Showing papers on "Electronic data capture published in 2011"

The Knowledge Program: an innovative, comprehensive electronic data capture system and warehouse.

Abstract: Data contained in the electronic health record (EHR) present a tremendous opportunity to improve quality-of-care and enhance research capabilities. However, the EHR is not structured to provide data for such purposes: most clinical information is entered as free text and content varies substantially between providers. Discrete information on patients' functional status is typically not collected. Data extraction tools are often unavailable. We have developed the Knowledge Program (KP), a comprehensive initiative to improve the collection of discrete clinical information into the EHR and the retrievability of data for use in research, quality, and patient care. A distinct feature of the KP is the systematic collection of patient-reported outcomes, which is captured discretely, allowing more refined analyses of care outcomes. The KP capitalizes on features of the Epic EHR and utilizes an external IT infrastructure distinct from Epic for enhanced functionality. Here, we describe the development and implementation of the KP.

Comparison of Electronic Data Capture (EDC) with the Standard Data Capture Method for Clinical Trial Data

Abstract: Background Traditionally, clinical research studies rely on collecting data with case report forms, which are subsequently entered into a database to create electronic records. Although well established, this method is time-consuming and error-prone. This study compares four electronic data capture (EDC) methods with the conventional approach with respect to duration of data capture and accuracy. It was performed in a West African setting, where clinical trials involve data collection from urban, rural and often remote locations. Methodology/Principal Findings Three types of commonly available EDC tools were assessed in face-to-face interviews; netbook, PDA, and tablet PC. EDC performance during telephone interviews via mobile phone was evaluated as a fourth method. The Graeco Latin square study design allowed comparison of all four methods to standard paper-based recording followed by data double entry while controlling simultaneously for possible confounding factors such as interview order, interviewer and interviewee. Over a study period of three weeks the error rates decreased considerably for all EDC methods. In the last week of the study the data accuracy for the netbook (5.1%, CI95%: 3.5–7.2%) and the tablet PC (5.2%, CI95%: 3.7–7.4%) was not significantly different from the accuracy of the conventional paper-based method (3.6%, CI95%: 2.2–5.5%), but error rates for the PDA (7.9%, CI95%: 6.0–10.5%) and telephone (6.3%, CI95% 4.6–8.6%) remained significantly higher. While EDC-interviews take slightly longer, data become readily available after download, making EDC more time effective. Free text and date fields were associated with higher error rates than numerical, single select and skip fields. Conclusions EDC solutions have the potential to produce similar data accuracy compared to paper-based methods. Given the considerable reduction in the time from data collection to database lock, EDC holds the promise to reduce research-associated costs. However, the successful implementation of EDC requires adjustment of work processes and reallocation of resources.

Enhancing the routine health information system in rural southern Tanzania: successes, challenges and lessons learned.

Abstract: OBJECTIVE To describe and evaluate the use of handheld computers for the management of Health Management Information System data. METHODS Electronic data capture took place in 11 sentinel health centres in rural southern Tanzania. Information from children attending the outpatient department (OPD) and the Expanded Program on Immunization vaccination clinic was captured by trained local school-leavers, supported by monthly supervision visits. Clinical data included malaria blood slides and haemoglobin colour scale results. Quality of captured data was assessed using double data entry. Malaria blood slide results from health centre laboratories were compared to those from the study's quality control laboratory. RESULTS The system took 5 months to implement, and few staffings or logistical problems were encountered. Over the following 12 months (April 2006-March 2007), 7056 attendances were recorded in 9880 infants aged 2-11 months, 50% with clinical malaria. Monthly supervision visits highlighted incomplete recording of information between OPD and laboratory records, where on average 40% of laboratory visits were missing the record of their corresponding OPD visit. Quality of microscopy from health facility laboratories was lower overall than that from the quality assurance laboratory. CONCLUSIONS Electronic capture of HMIS data was rapidly and successfully implemented in this resource-poor setting. Electronic capture alone did not resolve issues of data completeness, accuracy and reliability, which are essential for management, monitoring and evaluation; suggestions to monitor and improve data quality are made.

A Model for Dissemination and Independent Analysis of Industry Data

Abstract: Each day, patients and their physicians make treatment decisions with access to only a fraction of the relevant clinical research data. Many clinical studies, including randomized clinical trials, are never published in the biomedical literature.1,2 Among those that are published, key information is often not presented, such as data on specific outcomes and safety endpoints.3,4 Moreover, patient-level data from clinical trials are rarely available, leaving investigators to conduct meta-analyses of summary-level data, an approach with limitations.5 Current clinical research standards lack sufficiently strong requirements for transparency and availability. There are no uniform international standards requiring that study protocols, statistical analysis plans, and study results be made available, nor that completed clinical trial data be posted for independent analysis. Even data submitted to the U.S. Food and Drug Administration are not made publicly available.

