Time to Brain Imaging in Acute Stroke Is Improving
Secondary Analysis of the INSTINCT Trial
Background and Purpose—Patients with acute ischemic stroke benefit from rapid evaluation and treatment, and timely brain imaging is a necessary component. We determined the effect of a targeted behavioral intervention on door-to-imaging time (DIT) among patients with ischemic stroke treated with tissue-type plasminogen activator. Second, we examined the variation in DIT accounted for by patient-level and hospital-level factors.
Methods—The Increasing Stroke Treatment through Interventional behavioral Change Tactics (INSTINCT) trial was a cluster-randomized, controlled trial involving 24 Michigan hospitals. The intervention aimed to increase tissue-type plasminogen activator utilization. Detailed chart abstractions collected data for 557 patients with ischemic stroke. We used a series of hierarchical linear mixed-effects models to evaluate the effect of the intervention on DIT (difference-in-differences analysis) and used patient-level and hospital-level explanatory variables to decompose variation in DIT.
Results—DIT improved over time, without a difference between intervention and control hospitals (intervention: 23.7–19.3 minutes, control: 28.9–19.2 minutes; P=0.56). Adjusted DIT was faster in patients who arrived by ambulance (7.2 minutes; 95% confidence interval, 4.1–10.2), had severe strokes (1.0 minute per +5-point National Institutes of Health Stroke Scale; 95% confidence interval, 0.1–2.0), and presented in the postintervention period (4.9 minutes; 95% confidence interval, 2.3–7.4). After accounting for these factors, 13.8% of variation in DIT was attributable to hospital. Neither hospital stroke volume nor stroke center status was associated with DIT.
Conclusions—Performance on DIT improved similarly in intervention and control hospitals, suggesting that nonintervention factors explain the improvement. Hospital-level factors explain a modest proportion of variation in DIT, but further research is needed to identify the hospital-level factors responsible.
Tissue-type plasminogen activator (tPA) remains underutilized in the emergent care of acute ischemic stroke.1 Prolonged door-to-imaging time (DIT) may delay or prevent thrombolysis. Guidelines recommend DIT of 25 minutes,2 yet nationally, DITs are suboptimal.3 This may represent an intervention target to improve thrombolytic delivery. The Increasing Stroke Treatment through Interventional behavioral Change Tactics (INSTINCT) was a cluster-randomized, controlled trial aimed to increase appropriate tPA use with multilevel–targeted educational interventions.4
In this analysis, we determined the effect of the INSTINCT intervention on DIT among tPA-treated patients with acute ischemic stroke. We hypothesized that the standardized, barrier assessment, multicomponent educational intervention developed to increase tPA use in community hospitals would improve DIT as part of the overall improvement in local stroke systems. Second, we examined the variation in DIT accounted for by patient-level and hospital-level factors.
This is a secondary analysis of INSTINCT trial data,4 a cluster-randomized, controlled trial, matching 12 intervention with 12 control nonspeciality, acute-care community hospitals in Michigan. A multi-level barrier assessment and interactive educational program based on behavior change theory were delivered to intervention hospitals from January to December 2007. Design and intervention are further detailed in the online-only Data Supplement.
Detailed chart abstractions were conducted only for tPA-treated patients. We excluded patients with in-hospital stroke onset and patients with missing DIT (3.6% of sample; n=19). Excluded patients were similar in demographics, comorbidities, risk factors, and stroke severity, but more often from control hospital preintervention.
The primary outcome, DIT, was derived from medical records as the difference between emergency department arrival time and initial brain imaging time (computed tomography in all cases).
Data were analyzed using STATA version 12.1 (STATA Corp, College Station, TX). Baseline characteristics were compared by treatment group using χ2 or ANOVA as appropriate.
Hierarchical linear models examined the association between DIT and randomization group, accounting for observation time (before versus after intervention), before and after adjustment for patient and hospital factors, with a random hospital-level intercept. The parameter estimate for the randomization group-by-time interaction assessed the significance of the intervention effect (online-only Data Supplement).
A 2-level linear mixed-effect regression model examined the proportion of variation in DIT explained by patient-level and hospital-level factors. An empty model decomposed the unadjusted variation, then patient-level variables were added. Finally, hospital-level variables (stroke volume and stroke center status) were added. We made posterior predictions of the average marginal effects of ambulance arrival and stroke severity on predicted DIT, holding other variables constant (online-only Data Supplement).
