Risk adjustment of ischemic stroke outcomes for comparing hospital performance: a statement for healthcare professionals from the American Heart Association/American Stroke Association

Automated Extraction of Stroke Severity from Unstructured Electronic Health Records using Natural Language Processing

BACKGROUND

Multi-center electronic health records (EHR) can support quality improvement initiatives and comparative effectiveness research in stroke care. However, limitations of EHR-based research include challenges in abstracting key clinical variables from non-structured data at scale. This is further compounded by missing data. Here we develop a natural language processing (NLP) model that automatically reads EHR notes to determine the NIH stroke scale (NIHSS) score of patients with acute stroke.

METHODS

The study included notes from acute stroke patients (>= 18 years) admitted to the Massachusetts General Hospital (MGH) (2015-2022). The MGH data were divided into training (70%) and hold-out test (30%) sets. A two-stage model was developed to predict the admission NIHSS. A linear model with the least absolute shrinkage and selection operator (LASSO) was trained within the training set. For notes in the test set where the NIHSS was documented, the scores were extracted using regular expressions (stage 1), for notes where NIHSS was not documented, LASSO was used for prediction (stage 2). The reference standard for NIHSS was obtained from Get With The Guidelines Stroke Registry. The two-stage model was tested on the hold-out test set and validated in the MIMIC-III dataset (Medical Information Mart for Intensive Care-MIMIC III 2001-2012) v1.4, using root mean squared error (RMSE) and Spearman correlation (SC).

RESULTS

We included 4,163 patients (MGH = 3,876; MIMIC = 287); average age of 69 [SD 15] years; 53% male, and 72% white. 90% patients had ischemic stroke and 10% hemorrhagic stroke. The two-stage model achieved a RMSE [95% CI] of 3.13 [2.86-3.41] (SC = 0.90 [0.88-0. 91]) in the MGH hold-out test set and 2.01 [1.58-2.38] (SC = 0.96 [0.94-0.97]) in the MIMIC validation set.

CONCLUSIONS

The automatic NLP-based model can enable large-scale stroke severity phenotyping from EHR and therefore support real-world quality improvement and comparative effectiveness studies in stroke.

Validation of the Passive Surveillance Stroke Severity Score in Three Canadian Provinces

BACKGROUND

Stroke outcomes research requires risk-adjustment for stroke severity, but this measure is often unavailable. The Passive Surveillance Stroke SeVerity (PaSSV) score is an administrative data-based stroke severity measure that was developed in Ontario, Canada. We assessed the geographical and temporal external validity of PaSSV in British Columbia (BC), Nova Scotia (NS) and Ontario, Canada.

METHODS

We used linked administrative data in each province to identify adult patients with ischemic stroke or intracerebral hemorrhage between 2014-2019 and calculated their PaSSV score. We used Cox proportional hazards models to evaluate the association between the PaSSV score and the hazard of death over 30 days and the cause-specific hazard of admission to long-term care over 365 days. We assessed the models' discriminative values using Uno's c-statistic, comparing models with versus without PaSSV.

RESULTS

We included 86,142 patients (n = 18,387 in BC, n = 65,082 in Ontario, n = 2,673 in NS). The mean and median PaSSV were similar across provinces. A higher PaSSV score, representing lower stroke severity, was associated with a lower hazard of death (hazard ratio and 95% confidence intervals 0.70 [0.68, 0.71] in BC, 0.69 [0.68, 0.69] in Ontario, 0.72 [0.68, 0.75] in NS) and admission to long-term care (0.77 [0.76, 0.79] in BC, 0.84 [0.83, 0.85] in Ontario, 0.86 [0.79, 0.93] in NS). Including PaSSV in the multivariable models increased the c-statistics compared to models without this variable.

CONCLUSION

PaSSV has geographical and temporal validity, making it useful for risk-adjustment in stroke outcomes research, including in multi-jurisdiction analyses.

How to Use Costs in Value-Based Healthcare: Learning from Real-life Examples

BACKGROUND

Healthcare organizations measure costs for business operations but do not routinely incorporate costs in decision-making on the value of care.

AIM

Provide guidance on how to use costs in value-based healthcare (VBHC) delivery at different levels of the healthcare system.

SETTING AND PARTICIPANTS

Integrated practice units (IPUs) for diabetes mellitus (DM) and for acute myocardial infarction (AMI) at the Leiden University Medical Center and a collaboration of seven breast cancer IPUs of the Santeon group, all in the Netherlands.

PROGRAM DESCRIPTION AND EVALUATION

VBHC aims to optimize care delivery to the patient by understanding how costs relate to outcomes. At the level of shared decision-making between patient and clinician, yearly check-up consultations for DM type I were analyzed for patient-relevant costs. In benchmarking among providers, quantities of cost drivers for breast cancer care were assessed in scorecards. In continuous learning, cost-effectiveness analysis was compared with radar chart analysis to assess the value of telemonitoring in outpatient follow-up.

DISCUSSION

Costs vary among providers in healthcare, but also between provider and patient. The joint analysis of outcomes and costs using appropriate methods helps identify and optimize the aspects of care that drive desired outcomes and value.

Trends in Stroke Thrombolysis Care Metrics and Outcomes by Race and Ethnicity, 2003-2021

Importance

Understanding is needed of racial and ethnic-specific trends in care quality and outcomes associated with the US nationwide quality initiative Target: Stroke (TS) in targeting thrombolysis treatment for acute ischemic stroke.

Objective

To examine whether the TS quality initiative was associated with improvement in thrombolysis metrics and outcomes across racial and ethnic groups.

Design, Setting, and Participants

This retrospective cohort study included patients who presented within 4.5 hours of ischemic stroke onset at hospitals participating in the Get With The Guidelines-Stroke initiative from January 1, 2003, to December 31, 2021. The data analysis was performed between December 15, 2022, and November 27, 2023.

Exposures

TS phases I (2010-2013), II (2014-2018), and III (2019-2021).

Main Outcomes and Measures

The primary outcomes were thrombolysis rates and time metrics. Patient function and mortality were secondary outcomes.

Results

Analyses included 1 189 234 patients, of whom 1 053 539 arrived to the hospital within 4.5 hours. The cohort included 50.4% female and 49.6% male patients and 2.8% Asian [median (IQR) age, 72 (61-82) years], 15.2% Black [median (IQR) age, 64 (54-75) years], 7.3% Hispanic [median (IQR) age, 68 (56-79) years], and 74.1% White [median (IQR) age, 75 (63-84) years] patients). Unadjusted thrombolysis rates increased in both the pre-TS (2003-2009) and TS periods in all racial and ethnic groups from 10% to 15% in 2003 to 43% to 46% in 2021, but disparities were observed in adjusted analyses and persisted in TS phase III, with Asian, Black, and Hispanic patients having significantly lower odds of receiving thrombolysis than White patients (adjusted odds ratio, 0.85 [95% CI, 0.81-0.90], 0.76 [95% CI, 0.74-0.78], and 0.86 [95% CI, 0.83-0.89], respectively). Door-to-needle (DTN) times improved in all racial and ethnic groups during TS, with DTN times of 60 minutes or less increasing from 26% to 28% in 2009 to 66% to 72% in 2021. However, in adjusted analyses, racial and ethnic disparities emerged. During TS phase III, compared with White patients, Asian, Black, and Hispanic patients had significantly lower odds of receiving thrombolysis with a DTN time of 60 minutes or less compared with White patients (risk-adjusted odds ratios, 0.91 [95% CI, 0.84-0.98], 0.78 [95% CI, 0.75-0.81], and 0.87 [95% CI, 0.83-0.92], respectively). During TS, clinical outcomes improved for all racial and ethnic groups from pre-TS, with TS phase III showing higher odds of ambulation at discharge among Asian, Black, Hispanic, and White patients. Asian, Black, and Hispanic patients were less likely to present within 4.5 hours.

Conclusions and Relevance

In this cohort study of patients with ischemic stroke, the TS quality initiative was associated with improvement in thrombolysis frequency, timeliness, and outcomes for all racial and ethnic groups. However, disparities persisted, indicating a need for further interventions.

Change in Hospital Risk-standardized Stroke Mortality Performance With and Without the Passive Surveillance Stroke Severity Score

BACKGROUND

Adjustment for baseline stroke severity is necessary for accurate assessment of hospital performance. We evaluated whether adjusting for the Passive Surveillance Stroke SeVerity (PaSSV) score, a measure of stroke severity derived using administrative data, changed hospital-specific estimated 30-day risk-standardized mortality rate (RSMR) after stroke.

METHODS

We used linked administrative data to identify adults who were hospitalized with ischemic stroke or intracerebral hemorrhage across 157 hospitals in Ontario, Canada between 2014 and 2019. We fitted a random effects logistic regression model using Markov Chain Monte Carlo methods to estimate hospital-specific 30-day RSMR and 95% credible intervals with adjustment for age, sex, Charlson comorbidity index, and stroke type. In a separate model, we additionally adjusted for stroke severity using PaSSV. Hospitals were defined as low-performing, average-performing, or high-performing depending on whether the RSMR and 95% credible interval were above, overlapping, or below the cohort's crude mortality rate.

