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

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.

The Allure of Big Data to Improve Stroke Outcomes: Review of Current Literature

PURPOSE OF REVIEW

To critically appraise literature on recent advances and methods using "big data" to evaluate stroke outcomes and associated factors.

RECENT FINDINGS

Recent big data studies provided new evidence on the incidence of stroke outcomes, and important emerging predictors of these outcomes. Main highlights included the identification of COVID-19 infection and exposure to a low-dose particulate matter as emerging predictors of mortality post-stroke. Demographic (age, sex) and geographical (rural vs. urban) disparities in outcomes were also identified. There was a surge in methodological (e.g., machine learning and validation) studies aimed at maximizing the efficiency of big data for improving the prediction of stroke outcomes. However, considerable delays remain between data generation and publication. Big data are driving rapid innovations in research of stroke outcomes, generating novel evidence for bridging practice gaps. Opportunity exists to harness big data to drive real-time improvements in stroke outcomes.

Acute Ischemic Stroke Interventions in the United States and Racial, Socioeconomic, and Geographic Disparities

BACKGROUND AND OBJECTIVES

In patients with ischemic stroke (IS), IV alteplase (tissue plasminogen activator [tPA]) and endovascular thrombectomy (EVT) reduce long-term disability, but their utilization has not been fully optimized. Prior research has also demonstrated disparities in the use of tPA and EVT specific to sex, race/ethnicity, socioeconomic status, and geographic location. We sought to determine the utilization of tPA and EVT in the United States from 2016-2018 and if disparities in utilization persist.

METHODS

This is a retrospective, longitudinal analysis of the 2016-2018 National Inpatient Sample. We included adult patients who had a primary discharge diagnosis of IS. The primary study outcomes were the proportions who received tPA or EVT. We fit a multivariate logistic regression model to our outcomes in the full cohort and also in the subset of patients who had an available baseline National Institutes of Health Stroke Scale (NIHSS) score.

RESULTS

The full cohort after weighting included 1,439,295 patients with IS. The proportion who received tPA increased from 8.8% in 2016 to 10.2% in 2018 (p < 0.001) and who had EVT from 2.8% in 2016 to 4.9% in 2018 (p < 0.001). Comparing Black to White patients, the odds ratio (OR) of receiving tPA was 0.82 (95% confidence interval [CI] 0.79-0.86) and for having EVT was 0.75 (95% CI 0.70-0.81). Comparing patients with a median income in their zip code of ≤$37,999 to >$64,000, the OR of receiving tPA was 0.81 (95% CI 0.78-0.85) and for having EVT was 0.84 (95% CI 0.77-0.91). Comparing patients living in a rural area to a large metro area, the OR of receiving tPA was 0.48 (95% CI 0.44-0.52) and for having EVT was 0.92 (95% CI 0.81-1.05). These associations were largely maintained after adjustment for NIHSS, although the effect size changed for many of them. Contrary to prior reports with older datasets, sex was not consistently associated with tPA or EVT.

DISCUSSION

Utilization of tPA and EVT for IS in the United States increased from 2016 to 2018. There are racial, socioeconomic, and geographic disparities in the accessibility of tPA and EVT for patients with IS, with important public health implications that require further study.

Effect of Adjusting for Baseline Stroke Severity in the National Inpatient Sample

[Figure: see text].

Factors associated with arrival by ambulance for patients with stroke: a multicentre, national data linkage study

BACKGROUND

Hospital arrival via ambulance influences treatment of acute stroke. We aimed to determine the factors associated with use of ambulance and access to evidence-based care among patients with stroke.

METHODS

Patients with first-ever strokes from the Australian Stroke Clinical Registry (2010-2013) were linked with administrative data (emergency, hospital admissions). Multilevel, multivariable regression models were used to determine patient, clinical and system factors associated with arrival by ambulance.

RESULTS

Among the 6,262 patients with first-ever stroke, 4,737 (76%) arrived by ambulance (52% male; 80% ischaemic). Patients who were older, frailer, with comorbidities or were unable to walk on admission (stroke severity) were more likely to arrive by ambulance to hospital. Compared to those using other means of transport, those who used ambulances arrived to hospital sooner after stroke onset (minutes, 124 vs 397) and were more likely to receive reperfusion therapy (adjusted odds ratio, 1.57, 95% CI: 1.09, 2.27).

CONCLUSION

Patients with stroke who use ambulances arrived faster and were more likely to receive reperfusion therapy compared to those using personal transport. Further public education about using ambulance services at all times, instead of personal transport when stroke is suspected is needed to optimise access to time critical care.

Urban-Rural Inequities in Acute Stroke Care and In-Hospital Mortality

BACKGROUND AND PURPOSE

The rural-urban life-expectancy gap is widening, but underlying causes are incompletely understood. Prior studies suggest stroke care may be worse for individuals in more rural areas, and technological advancements in stroke care may disproportionately impact individuals in more rural areas. We sought to examine differences and 5-year trends in the care and outcomes of patients hospitalized for stroke across rural-urban strata.

METHODS

Retrospective cohort study using National Inpatient Sample data from 2012 to 2017. Rurality was classified by county of residence according to the 6-strata National Center for Health Statistics classification scheme.

