Pragmatic clinical trials embedded in healthcare systems: generalizable lessons from the NIH Collaboratory

Background: The clinical research enterprise is not producing the evidence decision makers arguably need in a timely and cost effective manner; research currently involves the use of labor-intensive parallel systems that are separate from clinical care. The emergence of pragmatic clinical trials (PCTs) poses a possible solution: these large-scale trials are embedded within routine clinical care and often involve cluster randomization of hospitals, clinics, primary care providers, etc. Interventions can be implemented by health system personnel through usual communication channels and quality improvement infrastructure, and data collected as part of routine clinical care. However, experience with these trials is nascent and best practices regarding design operational, analytic, and reporting methodologies are undeveloped. Methods: To strengthen the national capacity to implement cost-effective, large-scale PCTs, the Common Fund of the National Institutes of Health created the Health Care Systems Research Collaboratory (Collaboratory) to support the design, execution, and dissemination of a series of demonstration projects using a pragmatic research design. Results: In this article, we will describe the Collaboratory, highlight some of the challenges encountered and solutions developed thus far, and discuss remaining barriers and opportunities for large-scale evidence generation using PCTs. Conclusion: A planning phase is critical, and even with careful planning, new challenges arise during execution; comparisons between arms can be complicated by unanticipated changes. Early and ongoing engagement with both health care system leaders and front-line clinicians is critical for success. There is also marked uncertainty when applying existing ethical and regulatory frameworks to PCTS, and using existing electronic health records for data capture adds complexity

The Effects of Training School Staff for Utilizing Student Monitoring System Data

Part 1: Why Do We Need New Educational Management Information Systems?International audienceThe Dutch School Inspectorate defines achievement-oriented work (AOW) as the maximization of student performance in a systematic and goal-oriented way. Research by the Inspectorate shows that students in achievement-oriented schools perform better than students in schools that meet the criteria for achievement-oriented work less. The University of Twente has developed a training course in which school teams learn to work in an achievement-oriented way. Parallel to the training activities, the effects of training schools are studied. The research findings show that the training course has a positive effect on attitudes towards AOW, as well as on knowledge and skills relevant for AOW of school staff

Effects of a Data-Based Decision Making Intervention on Student Achievement

Data-based decision making (DBDM) is becoming important for teachers due to increasing amounts of digital feedback on student performance. In the quasi-experimental study reported here, teachers, principals, and academic coaches from 42 schools were trained for two years in using the results of half-year interim assessments for providing students with tailor-made instruction. Our results did not show any main effects of this DBDM training trajectory on student achievement but did indicate interaction effects with students’ low prior achievement levels and socioeconomic status. Teachers experience difficulties in translating student progress data into adaptive instruction in the classroom. Implications of our findings for teacher professionalization are discussed