RESULTS

We identified 65,082 patients [48.0% were female, the median age (25th,75th percentiles) was 76 years (65,84), and 86.4% had an ischemic stroke]. The crude 30-day all-cause mortality rate was 14.1%. The inclusion of PaSSV in the model reclassified 18.5% (n=29) of the hospitals. Of the 143 hospitals initially classified as average-performing, after adjustment for PaSSV, 20 were reclassified as high-performing and 8 were reclassified as low-performing. Of the 4 hospitals initially classified as low-performing, 1 was reclassified as high-performing. All 10 hospitals initially classified as high-performing remained unchanged.

CONCLUSION

PaSSV may be useful for risk-adjusting mortality when comparing hospital performance. External validation of our findings in other jurisdictions is needed.

Development and validation of a model predicting mild stroke severity on admission using electronic health record data

OBJECTIVE

Initial stroke severity is a potent modifier of stroke outcomes but this information is difficult to obtain from electronic health record (EHR) data. This limits the ability to risk-adjust for evaluations of stroke care and outcomes at a population level. The purpose of this analysis was to develop and validate a predictive model of initial stroke severity using EHR data elements.

METHODS

This observational cohort included individuals admitted to a US Department of Veterans Affairs hospital with an ischemic stroke. We extracted 65 independent predictors from the EHR. The primary analysis modeled mild (NIHSS score 0-3) versus moderate/severe stroke (NIHSS score ≥4) using multiple logistic regression. Model validation included: (1) splitting the cohort into derivation (65%) and validation (35%) samples and (2) evaluating how the predicted stroke severity performed in regard to 30-day mortality risk stratification.

RESULTS

The sample comprised 15,346 individuals with ischemic stroke (n = 10,000 derivation; n = 5,346 validation). The final model included 15 variables and correctly classified 70.4% derivation sample patients and 69.4% validation sample patients. The areas under the curve (AUC) were 0.76 (derivation) and 0.76 (validation). In the validation sample, the model performed similarly to the observed NIHSS in terms of the association with 30-day mortality (AUC: 0.72 observed NIHSS, 0.70 predicted NIHSS).

CONCLUSIONS

EHR data can be used to construct a surrogate measure of initial stroke severity. Further research is needed to better differentiate moderate and severe strokes, enhance stroke severity classification, and how to incorporate these measures in evaluations of stroke care and outcomes.

Comparison of Hospital Performance in Acute Ischemic Stroke Based on Mortality and Functional Outcome in South Korea

BACKGROUND

Recent evidence suggests a correlation between modified Rankin Scale-based measures, an outcome measure commonly used in acute stroke trials, and mortality-based measures used by health agencies in the evaluation of hospital performance. We aimed to examine whether the 2 types of measures are interchangeable in relation to evaluation of hospital performance in acute ischemic stroke.

METHODS

Five outcome measures, unfavorable functional outcome (3-month modified Rankin Scale score ≥2), death or dependency (3-month modified Rankin Scale score ≥3), 1-month mortality, 3-month mortality, and 1-year mortality, were collected for 8292 individuals who were hospitalized for acute ischemic stroke between January 2014 and May 2015 in 14 hospitals participating in the Clinical Research Collaboration for Stroke in Korea - National Institute of Health registry. Hierarchical regression models were used to calculate per-hospital risk-adjusted outcome rates for each measure. Hospitals were ranked and grouped based on the risk-adjusted outcome rates, and the correlations between the modified Rankin Scale-based and mortality-based ranking and their intermeasure reliability in categorizing hospital performance were analyzed.

RESULTS

The comparison between the ranking based on the unfavorable functional outcome and that based on 1-year mortality resulted in a Spearman correlation coefficient of -0.29 and Kendall rank coefficient of -0.23, and the comparison of grouping based on these 2 types of ranks resulted in a weighted kappa of 0.123 for the grouping in the top 33%/middle 33%/bottom 33% and 0.25 for the grouping in the top 20%/middle 60%/bottom 20%, respectively. No significant correlation or similarity in grouping capacities were found between the rankings based on the functional outcome measures and those based on the mortality measures.

CONCLUSIONS

This study shows that regardless of clinical correlation at an individual patient level, functional outcome-based measures and mortality-based measures are not interchangeable in the evaluation of hospital performance in acute ischemic stroke.

Predictors of Short-Term Mortality in Patients with Ischemic Stroke

Background and Objectives: The purpose of this study is to investigate the predictive factors for intrahospital mortality in ischemic stroke patients. We will examine the association between a range of clinical and demographic factors and intrahospital mortality, including age, sex, comorbidities, laboratory values, and medication use. Materials and Methods: This retrospective, longitudinal, analytic, observational cohort study included 243 patients over 18 years old with a new ischemic stroke diagnosis who were hospitalized in Cluj-Napoca Emergency County Hospital. Data collected included the patient demographics, baseline characteristics at hospital admission, medication use, carotid artery Doppler ultrasound, as well as cardiology exam, and intrahospital death. Results: Multivariate logistic regression was used to determine which variables were independently associated with intrahospital death. An NIHSS score > 9 (OR-17.4; p < 0.001) and a lesion volume > 22.3 mL (OR-5.8; p = 0.003) were found to be associated with the highest risk of death. In contrast antiplatelet treatment (OR-0.349; p = 0.04) was associated with lower mortality rates. Conclusions: Our study identified a high NIHSS score and large lesion volume as independent risk factors for intrahospital mortality in ischemic stroke patients. Antiplatelet therapy was associated with lower mortality rates. Further studies are needed to explore the potential mechanisms underlying these associations and to develop targeted interventions to improve patient outcomes.

Relationships among hospital acute ischemic stroke volumes, hospital characteristics, and outcomes in the US

BACKGROUND AND OBJECTIVES

Prior research on volume-based patient outcomes related to acute ischemic stroke (AIS) have demonstrated contradictory results and fail to reflect recent advances in stroke care. We sought to examine contemporary relationships between hospital AIS volumes and outcomes.

METHODS

We used complete Medicare datasets in a retrospective cohort study using validated International Classification of Diseases Tenth Revision codes to identify patients admitted with AIS from January 1, 2016 through December 31, 2019. AIS volume was calculated as the total number of AIS admissions per hospital during the study period. We examined several hospital characteristics by AIS volume quartile. We performed adjusted logistic regressions testing associations of AIS volume quartiles with: inpatient mortality, receipt of tissue plasminogen activator (tPA) and endovascular therapy (ET), discharge home, and 30-day outpatient visit. We adjusted for sex, age, Charlson comorbidity score, teaching hospital status, MDI, hospital urban-rural designation, stroke certification status and ICU and neurologist availability at the hospital.

RESULTS

There were 952400 AIS admissions among 5084 US hospitals; AIS 4-year volume quartiles were: 1^st: 1-8 AIS admissions; 2^nd: 9-44; 3^rd: 45-237; 4^th: 238+. Highest quartile hospitals more often were stroke-certified (49.1% vs 8.7% in lowest quartile, p<0.0001), with ICU bed availability (19.8% vs 4.1%, p<0.0001) and with neurologist expertise (91.1% vs 3%, p<0.0001). In the highest AIS quartile (compared to the lowest quartile), there was lower inpatient mortality (odds ratio [OR] 0.71 [95%CI 0.57-0.87, p<0.0001]), lower 30-day mortality (0.55 [0.49-0.62], p<0.0001), greater receipt of tPA (6.60 [3.19-13.65], p<0.0001) and ET (16.43 [10.64-25.37], p<0.0001, and greater likelihood of discharge home (1.38 [1.22-1.56], p<0.0001). However, when the highest quartile hospitals were examined separately, higher volumes were associated with higher mortality despite higher rates of tPA and ET receipt.

CONCLUSIONS

High AIS-volume hospitals have greater utilization of acute stroke interventions, stroke certification and availability of neurologist and ICU care. These features likely play a role in the better outcomes observed at such centers, including inpatient and 30-day mortality and discharge home. However, the highest volume centers had higher mortality despite greater receipt of interventions. Further research is needed to better understand volume-outcome relationships in AIS to improve care at lower volume centers.

Is the Activity Measure for Postacute Care "6-Clicks" Tool Associated With Discharge Destination Postacute Stroke?

Objective

To investigate the association of poststroke physical function, measured within 24 hours prior to discharge from the acute care hospital using Activity Measure for Postacute Care (AM-PAC) Inpatient "6-Clicks" scores and discharge destination (home vs facility and inpatient rehabilitation facility [IRF] vs skilled nursing facility [SNF]).

Design

Retrospective cross-sectional cohort study.

Setting

Acute care, University Hospital.

Participants

Individuals post acute ischemic stroke, N=721, 51.3% male, mean age 63.6±16.4 years.

Interventions

Not applicable.

Main Outcome Measures

AM-PAC "6-Clicks" 3 domains: basic mobility, daily activity, and applied cognition.

Results

AM-PAC basic mobility and daily activity were significant predictors of discharge. Those in the home discharge group had AM-PAC basic mobility mean t scale score of 48.5 compared with a score of 34.8 for individuals sent to a facility and daily activity score of 47.2 compared with 32.7 for individuals sent to a facility. The AM-PAC variables accounted for an additional 24% of the variance in the discharge destination, with basic mobility and daily activity accounting for most of the variance.The AM-PAC scores were not statistically different and were not able to discriminate between placement in an IRF vs SNF. The mean basic mobility t scale score for individuals going to an IRF was 34.9 compared with 34.6 for those going to an SNF. The daily activity score for IRF was 32.8 compared with 32.6 for SNF. The AM-PAC accounted for no additional variance in discharge destination to an IRF or SNF.

