The Biomedical Research Hub: a federated platform for patient research data.

OBJECTIVE: The objective was to develop and operate a cloud-based federated system for managing, analyzing, and sharing patient data for research purposes, while allowing each resource sharing patient data to operate their component based upon their own governance rules. The federated system is called the Biomedical Research Hub (BRH). MATERIALS AND METHODS: The BRH is a cloud-based federated system built over a core set of software services called framework services. BRH framework services include authentication and authorization, services for generating and assessing findable, accessible, interoperable, and reusable (FAIR) data, and services for importing and exporting bulk clinical data. The BRH includes data resources providing data operated by different entities and workspaces that can access and analyze data from one or more of the data resources in the BRH. RESULTS: The BRH contains multiple data commons that in aggregate provide access to over 6 PB of research data from over 400 000 research participants. DISCUSSION AND CONCLUSION: With the growing acceptance of using public cloud computing platforms for biomedical research, and the growing use of opaque persistent digital identifiers for datasets, data objects, and other entities, there is now a foundation for systems that federate data from multiple independently operated data resources that expose FAIR application programming interfaces, each using a separate data model. Applications can be built that access data from one or more of the data resources.

A research roadmap for next-generation sequencing informatics.

Next-generation sequencing technologies are fueling a wave of new diagnostic tests. Progress on a key set of nine research challenge areas will help generate the knowledge required to advance effectively these diagnostics to the clinic.

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.

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.

Use of data mining at the Food and Drug Administration.

OBJECTIVES: This article summarizes past and current data mining activities at the United States Food and Drug Administration (FDA). TARGET AUDIENCE: We address data miners in all sectors, anyone interested in the safety of products regulated by the FDA (predominantly medical products, food, veterinary products and nutrition, and tobacco products), and those interested in FDA activities. SCOPE: Topics include routine and developmental data mining activities, short descriptions of mined FDA data, advantages and challenges of data mining at the FDA, and future directions of data mining at the FDA.

Periprocedural cost-effectiveness analysis of mechanical thrombectomy for acute ischemic stroke in the stent retriever era.

BACKGROUND: Early reperfusion is critical for favorable outcomes in acute ischemic stroke (AIS). Stent retrievers lead to faster and more complete reperfusion than previous technologies. Our aim is to compare the cost-effectiveness of stent retrievers to the previous mechanical thrombectomy devices. METHODS: Retrospective review of endovascularly treated large-vessel AIS. Data from all consecutive patients who underwent thrombectomy from January 2012 through November 2012 were collected. Baseline characteristics, the total procedural cost, the rates of successful recanalization [modified thrombolysis in cerebral ischemia (mTICI) scores of 2b or 3], and the length of stay at the hospital were compared between the stent retriever (SR) and the non-stent retriever (NSR) groups. RESULTS: After excluding the patients who underwent concomitant extracranial stenting (n = 22) or received intra-arterial tissue plasminogen activator only (n = 6), the entire cohort included 150 patients. The cost of the reperfusion procedure was significantly higher in the SR compared to the NSR group (USD 13,419 vs. 9,308, p <0.001). We were unable to demonstrate a statistically significant difference in the rates of mTICI 2b/3 reperfusion (81 vs. 74%, p = 0.337) or the length of stay (11.1 ± 9.1 vs. 12.8 ± 9.6 days, p = 0.260) amongst the SR and the NSR patients. CONCLUSION: The procedural costs of thrombectomy for AIS are increasing and account for the bulk of hospitalization reimbursement. The impact of these expenditures in the long-term sustainability of stroke centers deserves greater consideration. While it is likely that the SR technology results in higher rates of optimal reperfusion, better clinical outcomes, and shorter lengths of stay, larger studies are needed to prove its cost-effectiveness.

Signal detection using change point analysis in postmarket surveillance.

PURPOSE: Signal detection methods have been used extensively in postmarket surveillance to identify elevated risks of adverse events associated with medical products (drugs, vaccines, and devices). However, current popular disproportionality methods ignore useful information such as trends when the data are aggregated over time for signal detection. METHODS: In this paper, we applied change point analysis (CPA) to trend analysis of medical products in a spontaneous adverse event reporting system. CPA was used to detect the time point at which statistical properties of a sequence of observations change over time. Two CPA approaches, change in mean and change in variance, were demonstrated by an example using neurostimulator adverse event dataset. RESULTS: Two significant change points associated with upward trends were detected in June 2008 (n = 20, p < 0.001) and May 2011 (n = 51, p = 0.003). Further investigation confirmed battery issues and expansion of the indication for use could be possible causes for the occurrence of these change points. Two time points showed extremely low number of loss of therapy events, two cases in October 2009 and three in November 2009, which could be the result of reporting issues such as underreporting. CONCLUSION: As a complimentary tool to current signal detection efforts at FDA, CPA can be used to detect changes in the association between medical products and adverse events over time. Detecting these changes could be critical for public health regulation, adverse events surveillance, product recalls, and regulators' understanding of the connection between adverse events and other events regarding regulated products. © 2015 The Authors. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons, Ltd.

A novel approach to diagnose reversible cerebral vasoconstriction syndrome: a case series.

