Documentation of stroke onset time: challenges and recommendations

Factors related to time of stroke onset versus time of hospital arrival: A SITS registry-based study in an Egyptian stroke center

BACKGROUND

High-quality data on time of stroke onset and time of hospital arrival is required for proper evaluation of points of delay that might hinder access to medical care after the onset of stroke symptoms.

PURPOSE

Based on (SITS Dataset) in Egyptian stroke patients, we aimed to explore factors related to time of onset versus time of hospital arrival for acute ischemic stroke (AIS).

MATERIAL AND METHODS

We included 1,450 AIS patients from two stroke centers of Ain Shams University, Cairo, Egypt. We divided the day to four quarters and evaluated relationship between different factors and time of stroke onset and time of hospital arrival. The factors included: age, sex, duration from stroke onset to hospital arrival, type of management, type of stroke (TOAST classification), National Institute of Health Stroke Scale (NIHSS) on admission and favorable outcome modified Rankin Scale (mRS ≤2).

RESULTS

Pre-hospital: highest stroke incidence was in the first and fourth quarters. There was no significant difference in the mean age, sex, type of stroke in relation to time of onset. NIHSS was significantly less in onset in third quarter of the day. Percentage of patients who received thrombolytic therapy was higher with onset in the first 2 quarters of the day (p = <0.001). In-hospital: there was no difference in percentage of patients who received thrombolytic therapy nor in outcome across 4 quarters of arrival to hospital.

CONCLUSION

Pre-hospital factors still need adjustment to improve percentage of thrombolysis, while in-hospital factors showed consistent performance.

Interrater reliability of a national acute myocardial infarction register

BACKGROUND

Disease-specific registers may be used for measuring and improving healthcare and patient outcomes, and for disease surveillance and research, provided they contain valid and reliable data. The aim of this study was to assess the interrater reliability of all variables in a national myocardial infarction register.

METHODS

We randomly selected 280 patients who had been enrolled from 14 hospitals to the Norwegian Myocardial Infarction Register during the year 2013. Experienced audit nurses, who were blinded to the data about the 280 patients already in the register, completed the Norwegian Myocardial Infarction paper forms for 240 patients by review of medical records. We then extracted all registered data on the same patients from the Norwegian Myocardial Infarction Register. To compare the interrater reliability between the register and the audit nurses, we calculated intraclass correlations coefficient for continuous variables, Cohen's kappa and Gwet's first agreement coefficient (AC1) for nominal variables, and quadratic weighted Cohen's kappa and Gwet's second AC for ordinal variables.

RESULTS

We found excellent (AC1 >0.80) or good (AC1 0.61-0.80) agreement for most variables, including date and time variables, medical history, investigations and treatments during hospitalization, medication at discharge, and ST-segment elevation or non-ST-segment elevation acute myocardial infarction. However, only moderate agreement (AC1 0.41-0.60) was found for family history of coronary heart disease, diagnostic electrocardiography, and complications during hospitalization, whereas fair agreement (AC1 0.21-0.40) was found for acute myocardial infarction location. A high percentage of missing data was found for symptom onset, family history, body mass index, infarction location, and new Q-wave.

CONCLUSION

Most variables in Norwegian Myocardial Infarction Register had excellent or good reliability. However, some important variables had lower reliability than expected or had missing data. Precise definitions of data elements and proper training of data abstractors are necessary to ensure that clinical registries contain valid and reliable data.

Emergency medical services transport delays for suspected stroke and myocardial infarction patients

BACKGROUND

Prehospital delays in receiving emergency care for suspected stroke and myocardial infarction (MI) patients have significant impacts on health outcomes. Use of Emergency Medical Services (EMS) has been shown to reduce these delays. However, disparities in EMS transport delays are thought to exist. Therefore the objective of this study was to investigate and identify disparities in EMS transport times for suspected stroke and MI patients.

