Michael S. Phipps

Predictors of Hospital Readmission After Stroke: A Systematic Review

Background and Purpose— Risk-standardized hospital readmission rates are used as publicly reported measures reflecting quality of care. Valid risk-standardized models adjust for differences in patient-level factors across hospitals. We conducted a systematic review of peer-reviewed literature to identify models that compare hospital-level poststroke readmission rates, evaluate patient-level risk scores predicting readmission, or describe patient and process-of-care predictors of readmission after stroke. Methods— Relevant studies in English published from January 1989 to July 2010 were identified using MEDLINE, PubMed, Scopus, PsycINFO, and all Ovid Evidence-Based Medicine Reviews. Authors of eligible publications reported readmission within 1 year after stroke hospitalization and identified ≥1 predictors of readmission in risk-adjusted statistical models. Publications were excluded if they lacked primary data or quantitative outcomes, reported only composite outcomes, or had <100 patients. Results— Of 374 identified publications, 16 met the inclusion criteria for this review. No model was specifically designed to compare risk-adjusted readmission rates at the hospital level or calculate scores predicting a patients risk of readmission. The studies providing multivariable models of patient-level and/or process-of-care factors associated with readmission varied in stroke definitions, data sources, outcomes (all-cause and/or stroke-related readmission), durations of follow-up, and model covariates. Few characteristics were consistently associated with readmission. Conclusions— This review identified no risk-standardized models for comparing hospital readmission performance or predicting readmission risk after stroke. Patient-level and system-level factors associated with readmission were inconsistent across studies. The current literature provides little guidance for the development of risk-standardized models suitable for the public reporting of hospital-level stroke readmission performance.

Estimating and Reporting on the Quality of Inpatient Stroke Care by Veterans Health Administration Medical Centers

Background— Reporting of quality indicators (QIs) in Veterans Health Administration Medical Centers is complicated by estimation error caused by small numbers of eligible patients per facility. We applied multilevel modeling and empirical Bayes (EB) estimation in addressing this issue in performance reporting of stroke care quality in the Medical Centers. Methods and Results— We studied a retrospective cohort of 3812 veterans admitted to 106 Medical Centers with ischemic stroke during fiscal year 2007. The median number of study patients per facility was 34 (range, 12–105). Inpatient stroke care quality was measured with 13 evidence-based QIs. Eligible patients could either pass or fail each indicator. Multilevel modeling of a patients pass/fail on individual QIs was used to produce facility-level EB-estimated QI pass rates and confidence intervals. The EB estimation reduced interfacility variation in QI rates. Small facilities and those with exceptionally high or low rates were most affected. We recommended 8 of the 13 QIs for performance reporting: dysphagia screening, National Institutes of Health Stroke Scale documentation, early ambulation, fall risk assessment, pressure ulcer risk assessment, Functional Independence Measure documentation, lipid management, and deep vein thrombosis prophylaxis. These QIs displayed sufficient variation across facilities, had room for improvement, and identified sites with performance that was significantly above or below the population average. The remaining 5 QIs were not recommended because of too few eligible patients or high pass rates with little variation. Conclusions— Considerations of statistical uncertainty should inform the choice of QIs and their application to performance reporting.

Do-not-resuscitate orders, quality of care, and outcomes in veterans with acute ischemic stroke.

Objective: There is concern that do-not-resuscitate (DNR) orders may lead to stroke patients receiving less aggressive treatment and poorer care. Our objectives were to assess the relationship between DNR orders and quality of stroke care among veterans. Methods: A cohort of 3,965 acute ischemic stroke patients admitted to 131 Veterans Health Administration (VHA) facilities in fiscal year 2007 underwent chart abstraction. DNR codes were identified through electronic orders or by documentation of “no code,” “no cardiopulmonary resuscitation,” or “no resuscitation.” Quality of care was measured using 14 inpatient ischemic stroke quality indicators. The association between DNR orders and quality indicators was examined using multivariable logistic regression. Results: Among 3,965 ischemic stroke patients, 535 (13.5%) had DNR code status, 71% of whom had orders first documented within 1 day of admission. Overall, 4.9% of patients died in-hospital or were discharged to hospice; these outcomes were substantially higher in patients with DNR orders (29.7%), particularly if they were not documented until ≥2 days after admission (47.1%). Patients with DNR orders were significantly older, had more comorbidities, and had greater stroke severity. Following adjustment there were few significant associations between DNR status and the 14 quality indicators, with the exception of lower odds of early ambulation (odds ratio = 0.58, 95% confidence interval = 0.41–0.81) in DNR patients. Conclusions: DNR orders were associated with limited differences in the select quality indicators investigated, which suggests that DNR orders did not impact quality of care. However, whether DNR orders influence treatment decisions that more directly affect survival remains to be determined.