Evaluation of Data Entry Errors and Data Changes to an Electronic Data Capture Clinical Trial Database

Abstract: Monitoring of clinical trials includes several disciplines, stakeholders, and skill sets. The aim of the present study was to identify database changes and data entry errors to an electronic data capture (EDC) clinical trial database, and to access the impact of the changes. To accomblish the aim, Target e*CRF was used as the EDC tool for a multinational, dose-finding, multicenter, double-blind, randomized, parallel, placebo-controlled trial to investigate efficacy and safety of a new treatment in men with lower urinary tract symptoms associated with benign prostatic hyperplasia. The main errors observed were simple transcription errors from the paper source documents to the EDC database. This observation was to be expected, since every transaction has an inherant error rate. What and how to monitor must be assessed within the risk-based monitoring section of the comprehensive data monitoring plan. With the advent of direct data entry, and the elimination of the requirement to transcribe from a paper source record to an EDC system, error rates should go down dramatically. In addition, protocol violations and data outside the normal range can be identified at the time of data entry and not days, weeks, and months after the fact.

Electronic data capture, documentation, and clinical decision support system

Abstract: An electronic data capture, documentation and clinical decision support system (EDDS) includes a user display and input device, where the device is configured to include symbolic language including icons, the icons being controllable based upon user input. Multiple input data feeds are provided from one or more external databases, and preferably from a user input device. A display presentation system cohorts or otherwise organizes the data received via the input data feeds. An external device control system serves to provide wireless remote control of medical devices. Optionally, a clinical decision support system for providing clinical information to the user, such as providing a diagnosis, suggested treatment, medication or other medical action. The recommended clinical action may be implemented automatically, or upon the further authorization of the medical professional.

Guidelines for fracture healing assessments in clinical trials. Part II: electronic data capture and image management systems--Global Adjudicator™ system.

Abstract: Adjudication of outcomes helps to reduce variation in outcome assessment when clinical judgement is used. Adjudication is extremely important when the outcome being measured is subjective, as in the assessment of fracture healing. Adjudication Committees have the potential to provide a systematic, independent, and unbiased method of determining fracture healing. In order to make the adjudication process less time consuming and more efficient, Global Research Solutions™, a Contract Research Organization which specialises in orthopaedic and surgical clinical trials, developed the Global Adjudicator™, a web-based system, to serve as both an image management system and electronic data capture system. This manuscript highlights the features of the Global Adjudicator™ and demonstrates the benefits of using a web-based adjudication system.

inSERT -- An NFC-based Self Reporting Questionnaire for Patients with Impaired Fine Motor Skills

Abstract: Self-reporting patient data are valuable feedback for medical treatment and care process, as well as for clinical trial studies and support of medical treatment. However, traditional paper-based medical patient longitudinal surveys or questionnaires for health and well-being status information are time- and cost-consuming, and may suffer from low patient compliance. Consequently, an NFC-based electronic data capture prototype called inSERT has been designed that allows quick and easy self-reporting for patients. inSERT allows patient monitoring enabling, electronic acquisition of well-being data right from the patient's home and real time representation of patient data, enabling direct medical intervention by physicians. The functional requirements for the inSERT system were determined through an extensive, user-centric elicitation process. We chose Near Field Communication (NFC) as a technology, for which the interaction paradigm is quick to learn and is intuitive, without prior knowledge being necessary, it is almost as simple as to fill out a paper-based questionnaire. Particularly for the target group (elderly people and people with impaired fine motor skills) - those who are not familiar with the use of mobile phones or computers - it makes NFC a very promising field compared to the control with touch based displays or computer mouse. The prototype is currently evaluated in a field test. The technical feasibility, implementation details, limitations and future research approaches are discussed in this paper.

Validity of an information and communication technology system for data capture in epidemiological studies.