METHODS

Over 3,900 records of suspected stroke and MI patients, reported during 2006-2009, were obtained from two EMS agencies (EMS 1 & EMS 2) in Tennessee. Summary statistics of transport time intervals were computed. Multivariable logistic models were used to identify predictors of time intervals exceeding EMS guidelines.

RESULTS

Only 66 and 10 % of suspected stroke patients were taken to stroke centers by EMS 1 and 2, respectively. Most (80-83 %) emergency calls had response times within the recommended 10 min. However, over 1/3 of the calls had on-scene times exceeding the recommended 15 min. Predictors of time intervals exceeding EMS guidelines were EMS agency, patient age, season and whether or not patients were taken to a specialty center. The odds of total transport time exceeding EMS guidelines were significantly lower for patients not taken to specialty centers. Noteworthy was the 72 % lower odds of total time exceeding guidelines for stroke patients served by EMS 1 compared to those served by EMS 2. Additionally, for every decade increase in age of the patient, the odds of on-scene time exceeding guidelines increased by 15 and 19 % for stroke and MI patients, respectively.

CONCLUSION

In this study, prehospital delays, as measured by total transport time exceeding guideline was influenced by season, EMS agency responsible, patient age and whether or not the patient is transported to a specialty center. The magnitude of the delays associated with some of the factors are large enough to be clinically important although others, though statistically significant, may not be large enough to be clinically important. These findings should be useful for guiding future studies and local health initiatives that seek to reduce disparities in prehospital delays so as to improve health services and outcomes for stroke and MI patients.

Inter-rater reliability of a national acute stroke register

Background

Medical quality registers are useful sources of knowledge about diseases and the health services. However, there are challenges in obtaining valid and reliable data. This study aims to assess the reliability in a national medical quality register.

Methods

We randomly selected 111 patients having had a stroke in 2012. An experienced stroke nurse completed the Norwegian Stroke Register paper forms for all 111 patients by review of the medical records. We then extracted all registered data on the same patients from the Norwegian Stroke Register and calculated Cohen’s kappa and Gwet’s AC₁ with 95 % confidence intervals for 51 nominal variables and Cohen’s quadratic weighted kappa and Gwet’s AC₂ for three ordinal variables. For two time variables, we calculated the Intraclass Correlation Coefficient.

Results

Substantial to excellent reliability (kappa > 0.60/AC₁ > 0.80) was observed for most variables related to past medical history, functional status, stroke subtype and discharge destination. Although excellent reliability was observed for time of stroke onset (ICC 0.93), this variable was hampered with a substantial amount of missing values. Some variables related to treatment and examinations in hospital displayed low levels of agreement. This applies to heart rate monitoring (kappa 0.17/AC₁ 0.46), swallowing test performed (kappa 0.19/AC₁ 0.27) and mobilized out of bed within 24 h after admission (kappa 0.04/AC₁ −0.11).

Conclusion

A majority of the variables in The Norwegian Stroke Register have substantial to excellent reliability. The problem areas seem to be the lack of completeness in the time variable indicating stroke onset and poor reliability in some variables concerning examinations and treatment received in hospital.

Electronic supplementary material

The online version of this article (doi:10.1186/s13104-015-1556-3) contains supplementary material, which is available to authorized users.

Times From Symptom Onset to Hospital Arrival in the Get With The Guidelines–Stroke Program 2002 to 2009

Background and Purpose—

Time from symptom onset to hospital arrival is the most important factor in determining eligibility for intravenous tissue-type plasminogen activator. We used data from a large contemporary nationwide study to determine temporal trends in the proportions of patients arriving within time windows for potential acute ischemic stroke therapies.

Methods—

Trends in symptom onset to hospital arrival time (“onset-to-door time”) for patients with acute ischemic stroke in the Get With The Guidelines–Stroke (GWTG-Stroke) program were analyzed between 2003 and 2009. Factors associated with early onset-to-door time (≤2 hours) were also examined.