Conclusions

The AM-PAC Inpatient "6-Clicks" 3 domains are able to distinguish individuals with stroke being discharged to home from postacute care (PAC) but not for differentiating between PAC facilities (IRF vs SNF) in this cohort of individuals post stroke.

Multicentric validation of a reduced features case-mix set for predicting functional outcome after ischemic stroke in Belgium

INTRODUCTION

Ischemic stroke is the second cause of death and leading cause of severe disability worldwide. A reduced features set of CT-DRAGON (age, NIHSS on admission and pre-stroke mRS) predicts 90-day functional outcome after stroke in a single center. The current study was designed to validate this adapted CT-DRAGON score in three major Belgian hospitals, in the framework of future case-mix adjustment.

METHODS

This retrospective study included stroke patients, treated by thrombolysis, thrombectomy, a combination of both or neither thrombolysis or thrombectomy (conservative treatment) in 2019. Patient characteristics and 90-day mRS were collected. Multivariable logistic regression analysis of 90-day mRS 0-2 vs. 3-6 and 0-5 vs. 6 with the reduced features set was performed. Discriminative performance was assessed by the area under the receiver operating characteristic curve (AUROC).

RESULTS

Thirty-three percent of patients (413/1243) underwent treatment. Majority of strokes was treated conservatively (n = 830, 67%), 18% (n = 225) was treated by thrombolysis, 7% (n = 88) by thrombectomy and 8% (n = 100) by thrombolysis and thrombectomy. Age, NIHSS and pre-stroke mRS were independently associated with 90-day mRS 0-2 (all p ≤ 0.0001, AUROC 0.88). When treatment modality was added in the model, age, NIHSS, pre-stroke mRS and treatment modality were independently associated with 90-day mRS 0-2 (p < 0.0001, p < 0.0001, p < 0.0001 and p = 0.0001) AUROC 0.89). Age, NIHSS, pre-stroke mRS and treatment modality were independently associated with 90-day survival (p = 0.0001, p < 0.0001, p < 0.0001 and p = 0.008, AUROC 0.86).

DISCUSSION

The reduced features set (age, NIHSS and pre-mRS) was independently associated with long-term functional outcome in a Belgian multicentric cohort, making it useful for case-mix adjustments in Belgian stroke centers. Treatment modality was associated with long-term outcome.

Disparities in Hospital Length of Stay Across Race and Ethnicity Among Patients With Heart Failure

BACKGROUND

Reducing hospital length of stay (LOS) has been identified as an important lever for minimizing the burden of heart failure hospitalization, yet the impact of social and structural determinants of health on LOS has received little attention. We investigated disparities in LOS across race/ethnicity and their possible drivers.

METHODS

We analyzed patients hospitalized for heart failure from 2017 to 2020 using the Get With The Guidelines-Heart Failure registry. We characterized LOS differences across race/ethnicity by insurance and disposition, adjusting for demographics, comorbidities, and clinical severity. Effects of hospital-level clustering on LOS across race/ethnicity were assessed using hierarchical mixed-effects models. We evaluated the association between LOS and discharge rates of guideline-directed medical therapy.

RESULTS

Three thousand three seven hundred thirty patients hospitalized for heart failure were identified. After excluding inpatient deaths, the adjusted LOS for Black (5.72 days [95% CI, 5.62-5.82]), Hispanic (5.94 days [95% CI, 5.79-6.08]), and Indigenous American/Pacific Islander (6.06 days [95% CI, 5.85-6.27]) patients remained significantly longer compared with non-Hispanic White patients (5.32 days [95% CI, 5.25-5.39]). This pattern was driven by LOS differences among patients discharged to hospice or nursing facilities. After accounting for variability between hospitals, associations of race/ethnicity with LOS either were attenuated or reversed in direction. Guideline-directed medical therapy rates on discharge did not differ significantly across race/ethnicity despite longer LOS for Black, Hispanic, and Indigenous American/Pacific Islander patients.

CONCLUSIONS

Differences between hospitals drive LOS disparities across race/ethnicity. Longer LOS among Black, Hispanic, and Indigenous American/Pacific Islander patients was not associated with improved quality of care.

Medicare Claim-Based National Institutes of Health Stroke Scale to Predict 30-Day Mortality and Hospital Readmission

BACKGROUND

The Centers for Medicare and Medicaid Services (CMS) penalizes hospitals for higher than expected 30-day mortality rates using methods without accounting for condition severity risk adjustment. For patients with stroke, CMS claims did not quantify stroke severity until recently, when the National Institutes of Health Stroke Scale (NIHSS) reporting began.

OBJECTIVE

Examine the predictive ability of claim-based NIHSS to predict 30-day mortality and 30-day hospital readmission in patients with ischemic stroke.

DESIGN

Retrospective cohort study of Medicare claims data.

PATIENTS

Medicare beneficiaries with ischemic stroke (N=43,241) acute hospitalization between October 2016 and November 2017.

MEASUREMENTS

All-cause 30-day mortality and 30-day hospital readmission. NIHSS score was derived from ICD-10 codes and stratified into the following: minor to moderate, moderate, moderate to severe, and severe categories.

RESULTS

Among 43,241 patients with ischemic stroke with NIHSS from 2,659 US hospitals, 64.6% had minor to moderate stroke, 14.3% had moderate, 12.7% had moderate to severe, and 8.5% had a severe stroke,10.1% died within 30 days, 12.1% were readmitted within 30 days. The NIHSS exhibited stronger discriminant property (C-statistic 0.83, 95% CI: 0.82-0.84) for 30-day mortality compared to Elixhauser (0.74, 95% CI: 0.73-0.75). A monotonic increase in the adjusted 30-day mortality risk occurred relative to minor to moderate stroke category: hazard ratio [HR]=2.92 (95% CI=2.59-3.29) for moderate stroke, HR=5.49 (95% CI=4.90-6.15) for moderate to severe stroke, and HR=7.82 (95% CI=6.95-8.80) for severe stroke. After accounting for competing risk of mortality, there was a significantly higher readmission risk in the moderate stroke (HR=1.11, 95% CI=1.03-1.20), but significantly lower readmission risk in the severe stroke (HR=0.84, 95% CI=0.74-0.95) categories.

LIMITATION

Timing of NIHSS reporting during hospitalization is unknown.

CONCLUSIONS

Medicare claim-based NIHSS is significantly associated with 30-day mortality in Medicare patients with ischemic stroke and significantly improves discriminant property relative to the Elixhauser comorbidity index.

Measuring Stroke Quality: Methodological Considerations in Selecting, Defining, and Analyzing Quality Measures

Knowledge about stroke and its management is growing rapidly and stroke systems of care must adapt to deliver evidence-based care. Quality improvement initiatives are essential for translating knowledge from clinical trials and recommendations in guidelines into routine clinical practice. This review focuses on issues central to the measurement of the quality of stroke care, including selection and definition of quality measures, identification of the eligible patient cohorts, optimization of data quality, and considerations for data analysis and interpretation.

Moving the Brazilian Ischemic Stroke Pathway to a Value-Based Care: Introduction of a Risk-Adjusted Cost Estimate Model for Stroke Treatment

The unsustainable increases in healthcare expenses and waste have motivated the migration of reimbursement strategies from volume to value. Value-based health care requires detailed comprehension of cost information at the patient level. This study introduces a clinical risk- and outcome-adjusted cost estimate model for stroke care sustained on time-driven activity-based costing (TDABC). In a cohort and multicenter study, a TDABC tool was developed to evaluate the costs per stroke patient, allowing us to identify and describe differences in cost by clinical risk at hospital arrival, treatment strategies, and modified Rankin Score (mRS) at discharge. The clinical risk was confirmed by multivariate analysis and considered patients' National Institute for Health Stroke Scale and age. Descriptive cost analyses were conducted, followed by univariate and multivariate models to evaluate the risk levels, therapies, and mRS stratification effect in costs. Then, the risk-adjusted cost estimate model for ischemic stroke treatment was introduced. All the hospitals collected routine prospective data from consecutive patients admitted with ischemic stroke diagnosis confirmed. A total of 822 patients were included. The median cost was I$2,210 (IQR: I$1,163-4,504). Fifty percent of the patients registered a favorable outcome mRS (0-2), costing less at all risk levels, while patients with the worst mRS (5-6) registered higher costs. Those undergoing mechanical thrombectomy had an incremental cost for all three risk levels, but this difference was lower for high-risk patients. Estimated costs were compared to observed costs per risk group, and there were no significant differences in most groups, validating the risk and outcome adjusted cost estimate model. By introducing a risk-adjusted cost estimate model, this study elucidates how healthcare delivery systems can generate local cost information to support value-based reimbursement strategies employing the data collection instruments and analysis developed in this study.

External validation of the Passive Surveillance Stroke Severity Indicator

BACKGROUND

The Passive Surveillance Stroke Severity (PaSSV) Indicator was derived to estimate stroke severity from variables in administrative datasets but has not been externally validated.

METHODS

We used linked administrative datasets to identify patients with first hospitalization for acute stroke between 2007-2018 in Alberta, Canada. We used the PaSSV indicator to estimate stroke severity. We used Cox proportional hazard models and evaluated the change in hazard ratios and model discrimination for 30-day and 1-year case fatality with and without PaSSV. Similar comparisons were made for 90-day home time thresholds using logistic regression. We also linked with a clinical registry to obtain National Institutes of Health Stroke Scale (NIHSS) and compared estimates from models without stroke severity, with PaSSV, and with NIHSS.