Abstract: The Belgian National Institute of Health Insurance is implementing an oral health data registration and surveillance system. This study aimed to develop and validate a system of electronic data capture for oral health surveys at a national level - Oral Survey-B - and to identify the advantages and disadvantages of the electronic system in comparison with the traditional handwritten data capture. Six series of full-mouth recordings simulating the clinical examination of 6 patients were set up in a Powerpoint presentation. The validation was undertaken by 52 general practitioners. A randomized one-period crossover design was used with two formats of data capture, i.e. electronic followed by handwritten or handwritten followed by electronic system. Further, 6 benchmarked handwritten forms were transferred to the electronic format. For the electronic data capture, 86.5% of the practitioners had a correct completion rate of ≥95%. The corresponding value for the handwritten data capture and transfer was 78.8% (p = 0.25, McNemar test). The overall accuracy of forms without any error was 73.4% for the electronic and 62.5% for the handwritten data capture (p < 0.001, signed-rank test). Significantly lower percentages of errors and less time were observed for the electronic data capture (p < 0.001, signed-rank test). Practitioners considered the electronic data capture as being much more difficult to carry out (p < 0.001). As information technology has turned into an ever more necessary working tool in epidemiology, there should be an important potential for uptake of further improvements in electronic data capture in the future.

Development and use of a web-based data management system for a randomized clinical trial of adolescents and young adults.

Abstract: Recent advances in technology provide support for multisite, Web-based data-entry systems and the storage of data in a centralized location, resulting in immediate access to data for investigators, reduced participant burden and human entry error, and improved integrity of clinical trial data. The purpose of this article was to describe the development of a comprehensive, Web-based data management system for a multisite randomized behavioral intervention trial. Strategies used to create this study-specific data management system included interdisciplinary collaboration, design mapping, feasibility assessments, and input from an advisory board of former patients with characteristics similar to the targeted population. The resulting data management system and development strategies provide a template for other behavioral intervention studies.

Distributed randomization and supply management in clinical trials

Abstract: A distributed clinical trial system that provides configurability, reusability and integration of randomization and inventory configurations for different clinical trials with various electronic data capture (EDC) systems The distributed clinical trial system includes a method of randomizing subjects in a multi-arm clinical trial In accordance with a method, a subject identifier and a trial identifier are received from an EDC system The trial identifier indicates the multi-arm clinical trial and the subject identifier indicates a subject enrolled in the multi-arm clinical trial A randomization design previously configured for the multi-arm clinical trial is retrieved from a database based on the received trial identifier The subject identifier is assigned to an arm identifier of the multi-arm clinical trial based on the randomization design The arm identifier indicates an arm of the multi-arm clinical trial to which the subject has been assigned

A key risk indicator approach to central statistical monitoring in multicentre clinical trials: method development in the context of an ongoing large-scale randomized trial

Abstract: Background Monitoring in randomized trials is recommended as part of International Conference on Harmonisation Good Clinical Practice standards. On-site monitoring in multicentre trials is common but is costly and can be inefficient. Central statistical monitoring can be used to detect unusual data patterns, identify intentional or unintentional trial misconduct, and to prioritise on-site visits and additional training. Motivated by an ongoing international multicentre clinical trial of over 25,000 randomized participants with electronic data capture, we developed key risk indicator (KRI) methods for central statistical monitoring in multicentre trials.

Using Real-time Data to Drive Better Decisions, Faster

Abstract: The new health landscape requires biopharmaceutical companies to conduct smarter clinical trials and produce better outcomes faster. Electronic data capture and electronic data review tools enable drug developers to review data shortly after it is captured, creating opportunities for improving the process and outcomes of clinical trials, and proactively managing quality, patient safety, and risk. We examine the extraordinary opportunity for the biopharmaceutical industry to use real-time data to drive better decisions faster. We identify the advantages of access to real-time data during a clinical trial, while recommending guidelines for mitigating associated risks. Topics discussed include the following:•Technologies that make access to real-time clinical trial data widely available•Regulatory implications of reviewing real-time data throughout clinical trials•Clinical trial roles and the rationale for granting real-time data access•Guidelines and controls for use of real-time data during clinical trials...

inSERT - An NFC-based Self-Reporting Questionnaire for Patients with Fine Motor Diseases

Abstract: Self-reporting patient data are valuable feedback for medical treatment and care process, as well as for clinical trial studies and support of medical treatment. However, traditional paper-based medical patient longitudinal surveys or questionnaires for health and well-being status information are time- and cost-consuming, and may suffer from low patient compliance. Consequently, an NFC-based electronic data capture prototype called inSERT has been designed that allows quick and easy self-reporting for patients. inSERT allows patient monitoring enabling, electronic acquisition of well-being data right from the patient's home and real time representation of patient data, enabling direct medical intervention by physicians. The functional requirements for the inSERT system were determined through an extensive, user-centric elicitation process. We chose Near Field Communication (NFC) as a technology, for which the interaction paradigm is quick to learn and is intuitive, without prior knowledge being necessary, it is almost as simple as to fill out a paper-based questionnaire. Particularly for the target group (elderly people and people with impaired fine motor skills) - those who are not familiar with the use of mobile phones or computers - it makes NFC a very promising field compared to the control with touch based displays or computer mouse. The prototype is currently evaluated in a field test. The technical feasibility, implementation details, limitations and future research approaches are discussed in this paper.

