. There were no 30-day ED visits for the KC3T participants and only one 30-day hospital readmission, which was not stroke-related. Individuals returning to rural communities following a stroke require, but often don't receive, follow-up education on chronic disease management, support in navigating the healthcare system and accessing essential resources. KC3T's navigator program appears to be effective in supporting the community transitions of individuals poststroke.

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.

Telemedicine-guided education on secondary stroke and fall prevention following inpatient rehabilitation for Texas patients with stroke and their caregivers: a feasibility pilot study

INTRODUCTION

The aftermath of stroke leaves many consequences including cognitive deficits and falls due to imbalance. Stroke survivors and families struggle to navigate the complex healthcare system with little assistance posthospital discharge, often leading to early hospital readmission and worse stroke outcomes. Telemedicine Guided Education on Secondary Stroke and Fall Prevention Following Inpatient Rehabilitation feasibility study examines whether stroke survivors and their caregivers find value in telerehabilitation (TR) home visits that provide individualised care and education by a multidisciplinary team after discharge from inpatient rehabilitation.

METHODS AND ANALYSIS

A prospective, single arm, pilot study is designed to evaluate the feasibility of weekly TR home visits initiated postdischarge from inpatient rehabilitation. Newly diagnosed patients with stroke are recruited from a Houston-based comprehensive stroke centre inpatient rehabilitation unit, loaned an iPad with data plan and trained to use information technology security-approved videoconferencing application. After hospital discharge, six weekly TR home visits are led by rotating specialists (pharmacist, physical/occupational therapist, speech therapist, rehabilitation physician, social worker, geriatrician specialised in fracture prevention) followed by satisfaction survey on week 7. Specialists visually assess patients in real time, educate them on secondary stroke and fall prevention and suggest ways to improve function including direct medical interventions when indicated. Primary outcomes are proportion of eligible patients consenting to the study, participation rate in all six TR home visits and satisfaction score. The study started 31 December 2015 with plan to enrol up to 50 patients over 24 months. Feasibility study results will inform us as to whether a randomised controlled trial is warranted to determine efficacy of TR home visit intervention in improving stroke outcomes.

ETHICS AND DISSEMINATION

Ethics approval obtained by the Institutional Review Board (IRB), Committee for the Protection of Human Subjects, IRB number: HSC-MS-14-0994. Study results will be submitted for publication in a peer-reviewed journal.

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

OBJECTIVE

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

DESIGN

A retrospective cohort study of patients with cerebrovascular conditions.

SETTINGS

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

PARTICIPANTS

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

MAIN OUTCOME MEASURE

Annual number of emergency hospital readmissions.

RESULTS

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

CONCLUSION

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

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.

Nationwide Estimates of 30-Day Readmission in Patients With Ischemic Stroke

Background and Purpose—

Readmission within 30 days of hospital discharge for ischemic stroke is an important quality of care metric. We aimed to provide nationwide estimates of 30-day readmission in the United States, describe important reasons for readmission, and sought to explore factors associated with 30-day readmission, particularly the association with recanalization therapy.

Methods—

We conducted a weighted analysis of the 2013 Nationwide Readmission Database to represent all US hospitalizations. Adult patients with acute ischemic stroke including those who received intravenous tissue-type plasminogen activator and intra-arterial therapy were identified using International Classification of Diseases -Ninth Revision codes. Readmissions were defined as any readmission during the 30-day post-index hospitalization discharge period for the eligible patient population. Proportions and 95% confidence intervals for overall 30-day readmissions and for unplanned and potentially preventable readmissions are reported. Survey design logistic regression models were fit for determining crude and adjusted odds ratios and 95% confidence interval for association between recanalization therapy and 30-day readmission.

Results—

Of the 319 317 patients with acute ischemic stroke, 12.1% (95% confidence interval, 11.9–12.3) were readmitted. Of these, 89.6% were unplanned and 12.9% were potentially preventable. More than 20% of all readmissions were attributable to acute cerebrovascular disease. Readmitted patients were older and had a higher comorbidity burden. After controlling for age, sex, insurance status, and comorbidities, patients who underwent recanalization therapy had significantly lower odds of 30-day readmission (odds ratio, 0.82; 95% confidence interval, 0.77–0.89).

