Pilot test of an accrual Common Metric for the NIH Clinical and Translational Science Awards (CTSA) Consortium: Metric feasibility and data quality

Failure to accrue participants into clinical trials incurs economic costs, wastes resources, jeopardizes answering research questions meaningfully, and delays translating research discoveries into improved health. This paper reports the results of a pilot test of the Median Accrual Ratio (MAR) metric developed as a part of the Common Metrics Initiative of the NIH’s National Center for Advancing Translational Science (NCATS) Clinical and Translational Science Award (CTSA) Consortium. Using the metric is intended to enhance the ability of the CTSA Consortium and its “hubs” to increase subject accrual into trials within expected timeframes. The pilot test was undertaken at Tufts Clinical and Translational Science Institute (CTSI) with eight CTSA Consortium hubs. We describe the pilot test methods, and results regarding feasibility of collecting metric data and the quality of data that was collected. Participating hubs welcomed the opportunity to assess accrual efforts, but experienced challenges in collecting accrual metric data due to insufficient infrastructure and inconsistent implementation of electronic data systems and lack of uniform data definitions. Also, the metric could not be constructed for all trial designs, particularly those using competitive enrollment strategies. We offer recommendations to address the identified challenges to facilitate progress to broad accrual metric data collection and use.

Models and Surveillance Systems to Detect and Predict West Nile Virus Outbreaks

Over the past 20 yr, many models have been developed to predict risk for West Nile virus (WNV; Flaviviridae: Flavivirus) disease in the human population. These models have aided our understanding of the meteorological and land-use variables that drive spatial and temporal patterns of human disease risk. During the same period, electronic data systems have been adopted by surveillance programs across much of the United States, including a growing interest in integrated data services that preserve the autonomy and attribution of credit to originating agencies but facilitate data sharing, analysis, and visualization at local, state, and national scales. At present, nearly all predictive models have been limited to the scientific literature, with few having been implemented for use by public-health and vector-control decision makers. The current article considers the development of models for spatial patterns, early warning, and early detection of WNV over the last 20 yr and considers some possible paths toward increasing the utility of these models for guiding interventions.

A Tale of Two Turnarounds at EDS: The Jordan Rules

The case briefly describes the history of Electronic Data Systems (EDS) under Ross Perot and GM before turning to the beginning of a tumultuous decade in the late 1990s. As the turn of the century approached, EDS made critical strategic missteps such as missing opportunities in the Internet space, overlooking the onset of client-server computing, and failing to obtain major Y2K-related projects. The company attempted a turnaround by replacing the CEO with Dick Brown, whose leadership helped streamline the sprawling company. Despite initial successes, Brown's tenure ultimately ended in failure, due largely to his failure to recognize the growing Indian market and his willingness to buy business at the expense of the company's margin. The disastrous multibillion-dollar Navy & Marine Corp Intranet contract typified the type of high-profile transactions that Brown pursued, often boosting EDS's stock price in the short term while eroding its cash flow short term and its profitability over the long term. EDS management went through several stages of the turnaround process: the blinded phase, the inactive phase, and the faulty action phase, until Michael Jordan replaced Brown as CEO and enacted a three-tiered operational, strategic, and financial turnaround.EDS's near-decade of turnaround efforts takes students through every phase of the turnaround process and demonstrates that even initially successful turnaround efforts can become distracted, rendering them ineffective. The case will show both a failed turnaround and a subsequent successful one, while adding an international component with respect to EDS's overlooking an important, growing Indian market.

Increasing the efficiency and yield of a tuberculosis contact investigation through electronic data systems matching

Background Electronic health data may improve the timeliness and accuracy of resource-intense contact investigations (CIs) in healthcare settings. Methods In September 2013, we initiated a CI around a healthcare worker (HCW) with infectious tuberculosis (TB) who worked in a maternity ward. Two sources of electronic health data were employed: hospital-based electronic medical records (EMRs), to identify patients exposed to the HCW, and an electronic immunization registry, to obtain contact information for exposed infants and their providers at two points during follow-up. Results Among 954 patients cared for in the maternity ward during the HCW’s infectious period, the review of EMRs identified 285 patients (30%) who interacted with the HCW and were, thus, exposed to TB. Matching infants to the immunization registry offered new provider information for 52% and 30% of the infants in the first and second matches. Providers reported evaluation results for the majority of patients (66%). Conclusion Data matching improved the efficiency and yield of this CI, thereby demonstrating the usefulness of enhancing CIs with electronic health data.