Of the 511 tPA-treated patients, mean age was 69.9 years, 52.5% were men, and 75.9% non-Hispanic white. Mean National Institutes of Health Stroke Scale (NIHSS) score was 12.2 points (SD, 5.9). Most arrived by ambulance (83.2%) and received tPA within 180 minutes of onset (84.7%; Table I in the online-only Data Supplement).
Mean DIT was 20.3 minutes (SD, 13.5 minutes). Baseline DIT and improvement in DIT from preintervention to postintervention were similar between intervention (23.7–19.3 minutes) and control hospitals (28.9–19.2 minutes; P=0.30 for difference in baseline; P=0.56 for difference in improvement).
Of the unadjusted variation in DIT, 13.4% was attributable to hospitals (intraclass correlation coefficient, 0.134). After including patient-level factors, the variation attributable to hospitals changed minimally (intraclass correlation coefficient, 0.138). Adding hospital stroke center status and stroke volume did not predict DIT but did explain 18.4% of the between-hospital variance (intraclass correlation coefficient, 0.116; Figure 1).
In multivariable analysis, predictors of faster DIT were stroke severity (1 minute per 5-point increase in NIHSS; 95% confidence interval, 0.1–2.0 minutes), ambulance arrival (7.2 minutes; 95% confidence interval, 4.1–10.2 minutes), and presentation postintervention (2009–2010 versus 2005–2006, 4.9 minutes; 95% confidence interval, 2.3–7.4 minutes; Table). Ambulance arrival and stroke severity operated independently to effect DIT (Figure 2).
We found that a targeted educational intervention aimed to improve acute stroke care, and emergent tPA delivery had no effect on DIT performance of hospitals. Although we found no difference between change over time of control and intervention hospitals, both groups showed similar significant improvements. This finding, in a sample deliberately selected for broader generalizability,4 signals strongly for the effect of secular trends. This may be because of increasing awareness and better stroke recognition in the prehospital or emergency department settings, improvements in computed tomography availability, increasing primary stroke center hospitals, the American Heart Association Get-with-the-Guidelines program, and national quality reporting incentives.5–7
We found a modest proportion of DIT variation attributable to hospital differences, yet this was not explained by stroke center status or stroke volume. As Figure 1 highlights, differences between hospitals are small and difficult to differentiate. Examination of a larger sample of hospitals and hospital characteristics may better identify actionable targets for DIT.
Consistent with previous reports, stroke severity and ambulance arrival were strong predictors of DIT.3,8 The magnitude of the relationship between ambulance arrival and DIT reaffirms the importance of the prehospital and triage settings as targets for improving quality and reducing delays.
Our focus on DIT only among tPA-treated patients was an inherent limitation of the original study design but may have created bias by excluding untreated patients. We also excluded patients with missing DIT, but this small group of patients was similar to included patients. Finally, we could not assess several potential predictors of DIT, including background quality improvement initiatives, stroke registry participation, emergency medical service prenotification, and temporal changes in telemedicine or imaging capabilities.
Although the targeted educational intervention of the INSTINCT trial did not seem to improve DIT, we found that DIT performance is improving over time. Better understanding of the trends in DIT and reasons for DIT variation across hospitals will have important quality improvement and policy implications.
Sources of Funding
The parent study was funded by the National Institutes of Health (NIH) National Institute of Neurological Disorders and Stroke grant R01-NS-050372. Dr Levine is funded by NIH K23 AG040278 and received support from NIH P30DK092926.
The online-only Data Supplement is available with this article at http://stroke.ahajournals.org/lookup/suppl/doi:10.1161/STROKEAHA.113.003678/-/DC1.
- Received September 27, 2013.
- Accepted October 7, 2013.
- © 2013 American Heart Association, Inc.
- Kelly AG,
- Hellkamp AS,
- Olson D,
- Smith EE,
- Schwamm LH
- Jauch EC,
- Saver JL,
- Adams HP Jr.,
- Bruno A,
- Connors JJ,
- Demaerschalk BM,
- et al
- Prabhakaran S,
- McNulty M,
- O’Neill K,
- Ouyang B
- Schwamm LH,
- Fonarow GC,
- Reeves MJ,
- Pan W,
- Frankel MR,
- Smith EE,
- et al
- 7.↵Hospital outpatient quality reporting specifications manual, v6.0b. Quality Net. 2013. http://www.qualitynet.org/dcs/ContentServer?c=Page&pagename=QnetPublic%2FPage%2FSpecsManualTemplate&cid=1228772438492. Accessed September 25, 2013.
- Abdullah AR,
- Smith EE,
- Biddinger PD,
- Kalenderian D,
- Schwamm LH