Conclusions—

Up to 12% of patients with ischemic stroke get readmitted within 30 days post-discharge period, and recanalization therapy is associated with 11% to 23% lower odds of 30-day readmission.

Risk assessment of comorbidities on 30-day avoidable hospital readmissions among internal medicine patients

RATIONALE, AIMS AND OBJECTIVES

Reducing the rate of hospital readmissions, particularly avoidable ones, has significant implications on patient outcomes, cost containment, and quality of care. Given that the reason of readmission may differ from the patient's main diagnosis in the index admission, this study aims to assess the influence of index comorbidities on the primary readmission diagnoses and explore the risk of deemed avoidable readmission because of prior comorbidities.

METHODS

A retrospective review of 3962 discharges was conducted at a 527-bed teaching hospital in Jordan, utilizing data related to 2025 internal medicine patients.

RESULTS

Among all discharges, 29% were followed by a 30-day readmission, of which 13% were identified as potentially avoidable. Of all readmissions, 36% of patients were readmitted because of one of the comorbidities that had been identified at index admission. In addition, 47% of the potentially avoidable readmissions had a main diagnosis that was one of the index comorbidities. The results also showed an association between readmission for one of the index stay's comorbidities and being avoidable, with an adjusted odds ratio of 2.12 (95% confidence interval, 1.65-2.72). Overall, the presence of certain diseases, being identified as one of the preceding comorbidities, was found to have a substantial influence on the risk of potentially avoidable readmission. These diseases included digestive, circulatory, respiratory, genitourinary systems, and infectious and parasitic diseases (adjusted relative risks = 1.57, 1.49, 1.36, 1.30, and 2.30, respectively).

CONCLUSION

To help reduce the rates of readmission, potential gains seem available if hospitals adopt clinical practices that support the patient's care during the post-discharge transition. This implies that health care providers need to pay more attention to the comorbidities of high-risk patients to be closely monitored after discharge.

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.

Framing new pathways in transformative exercise for individuals with existing and newly acquired disability

PURPOSE

This paper describes a continuum of customized exercise options for people with an existing and newly acquired disability or diagnosis referred to as the Transformative Exercise Framework.

BACKGROUND

The period directly after rehabilitation is a critical juncture where many individuals return to life with high rates of sedentary behavior. After rehabilitation discharge, people with newly acquired disability or diagnoses often never make the transition into usage of community-based exercise services that are tailored, safe and effective.

METHODS

Narrative review.

RESULTS

The Transformative Exercise Framework supports a patient-to-participant, rehab-to-wellness model that emphasizes a linkage between physical and occupational therapists and community-based exercise trainers. The four focus areas - Rehabilitation, Condition-specific Exercise, Fitness and Lifetime Physical Activity - emphasize a range of options for people with newly acquired disability and diagnoses, or for people with existing disability and/or chronic health conditions who have a new injury, secondary condition or are severely deconditioned.

CONCLUSION

The concept of transformative exercise is to support people with disabilities and diagnoses with a seamless restore-improve-prevent continuum of programs and services. This continuum connects individuals to rehabilitation and exercise professionals in a dynamic framework, which maximizes the expertise of both sets of professionals and provides the most effective interventions to achieve the greatest gains in health and function and/or to avoid future health decline. Implications for Rehabilitation Patients discharged from rehabilitation should be transformed into participants in lifelong physical activity through a continuum of health services, which we refer to as Transformative Exercise. Transformative exercise is a continuum of individually tailored exercise strategies/programs that aims to improve the function of underperforming systems, which inhibit community and/or lifelong physical activity participation. The Transformative Exercise Framework can be used by a therapist or exercise trainer to design a program that maximizes performance and time and is based on a specific process for identifying short and long term goals.

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.

