Transformation of the GWTG – Stroke Patient Registry to into a National Representative Database of Acute Ischemic Strokes (AIS) in the U.S.

Stroke remains a leading cause of death and disability in the United States.1  Approximately 800,000 people in the United States have a stroke every year.1  Eighty percent of all strokes can be prevented by screening for and treating known risk factors (hypertension, tobacco smoking, and atrial fibrillation).2 Recurrent strokes can also be prevented with proper management of these risk factors.3 Disease surveillance is crucial to the prevention of stroke, particularly in high-risk groups. Blacks and Hispanics report increasing stroke rates.4  Deprived populations within high-income countries are less likely to receive good-quality acute hospital and rehabilitation care than people with higher socioeconomic status.5  Findings from robust surveillance systems can be useful as healthcare providers can make informed decisions in the better medical management of strokes. Policymakers can work towards the development of aggressive campaigns to decrease the incidence of strokes in our communities and associated disparities in ethnic minorities and low-income groups.4,6  We can further estimate progress made towards the reduction and elimination of common risk factors of stroke.

Previously, the Institutes of Medicine recommended the development of surveillance systems in efforts to monitor the incidence and associated disabling burden from cardiovascular disease and strokes.7-8 The CDC’s Division for Heart Disease and Stroke Prevention (DHDSP) supports state, local, and tribal efforts to prevent, manage, and reduce risk factors related to stroke. The CDC has supported the implementation of stroke programs through cooperative agreements at these levels (CDC, 2020).9 However, due to the voluntary nature of these agreements, stroke surveillance data has been limited to only participant states. Therefore, it has been difficult to estimate the burden of a stroke at the national level.

A recent study by Ziaeian and colleagues presented the transformation of The Get With The Guidelines (GWTG) Stroke Patient Registry into a nationally representative database.10  This is the first study that has transformed a patient registry using post-stratification weights to represent a larger population of interest. The ability to translate observations from large registries to a national scale fills a considerable gap in the surveillance of the clinical characteristics, quality of care, and outcomes for Acute Ischemic Strokes (AIS) hospitalizations nationally.10  An acute stroke quality registry that is integrated with a guideline-based support tool can be a powerful tool for measuring and improving the quality of stroke care.11  Here we provide a summary of this recent study.10

Study population: The target population for the post-stratification weighting procedure is the total AIS presenting to U.S. hospitals by year. The NIS defines the AIS burden nationally stratified between the years of 2012 and 2014 and the nine U.S. Census regions – preserving the smallest sampling unit recommended by the NIS sponsors.  The National Inpatient Sample (NIS) is a weighted structured random sample of U.S. hospitalizations to represent national hospital utilization. However, the database does not include detailed clinical data such as stroke severity, laboratory data, medical treatments received, and patient-reported outcomes. The NIS is sponsored by the Agency for Healthcare Research and Quality’s Healthcare Cost and Utilization Project.

GWTG Stroke Patient Registry History: The GWTG – Stroke Patient Registry is a voluntary registry and continuous quality improvement initiative that collects data on patient characteristics, hospital adherence to guidelines and inpatient outcomes.  It was developed as part of a strategic goal of the American Heart Association (AHA) to reduce stroke and its associated risks, and Healthy People 2010 (HP2010) established national goals for stroke prevention and management.  The implementation of the GWTG Stroke registry has led to the implementation of evidence-based care and improved patient outcomes in many hospitals, acute care, and long-term care settings.6

GWTG hospitals comprise a mix of Joint Commission-certified stroke centers, PCNASR hospitals and small and large hospitals in urban and rural settings across the USA and Puerto Rico. Based on previous studies, the population of patients enrolled in GWTG is similar in age and racial makeup to the US population according to the U.S. census 2000.  Medicare beneficiaries linked to the GWTG registry are similar in demographics, comorbidities, and in-hospital outcomes compared with Medicare beneficiaries who are not linked.6,10

Methods: Ziaeian and colleagues integrated two data sources, The National Inpatient Sample (NIS), a structured random sample of U.S. hospitalizations weighted to represent national hospital utilization.10 The AHA-sponsored Get With The Guidelines Program (GWTG) program includes rich clinical data for quality improvement and research analyses.  They transformed these non-representative databases into a representative one with the use of post-stratification weights to rebalance over and underrepresented segments of the U.S. acute ischemic stroke (AIS) population. The approach described in the present paper is a far more robust estimation of the characteristics of stroke presentation and the quality of hospital care nationally.

The NIS lacks detailed clinical data such as stroke severity, laboratory data, medical treatments received, and patient-reported outcomes. It is not nationally representative and inadequate to measure stroke burden and quality of care nationally.  The GWTG-Stroke patient registry captures 58% of all strokes nationally. The GWTG program registries with volunteer hospitals are not proportionally representative of the entire nation.10  Ziaeian and colleagues used the GWTG-Stroke registry from 2012 to 2014 to evaluate post-stratification weighting procedures to represent the entire US AIS population.10

To determine the total number of AIS hospitalizations in the U.S. and marginal population characteristics for post-stratification weights, the investigators used target population counts from the NIS database. The NIS sampled 20% of the administrative discharge records from all participating hospitals (approximately 4300 hospitals) covering 95% of the U.S. population and 94% of all community hospital discharges from 2010 to 2014.  Raking and Bayesian interpolation, two parallel methods to estimate post-stratification survey weights, were used and their distribution was analyzed with histograms and treemaps to provide a perspective on the skewed representation of the GWTG-Stroke raw sample.

Results:  There were an estimated 1,388,296 AIS hospitalizations between 2012 to 2014 in the U.S. For the raking method, anchored characteristics in the weighted GWTG-Stroke sample matched the exact population totals estimated from the NIS. On admission, 49.2% of stroke patients nationally were using antiplatelet medications, 15.5% anticoagulants, 69.1% antihypertensives, 43.6% cholesterol-lowering medications, and 27.4% used diabetic medications. Approximately 48% of patients were discharged home, 40.2% to transitional care facilities, and 4.6% with hospice-related services.

Conclusions and Implications:  This research demonstrated the integration of two valuable data systems to make better population wide clinical estimates of acute ischemic stroke in the U.S., the GWTG Stroke Patient Registry and the NIS.  Their work demonstrates that methods exist to marry existing databases to make more reliable statistical inferences of population health and health services utilization. Understanding the effectiveness of hospital systems at a national and regional level is critical to insure consistency and timeliness in the receipt of evidence-based care. With the expansion of patient registries, the inclusion of clinical outcomes in these registries, and advanced statistical methods are available to transform non-random samples into representative population estimates.


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