Results—

Between April 2003 and March 2009, 1287 hospitals submitted data on 413 147 patients with acute ischemic stroke of whom 194 352 (47.0%) had a specific onset time documented. Among all 413 147 patients, onset-to-door time was documented as ≤2 hours in 20.6%, ≤3 hours in 25.1%, ≤3.5 hours in 26.8%, and ≤8 hours in 35.8%. Early arrival within 2 hours was significantly associated with emergency medical services transport ( P <0.0001). There was no substantial change in onset-to-door time over the 6-year study period. Expansion of the tissue-type plasminogen activator treatment window from 3 to 4.5 hours (allowing 60 minutes for provision of tissue-type plasminogen activator) increases the pool of potentially eligible patients by 6.3% (30.1% relative increase).

Conclusions—

More than one fourth of patients with ischemic stroke arrive within the time window for tissue-type plasminogen activator therapy; however, this percentage has remained unchanged over recent years. Further efforts are needed to increase the portion of patients with acute ischemic stroke presenting within the time window for acute interventions.

Data quality in the American Heart Association Get With The Guidelines-Stroke (GWTG-Stroke): results from a national data validation audit

BACKGROUND

Get With The Guidelines (GWTG)-Stroke is a national stroke registry and quality improvement program. We examined the accuracy and reliability of data entered in GWTG-Stroke.

METHODS

Data entered by sites in the GWTG-Stroke database were compared with that abstracted from de-identified medical records by trained auditors. Accuracy for each individual data element and a composite accuracy measure were calculated. Reliability was assessed using kappa (κ) statistics for categorical variables and intraclass correlation (ICC) for continuous variables.

RESULTS

A random selection of 438 medical records from 147 GWTG-Stroke hospitals was obtained. Overall accuracy was above 90% for all variables abstracted except for weight (84.9%), serum creatinine (88.1%), deep venous thrombosis prophylaxis (79.0%), and date/time last known well (85.3%). Intermediate to good (κ or ICC 0.40-0.75) or excellent agreement (κ or ICC ≥0.75) was observed for nearly all audited variables, including time-related performance measures such as arrival within 2 hours of symptom onset (κ = 0.90) and door-to-needle time ≤60 minutes (κ = 0.72). The overall composite accuracy rate was 96.1%. The composite measure varied slightly by region and hospital academic status, but there were no significant differences in composite accuracy by bed size, ischemic stroke volume, primary stroke center certification, or Coverdell Registry participation.

CONCLUSIONS

This audit establishes the reliability of GWTG-Stroke registry data. Individual data elements with suboptimal accuracy should be targeted for further data quality improvement.

Presenting symptoms and onset-to-arrival time in patients with acute stroke and transient ischemic attack

Delayed arrival to the emergency department (ED) precludes most stroke patients from receiving thrombolytic treatment. Our objective in this study was to examine the association between presenting symptoms and onset-to-arrival time (ie, time between onset of symptoms to arrival at the ED) in a statewide stroke registry. Demographics, clinical data, and presenting symptoms were collected for patients with acute stroke or symptomatic transient ischemic attack (TIA) admitted to 15 Michigan hospitals (n = 1922). Polytomous logistic regression models were developed to test the association between presenting symptoms and onset-to-arrival time (classified as <2 hours, 2-6 hours, or >6 hours/unknown). Onset-to-arrival time was <2 hours in 19% of the patients, 2-6 hours in 22%, and >6 hours/unknown in 59%. Unilateral symptoms (reported by 40%) and speech difficulties (reported by 22%) were associated with increased likelihood of arriving within 2 hours (unilateral: adjusted odds ratio [aOR], 1.5; 95% confidence interval [CI], 1.1-1.9; speech: aOR, 1.6; 95% CI, 1.2-2.2). Difficulty with walking, balance, or dizziness (12%), confusion (9%), loss of consciousness (6.7%) and falls (3.4%) were associated with lower likelihood of arriving within 2 hours (walking: aOR, 0.7; 95% CI, 0.4-1.0; confusion: aOR, 0.5; 95% CI, 0.3-0.8; consciousness: aOR, 0.5; 95% CI, 0.1-0.9; falls: aOR, 0.4; 95% CI, 0.3-0.9). Presenting symptoms were strongly associated with time of arrival; patients with unilateral symptoms and speech difficulties were more likely to seek care early. Future studies should consider including more specific patient-level data to identify psychosocial and behavioral aspects of recognition and action to stroke symptoms.