Epidemiology and Outcomes of Fever Burden Among Patients With Acute Ischemic Stroke

Background and Purpose— Although fever following ischemic stroke is common and has been associated with poor patient outcomes, little is known about which aspects of fever (eg, frequency, severity, or duration) are most associated with outcomes. Methods— We used data from a retrospective cohort of acute ischemic stroke patients who were admitted to 1 of 5 hospitals (1998–2003). A fever event was defined as a period with a temperature ≥100.0°F (37.8°C). Fever burden was defined as the maximum temperature (Tmax) minus 100.0°F, multiplied by the number of days with a fever. Fever burden (in degree-days) was categorized as low (0.1–2.0), medium (2.1–4.0), or high (≥4.0). Logistic regression was used to evaluate the adjusted association of any fever episode and fever burden with the combined outcome of in-hospital mortality or discharge to hospice. Results— Among 1361 stroke patients, 483 patients (35.5%) had ≥1 fever event. Among febrile patients, the median Tmax was 100.9°F (range, 100.0–106.6°F), 87% had ⩽2 events and median total fever days was 2. Patients with any fever event had higher combined outcome rates after adjusting for demographics, stroke severity, and clinical characteristics: adjusted odds ratio (aOR), 2.7 (95% CI, 1.6–4.4). Higher fever burden was also associated with the combined outcome: high burden aOR, 6.7 (95% CI, 3.6–12.7); medium burden aOR, 3.9 (95% CI, 1.9–8.2); and low burden aOR, 1.2 (95%CI, 0.6–2.3) versus no fever. Conclusions— This study confirms that poststroke fever occurs commonly and demonstrates that patients with high fever burden have a 6-fold increased odds of death or discharge to hospice.

Cocaine Use and Risk of Ischemic Stroke in Young Adults

Background and Purpose— Although case reports have long identified a temporal association between cocaine use and ischemic stroke (IS), few epidemiological studies have examined the association of cocaine use with IS in young adults, by timing, route, and frequency of use. Methods— A population-based case–control study design with 1090 cases and 1154 controls was used to investigate the relationship of cocaine use and young-onset IS. Stroke cases were between the ages of 15 and 49 years. Logistic regression analysis was used to evaluate the association between cocaine use and IS with and without adjustment for potential confounders. Results— Ever use of cocaine was not associated with stroke with 28% of cases and 26% of controls reporting ever use. In contrast, acute cocaine use in the previous 24 hours was strongly associated with increased risk of stroke (age–sex–race adjusted odds ratio, 6.4; 95% confidence interval, 2.2–18.6). Among acute users, the smoking route had an adjusted odds ratio of 7.9 (95% confidence interval, 1.8–35.0), whereas the inhalation route had an adjusted odds ratio of 3.5 (95% confidence interval, 0.7–16.9). After additional adjustment for current alcohol, smoking use, and hypertension, the odds ratio for acute cocaine use by any route was 5.7 (95% confidence interval, 1.7–19.7). Of the 26 patients with cocaine use within 24 hours of their stroke, 14 reported use within 6 hours of their event. Conclusions— Our data are consistent with a causal association between acute cocaine use and risk of early-onset IS.

Quality improvement in neurology: Multiple sclerosis quality measures: Executive summary.

All clinicians believe they provide quality care, yet most clinicians do not directly measure quality parameters in their practice to provide verifiable health care outcomes.1 Quality measures related to a chronic disease provide reportable and repeatable measures that can either document performance of quality care or identify gaps in care for future action/improvement. Disease-specific quality measures in neurology provide a framework that can assist clinicians in practice measurement and modification; these have the potential to benefit both subspecialist and generalist alike. Multiple sclerosis (MS) is a common, chronic, and ultimately disabling disease with multiple potential clinical intervention points during its course. It is therefore appropriate to have quality measures specific for this condition that span the course of the disease.

Expanding the Safety Net of Specialty Care for the Uninsured: A Case Study

OBJECTIVE To describe core principles and processes in the implementation of a navigated care program to improve specialty care access for the uninsured. STUDY SETTING Academic researchers, safety-net providers, and specialty physicians, partnered with hospitals and advocates for the underserved to establish Project Access-New Haven (PA-NH). PA-NH expands access to specialty care for the uninsured and coordinates care through patient navigation. STUDY DESIGN Case study to describe elements of implementation that may be relevant for other communities seeking to improve access for vulnerable populations. PRINCIPAL FINDINGS Implementation relied on the application of core principles from community-based participatory research (CBPR). Effective partnerships were achieved by involving all stakeholders and by addressing barriers in each phase of development, including (1) assessment of the problem; (2) development of goals; (3) engagement of key stakeholders; (4) establishment of the research agenda; and (5) dissemination of research findings. CONCLUSIONS Including safety-net providers, specialty physicians, hospitals, and community stakeholders in all steps of development allowed us to respond to potential barriers and implement a navigated care model for the uninsured. This process, whereby we integrated principles from CBPR, may be relevant for future capacity-building efforts to accommodate the specialty care needs of other vulnerable populations.

Rostral midbrain infarction producing isolated lateropulsion.