RESULTS

There were 28,672 patients with acute stroke in the full sample. In comparison to no stroke severity, addition of PaSSV to the 30-day case fatality models resulted in improvement in model discrimination (C-statistic 0.72 [95%CI 0.71-0.73] to 0.80 [0.79-0.80]). After adjustment for PaSSV, admission to a comprehensive stroke center was associated with lower 30-day case fatality (adjusted hazard ratio changed from 1.03 [0.96-1.10] to 0.72 [0.67-0.77]). In the registry sample (N = 1328), model discrimination for 30-day case fatality improved with the inclusion of stroke severity. Results were similar for 1-year case fatality and home time outcomes.

CONCLUSION

Addition of PaSSV improved model discrimination for case fatality and home time outcomes. The validity of PASSV in two Canadian provinces suggests that it is a useful tool for baseline risk adjustment in acute stroke.

Rationale for a Clinical Trial That Compares Acute Stroke Rehabilitation at Inpatient Rehabilitation Facilities to Skilled Nursing Facilities: Challenges and Opportunities

In the United States, approximately 400,000 patients with acute stroke are discharged annually to inpatient rehabilitation facilities (IRFs) or skilled nursing facilities (SNFs). Typically, IRFs provide time-intensive therapy for an average of 2-3 weeks, whereas SNFs provide more moderately intensive therapy for 4-5 weeks. The factors that influence discharge to an IRF or SNF are multifactorial and poorly understood. The complexity of these factors in combination with subjective clinical indications contributes to large variations in the use of IRFs and SNFs. This has significant financial implications for health care expenditure, given that stroke rehabilitation at IRFs costs approximately double that at SNFs. To control health care spending without compromising outcomes, the Institute of Medicine has stated that policy reforms that promote more efficient use of IRFs and SNFs are critically needed. A major barrier to the formulation of such policies is the highly variable and low-quality evidence for the comparative effectiveness of IRF- vs SNF-based stroke rehabilitation. The current evidence is limited by the inability of observational data to control for residual confounding, which contributes to substantial uncertainty around any magnitude of benefit for IRF- vs SNF-based care. Furthermore, it is unclear which specific patients would receive the most benefit from each setting. A randomized controlled trial addresses these issues, because random treatment allocation facilitates an equitable distribution of measured and unmeasured confounders. We discuss several measurement, practical, and ethical issues of a trial and provide our rationale for design suggestions that overcome some of these issues.

Specialized Outpatient Clinic vs Stroke Unit for TIA and Minor Stroke: A Cohort Study

OBJECTIVE

To evaluate the effects of an outpatient clinic setup for minor stroke/TIA using subsequent admission of patients at high risk of recurrent stroke.

METHODS

We performed a cohort study of all patients with suspected minor stroke/TIA seen in an outpatient clinic at Aarhus University Hospital, Denmark, between September 2013 and August 2014. Patients with stroke were compared to historic (same hospital) and contemporary (another comparable hospital) matched, hospitalized controls on nonprioritized outcomes: length of stay, readmissions, care quality (10 process-performance measures), and mortality. Patients with TIA were compared to contemporary matched, hospitalized controls. Following complete diagnostic workup, patients with stroke/TIA were classified into low/high risk of recurrent stroke ≤7 days.

RESULTS

We analyzed 1,076 consecutive patients, of whom 253 (23.5%) were subsequently admitted to the stroke ward. Stroke/TIA was diagnosed in 215/171 patients, respectively. Fifty-six percent (121/215) of the patients with stroke were subsequently admitted to the stroke ward. Comparison with the historic stroke cohort (n = 191) showed a shorter acute hospital stay for the strokes (median 1 vs 3 days; adjusted length of stay ratio 0.49; 95% confidence interval 0.33-0.71). Thirty-day readmission rate was 3.2% vs 11.6% (adjusted hazard ratio 0.23 [0.09-0.59]), and care quality was higher, with a risk ratio of 1.30 (1.15-1.47). The comparison of stroke and TIAs to contemporary controls showed similar results. Only one patient in the low risk category and not admitted experienced stroke within 7 days (0.6%).

CONCLUSIONS

An outpatient clinic setup for patients with minor stroke/TIA yields shorter acute hospital stay, lower readmission rates, and better quality than hospitalization in stroke units.

CLASSIFICATION OF EVIDENCE

This study provides Class III evidence that a neurovascular specialist-driven outpatient clinic for patients with minor stroke/TIA with the ability of subsequent admission is safe and yields shorter acute hospital stay, lower readmission rates, and better quality than hospitalization in stroke units.

Comparison between EQ-5D-5L and PROMIS-10 to evaluate health-related quality of life 3 months after stroke: a cross-sectional multicenter study

BACKGROUND

Although the use of patient-reported outcome measures to assess Health-Related Quality of Life (HRQoL) has been advocated, it is still open to debate which patient-reported outcome measure should be preferred to evaluate HRQoL after stroke.

AIM

To compare the measurement properties (including concurrent validity and discriminant ability) between the 5-dimensional 5-level EuroQol (EQ-5D-5L) and the Patient-Reported Outcomes Measurement Information System 10-Question Global Health Short Form (PROMIS-10) to evaluate HRQoL 3 months after stroke.

DESIGN

Cross-sectional study.

SETTING

Neurology outpatient clinics in 6 Dutch hospitals.

POPULATION

The participants 360 consecutive individuals with stroke. Their median age was 71 years, 143 (39.7%) were female and 335 (93.0%) had suffered an ischemic stroke.

METHODS

The EQ-5D-5L, PROMIS-10, modified Rankin Scale and two items on experienced decrease in health and activities post-stroke were administered by a stroke nurse or nurse practitioner through a telephone interview 3 months after stroke. The internal consistency, distribution, floor/ceiling effects, inter-correlations and discriminant ability (using the modified Rankin Scale and experienced decrease in health and in activities post-stroke as external anchors) were calculated for both the EQ-5D-5L and PROMIS-10.

RESULTS

Ninety-six percent of the participants were living at home and 50.9% experienced minimal or no disabilities (modified Rankin Scale 0-1) 3 months after stroke. A ceiling effect and a non-normal left skewed distribution were observed in the EQ-5D-5L. The PROMIS-10 showed higher internal consistency (α=0.90) compared to the EQ-5D-5L (α=0.75). Both the EQ-5D-5L and the PROMIS-10 were strongly correlated with the modified Rankin Scale (r=0.62 and 0.60 respectively). The PROMIS-10 showed better discriminant ability in less affected individuals with stroke, whereas the EQ-5D-5L showed slightly better discriminant ability in more affected individuals with stroke.

CONCLUSIONS

Both EQ-5D-5L and PROMIS-10 prove to be useful instruments to evaluate HRQoL in patients who are living at home 3 months after stroke.

CLINICAL REHABILITATION IMPACT

The clinical rehabilitation impact depended on the setting and underlying goal which patient-reported outcome measure is preferred to evaluate HRQoL 3 months after stroke. The PROMIS-10 should be preferred to detect differences in less affected stroke patients, whereas the EQ-5D-5L provides slightly more information in more affected stroke patients.

Identifying Performance Outliers for Stroke Care Based on Composite Score of Process Indicators: an Observational Study in China

BACKGROUND

Variability in the quality of stroke care is widespread. Identifying performance-based outlier hospitals based on quality indicators (QIs) has become a common practice.

OBJECTIVES

To develop a tool for identifying performance-based outlier hospitals based on risk-adjusted adherence rates of process indicators.

DESIGN

Hospitals were classified into five-level outliers based on the observed-to-expected ratio and P value. The composite quality score was derived by summation of the points for each indicator for each hospital, and associations between outlier status and outcomes were determined.

PARTICIPANTS

Patients diagnosed with acute ischemic stroke, January 1, 2011-May 31, 2017.

INTERVENTION

N/A MAIN OUTCOME MEASURES: Independence at discharge (the modified Rankin Scale = 0-2).

KEY RESULTS

A total of 501,132 patients from 519 hospitals were identified. From 0.39 to 19.65% of hospitals were identified as high outliers according to various QIs. Composite quality scores ranged from - 20 to 16. Providers that were high outliers based on QI2, QI8, QI9, and QI11 had higher independent rates. For composite quality score, each point increase corresponded to an 8% increase in the odds of independent rate.

CONCLUSION

Nationwide variation in the quality of acute stroke care exists at the hospital level. Variability in the quality of stroke care can be captured by our proposed quality score. Applying this quality score as a benchmarking tool could provide audit-level feedback to policymakers and hospitals to aid quality improvement.

Hospital Volume and Mortality in Acute Ischemic Stroke Patients: Effect of Adjustment for Stroke Severity

OBJECTIVE

Stroke severity of 1 hospital is a crucial information when assessing hospital performance. We aimed to determine the effect of stroke severity in the association between hospital patient volume and outcome after acute ischemic stroke.

METHODS

Data from National Acute Stroke Quality Assessment in 2013 and 2014 were analyzed. Hospital patient volume was defined as the annual number of acute ischemic stroke patients who admitted to each hospital. Comparisons among hospital patient volume quartiles before and after adjusting age, sex, onset to arrival and stroke severity were made to determine the associations between hospital patient volume and mortality at 30 days, 90 days and 1 year. Assessments for the nonlinear associations, with treating hospital patient volume as a continuous variable, and the associations between hospital patient volume and quality of care were also made.