Day labour mobile electronic data capture and browsing system

Abstract: In this paper, a day-labour Mobile Electronic Data Capture and Browsing (MEDCB) system is presented. In building and evaluating this system, the primary aim was to evaluate the possibility of applying mobile data capture and browsing to the day-labour market with a view to improving data capture and verification accuracy and efficiency. The MEDCB system consists of a mobile client application and a web interface. The system was evaluated with non-profit organizations working for day labour semiliterate job seekers. Results showed that data capture, processing and browsing is a possibility in day labour market. Improvement in accuracy and efficiency was also seen with the use of MEDCB. We describe the design process, present initial findings and discuss the results.

Managing research data for clinical drug trials

Abstract: A machine, computer program product, and computer-implemented method for performing a process of managing clinical research data by collating a plurality of clinical patient records into a database system and a process of allowing particular clinical users to access the clinical research records.

The Clinical Assessment and Remote Administration Tablet

Abstract: Electronic data capture of case report forms (CRFs), demographic, neuropsychiatric, or clinical assessments, can vary from scanning hand-written forms into databases to fully electronic systems. Web-based forms can be extremely useful for self-assessment; however, in the case of neuropsychiatric assessments, self-assessment is often not an option. The clinician often must be the person either summarizing or making their best judgment about the subject’s response in order to complete an assessment, and having the clinician turn away to type into a web browser may be disruptive to the flow of the interview. The Mind Research Network (MRN) has developed a prototype for a software tool for the real-time acquisition and validation of clinical assessments in remote environments. We have developed the Clinical Assessment and Remote Administration Tablet (CARAT) on a Microsoft Windows PC tablet system, which has been adapted to interact with various data models already in use in several large-scale databases of neuroimaging studies in clinical populations. The tablet has been used successfully to collect and administer clinical assessments in several large-scale studies, so that the correct clinical measures are integrated with the correct imaging and other data. It has proven to be incredibly valuable in confirming that data collection across multiple research groups is performed similarly, quickly, and with accountability for incomplete datasets. We present the overall architecture and an evaluation of its use.

The Prostate Cancer Clinical Trials Consortium (PCCTC) bone scan data capture tool for clinical trials using Prostate Cancer Working Group 2 (PCWG2) criteria: Effect on data accuracy and workload.

Abstract: 121 Background: PCWG2 Concensus Criteria proposed time-to-event endpoints in early phase clinical trials. Chief among these was time to radiographic progression for bone scintigraphy (BS), based on a standardized definition with additional rulesets to account for early flare. The PCCTC created a tool to operationalize these definitions in clinical trials. We tested the impact of the tool on clinical trial workload and data adequacy. Methods: The BS capture tool was vetted and amended through nine versions by a multidisciplinary group from PCCTC participating institutions. Accruals at Memorial Sloan-Kettering Cancer Center on two phase III trials using the same drug, contracting research organization (CRO), and electronic data capture system were analyzed. The first trial did not use the PCCTC tool. The second incorporated the tool in its data collection plan and case report form. Workload and data capture adequacy for each trial were determine by examining the total number of imaging queries from the data...

Economic Analysis of Centralized vs. Decentralized Electronic Data Capture in Multi-Center Clinical Studies

Abstract: Background New data management models are emerging in multi-center clinical studies. We evaluated the incremental costs associated with decentralized vs. centralized models. Methods We developed clinical research network economic models to evaluate three data management models: centralized, decentralized with local software, and decentralized with shared database. Descriptive information from three clinical research studies served as inputs for these models. Main outcome measures The primary outcome was total data management costs. Secondary outcomes included: data management costs for sites, local data centers, and central coordinating centers. Results Both decentralized models were more costly than the centralized model for each clinical research study: the decentralized with local software model was the most expensive. Decreasing the number of local data centers and case book pages reduced cost differentials between models. Conclusion Decentralized vs. centralized data management in multi-center clinical research studies is associated with increases in data management costs.

HIS-Based Support of Follow-Up Documentation - Concept and Implementation for Clinical Studies.