Assessing the Public's Health

Metrics are an important part of the assessment of public health. They include traditional measures of mortality and newly described summary measures to describe the disability engendered by diseases. Epidemiology has transformed the understanding of risk factors for disease; however, a holistic approach includes recognition of social determinants and the neighborhood and communities where the people most at risk reside.

Validity of a stroke severity index for administrative claims data research: a retrospective cohort study

Background

Ascertaining stroke severity in claims data-based studies is difficult because clinical information is unavailable. We assessed the predictive validity of a claims-based stroke severity index (SSI) and determined whether it improves case-mix adjustment.

Methods

We analyzed patients with acute ischemic stroke (AIS) from hospital-based stroke registries linked with a nationwide claims database. We estimated the SSI according to patient claims data. Actual stroke severity measured with the National Institutes of Health Stroke Scale (NIHSS) and functional outcomes measured with the modified Rankin Scale (mRS) were retrieved from stroke registries. Predictive validity was tested by correlating SSI with mRS. Logistic regression models were used to predict mortality.

Results

The SSI correlated with mRS at 3 months (Spearman rho = 0.578; 95 % confidence interval [CI], 0.556–0.600), 6 months (rho = 0.551; 95 % CI, 0.528–0.574), and 1 year (rho = 0.532; 95 % CI 0.504–0.560). Mortality models with the SSI demonstrated superior discrimination to those without. The AUCs of models including the SSI and models with the NIHSS did not differ significantly.

Conclusions

The SSI correlated with functional outcomes after AIS and improved the case-mix adjustment of mortality models. It can act as a valid proxy for stroke severity in claims data-based studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12913-016-1769-8) contains supplementary material, which is available to authorized users.

Ethnic Comparison of 30-Day Potentially Preventable Readmissions After Stroke in Hawaii

BACKGROUND AND PURPOSE

Ethnic disparities in readmission after stroke have been inadequately studied. We sought to compare potentially preventable readmissions (PPR) among a multiethnic population in Hawaii.

METHODS

Hospitalization data in Hawaii from 2007 to 2012 were assessed to compare ethnic differences in 30-day PPR after stroke-related hospitalizations. Multivariable models using logistic regression were performed to assess the impact of ethnicity on 30-day PPR after controlling for age group (<65 and ≥65 years), sex, insurance, county of residence, substance use, history of mental illness, and Charlson Comorbidity Index.

RESULTS

Thirty-day PPR was seen in 840 (8.4%) of 10 050 any stroke-related hospitalizations, 712 (8.7%) of 8161 ischemic stroke hospitalizations, and 128 (6.8%) of 1889 hemorrhagic stroke hospitalizations. In the multivariable models, only the Chinese ethnicity, compared with whites, was associated with 30-day PPR after any stroke hospitalizations (odds ratio [OR] [95% confidence interval {CI}], 1.40 [1.05-1.88]) and ischemic stroke hospitalizations (OR, 1.42 [CI, 1.04-1.96]). When considering only one hospitalization per individual, the impact of Chinese ethnicity on PPR after any stroke hospitalization (OR, 1.22 [CI, 0.89-1.68]) and ischemic stroke hospitalization (OR, 1.21 [CI, 0.86-1.71]) was attenuated. Other factors associated with 30-day PPR after any stroke hospitalizations were Charlson Comorbidity Index (per unit increase) (OR, 1.21 [CI, 1.18-1.24]), Medicaid (OR, 1.42 [CI, 1.07-1.88]), Hawaii county (OR, 0.78 [CI, 0.62-0.97]), and mental illness (OR, 1.37 [CI, 1.10-1.70]).

CONCLUSIONS

In Hawaii, Chinese may have a higher risk of 30-day PPR after stroke compared with whites. However, this seems to be driven by the high number of repeated PPR within the Chinese ethnic group.

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.

Hospital Readmissions of Stroke Patients with Percutaneous Endoscopic Gastrostomy Feeding Tubes

OBJECTIVES

A critical mission of acute care hospitals is to reduce hospital readmissions to improve patient care and avoid monetary penalties. We speculated that stroke patients with enteral tube feeding are high-risk patients and sought to evaluate their hospital readmissions.