RESULTS

A total of 14,666 acute ischemic stroke patients admitted to 202 hospitals were analyzed. In the crude analysis, patients admitted to hospitals with lower patient volume showed higher mortality with a non-linear inverse association with a cut-off value of 227 patients/year. While the associations remained significant after adjusting age, sex and onset to arrival time (P's < .05), they disappeared when stroke severity was further adjusted (P's > .05). In contrary, hospital patient volume showed a nonlinear positive association with a plateau for summary measures of quality indicators even after adjustments for covariates including stroke severity (P < .001).

CONCLUSIONS

Our study implicates that stroke severity should be considered when assessing hospital performance regarding outcomes of acute stroke care.

Assessing whether ad hoc clinician-generated patient questionnaires provide psychometrically valid information

Background

The provision of psychometrically valid patient reported outcomes (PROs) improves patient outcomes and reflects their quality of life. Consequently, ad hoc clinician-generated questionnaires of the past are being replaced by more rigorous instruments. This change, while beneficial, risks the loss/orphaning of decades-long information on difficult to capture/chronically ill populations. The goal of this study was to assess to the quality of data retrieved from these legacy questionnaires.

Methods

Participants included 8563 patients who generated a total of 12,626 hospital admissions over the 2004–2014 study period. Items used to screen for issues related to function, mood, symptoms, and social support among patients with chronic disease were identified in our medical center’s patient information questionnaire. Cluster and exploratory factor analyses (EFA) followed by multidimensional item response theory (MIRT) analyses were used to select items that defined factors. Scores were derived with summation and MIRT approaches; inter-factor relationships and relationships of factor scores to assigned diagnostic codes were assessed. Rasch analyses assessed the constructs’ measurement properties.

Results

Literature review and clinician interviews yielded four hypothesized constructs: psychological distress/wellbeing, symptom burden, social support, and physical function. Rasch analyses showed that, while all had good measurement properties, only one, function, separated individuals well. In exploratory factor analyses (EFA), 11 factors representing depression, respiratory symptoms, musculoskeletal pain, family support, mobility, activities of daily living, alcohol consumption, weight loss, fatigue, neurological disorders, and fear at home were identified. Based on the agreement between EFA and cluster analyses as well as Cronbach’s alpha, six domains were retained for analyses. Correlations were strong between activities of daily living and mobility (.84), and moderate between pain and mobility (.37) and psychological distress (.59) Known-group validity was supported from the relationships between factor scores and the relevant diagnostic code assignments (.12 to .20).

Conclusions and discussion

Items from ad hoc clinician-generated patient information questionnaires can be aggregated into valid factors that assess supportive care domains among chronically ill patients. However, the binary response options offered by many screening items limit their information content and consequently, as highlighted by Rasch analyses, their ability to meaningfully discriminate trait levels in these populations.

Non-Survivor Ischemic Stroke Patients Maintain High Serum Caspase-Cleaved Cytokeratin-18 Levels

OBJECTIVE

Caspase-cleaved cytokeratin (CCCK)-18 could appear in blood during apoptosis. In two different studies, on day 1 of cerebral infarction and at 72 hours of cerebral infarction, respectively, higher circulating CCCK-18 levels were found in non-surviving than in surviving patients. The objective of this study was to analyze the ability of these levels to predict mortality at any time during the first week of cerebral infarction.

METHODS

Patients with malignant middle cerebral artery infarction (MMCAI) were included and the diagnosis criteria were the presence, observed in a computed tomography, of an acute cerebral infarction in at least 50% of this territory and midline shift, and an acute neurological deterioration with a Glasgow Coma Scale ≤ 8. Serum CCCK-18 levels at days 1, 4 and 8 of MMCAI were determined.

RESULTS

Serum concentrations of CCCK-18 at days 1, 4 and 8 of MMCAI were higher in non-surviving (n = 34) than in surviving patients (n = 34). Serum CCCK-18 concentrations at days 1, 4 and 8 of MMCAI had an area under curve (95% CI) used to predict a 30-day mortality of 0.83 (0.72--0.91; p < 0.001), 0.78 (0.65-0.89; p < 0.001) and 0.82 (0.68-0.92; p < 0.001).

CONCLUSIONS

The novel finding is that serum levels of CCCK-18 levels at any time after the first week of MMCAI could help predict 30-day mortality.

Deriving a Passive Surveillance Stroke Severity Indicator From Routinely Collected Administrative Data: The PaSSV Indicator

BACKGROUND

Adjusting for stroke severity is crucial for stroke outcomes research. However, this information is not available in administrative healthcare data. We aimed to derive an indicator of baseline stroke severity using these data.

METHODS AND RESULTS

We identified patients with stroke enrolled in a population-based registry in Ontario, Canada, and used the Canadian Neurological Scale (CNS), documented in the registry, as a measure of stroke severity. We derived an estimated CNS from a linear regression model in which we regressed the observed CNS on predictor variables: age, sex, arrival by ambulance, interhospital transfer, mechanical ventilation, and an emergency department triage score. The effect of stroke severity on the estimated hazard ratios for 30-day mortality was determined in 3 Cox-proportional hazards models with (1) no CNS, (2) observed CNS, and (3) estimated CNS, all adjusted for age, sex, Charlson index, and stroke type. We assessed model discrimination using C statistics. To assess for construct validity, we repeated these analyses in a subset of patients with documented National Institute of Health Stroke Scale and in a cohort of patients with stroke external to the registry. We derived the estimated stroke severity in 41 481 patients (48.7% female, median age of 75 years [interquartile range, 64- 83]). The magnitude of the association between stroke severity and mortality was similar for the observed and estimated CNS. The discriminative ability of the Cox-proportional hazards models to predict mortality was highest when the observed CNS was included (C statistic, 0.82 [95% CI, 0.81-0.82]), moderate with estimated CNS (0.76 [0.75-0.76]), and lowest without CNS (0.69 [0.69-0.70]. Our findings were replicated with the National Institute of Health Stroke Scale and in the external cohort.

CONCLUSIONS

We derived an estimated measure of stroke severity using administrative data. This can be applied for risk adjustment in population-based stroke outcomes research and in assessments of health system performance.

Population Health Indicators Associated with a Statewide Telestroke Program

Background: Studies show that telestroke (TS) improves rural access to care and outcome for stroke patients receiving TS services, but population health impacts of TS are not known. We examine impacts associated with South Carolina's (SC) statewide TS network on an entire state population of patients suffering acute ischemic stroke (AIS) as TS became available across SC counties. Methods: A population health study using Donabedian's conceptual model and an ecological design to describe the change observed over time in use of thrombolysis and endovascular therapy (EVT) as the SC TeleStroke Network (SCTN) diffused across SC counties. Changes in county rates of stroke mortality and discharge destination are reported. The unit of interest is the population rate for AIS patients living in a SC county. Patients' county of residence at the time of hospitalization defined county cohorts. Relative risks were estimated using logistic regression adjusted for age >75 years. Results: Overall tissue plasminogen activator (tPA) rate was 6.28%, and EVT rate was 1.10%. Patients living where SCTN was available had a 25% higher likelihood of receiving tPA (adjusted relative risk [ARR] = 1.25, 95% confidence interval [CI] = 1.15-1.36) and lower risks of mortality (ARR = 0.91; 95% CI = 0.84-0.99) or discharge to skilled nursing (ARR = 0.93; 95% CI = 0.89-0.97). Conclusions: TS diffusion affects the structure of the health system serving a county, as well as the processes of care delivered in the emergency department; these changes are associated with measurable population health improvements. Results support a population benefit of TS implementation.

Hospital Volume Threshold Associated with Higher Survival after Endovascular Recanalization Therapy for Acute Ischemic Stroke

BACKGROUND AND PURPOSE

Endovascular recanalization therapy (ERT) is becoming increasingly important in the management of acute ischemic stroke (AIS). However, the hospital volume threshold for optimal ERT remains unknown. We investigated the relationship between hospital volume of ERT and risk-adjusted patient outcomes.

METHODS

From the National Health Insurance claims data in Korea, 11,745 patients with AIS who underwent ERT from July 2011 to June 2016 in 111 hospitals were selected. We measured the hospital's ERT volume and patient outcomes, including the 30-day mortality, readmission, and postprocedural intracranial hemorrhage (ICH) rates. For each outcome measure, we constructed risk-adjusted prediction models incorporating demographic variables, the modified Charlson comorbidity index, and the stroke severity index (SSI), and validated them. Risk-adjusted outcomes of AIS cases were compared across hospital quartiles to confirm the volume-outcome relationship (VOR) in ERT. Spline regression was performed to determine the volume threshold.

RESULTS

The mean AIS volume was 14.8 cases per hospital/year and the unadjusted means of mortality, readmission, and ICH rates were 11.6%, 4.6%, and 8.6%, respectively. The VOR was observed in the risk-adjusted 30-day mortality rate across all quartile groups, and in the ICH rate between the first and fourth quartiles (P<0.05). The volume threshold was 24 cases per year.

CONCLUSIONS

There was an association between hospital volume and outcomes, and the volume threshold in ERT was identified. Policies should be developed to ensure the implementation of the AIS volume threshold for hospitals performing ERT.