A comprehensive review of prehospital and in-hospital delay times in acute stroke care

The purpose of this study was to systematically review and summarize prehospital and in-hospital stroke evaluation and treatment delay times. We identified 123 unique peer-reviewed studies published from 1981 to 2007 of prehospital and in-hospital delay time for evaluation and treatment of patients with stroke, transient ischemic attack, or stroke-like symptoms. Based on studies of 65 different population groups, the weighted Poisson regression indicated a 6.0% annual decline (P<0.001) in hours/year for prehospital delay, defined from symptom onset to emergency department arrival. For in-hospital delay, the weighted Poisson regression models indicated no meaningful changes in delay time from emergency department arrival to emergency department evaluation (3.1%, P=0.49 based on 12 population groups). There was a 10.2% annual decline in hours/year from emergency department arrival to neurology evaluation or notification (P=0.23 based on 16 population groups) and a 10.7% annual decline in hours/year for delay time from emergency department arrival to initiation of computed tomography (P=0.11 based on 23 population groups). Only one study reported on times from arrival to computed tomography scan interpretation, two studies on arrival to drug administration, and no studies on arrival to transfer to an in-patient setting, precluding generalizations. Prehospital delay continues to contribute the largest proportion of delay time. The next decade provides opportunities to establish more effective community-based interventions worldwide. It will be crucial to have effective stroke surveillance systems in place to better understand and improve both prehospital and in-hospital delays for acute stroke care.

Air pollution and risk of stroke: underestimation of effect due to misclassification of time of event onset

BACKGROUND

Epidemiologic studies linking ambient air pollution to the onset of acute cardiovascular events often rely on date of hospital admission for exposure assessment.

METHODS

We investigated the extent of exposure misclassification resulting from assigning exposure to particulate matter based on (1) date of hospital admission, or (2) time of hospital presentation compared with particulate matter exposure based on time of stroke symptom onset. We performed computer simulations to evaluate the impact of this source of exposure misclassification on estimates of air pollution health effects in the context of a time-stratified case-crossover study.

RESULTS

Among 1101 patients admitted for a confirmed acute ischemic stroke to a Boston area hospital, symptom onset occurred a median of 1 calendar day before hospital admission (range = 0-30 days). The difference between ambient particulate matter exposure based on the calendar day of admission versus time of symptom onset ranged from -47 to 36 microg/m3 (-0.1 +/- 7.1 microg/m3; mean +/- SD). The simulation study indicated that for nonnull associations, exposure assessment based on hospitalization date led to estimates that were biased toward the null by 60%-66%, whereas assessment based on time of hospital presentation yielded estimates that were biased toward the null by 37%-42%.

CONCLUSIONS

Epidemiologic studies of air pollution-related risk of acute cardiovascular events that assess exposure based on date of hospitalization likely underestimate the strength of associations. Using data on time of hospital presentation would marginally attenuate, but not eliminate, this important source of bias.

Pediatric stroke: do clinical factors predict delays in presentation?

OBJECTIVE

To explore associations between age, clinical presentation, or predisposing conditions and delayed diagnosis of arterial ischemic stroke.

STUDY DESIGN

This was a retrospective chart review of children admitted to tertiary care medical centers in San Diego County between 1995 and 2000. Inpatient charts were screened by ICD-9 codes for stroke, cerebrovascular anomalies, hemiplegia, and migraine.

RESULTS

Time of presentation for medical evaluation did not differ by age group, clinical presentation, or risk factors. There was no relationship between time of presentation and Glasgow Outcome Score. Only 24% (9/37) of the patients with ischemic stroke presented for clinical evaluation within 6 hours after onset of symptoms, and an additional 41% (13/37) presented within the first 24 hours. Children who initially presented with altered mental status were more likely to die than those with other initial presentations (odds ratio = 9.94; 95% confidence interval = 2.05 to 47.9), but none of the 16 children who presented with hemiparesis died (P = .01).

