Common data elements for secondary use of electronic health record data for clinical trial execution and serious adverse event reporting

Background: Data capture is one of the most expensive phases during the conduct of a clinical trial and the increasing use of electronic health records (EHR) offers significant savings to clinical research. To facilitate these secondary uses of routinely collected patient data, it is beneficial to know what data elements are captured in clinical trials. Therefore our aim here is to determine the most commonly used data elements in clinical trials and their availability in hospital EHR systems.Methods: Case report forms for 23 clinical trials in differing disease areas were analyzed. Through an iterative and consensus-based process of medical informatics professionals from academia and trial experts from the European pharmaceutical industry, data elements were compiled for all disease areas and with special focus on the reporting of adverse events. Afterwards, data elements were identified and statistics acquired from hospital sites providing data to the EHR4CR project.Results: The analysis identified 133 unique data elements. Fifty elements were congruent with a published data inventory for patient recruitment and 83 new elements were identified for clinical trial execution, including adverse event reporting. Demographic and laboratory elements lead the list of available elements in hospitals EHR systems. For the reporting of serious adverse events only very few elements could be identified in the patient records.Conclusions: Common data elements in clinical trials have been identified and their availability in hospital systems elucidated. Several elements, often those related to reimbursement, are frequently available whereas more specialized elements are ranked at the bottom of the data inventory list. Hospitals that want to obtain the benefits of reusing data for research from their EHR are now able to prioritize their efforts based on this common data element list.</p

Baseline Characteristics and Prescription Patterns of Standard Drugs in Patients with Angiographically Determined Coronary Artery Disease and Renal Failure (CAD-REF Registry)

BACKGROUND: Chronic kidney disease (CKD) is strongly associated with coronary artery disease (CAD). We established a prospective observational nationwide multicenter registry to evaluate current treatment and outcomes in patients with both CKD and angiographically documented CAD. METHODS: In 32 cardiological centers 3,352 CAD patients with ≥50% stenosis in at least one coronary artery were enrolled and classified according to their estimated glomerular filtration rate and proteinuria into one of five stages of CKD or as a control group. RESULTS: 2,723 (81.2%) consecutively enrolled patients suffered from CKD. Compared to controls, CKD patients had a higher prevalence of diabetes, hypertension, peripheral artery diseases, heart failure, and valvular heart disease (each p<0.001). Myocardial infarctions (p = 0.02), coronary bypass grafting, valve replacements and pacemaker implantations had been recorded more frequently (each p<0.001). With advanced CKD, the number of diseased coronary vessels and the proportion of patients with reduced left ventricular ejection fraction (LVEF) increased significantly (both p<0.001). Percutaneous coronary interventions were performed less frequently (p<0.001) while coronary bypass grafting was recommended more often (p = 0.04) with advanced CKD. With regard to standard drugs in CAD treatment, prescriptions were higher in our registry than in previous reports, but beta-blockers (p = 0.008), and angiotensin-converting-enzyme inhibitors and/or angiotensin-receptor blockers (p<0.001) were given less often in higher CKD stages. In contrast, in the subgroup of patients with moderately to severely reduced LVEF the prescription rates did not differ between CKD stages. In-hospital mortality increased stepwise with each CKD stage (p = 0.02). COMCLUSIONS: In line with other studies comprising CKD cohorts, patients’ morbidity and in-hospital mortality increased with the degree of renal impairment. Although cardiologists’ drug prescription rates in CAD-REF were higher than in previous studies, they were still lower especially in advanced CKD stages compared to cohorts treated by nephrologists

Vegetative Ecological Characteristics of Restored Reed (Phragmites australis) Wetlands in the Yellow River Delta, China

In this study, we compared ecological characteristics of wetland vegetation in a series of restoration projects that were carried out in the wetlands of Yellow River Delta. The investigated characteristics include plant composition structure, species diversity and community similarity in three kinds of Phragmites australis wetlands, i.e. restored P. australis wetlands (R1, R2, R3 and R4: restored in 2002, 2005, 2007 and 2009, respectively), natural P. australis wetland (N) and degraded P. australis wetland (D) to assess the process of wetlands restoration. The coverage of the R1 was 99%, which was similar to natural wetland. Among all studied wetlands, the highest and lowest stem density was observed in R1 and R2, respectively, Plant height and stem diameter show the same trend as N > R2 > R1 > R3 > D > R4. Species diversity of restored P. australis wetlands became closed to natural wetland. Both species richness and Shannon–Wiener index had similar tendency: increased first and then decreased with restored time. The highest species richness and species diversity were observed in R2, while the lowest values of those parameters were found in natural P. australis wetland. Similarity indexes between restored wetlands and natural wetland increased with the restoration time, but they were still less than 50%. The results indicate that the vegetation of P. australis wetlands has experienced a great improvement after several years’ restoration, and it is feasible to restored degraded P. australis wetlands by pouring fresh water into those wetlands in the Yellow River Delta. However, it is notable that costal degraded P. australis wetland in this region may take years to decades to reach the status of natural wetland