Assessing stroke severity using electronic health record data: a machine learning approach

Background

Stroke severity is an important predictor of patient outcomes and is commonly measured with the National Institutes of Health Stroke Scale (NIHSS) scores. Because these scores are often recorded as free text in physician reports, structured real-world evidence databases seldom include the severity. The aim of this study was to use machine learning models to impute NIHSS scores for all patients with newly diagnosed stroke from multi-institution electronic health record (EHR) data.

Methods

NIHSS scores available in the Optum© de-identified Integrated Claims-Clinical dataset were extracted from physician notes by applying natural language processing (NLP) methods. The cohort analyzed in the study consists of the 7149 patients with an inpatient or emergency room diagnosis of ischemic stroke, hemorrhagic stroke, or transient ischemic attack and a corresponding NLP-extracted NIHSS score. A subset of these patients (n = 1033, 14%) were held out for independent validation of model performance and the remaining patients (n = 6116, 86%) were used for training the model. Several machine learning models were evaluated, and parameters optimized using cross-validation on the training set. The model with optimal performance, a random forest model, was ultimately evaluated on the holdout set.

Results

Leveraging machine learning we identified the main factors in electronic health record data for assessing stroke severity, including death within the same month as stroke occurrence, length of hospital stay following stroke occurrence, aphagia/dysphagia diagnosis, hemiplegia diagnosis, and whether a patient was discharged to home or self-care. Comparing the imputed NIHSS scores to the NLP-extracted NIHSS scores on the holdout data set yielded an R² (coefficient of determination) of 0.57, an R (Pearson correlation coefficient) of 0.76, and a root-mean-squared error of 4.5.

Conclusions

Machine learning models built on EHR data can be used to determine proxies for stroke severity. This enables severity to be incorporated in studies of stroke patient outcomes using administrative and EHR databases.

Value-based healthcare in ischemic stroke care: case-mix adjustment models for clinical and patient-reported outcomes

Background

Patient-Reported Outcome Measures (PROMs) have been proposed for benchmarking health care quality across hospitals, which requires extensive case-mix adjustment. The current study’s aim was to develop and compare case-mix models for mortality, a functional outcome, and a patient-reported outcome measure (PROM) in ischemic stroke care.

Methods

Data from ischemic stroke patients, admitted to four stroke centers in the Netherlands between 2014 and 2016 with available outcome information (N = 1022), was analyzed. Case-mix adjustment models were developed for mortality, modified Rankin Scale (mRS) scores and EQ-5D index scores with respectively binary logistic, proportional odds and linear regression models with stepwise backward selection. Predictive ability of these models was determined with R-squared (R²) and area-under-the-receiver-operating-characteristic-curve (AUC) statistics.

Results

Age, NIHSS score on admission, and heart failure were the only common predictors across all three case-mix adjustment models. Specific predictors for the EQ-5D index score were sex (β = 0.041), socio-economic status (β = − 0.019) and nationality (β = − 0.074). R²-values for the regression models for mortality (5 predictors), mRS score (9 predictors) and EQ-5D utility score (12 predictors), were respectively R² = 0.44, R² = 0.42 and R² = 0.37.

Conclusions

The set of case-mix adjustment variables for the EQ-5D at three months differed considerably from the set for clinical outcomes in stroke care. The case-mix adjustment variables that were specific to this PROM were sex, socio-economic status and nationality. These variables should be considered in future attempts to risk-adjust for PROMs during benchmarking of hospitals.

Developing an adapted Charlson comorbidity index for ischemic stroke outcome studies

Background

The Charlson comorbidity index (CCI) is commonly used to adjust for patient casemix. We reevaluated the CCI in an ischemic stroke (IS) cohort to determine whether the original seventeen comorbidities and their weights are relevant.

Methods

We identified an IS cohort (N = 6988) from the Ontario Stroke Registry (OSR) who were discharged from acute hospitals (N = 100) between April 1, 2012 and March 31, 2013. We used hospital discharge ICD-10-CA data to identify Charlson comorbidities. We developed a multivariable Cox model to predict one-year mortality retaining statistically significant (P < 0.05) comorbidities with hazard ratios ≥1.2. Hazard ratios were used to generate revised weights (1–6) for the comorbid conditions. The performance of the IS adapted Charlson comorbidity index (ISCCI) mortality model was compared to the original CCI using the c-statistic and continuous Net Reclassification Index (cNRI).

Results

Ten of the 17 Charlson comorbid conditions were retained in the ISCCI model and 7 had reassigned weights when compared to the original CCI model . The ISCCI model showed a small but significant increase in the c-statistic compared to the CCI for 30-day mortality (c-statistic 0.746 vs. 0.732, p = 0.009), but no significant increase in c-statistic for in-hospital or one-year mortality. There was also no improvement in the cNRI when the ISCCI model was compared to the CCI.

Conclusions

The ISCCI model had similar performance to the original CCI model. The key advantage of the ISCCI model is it includes seven fewer comorbidities and therefore easier to implement in situations where coded data is unavailable.

Impact of Missing Stroke Severity Data on the Accuracy of Hospital Ischemic Stroke Mortality Profiling

BACKGROUND

The Centers for Medicare and Medicaid Services have proposed 30-day ischemic stroke risk-standardized mortality rates that include adjustment for stroke severity using the National Institute of Health Stroke Scale (NIHSS), which is often undocumented. We used simulations to quantify the effect of missing NIHSS data on the accuracy of hospital-level ischemic stroke risk-standardized mortality rate profiling for 100 hypothetical hospitals with different case volumes.

METHODS AND RESULTS

We generated simulated data sets of patients with NIHSS scores and other predictors of 30-day mortality based on empirical analysis of data from 7654 patients with ischemic stroke in the Michigan Stroke Registry. We assigned and rank-ordered a true (known) 30-day mortality rate to each hospital in the simulated data sets of N=100 hospitals with either low (100 patients with stroke), medium (300), or high (500) case volumes. We then estimated and rank-ordered 30-day risk-standardized mortality rates for the N=100 hospitals in each simulated data set using hierarchical logistic regression models. In each data set, we systematically varied the rate of missing NIHSS data and whether missing NIHSS data was independent (missing completely at random) or dependent (missing not at random) on the NIHSS score. With no missing NIHSS data, the Spearman correlation between the true hospital performance rank order assigned during data set generation and the estimated 30-day risk-standardized mortality rate rank order was 0.72, 0.88, and 0.91 in low, medium, and high volume hospitals, respectively. However, this fell to as low as 0.50, 0.71, and 0.79 as missing NIHSS data reached 70%.

CONCLUSIONS

Missing NIHSS data had substantial detrimental effects on the accuracy of profiling of ischemic stroke mortality, especially in lower volume hospitals. Even with complete NIHSS documentation, significant limitations in ischemic stroke mortality profiling remain.

DNA and RNA oxidative damage are associated to mortality in patients with cerebral infarction

OBJECTIVE

Secondary injury due to oxidation may occur during ischemic stroke, possibly leading to oxidative damage to deoxyribonucleic acid (DNA) and ribonucleic acid (RNA). Higher blood concentrations of 8-hydroxy-2'-deoxyguanosine (8-OHdG) (through the oxidation of guanosine from DNA) have been found in ischemic stroke patients than in healthy subjects, and in patients with versus without post-ischemic stroke depression. The present study was carried out to explore the possible association between serum DNA and RNA oxidative damage and mortality in patients with cerebral infarction.

METHODS

A prospective, multicenter observational study was carried out in the Intensive Care Units of 6 Spanish hospitals. We included patients with severe malignant middle cerebral artery infarction (MMCAI) defined as ischemic changes evidenced by computed tomography in more than 50% of the middle cerebral artery territory and a Glasgow Coma Score (GCS)<9. Serum concentrations of the three oxidized guanine species (OGS) (8-hydroxyguanine from DNA or RNA, 8-hydroxyguanosine from RNA, and 8-OHdG from DNA) on the day of MMCAI diagnosis were determined. The study endpoint was 30-day mortality.

RESULTS

We found higher serum OGS levels (p<0.001) in non-surviving (n=34) than in surviving patients (n=34). Logistic regression analyses showed serum OGS levels to be associated to 30-day mortality controlling for lactic acid, GCS and platelet count (OR=1.568; 95%CI=1.131-2.174; p=0.01).

CONCLUSIONS

The novel observation in this study is the association between global serum OGS concentration and mortality in ischemic stroke patients.

Disparities in outcomes associated with rural-urban insurance status in China among inpatient women with stroke: a registry-based cohort study

Background

Despite a few studies have demonstrated sex differences in stroke care and outcomes, limited research has explored insurance-related disparities in outcomes, particularly among women stroke patients. The aim was to determine whether rural-urban health insurance status affect the stroke treatment, process of care, and 1-year clinical outcomes for inpatient ischemic stroke in women.

Methods

Women patients with acute ischemic stroke (AIS) covered by New Rural Cooperative Medical Scheme (NRCMS) and urban resident/employee-based basic medical insurance scheme (URBMI/UEBMI) were abstracted from the China National Stroke Registry II (CNSR II). Shared frailty model in the Cox model or generalized estimating equation with consideration of the hospital's cluster effect were used to assess the associations between rural-urban insurance status and quality of care during hospitalization and 1-year stroke outcomes including all-cause death, 1-year recurrence, and 1-year disability.

