Application of change point analysis to daily influenza-like illness emergency department visits

Background: The utility of healthcare utilization data from US emergency departments (EDs) for rapid monitoring of changes in influenza-like illness (ILI) activity was highlighted during the recent influenza A (H1N1) pandemic. Monitoring has tended to rely on detection algorithms, such as the Early Aberration Reporting System (EARS), which are limited in their ability to detect subtle changes and identify disease trends. Objective: To evaluate a complementary approach, change point analysis (CPA), for detecting changes in the incidence of ED visits due to ILI. Methodology and principal findings Data collected through the Distribute project (isdsdistribute.org), which aggregates data on ED visits for ILI from over 50 syndromic surveillance systems operated by state or local public health departments were used. The performance was compared of the cumulative sum (CUSUM) CPA method in combination with EARS and the performance of three CPA methods (CUSUM, structural change model and Bayesian) in detecting change points in daily time-series data from four contiguous US states participating in the Distribute network. Simulation data were generated to assess the impact of autocorrelation inherent in these time-series data on CPA performance. The CUSUM CPA method was robust in detecting change points with respect to autocorrelation in time-series data (coverage rates at 90% when −0.2≤ρ≤0.2 and 80% when −0.5≤ρ≤0.5). During the 2008–9 season, 21 change points were detected and ILI trends increased significantly after 12 of these change points and decreased nine times. In the 2009–10 flu season, we detected 11 change points and ILI trends increased significantly after two of these change points and decreased nine times. Using CPA combined with EARS to analyze automatically daily ED-based ILI data, a significant increase was detected of 3% in ILI on April 27, 2009, followed by multiple anomalies in the ensuing days, suggesting the onset of the H1N1 pandemic in the four contiguous states. Conclusions and significance As a complementary approach to EARS and other aberration detection methods, the CPA method can be used as a tool to detect subtle changes in time-series data more effectively and determine the moving direction (ie, up, down, or stable) in ILI trends between change points. The combined use of EARS and CPA might greatly improve the accuracy of outbreak detection in syndromic surveillance systems

Self-Reported Fever and Measured Temperature in Emergency Department Records Used for Syndromic Surveillance

Many public health agencies monitor population health using syndromic surveillance, generally employing information from emergency department (ED) visit records. When combined with other information, objective evidence of fever may enhance the accuracy with which surveillance systems detect syndromes of interest, such as influenza-like illness. This study found that patient chief complaint of self-reported fever was more readily available in ED records than measured temperature and that the majority of patients with an elevated temperature recorded also self-reported fever. Due to its currently limited availability, we conclude that measured temperature is likely to add little value to self-reported fever in syndromic surveillance for febrile illness using ED records

A New Approach to Monitoring Dengue Activity

Discusses informal surveillance tools for monitoring dengue activity, such as ProMED, GPHIN HealthMap and BioCaster

Risk Index Score (RISc)

The main objective of this study was to develop and validate a computer-based statistical algorithm based on a multivariable logistic model that can be translated into a simple scoring system in order to ascertain stroke cases using hospital admission medical records data. This algorithm, the Risk Index Score (RISc), was developed using data collected prospectively by the Brain Attack Surveillance in Corpus Christ (BASIC) project. The validity of the RISc was evaluated by estimating the concordance of scoring system stroke ascertainment to stroke ascertainment accomplished by physician review of hospital admission records. The goal of this study was to develop a rapid, simple, efficient, and accurate method to ascertain the incidence of stroke from routine hospital admission hospital admission records for epidemiologic investigations. The main objectives of this study were to develop and validate a computer-based statistical algorithm based on a multivariable logistic model that could be translated into a simple scoring system to ascertain stroke cases using hospital admission medical records data. (Abstract shortened by UMI.

Longer procedural times are independently associated with symptomatic intracranial hemorrhage in patients with large vessel occlusion stroke undergoing thrombectomy

BACKGROUND: Time to reperfusion is an essential factor in determination of outcomes in acute ischemic stroke (AIS). OBJECTIVE: To establish the effect of the procedural time on the clinical outcomes of patients with AIS. METHODS: Data from all consecutive patients who underwent mechanical thrombectomy between September 2010 and July 2012 were analysed retrospectively. The variable of interest was procedural time (defined as time from groin puncture to final recanalization time). Outcome measures included the rates of symptomatic intracranial hemorrhage (sICH, defined as any parenchymal hematoma-eg, PH-1/PH-2), final infarct volume, 90-day mortality, and independent functional outcomes (modified Rankin Scale 0-2) at 90 days. RESULTS: The cohort included 242 patients with a mean age of 65.5±14.2 and median baseline National Institutes of Health Stroke Scale score 20. 51% of the patients were female. The mean procedure time was significantly shorter in patients with a good outcome (86.7 vs 73.1 min, respectively, p=0.0228). Patients with SICH had significantly higher mean procedure time than patients without SICH (79.67 vs 104.5 min, respectively; p=0.0319), which remained significant when controlling for the previous factors (OR=0.974, 95% CI 0.957 to 0.991). No correlation was found between the volume of infarction and the procedure time (r=0.10996, p=0.0984). No association was seen between procedure time and 90-day mortality (77.8 vs 88.2 min in survivals vs deaths, respectively; p=0.0958). CONCLUSIONS: Our data support an association between the risk of SICH and a longer procedure time, but no association between procedural times and the final infarction volume or long-term functional outcomes was found