BACKGROUND: Reversible cerebral vasoconstriction syndrome (RCVS) is classically diagnosed based on the presence of severe thunderclap headache, focal neurologic symptoms, and the radiographic findings of reversible diffuse segmental cerebral vasoconstriction. We present a diagnostic test that may assist in the clinical diagnosis and facilitate treatment. METHODS: From October 1, 2010, to August 1, 2013, we identified consecutive patients who presented with a presumptive diagnosis of RCVS and underwent cerebral diagnostic angiography with intra-arterial (IA) vasodilator therapy. Medical records including clinical presentation, radiographic, and angiographic images were all reviewed. RESULTS: We identified a total of 7 patients (4 females; age range, 22-56; mean, 45 years) who met our inclusion criteria. Four patients received a combination of milrinone and nicardipine infusion either in the internal carotid arteries or in the left vertebral artery; the remaining patients received IA therapy solely with either nicardipine or milrinone. Five patients had a positive angiographic response, defined as significant improvement or resolution of the blood vessels irregularities. All 5 patients had a definite discharge diagnosis of RCVS. The remaining 2 patients had a negative angiographic response and based on their clinical and radiographic course had a final diagnosis of intracranial atherosclerotic disease. CONCLUSIONS: Our small case series suggest that IA administration of vasodilators is safe and may aid in distinguishing vasodilator responsive syndromes such as RCVS from other causes. Further study is required with long-term clinical outcome to determine the utility of this diagnostic test.

Clinical, angiographic and radiographic outcome differences among mechanical thrombectomy devices: initial experience of a large-volume center.

BACKGROUND AND PURPOSE: Higher reperfusion rates have been established with endovascular treatment of acute ischemic stroke (AIS). There are limited data on the comparative performance of mechanical thrombectomy devices. METHODS: A retrospective single-center analysis was undertaken of all consecutive patients who underwent thrombectomy using Merci, Penumbra or stent retrievers (SR) from September 2010 to November 2012. Baseline characteristics, rates of successful recanalization (modified Thrombolysis in Cerebral Infarction (mTICI) score 2b-3), symptomatic intracerebral hemorrhage (sICH), final infarct volume, 90-day mortality and independent functional outcomes at 90 days were compared across the three devices. RESULTS: Our cohort included 287 patients. There were mild imbalances in baseline characteristics with trends towards higher National Institutes of Health Stroke Scale (NIHSS) score in patients in the Merci group (SR=18 vs Merci=21 vs Penumbra=19, p=0.06) and lower Alberta Stroke Program Early CT Score (ASPECTS) in patients in the SR group (>7: SR=51% vs Merci=61% vs Penumbra=62%, p=0.12). On univariate analysis there were no differences in the rate of sICH (SR=7% vs Merci=7% vs Penumbra=6%, p=0.921) and infarct volume (SR=61.5 mL vs Merci=69.5 mL vs Penumbra=59.2 mL, p=0.621). Trends towards better functional outcomes were found with Penumbra and SR vs Merci (41% vs 36% vs 25%, respectively, p=0.079). Complete or near complete reperfusion (mTICI 2b-3) was higher in the SR and Penumbra groups than in the Merci group (86% vs 78% vs 70%, respectively, p=0.027). Binary logistic regression showed that SR was an independent predictor of good functional outcome (OR 2.27, 95% CI 1.018 to 5.048; p=0.045). CONCLUSIONS: Although our initial data confirm the superiority of SR technology over the Merci device, there was no significant difference in near complete/complete reperfusion, final infarct volumes or clinical outcomes between SR and Penumbra thromboaspiration.

Digital drug safety surveillance: monitoring pharmaceutical products in twitter.

BACKGROUND: Traditional adverse event (AE) reporting systems have been slow in adapting to online AE reporting from patients, relying instead on gatekeepers, such as clinicians and drug safety groups, to verify each potential event. In the meantime, increasing numbers of patients have turned to social media to share their experiences with drugs, medical devices, and vaccines. OBJECTIVE: The aim of the study was to evaluate the level of concordance between Twitter posts mentioning AE-like reactions and spontaneous reports received by a regulatory agency. METHODS: We collected public English-language Twitter posts mentioning 23 medical products from 1 November 2012 through 31 May 2013. Data were filtered using a semi-automated process to identify posts with resemblance to AEs (Proto-AEs). A dictionary was developed to translate Internet vernacular to a standardized regulatory ontology for analysis (MedDRA(®)). Aggregated frequency of identified product-event pairs was then compared with data from the public FDA Adverse Event Reporting System (FAERS) by System Organ Class (SOC). RESULTS: Of the 6.9 million Twitter posts collected, 4,401 Proto-AEs were identified out of 60,000 examined. Automated, dictionary-based symptom classification had 86 % recall and 72 % precision [corrected]. Similar overall distribution profiles were observed, with Spearman rank correlation rho of 0.75 (p < 0.0001) between Proto-AEs reported in Twitter and FAERS by SOC. CONCLUSION: Patients reporting AEs on Twitter showed a range of sophistication when describing their experience. Despite the public availability of these data, their appropriate role in pharmacovigilance has not been established. Additional work is needed to improve data acquisition and automation.

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.

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.

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.