Results

A total of 5,707 women patients enrolled from 219 hospitals in CNSR II were analyzed. Compared with 2,880 women patients covered by URBMI/UEBMI, 2,827 women patients covered by NRCMS were younger (65.7 versus 68.9 years), less likely to have vascular risk factors, awareness and treatment of hypertension and dyslipidemia prior to stroke. Women covered by NRCMS were more likely to receive early antithrombotics, discharge antithrombotics, lipid-lowering drugs, but less likely to receive antihypertensive medication than those covered by URBMI/UEBMI. One-year all-cause mortality and stroke recurrence were both significantly higher in women patients with NRCMS than those with URBMI/UEBMI [adjusted hazard ratio (95% confidence interval): 1.40 (1.06-1.84) and 1.38 (1.04-1.83), separately].

Conclusions

AIS women patients with rural-urban insurance status demonstrated remarkable differences in age, stroke risk factors, awareness and treatment, the process of care, and 1-year stroke recurrence and mortality. Healthcare policymakers need to focus their attention on these disparities and take proper steps to improve primary healthcare service in rural areas.

Predictors of poor outcome in embolic stroke of undetermined source

Objectives:

To identify the clinical predictors of death or disability at discharge.

Methods:

We retrospectively reviewed all ischemic stroke patients admitted to the stroke unit of King Abdulaziz Medical City, Riyadh, Saudi Arabia, from February 2016 - July 2018. We applied the Cryptogenic Stroke/ESUS International Working Group Embolic stroke of undetermined source (ESUS) criteria. We compared patients with poor outcomes (death or modified Rankin Scale [mRS] score >2) to those with favorable outcomes. Multivariate logistic regression was used to identify predictors of poor outcome. The regression model included age >60 years, gender, body mass index >25 kg/m², smoking history, comorbidities, previous ischemic/transient ischemic attack, pre-stroke mRS score >1, National Institutes of Health Stroke Scale (NIHSS) score at admission >5, pre-stroke antiplatelet use, and thrombolysis treatment.

Results:

Out of 147 patients who met the ESUS criteria, 28.8% had poor outcomes. Predictors of poor outcome were NIHSS score >5 (odds ratio [OR] 11.1, 95% confidence interval [CI] 4.4–28.2), pre-stroke mRS score >1 (OR 3.7, 95% CI 1.14–11.59), and age >60 years (OR 2.4, 95% CI 1.14–5.22).

Conclusion:

A significant proportion of ESUS patients were dead or disabled at discharge. Poor outcome was more in older patients with pre-stroke functional disability and moderate to severe stroke.

The impact of disease severity adjustment on hospital standardised mortality ratios: Results from a service-wide analysis of ischaemic stroke admissions using linked pre-hospital, admissions and mortality data

Background

Administrative data are used to examine variation in thirty-day mortality across health services in several jurisdictions. Hospital performance measurement may be error-prone as information about disease severity is not typically available in routinely collected data to incorporate into case-mix adjusted analyses. Using ischaemic stroke as a case study, we tested the extent to which accounting for disease severity impacts on hospital performance assessment.

Methods

We linked all recorded ischaemic stroke admissions between July, 2011 and June, 2014 to death registrations and a measure of stroke severity obtained at first point of patient contact with health services, across New South Wales, Australia’s largest health service jurisdiction. Thirty-day hospital standardised mortality ratios were adjusted for either comorbidities, as is typically done, or for both comorbidities and stroke severity. The impact of stroke severity adjustment on mortality ratios was determined using 95% and 99% control limits applied to funnel plots and by calculating the change in rank order of hospital risk adjusted mortality rates.

Results

The performance of the stroke severity adjusted model was superior to incorporating comorbidity burden alone (c-statistic = 0.82 versus 0.75; N = 17,700 patients, 176 hospitals). Concordance in outlier classification was 89% and 97% when applying 95% or 99% control limits to funnel plots, respectively. The sensitivity rates of outlier detection using comorbidity adjustment compared with gold-standard severity and comorbidity adjustment was 74% and 83% with 95% and 99% control limits, respectively. Corresponding positive predictive values were 74% and 91%. Hospital rank order of risk adjusted mortality rates shifted between 0 to 22 places with severity adjustment (Median = 4.0, Inter-quartile Range = 2–7).

Conclusions

Rankings of mortality rates varied widely depending on whether stroke severity was taken into account. Funnel plots yielded largely concordant results irrespective of severity adjustment and may be sufficiently accurate as a screening tool for assessing hospital performance.

Recommendations for the Establishment of Stroke Systems of Care: A 2019 Update

In 2005, the American Stroke Association published recommendations for the establishment of stroke systems of care and in 2013 expanded on them with a statement on interactions within stroke systems of care. The aim of this policy statement is to provide a comprehensive review of the scientific evidence evaluating stroke systems of care to date and to update the American Stroke Association recommendations on the basis of improvements in stroke systems of care. Over the past decade, stroke systems of care have seen vast improvements in endovascular therapy, neurocritical care, and stroke center certification, in addition to the advent of innovations, such as telestroke and mobile stroke units, in the context of significant changes in the organization of healthcare policy in the United States. This statement provides an update to prior publications to help guide policymakers and public healthcare agencies in continually updating their stroke systems of care in light of these changes. This statement and its recommendations span primordial and primary prevention, acute stroke recognition and activation of emergency medical services, triage to appropriate facilities, designation of and treatment at stroke centers, secondary prevention at hospital discharge, and rehabilitation and recovery.

Racial/ethnic disparities in hospital utilization in intracerebral hemorrhage

Background and purpose

There is evidence that racial and ethnic differences among intracerebral hemorrhage (ICH) patients exist. We sought to establish the occurrence of disparities in hospital utilization in the United States.

Methods

We identified ICH patients from United States Nationwide Inpatient Sample database for years 2006–2014 using codes (DX1 = 431, 432.0) from the International Classification of Diseases, 9th edition. We compared five race/ethnic categories: White, Black, Hispanic, Asian or Pacific Islander, and Others ( Native American and other) with regard to demographics, comorbidities, disease severity, in-hospital complications, in-hospital procedures, length of stay (LOS), total hospital charges, in-hospital mortality, palliative care, (PC) and do not resuscitate (DNR). We categorized procedures as lifesaving (i.e. ventriculostomy, craniotomy, craniectomy, and ventriculoperitoneal (VP) shunt), life sustaining (i.e. mechanical ventilation, tracheostomy, transfusions, and gastrostomy). White race/ethnicity was set as the reference group.

Results

Out of 710,293 hospitalized patients with ICH 470,539 (66.2%), 114,821 (16.2%), 66,451 (9.3%), 30,297 (4.3%) and 28,185 (3.9%) were White, Black, Hispanic, Asian or Pacific Islander, and Others, respectively. Minorities (Black, Hispanic, Asian or Pacific Islander, and Others) had a higher rate of in-hospital complications, in-hospital procedures, mean LOS, and hospital charges compared to Whites. In contrast, Whites had a higher rate of in-hospital mortality, PC, and DNR. In multivariable analysis, all minorities had higher rate of MV, tracheostomy, transfusions, and gastrostomy compared to Whites, while Hispanics had higher rate of craniectomy and VP shunt; and Asian or Pacific Islander and Others had higher rate of craniectomy. Whites had a higher rate of in-hospital mortality, palliative care, and DNR compared to minorities. In mediation analysis, in-hospital mortality for whites remained high after adjusting with PC and DNR.

Conclusion

Minorities had greater utilization of lifesaving and life sustaining procedures, and longer LOS. Whites had greater utilization of palliative care, hospice, and higher in-hospital mortality. These results may reflect differences in culture or access to care and deserve further study.

Relationship between hospital performance measures and outcomes in patients with acute ischaemic stroke: a prospective cohort study

OBJECTIVE

Evidence-based performance measures have been increasingly used to evaluate hospital quality of stroke care, but their impact on stroke outcomes has not been verified. We aimed to evaluate the correlations between hospital performance measures and outcomes among patients with acute ischaemic stroke in a Chinese population.

METHODS

Data were derived from a prospective cohort, which included 120 hospitals participating in the China National Stroke Registry between September 2007 and August 2008. Adherence to nine evidence-based performance measures was examined, and the composite score of hospital performance measures was calculated. The primary stroke outcomes were hospital-level, 30-day and 1-year risk-standardised mortality (RSM). Associations of individual performance measures and composite score with stroke outcomes were assessed using Spearman correlation coefficients.

RESULTS

One hundred and twenty hospitals that recruited 12 027 patients with ischaemic stroke were included in our analysis. Among 12 027 patients, 61.59% were men, and the median age was 67 years. The overall composite score of performance measures was 63.3%. The correlation coefficients between individual performance measures ranged widely from 0.01 to 0.66. No association was observed between the composite score and 30-day RSM. The composite score was modestly associated with 1-year RSM (Spearman correlation coefficient, 0.34; p<0.05). The composite score explained only 2.53% and 10.18% of hospital-level variation in 30-day and 1-year RSM for patients with acute stroke.

CONCLUSIONS

Adherence to evidence-based performance measures for acute ischaemic stroke was suboptimal in China. There were various correlations among hospital individual performance measures. The hospital performance measures had no correlations with 30-day RSM rate and modest correlations with 1-year RSM rate.

Effects of centralizing acute stroke services: A prospective cohort study

OBJECTIVE

To investigate the effects of centralizing the acute stroke services in the Central Denmark Region (CDR).