RESULTS

There were 792 054 hospitalizations for acute stroke in our sample. Rural patients were more often white (78% versus 49%), older than 75 (44% versus 40%), and in the lowest quartile of income (59% versus 32%) compared with urban patients. Among patients with acute ischemic stroke, intravenous thrombolysis and endovascular therapy use were lower for rural compared with urban patients (intravenous thrombolysis: 4.2% versus 9.2%, adjusted odds ratio, 0.55 [95% CI, 0.51-0.59], P<0.001; endovascular therapy: 1.63% versus 2.41%, adjusted odds ratio, 0.64 [0.57-0.73], P<0.001). Urban-rural gaps in both therapies persisted from 2012 to 2017. Overall, stroke mortality was higher in rural than urban areas (6.87% versus 5.82%, P<0.001). Adjusted in-patient mortality rates increased across categories of increasing rurality (suburban, 0.97 [0.94-1.0], P=0.086; large towns, 1.05 [1.01-1.09], P=0.009; small towns, 1.10 [1.06-1.15], P<0.001; micropolitan rural, 1.16 [1.11-1.21], P<0.001; and remote rural 1.21 [1.15-1.27], P<0.001 compared with urban patients. Mortality for rural patients compared with urban patients did not improve from 2012 (adjusted odds ratio, 1.12 [1.00-1.26], P<0.001) to 2017 (adjusted odds ratio, 1.27 [1.13-1.42], P<0.001).

CONCLUSIONS

Rural patients with stroke were less likely to receive intravenous thrombolysis or endovascular therapy and had higher in-hospital mortality than their urban counterparts. These gaps did not improve over time. Enhancing access to evidence-based stroke care may be a target for reducing rural-urban disparities.

Measuring stroke outcomes for 74 501 patients using linked administrative data: System-wide estimates and validation of 'home-time' as a surrogate measure of functional status

AIMS

Administrative data offer cost-effective, whole-of-population stroke surveillance yet the lack of validated measures of functional status is a shortcoming. The number of days spent living at home after stroke ('home-time') is a patient-centred outcome that can be objectively ascertained from administrative data. Population-based validation against both severity and outcome measures and for all subtypes is lacking. We aimed to report representative 'home-time' estimates and validate 'home-time' as a surrogate measure of functional status after stroke.

METHODS

Stroke hospitalisations from a state-wide census in New South Wales, Australia, from January 1, 2005 to March 31, 2014 were linked to prehospital data, poststroke admissions and deaths. We correlated 90-day 'home-time' with Glasgow Coma Scale (GCS) scores, measured upon a patient's initial contact with paramedics and Functional Independence Measure (FIM) scores, measured upon entry to rehabilitation after the acute hospital stroke admission. Negative binomial regressions identified predictors of 'home-time'.

RESULTS

Patients with stroke (N = 74 501) spent a median of 53 days living at home 90 days after the event. Median 'home-time' was 60 days after ischaemic stroke, 49 days after subarachnoid haemorrhage and 0 days after intracerebral haemorrhage. GCS and FIM scores significantly correlated with 'home-time' (P < .001). Women spent significantly less time at home compared with men after stroke, although being married increased 'home-time' after ischaemic stroke and subarachnoid haemorrhage.

CONCLUSIONS

These findings underscore the immediate and adverse impact of stroke. 'Home-time' measured using administrative data is a robust, replicable and valid patient-centred outcome enabling inexpensive population-based surveillance and system-wide quality assessment.

Population-based stroke surveillance using big data: state-wide epidemiological trends in admissions and mortality in New South Wales, Australia

OBJECTIVES

Epidemiological trends for major causes of death and disability, such as stroke, may be monitored using administrative data to guide public health initiatives and service delivery.

METHODS

We calculated admissions rates for ischaemic stroke, intracerebral haemorrhage and subarachnoid haemorrhage between 1 January 2005 and December 31^st, 2013 and rates of 30-day mortality and 365-day mortality in 30-day survivors to 31 December 2014 for patients aged 15 years or older from New South Wales, Australia. Annual Average Percentage Change in rates was estimated using negative binomial regression.

RESULTS

Of 81,703 eligible admissions, 64,047 (78.4%) were ischaemic strokes and 13,302 (16.3%) and 4,778 (5.8%) were intracerebral and subarachnoid haemorrhages, respectively. Intracerebral haemorrhage admissions significantly declined by an average of 2.2% annually (95% Confidence Interval = -3.5% to -0.9%) (p < 0.001). Thirty-day mortality rates significantly declined for ischaemic stroke (Average Percentage Change -2.9%, 95% Confidence Interval = -5.2% to -1.0%) (p = 0.004) and subarachnoid haemorrhage (Average Percentage Change = -2.6%, 95% Confidence Interval = -4.8% to -0.2%) (p = 0.04). Mortality at 365-days amongst 30-day survivors of ischaemic stroke and intracerebral haemorrhage was stable over time and increased in subarachnoid haemorrhage (Annual Percentage Change 6.2%, 95% Confidence Interval = -0.1% to 12.8%), although not significantly (p = 0.05).

DISCUSSION

Improved prevention may have underpinned declining intracerebral haemorrhage rates while survival gains suggest that innovations in care are being successfully translated. Mortality in patients surviving the acute period is unchanged and may be increasing for subarachnoid haemorrhage warranting investment in post-discharge care and secondary prevention.