CONCLUSION

Time of presentation was not related to the clinical factors studied. Early recognition of stroke in children is an important goal for families and health care providers.

Predictors of Time From Hospital Arrival to Initial Brain-Imaging Among Suspected Stroke Patients

Background and Purpose— We examined patient demographic and hospital characteristics and clinical predictors of delay time from hospital arrival until CT among 20 374 patients enrolled in the North Carolina Collaborative Stroke Registry (January 2005 to April 2008).

Methods— Delay time was log-transformed in linear regression analyses and dichotomized (≤25 minutes, >25 minutes) in logistic regression analyses to correspond to a 1999 National Institute of Neurological Disorders and Stroke guideline.

Results— In multiple linear regression analyses, prehospital delay time, mode of transport, race, gender, presumptive diagnosis, time of day of arrival, weekday versus weekend arrival, and hospital type (defined by Joint Commission Primary Stroke Center certification and teaching status) were significantly associated with CT delay. In analyses of 3549 patients arriving within 2 hours of symptom onset, time of day of arrival and weekday versus weekend arrival were no longer significant. Among patients arriving within 2 hours of symptom onset, the strongest independent predictors of meeting the National Institute of Neurological Disorders and Stroke (NINDS) guideline were arrival by emergency medical services versus other modes of transportation (odds ratio, 95% CI=2.3 [1.9, 2.8]) and a presumptive diagnosis of transient ischemic attack versus unspecified stroke type (odds ratio, 95% CI=0.4 [0.3, 0.5]).

Conclusions— Most patients do not arrive to the hospital in a timely manner and cannot be considered for time-dependent therapies. Among those that do, disparities exist in time to receipt of CT scan, suggesting room for improvement in hospital-level stroke systems of care.

Inter-rater reliability of data elements from a prototype of the Paul Coverdell National Acute Stroke Registry

BACKGROUND

The Paul Coverdell National Acute Stroke Registry (PCNASR) is a U.S. based national registry designed to monitor and improve the quality of acute stroke care delivered by hospitals. The registry monitors care through specific performance measures, the accuracy of which depends in part on the reliability of the individual data elements used to construct them. This study describes the inter-rater reliability of data elements collected in Michigan's state-based prototype of the PCNASR.

METHODS

Over a 6-month period, 15 hospitals participating in the Michigan PCNASR prototype submitted data on 2566 acute stroke admissions. Trained hospital staff prospectively identified acute stroke admissions, abstracted chart information, and submitted data to the registry. At each hospital 8 randomly selected cases were re-abstracted by an experienced research nurse. Inter-rater reliability was estimated by the kappa statistic for nominal variables, and intraclass correlation coefficient (ICC) for ordinal and continuous variables. Factors that can negatively impact the kappa statistic (i.e., trait prevalence and rater bias) were also evaluated.

RESULTS

A total of 104 charts were available for re-abstraction. Excellent reliability (kappa or ICC > 0.75) was observed for many registry variables including age, gender, black race, hemorrhagic stroke, discharge medications, and modified Rankin Score. Agreement was at least moderate (i.e., 0.75 > kappa >/=; 0.40) for ischemic stroke, TIA, white race, non-ambulance arrival, hospital transfer and direct admit. However, several variables had poor reliability (kappa < 0.40) including stroke onset time, stroke team consultation, time of initial brain imaging, and discharge destination. There were marked systematic differences between hospital abstractors and the audit abstractor (i.e., rater bias) for many of the data elements recorded in the emergency department.

CONCLUSION

The excellent reliability of many of the data elements supports the use of the PCNASR to monitor and improve care. However, the poor reliability for several variables, particularly time-related events in the emergency department, indicates the need for concerted efforts to improve the quality of data collection. Specific recommendations include improvements to data definitions, abstractor training, and the development of ED-based real-time data collection systems.