Social media in public health.

INTRODUCTION OR BACKGROUND: While social media interactions are currently not fully understood, as individual health behaviors and outcomes are shared online, social media offers an increasingly clear picture of the dynamics of these processes. SOURCES OF DATA: Social media is becoming an increasingly common platform among clinicians and public health officials to share information with the public, track or predict diseases. AREAS OF AGREEMENT: Social media can be used for engaging the public and communicating key public health interventions, while providing an important tool for public health surveillance. AREAS OF CONTROVERSY: Social media has advantages over traditional public health surveillance, as well as limitations, such as poor specificity, that warrant additional study. GROWING POINTS: Social media can provide timely, relevant and transparent information of public health importance; such as tracking or predicting the spread or severity of influenza, west nile virus or meningitis as they propagate in the community, and, in identifying disease outbreaks or clusters of chronic illnesses. AREAS TIMELY FOR DEVELOPING RESEARCH: Further work is needed on social media as a valid data source for detecting or predicting diseases or conditions. Also, whether or not it is an effective tool for communicating key public health messages and engaging both, the general public and policy-makers.

Transportation barriers to accessing health care for urban children.

The Texas Children's Hospital Residents' Primary Care Group Clinic provides primary care to urban low-income children. The objective of this cross-sectional study was to investigate the impact of transportation problems on a family's ability to keep an appointment. One hundred eighty-three caregivers of children with an appointment were interviewed. Caregivers who kept their appointment were compared with those who did not with respect to demographic and transportation-related characteristics. Logistic regression modeling predicted caregivers with the following characteristics were more likely not to keep an appointment: not using a car to the last kept appointment, not keeping an appointment in the past due to transportation problems, having more than two people in the household, and not keeping an appointment in the past due to reasons other than transportation problems. Future research should focus on developing interventions to help low-income urban families overcome non-financial access barriers, including transportation problems.

OpenFDA: an innovative platform providing access to a wealth of FDA's publicly available data.

OBJECTIVE: The objective of openFDA is to facilitate access and use of big important Food and Drug Administration public datasets by developers, researchers, and the public through harmonization of data across disparate FDA datasets provided via application programming interfaces (APIs). MATERIALS AND METHODS: Using cutting-edge technologies deployed on FDA's new public cloud computing infrastructure, openFDA provides open data for easier, faster (over 300 requests per second per process), and better access to FDA datasets; open source code and documentation shared on GitHub for open community contributions of examples, apps and ideas; and infrastructure that can be adopted for other public health big data challenges. RESULTS: Since its launch on June 2, 2014, openFDA has developed four APIs for drug and device adverse events, recall information for all FDA-regulated products, and drug labeling. There have been more than 20 million API calls (more than half from outside the United States), 6000 registered users, 20,000 connected Internet Protocol addresses, and dozens of new software (mobile or web) apps developed. A case study demonstrates a use of openFDA data to understand an apparent association of a drug with an adverse event. CONCLUSION: With easier and faster access to these datasets, consumers worldwide can learn more about FDA-regulated products.

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.

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.

NHIN, RHIOs, and Public Health.

Public health plays a critical role in forming the building blocks for community or regional health-information sharing, which is essential to the long-term viability of a Nationwide Health Information Network (NHIN) and the Regional Health Information Organizations (RHIOs). By contributing to its visions, policies, processes, standards, and needs/requirements, public health will close the loop within an NHIN and the RHIOs environment. In this article we illustrate public health's essential role in an NHIN and the RHIOs by examining the mutual benefits to healthcare and public health.