METHODS

We analyzed archival hospital billing data from stroke patients discharged from acute care hospitals in Florida in 2012 for 30- and 60-day readmission rates, 30-day readmission rates by discharge destination, most frequent primary readmission diagnoses, and predictors of 30-day readmissions. We conducted univariate and multivariable logistic regression analyses.

RESULTS

We analyzed 26,774 discharge records. Within 30 days after discharge, 21.06% (N = 299) of stroke patients with percutaneous endoscopic gastrostomy (PEG) tube placement were rehospitalized. Of those readmissions, 11.71% (N = 35) were preventable. Among stroke patients with a PEG tube placement, 53.80% were discharged to skilled nursing facilities and 27.88% were rehospitalized within 30 days. Septicemia was the most frequent primary readmission diagnosis. Comorbidities, stroke type, length of hospital stay, and discharge destinations were predictive for 30-day readmissions (area under the receiver operating characteristic curve was .81).

CONCLUSIONS

Stroke patients with a PEG tube placement during their index hospital stay are twice as likely to be readmitted within 30 days compared to stroke patients without PEG tube placements. The primary readmission diagnosis for some patients was directly linked to PEG tube complications. We have identified risk factors that can be used to focus resources for readmission prevention.

A population-based study for 30-d hospital readmissions after acute ischemic stroke

OBJECTIVE

To determine post-stroke 30-d readmission rate, its predictors, its impact on mortality and to identify potentially preventable causes of post-stroke 30-d readmission in a population-based study.

PATIENTS AND METHODS

We identified all acute ischemic strokes (AIS) using the International Classification of Diseases 9th revision codes (433.x1, 434.xx and 436) via the Rochester Epidemiology Project (REP) between January 2007 and December 2011. Acute stroke care in Olmsted County is provided by two medical centers, Saint Marys Hospital and Olmsted Medical Center Hospital. All readmissions to these two hospitals were accounted for this study. Thirty-day readmission data was abstracted through manual chart review. The REP linkage database was used to identify the status (living/dead) of all patients at last follow up.

RESULTS

Forty-one (7.6%, 95% CI 5.7%-10.2%) of total 537 AIS patients were readmitted 30-d post-stroke. In a multivariable logistic regression model, discharge to nursing home following index stroke (OR: 0.29, 95% CI 0.08-0.84) was an independent negative predictor of unplanned 30-d readmission. In a subgroup of patients with dementia, being married at time of index stroke was found to be a negative predictor of readmission (OR: 0.10, 95% CI 0.005-0.58). Only 2.8% of the patients had potentially preventable readmissions. Hospital readmission had no significant impact on patient's short-term (three months) or long-term (one or two years) mortality (p > 0.05).

CONCLUSION

Post-stroke 30-d readmission rate is low in AIS patients from Olmsted County. Further research is needed in regarding discharge checklists, protocols and stroke transitional programs to reduce potentially preventable readmissions.

Reducing Readmissions After Stroke With a Structured Nurse Practitioner/Registered Nurse Transitional Stroke Program

Background and Purpose—

Our aim was to determine whether a standardized Transitional Stroke Clinic (TSC) led by nurse practitioners could reduce 30-day and 90-day readmissions for stroke or transient ischemic attack patients discharged home.

Methods—

Phase I consisted of nurse practitioners calling only high-risk patients discharged home within 7 days and performing an office visit within 2 to 4 weeks of discharge. Phase II consisted of all patients discharged home receiving both a 2-day follow-up phone call by a registered nurse and a follow-up visit with a nurse practitioner within 7 to 14 days. Differences in process metrics and readmissions across the 2 phases and overall were assessed. Increasing complexity with multiple chronic conditions (diabetes mellitus, coronary artery disease, and congestive heart failure) was represented in a continuous variable from 0 to 3. Multivariable logistic regression models for 30-day and 90-day readmissions were performed with adjustment for National Institutes of Health Stroke Scale (NIHSS) and previous hospitalizations.