METHODS

The CDR (1.3 million inhabitants) centralized acute stroke care from 6 to 2 designated acute stroke units with 7-day outpatient clinics. We performed a prospective "before-and-after" cohort study comparing all strokes from the CDR with strokes in the rest of Denmark to discover underlying general trends, adopting a difference-in-differences approach. The population comprised 22,141 stroke cases hospitalized from May 2011 to April 2012 and May 2013 to April 2014.

RESULTS

Centralization was associated with a significant reduction in length of acute hospital stay from a median of 5 to 2 days with a length-of-stay ratio of 0.53 (95% confidence interval 0.38-0.75, data adjusted) with no corresponding change seen in the rest of Denmark. Similarly, centralization led to a significant increase in strokes with same-day admission (mainly outpatients), whereas this remained unchanged in the rest of Denmark. We observed a significant improvement in quality of care captured in 11 process performance measures in both the CDR and the rest of Denmark. Centralization was associated with a nonsignificant increase in thrombolysis rate. We observed a slight increase in readmissions at day 30, but this was not significantly different from the general trend. Mortality at days 30 and 365 remained unchanged, as in the rest of Denmark.

CONCLUSIONS

Centralizing acute stroke care in the CDR significantly reduced the length of acute hospital stay without compromising quality. Readmissions and mortality stayed comparable to the rest of Denmark.

Standardized Measurement of Sensorimotor Recovery in Stroke Trials: Consensus-Based Core Recommendations from the Stroke Recovery and Rehabilitation Roundtable

Finding, testing and demonstrating efficacy of new treatments for stroke recovery is a multifaceted challenge. We believe that to advance the field, neurorehabilitation trials need a conceptually rigorous starting framework. An essential first step is to agree on definitions of sensorimotor recovery and on measures consistent with these definitions. Such standardization would allow pooling of participant data across studies and institutions aiding meta-analyses of completed trials, more detailed exploration of recovery profiles of our patients and the generation of new hypotheses. Here, we present the results of a consensus meeting about measurement standards and patient characteristics that we suggest should be collected in all future stroke recovery trials. Recommendations are made considering time post stroke and are aligned with the international classification of functioning and disability. A strong case is made for addition of kinematic and kinetic movement quantification. Further work is being undertaken by our group to form consensus on clinical predictors and pre-stroke clinical data that should be collected, as well as recommendations for additional outcome measurement tools. To improve stroke recovery trials, we urge the research community to consider adopting our recommendations in their trial design.

Hospital readmissions after spontaneous intracerebral hemorrhage in Southern Portugal

OBJECTIVES

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

PATIENTS AND METHODS

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

RESULTS

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

CONCLUSIONS

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

Standardized measurement of sensorimotor recovery in stroke trials: Consensus-based core recommendations from the Stroke Recovery and Rehabilitation Roundtable

Finding, testing and demonstrating efficacy of new treatments for stroke recovery is a multifaceted challenge. We believe that to advance the field, neurorehabilitation trials need a conceptually rigorous starting framework. An essential first step is to agree on definitions of sensorimotor recovery and on measures consistent with these definitions. Such standardization would allow pooling of participant data across studies and institutions aiding meta-analyses of completed trials, more detailed exploration of recovery profiles of our patients and the generation of new hypotheses. Here, we present the results of a consensus meeting about measurement standards and patient characteristics that we suggest should be collected in all future stroke recovery trials. Recommendations are made considering time post stroke and are aligned with the international classification of functioning and disability. A strong case is made for addition of kinematic and kinetic movement quantification. Further work is being undertaken by our group to form consensus on clinical predictors and pre-stroke clinical data that should be collected, as well as recommendations for additional outcome measurement tools. To improve stroke recovery trials, we urge the research community to consider adopting our recommendations in their trial design.

Validation and comparison of two stroke prognostic models for in hospital, 30-day and 90-day mortality

INTRODUCTION

We aimed to validate and compare two clinical prognostic models for mortality which include the National Institutes of Health Stroke Scale (NIHSS); the Age and NIHSS Score (ANS) and case mix model (CMM) of the Sentinel Stroke National Audit Program (SSNAP). The NIHSS on admission was also tested as a prognostic score.

PATIENTS AND METHODS

Prospectively collected data from the SSNAP register for a cohort of patients (ischaemic and haemorrhagic stroke) admitted over 1 year to Gloucestershire Royal Hospital, England were accessed. The ANS and CMM were calculated and tested for in hospital, 30-day and 90-day mortality using calibration plots with Hosmer-Lemeshow tests, receiver operating characteristics curves and other measures of prognostic accuracy.

RESULTS

Of 848 patients, 110 (12.9%) died in hospital, 112 (13.2%) at 30 days and 164 (19.2%) at 90 days. Calibration for all three scores was good, although Hosmer-Lemeshow test p values were <0.05 with the NIHSS alone for in hospital and 30-day deaths, suggesting deviation from good fit. The c-statistics for in hospital, 30-day and 90-day mortality were ANS (0.783, 0.782, 0.779) and CMM (0.783, 0.774, 0.758), respectively. The NIHSS alone showed fair discrimination but performed less well. A NIHSS score ≥6 was associated with significant mortality (p < 0.0001) in comparison to a score <6.

CONCLUSION

A simple prognostic model containing age and admission NIHSS only, performed as well as a more complex score at predicting in hospital, 30-day and 90-day mortality. Admission NIHSS recording should be encouraged for stroke registries.

Prognostic value of thyroid hormones in acute ischemic stroke - a meta analysis

Previous studies on the association between thyroid hormones and prognosis of acute ischemic stroke (AIS) reported conflicting results. We conducted a meta-analysis to assess the prognostic value of thyroid hormones in AIS. The PubMed, EMBASE, and Cochrane library databases were searched through May 12, 2017 to identify eligible studies on this subject. Out of 2,181 studies retrieved, 11 studies were finally included with a total number of 3,936 acute stroke patients for analysis. Odds ratio (OR) for predicting poor outcome or standardized mean difference (SMD) of thyroid hormone levels with 95% confidence intervals (95% CI) obtained from the studies were pooled using Review Manager 5.3. From the results, in AIS, patients with a poor outcome had lower levels of triiodothyronine (T3) and higher thyroxine (T4). Pooled OR confirmed the same association. Our study provides statistical evidence supporting the utility of thyroid hormone levels in prognosis of acute stroke.

Oral Anticoagulation and Functional Outcome after Intracerebral Hemorrhage

OBJECTIVE

Oral anticoagulation treatment (OAT) resumption is a therapeutic dilemma in intracerebral hemorrhage (ICH) care, particularly for lobar hemorrhages related to amyloid angiopathy. We sought to determine whether OAT resumption after ICH is associated with long-term outcome, accounting for ICH location (ie, lobar vs nonlobar).

METHODS

We meta-analyzed individual patient data from: (1) the multicenter RETRACE study (n = 542), (2) a U.S.-based single-center ICH study (n = 261), and (3) the Ethnic/Racial Variations of Intracerebral Hemorrhage study (n = 209). We determined whether, within 1 year from ICH, OAT resumption was associated with: (1) mortality, (2) favorable functional outcome (modified Rankin Scale = 0-3), and (3) stroke incidence. We separately analyzed nonlobar and lobar ICH cases using propensity score matching and Cox regression models.

RESULTS

We included 1,012 OAT-related ICH survivors (633 nonlobar and 379 lobar). Among nonlobar ICH survivors, 178/633 (28%) resumed OAT, whereas 86/379 (23%) lobar ICH survivors did. In multivariate analyses, OAT resumption after nonlobar ICH was associated with decreased mortality (hazard ratio [HR] = 0.25, 95% confidence interval [CI] = 0.14-0.44, p < 0.0001) and improved functional outcome (HR = 4.22, 95% CI = 2.57-6.94, p < 0.0001). OAT resumption after lobar ICH was also associated with decreased mortality (HR = 0.29, 95% CI = 0.17-0.45, p < 0.0001) and favorable functional outcome (HR = 4.08, 95% CI = 2.48-6.72, p < 0.0001). Furthermore, OAT resumption was associated with decreased all-cause stroke incidence in both lobar and nonlobar ICH (both p < 0.01).

INTERPRETATION

These results suggest novel evidence of an association between OAT resumption and outcome following ICH, regardless of hematoma location. These findings support conducting randomized trials to explore risks and benefits of OAT resumption after ICH. Ann Neurol 2017;82:755-765.

Stroke Administrative Severity Index: using administrative data for 30-day poststroke outcomes prediction

Aim:

Current stroke severity scales cannot be used for archival data. We develop and validate a measure of stroke severity at hospital discharge (Stroke Administrative Severity Index [SASI]) for use in billing data.

Methods:

We used the NIH Stroke Scale (NIHSS) as the theoretical framework and identified 285 relevant International Classification of Diseases, 9th Revision diagnosis and procedure codes, grouping them into 23 indicator variables using cluster analysis. A 60% sample of stroke patients in Medicare data were used for modeling risk of 30-day postdischarge mortality or discharge to hospice, with validation performed on the remaining 40% and on data with NIHSS scores.

Results:

Model fit was good (p > 0.05) and concordance was strong (C-statistic = 0.76–0.83). The SASI predicted NIHSS at discharge (C = 0.83).

Conclusion:

The SASI model and score provide important tools to control for stroke severity at time of hospital discharge. It can be used as a risk-adjustment variable in administrative data analyses to measure postdischarge outcomes.