Additional file 1: of S2O – A software tool for integrating research data from general purpose statistic software into electronic data capture systems

Sample SPSS file. The data contains variables with all possible data types and example cases with values. (SAV 3 kb

The Effects of Smiling and Frowning on Perceived Affect and Exertion While Physically Active

Philippen P, Bakker FC, Oudejans RRD, Canal-Bruland R. The Effects of Smiling and Frowning on Perceived Affect and Exertion While Physically Active. Journal of Sport Behavior. 2012;35(3):337-353

ODM Data Analysis—A tool for the automatic validation, monitoring and generation of generic descriptive statistics of patient data

<div><p>Introduction</p><p>A required step for presenting results of clinical studies is the declaration of participants demographic and baseline characteristics as claimed by the FDAAA 801. The common workflow to accomplish this task is to export the clinical data from the used electronic data capture system and import it into statistical software like SAS software or IBM SPSS. This software requires trained users, who have to implement the analysis individually for each item. These expenditures may become an obstacle for small studies. Objective of this work is to design, implement and evaluate an open source application, called ODM Data Analysis, for the semi-automatic analysis of clinical study data.</p><p>Methods</p><p>The system requires clinical data in the CDISC Operational Data Model format. After uploading the file, its syntax and data type conformity of the collected data is validated. The completeness of the study data is determined and basic statistics, including illustrative charts for each item, are generated. Datasets from four clinical studies have been used to evaluate the application’s performance and functionality.</p><p>Results</p><p>The system is implemented as an open source web application (available at <a href="https://odmanalysis.uni-muenster.de" target="_blank">https://odmanalysis.uni-muenster.de</a>) and also provided as Docker image which enables an easy distribution and installation on local systems. Study data is only stored in the application as long as the calculations are performed which is compliant with data protection endeavors. Analysis times are below half an hour, even for larger studies with over 6000 subjects.</p><p>Discussion</p><p>Medical experts have ensured the usefulness of this application to grant an overview of their collected study data for monitoring purposes and to generate descriptive statistics without further user interaction. The semi-automatic analysis has its limitations and cannot replace the complex analysis of statisticians, but it can be used as a starting point for their examination and reporting.</p></div

Pragmatic MDR: a metadata repository with bottom-up standardization of medical metadata through reuse

Background!#!The variety of medical documentation often leads to incompatible data elements that impede data integration between institutions. A common approach to standardize and distribute metadata definitions are ISO/IEC 11179 norm-compliant metadata repositories with top-down standardization. To the best of our knowledge, however, it is not yet common practice to reuse the content of publicly accessible metadata repositories for creation of case report forms or routine documentation. We suggest an alternative concept called pragmatic metadata repository, which enables a community-driven bottom-up approach for agreeing on data collection models. A pragmatic metadata repository collects real-world documentation and considers frequent metadata definitions as high quality with potential for reuse.!##!Methods!#!We implemented a pragmatic metadata repository proof of concept application and filled it with medical forms from the Portal of Medical Data Models. We applied this prototype in two use cases to demonstrate its capabilities for reusing metadata: first, integration into a study editor for the suggestion of data elements and, second, metadata synchronization between two institutions. Moreover, we evaluated the emergence of bottom-up standards in the prototype and two medical data managers assessed their quality for 24 medical concepts.!##!Results!#!The resulting prototype contained 466,569 unique metadata definitions. Integration into the study editor led to a reuse of 1836 items and item groups. During the metadata synchronization, semantic codes of 4608 data elements were transferred. Our evaluation revealed that for less complex medical concepts weak bottom-up standards could be established. However, more diverse disease-related concepts showed no convergence of data elements due to an enormous heterogeneity of metadata. The survey showed fair agreement (K!##!Conclusions!#!We demonstrated the feasibility of the pragmatic metadata repository concept for medical documentation. Applications of the prototype in two use cases suggest that it facilitates the reuse of data elements. Our evaluation showed that bottom-up standardization based on a large collection of real-world metadata can yield useful results. The proposed concept shall not replace existing top-down approaches, rather it complements them by showing what is commonly used in the community to guide other researchers