Results—

From October 2012 through September 2015, 510 patients were enrolled. From phase I to II, a higher proportion of follow-up calls were made and days from discharge to TSC decreased. Patients readmitted within 30 days were less likely to show for TSC visits (60.85% versus 76.3%; P =0.021). Multivariable modeling showed that TSC visit was associated with a 48% reduction in 30-day readmission (odds ratio, 0.518; 95% confidence interval, 0.272–0.986), whereas multiple chronic conditions and previous stroke/transient ischemic attack increased the risk. TSC visit did not impact 90-day readmissions.

Conclusions—

Evaluation in a nurse practitioner–led structured clinic is a model that may reduce readmissions at 30 days for stroke patients discharged home.

Care pathways and healthcare use of stroke survivors six months after admission to an acute-care hospital in France in 2012

INTRODUCTION

Care pathways and healthcare management are not well described for patients hospitalized for stroke.

METHODS

Among the 51 million beneficiaries of the French national health insurance general scheme (77% of the French population), patients hospitalized for a first stroke in 2012 and still alive six months after discharge were included using data from the national health insurance information system (Sniiram). Patient characteristics were described by discharge destination-home or rehabilitation center (for < 3 months)-and were followed during their first three months back home.

RESULTS

A total of 61,055 patients had a first admission to a public or private hospital for stroke (mean age; 72 years, 52% female), 13% died during their stay and 37% were admitted to a stroke management unit. Overall, 40,981 patients were still alive at six months: 33% of them were admitted to a rehabilitation center (mean age: 73 years) and 54% were discharged directly to their home (mean age 67 years). For each group, 45 and 62% had been previously admitted to a stroke unit. Patients discharged to rehabilitation centers had more often comorbidities, 39% were highly physically dependent and 44% were managed in specialized neurology centers. For patients with a cerebral infarction who were directly discharged to their home 76% received at least one antihypertensive drug, 96% an antithrombotic drug and 76% a lipid-lowering drug during the following month. For those with a cerebral hemorrhage, these frequencies were respectively 46, 33 and 28%. For those admitted to a rehabilitation center, more than half had at least one visit with a physiotherapist or a nurse, 15% a speech therapist, 10% a neurologist or a cardiologist and 15% a psychiatrist during the following three months back home (average numbers of visits for those with at least one visit: 23 for physiotherapists and 100 for nurses). Patients who returned directly back home had fewer physiotherapist (30%) or nurse (47%) visits but more medical consultations. The 3-month re-hospitalization rate for patients who were discharged directly to their home was 23% for those who had been admitted to a stroke unit and 25% for the others. In rehabilitation centers, this rate was 10% for patients who stayed < 3 months.

CONCLUSIONS

These results illustrate the value of administrative databases to study stroke management, care pathways and ambulatory care. These data should be used to improve care pathways, organization, discharge planning and treatments.

Short- and longer-term health-care resource utilization and costs associated with acute ischemic stroke

Objectives

The mean lifetime cost of ischemic stroke is approximately $140,048 in the United States, placing stroke among the top 10 most costly conditions among Medicare beneficiaries. The objective of this study was to describe the health-care resource utilization and costs in the year following hospitalization for acute ischemic stroke (AIS).

Methods

This retrospective claims analysis quantifies utilization and costs following inpatient admission for AIS among the commercially insured and Medicare beneficiaries in the Truven Health databases. Patients who were 18 years or older and continuously enrolled for 12 months before and after an AIS event occurring (index) between January 2009 and December 2012 were identified. Patients with AIS in the year preindex were excluded. Demographic and clinical characteristics were evaluated at admission and in the preindex, respectively. Direct costs, readmissions, and inpatient length of stay (LOS) were described in the year postindex.