Abstract: Objective: Follow-up data must be collected according to the protocol of each clinical study, i.e. at certain time points. Missing follow-up information is a critical problem and may impede or bias the analysis of study data and result in delays. Moreover, additional patient recruitment may be necessary due to incomplete follow-up data. Current electronic data capture (EDC) systems in clinical studies are usually separated from hospital information systems (HIS) and therefore can provide limited functionality to support clinical workflow. In two case studies, we assessed the feasibility of HIS-based support of follow-up documentation. Methods: We have developed a data model and a HIS-based workflow to provide follow-up forms according to clinical study protocols. If a follow-up form was due, a database procedure created a followup event which was translated by a communication server into an HL7 message and transferred to the import interface of the clinical information system (CIS). This procedure generated the required followup form and enqueued a link to it in a work list of the relating study nurses and study physicians, respectively. Results: A HIS-based follow-up system automatically generated follow-up forms as defined by a clinical study protocol. These forms were scheduled into work lists of study nurses and study physicians. This system was integrated into the clinical workflow of two clinical studies. In a study from nuclear medicine, each scenario from the test concept according to the protocol of the single photon emission computer tomography/computer tomography (SPECT/CT) study was simulated and each scenario passed the test. For a study in psychiatry, 128 follow-up forms were automatically generated within 27 weeks, on average five forms per week (maximum 12, minimum 1 form per week). Conclusion: HIS-based support of follow-up documentation in clinical studies is technically feasible and can support compliance with study protocols.

Clinical Study Data Management Systems

Abstract: Clinical Study Data Management Systems (CSDMSs) support the process of managing data gathered during clinical research. Clinical research involves much more than clinical data management – for example, research-grant tracking and reporting to the sponsor and to institutional review boards (IRBs, also called Human Investigations Committees) as well as financial management. I’ll focus on the data-capture, reporting and query aspects, as these are the components that benefit from metadata.

The promise of electronic data capture in respiratory medicine.

Abstract: In the 17th century the English physician John Floyer, himself severely asthmatic, used symptom diaries to record his own and his patients’ symptoms to understand the determinants of asthma exacerbations, and inform disease management 1. If long-term serial data on designated patients with chronic lung disease were available to physicians, it could fundamentally change clinical practice and influence the design of clinical research studies. However, methods of symptom diary data collection that frustrate patients and which require analysis by physicians before interpretation are unlikely to achieve broad success. A recent editorial in the European Respiratory Journal 2 drew attention to the emphasis, in current guidelines for asthma management 3 and in the conduct of clinical trials in asthma 4, of the importance of estimating “future risk” to patients. The concept has equal relevance in other chronic lung diseases. Guidances issued by both the European Medicines Agency and the US Food and Drug Administration 5, 6 have contemplated and encouraged the adoption of patient reported outcomes (PROs) in chronic disease research. The report by Liu et al. 7 in the current issue of the European Respiratory Journal describes the experimental evaluation of a mobile telephone-based system compared with a paper diary for monitoring the management of adult asthmatics, and found significant clinical improvements in the electronically monitored patients. As noted in a recent meta-analysis of studies of electronic patient-reported symptom monitoring in respiratory disease 8, there are as yet an inadequate number of published reports of studies with robust designs and formal evaluation in this area, and the study by Liu et al. 7 is a welcome addition. The approach taken to symptom diary data collection was inexpensive and used technologies that are becoming almost universally available. Importantly, this study also showed good patient …

The swedish athletics study: design of a protocol for large-scale epidemiological studies in individual sports

Abstract: Background Epidemiological studies of injury have mainly been performed on team sports. Present methods for data collection and analysis neglect important features of individual sports. Aims To develop a study protocol for large-scale epidemiological studies of injuries in individual sports, exemplified by athletics. Design Structured information system development. Specification of the study protocol was preceded by an examination of requirements on injury surveillance in individual sports and iterated drafting of protocol specifications, and followed by formative evaluations. A preliminary protocol was evaluated in a pilot study involving athletic coaches and athletes and revised into the final version. Setting Swedish youth and adult elite athletics. Participants Six elite athletics coaches and 22 athletic athletes. Results The requirements analysis showed that the central demand on a study protocol to be used for epidemiological surveillance in athletics is to enable detailed analyses of overuse injuries, which subsequently requires continuous and prospective collection of athlete self-reported data. The study protocol fulfils these requirements by using a web-based athlete diary for collection of data regarding exposure to practice and competition as well as injuries. In addition, the requirements analysis showed that the study protocol should cover collection of detailed baseline data, including injury history, subject characteristics and a psychological profile. The evaluation data showed that the preliminary protocol only needed minor revisions at the level of web-questionnaire design. Conclusion The resulting study protocol for injury surveillance is specifically targeted at individual sports. It can be employed in surveillance preceding intervention programs for preventing injuries and suffering among both adult elite and youth athletes. Electronic data capture is crucial for injury surveillance in individual sports, such as athletics in order to ensure high validity of data.