A distinct syndrome characterized by lateropulsion arises from lacunar infarctions of the paramedian tegmentum of the rostral midbrain. Only a few reports are available, and in little more than a handful was the infarct documented with modern imaging techniques. We describe two cases and review the pertinent literature. ### Case reports. #### Patient 1. Over the course of 2 months, a 76-year-old man had several small vessel infarctions in various vascular territories. He had been anticoagulated with warfarin for chronic atrial fibrillation but his International Normalized Ratio was subtherapeutic during his first two hospitalizations for these events. He recovered without neurologic deficit and was discharged after warfarin adjustment and initiation of acetylsalicylic acid. He returned to the hospital 2 weeks later complaining of imbalance. On admission, his blood pressure was 161/74 mm Hg and his heartbeat was irregular at a rate of 78/minute. He was afebrile. Signs of meningeal irritation were absent. He was alert and oriented with fluent language. There were no abnormalities of conjugate gaze or pupil function, cyclotropia or head tilt. Gait and stance were wide based. There was lateropulsion to the left, both sitting and standing. MRI findings are shown in the figure. Duplex ultrasonography of neck vessels and echocardiography were unrevealing. After reversal of anticoagulation, a lumbar puncture was performed (protein 128 mg/dL, glucose 40 mg/dL …

Does Inpatient Quality of Care Differ by Age Among US Veterans with Ischemic Stroke

BACKGROUND Some studies have found that older individuals are not as likely as their younger counterparts to be treated with some guideline-based stroke therapies. We examined whether age-related differences in inpatient quality of care exist among US veterans with ischemic stroke. METHODS This was a retrospective study of a national sample of veterans admitted to 129 Veterans Affairs medical centers for ischemic stroke during fiscal year 2007. Inpatient stroke care quality was examined across 14 inpatient processes of care, including dysphagia screening, National Institutes of Health Stroke Scale (NIHSS) score documentation, thrombolysis, deep venous thrombosis prophylaxis, antithrombotic therapy by hospital day 2 and at discharge, early ambulation, fall risk assessment, pressure ulcer risk assessment, rehabilitation needs assessment, atrial fibrillation management, lipid management, smoking cessation counseling, and stroke education. RESULTS Among the 3939 veterans with ischemic stroke, the mean age was 67.8 years (standard deviation, 11.5). The overall performance rate was >70% for 10 of the 14 quality indicators. In unadjusted analyses, older patients were less likely to receive lipid management, smoking cessation, NIHSS documentation, and early ambulation compared with younger patients; conversely, older patients were more likely to receive dysphagia screening and stroke education. After adjusting for demographic, clinical, and hospital level characteristics, the age-related differences in processes of care were less consistent; however, the youngest patients were more likely to receive smoking cessation counseling and the oldest patients were less likely to receive lipid management. CONCLUSIONS Risk-adjusted inpatient stroke care quality varies little with age for veterans admitted to a Veterans Affairs medical center for acute ischemic stroke.

Does the Inclusion of Stroke Severity in a 30-Day Mortality Model Change Standardized Mortality Rates at Veterans Affairs Hospitals?

Background— The Centers for Medicare and Medicaid Services is considering developing a 30-day ischemic stroke hospital-level mortality model using administrative data. We examined whether inclusion of the National Institutes of Health Stroke Scale (NIHSS), a measure of stroke severity not included in administrative data, would alter 30-day mortality rates in the Veterans Health Administration. Methods and Results— A total of 2562 veterans admitted with ischemic stroke to 64 Veterans Health Administration Hospitals in the fiscal year 2007 were included. First, we examined the distribution of unadjusted mortality rates across the Veterans Health Administration. Second, we estimated 30-day all-cause, risk standardized mortality rates (RSMRs) for each hospital by adjusting for age, sex, and comorbid conditions using hierarchical models with and without the inclusion of the NIHSS. Finally, we examined whether adjustment for the NIHSS significantly changed RSMRs for each hospital compared with other hospitals. The median unadjusted mortality rate was 3.6%. The RSMR interquartile range without the NIHSS ranged from 5.1% to 5.6%. Adjustment with the NIHSS did not change the RSMR interquartile range (5.1%–5.6%). Among veterans ≥65 years, the RSMR interquartile range without the NIHSS ranged from 9.2% to 10.3%. With adjustment for the NIHSS, the RSMR interquartile range changed from 9.4% to 10.0%. The plot of 30-day RSMRs estimated with and without the inclusion of the NIHSS in the model demonstrated overlapping 95% confidence intervals across all hospitals, with no hospital significantly below or above the mean-unadjusted 30-day mortality rate. The 30-day mortality measure did not discriminate well among hospitals. Conclusions— The impact of the NIHSS on RSMRs was limited. The small number of stroke admissions and the narrow range of 30-day stroke mortality rates at the facility level in the Veterans Health Administration cast doubt on the value of using 30-day RSMRs as a means of identifying outlier hospitals based on their stroke care quality.