Results

The eligible populations comprised 20,314 commercially insured patients and 31,037 Medicare beneficiaries. Average all-cause costs were $61,354 and $44,929 (commercial and Medicare, respectively) in the first year after the AIS. Approximately 50%–55% of total 12-month costs were incurred between day 31 and day 365 following the incident AIS. One quarter (24.6%) of commercially insured patients and 38.8% of Medicare beneficiaries were readmitted within 30 days with 16.6% and 71.7% (commercial and Medicare, respectively) of those having a principal diagnosis of AIS. The average AIS-related readmission length of stay was nearly three times that of the initial hospitalization for both commercially insured patients (3.8 vs 10.8 days) and Medicare beneficiaries (4.0 vs 10.8 days).

Conclusion

In addition to the substantial costs of the initial hospitalization of an AIS, these costs double within the year following this event. Given the high cost associated with AIS, new interventions reducing either the acute or longer-term burden of AIS are needed.

A feasibility pilot using a mobile personal health assistant (PHA) app to assist stroke patient and caregiver communication after hospital discharge

BACKGROUND

Recent advancements have lowered national acute stroke mortality, yet posthospital care and readmission rates remain challenges. A personal health assistant (PHA) may help manage the spectrum of posthospital care. We hypothesized that a PHA application (app) would be associated with high poststroke patient care satisfaction and might prevent hospital readmission.

METHODS

This is a case series of acute stroke patients admitted to a single, tertiary care, comprehensive stroke center (Mayo Clinic, Jacksonville, Florida) who were offered a personal health assistance through a smart phone app. Patients were screened based on having a cerebrovascular event and the ability to use a necessary device. All patients received the standard poststroke discharge protocol, the PHA app, and the 30-day Likert scale survey.

RESULTS

We screened 21 patients and enrolled 3 (14%) before premature financial closure. Two of the 3 patients rated the app highly, and the third patient had not started using it. Of the ineligible patients, 4 had no device, 3 declined enrollment, and 2 were not able to use the device. One of the 2 patients who used the PHA app was readmitted for new stroke symptoms.

CONCLUSIONS

Both patients who used the app were very satisfied with the PHA and their posthospital care coordination. This study had an enrollment rate of about 14% due to various factors, including limited access or utilization of necessary technology. Though limited by final patient sample size and early termination from funding, this study provides useful information about developing future mobile health apps for acute stroke patients.

Association of Rehabilitation Intensity for Stroke and Risk of Hospital Readmission

BACKGROUND

Little is known about the use of rehabilitation in the acute care setting and its impact on hospital readmissions.

OBJECTIVE

The objective of this study was to examine the association between the intensity of rehabilitation services received during the acute care stay for stroke and the risk of 30-day and 90-day hospital readmission.

DESIGN

A retrospective cohort analysis of all acute care hospitals in Arkansas and Florida was conducted.

METHODS

Patients (N=64,065) who were admitted for an incident stroke in 2009 or 2010 were included. Rehabilitation intensity was categorized as none, low, medium-low, medium-high, or high based on the sum and distribution of physical therapy, occupational therapy, and speech therapy charges within each hospital. Cox proportional hazards regression was used to estimate hazard ratios, controlling for demographic characteristics, illness severity, comorbidities, hospital variables, and state.

RESULTS

Relative to participants who received the lowest intensity therapy, those who received higher-intensity therapy had a decreased risk of 30-day readmission. The risk was lowest for the highest-intensity group (hazard ratio=0.86; 95% confidence interval=0.79, 0.93). Individuals who received no therapy were at an increased risk of hospital readmission relative to those who received low-intensity therapy (hazard ratio=1.30; 95% confidence interval=1.22, 1.40). The findings were similar, but with smaller effects, for 90-day readmission. Furthermore, patients who received higher-intensity therapy had more comorbidities and greater illness severity relative to those who received lower-intensity therapy.

LIMITATIONS

The results of the study are limited in scope and generalizability. Also, the study may not have adequately accounted for all potentially important covariates.

CONCLUSIONS

Receipt of and intensity of rehabilitation therapy in the acute care of stroke is associated with a decreased risk of hospital readmission.