Showing papers on "Electronic data capture published in 2017"

Electronic health records to facilitate clinical research.

Abstract: Electronic health records (EHRs) provide opportunities to enhance patient care, embed performance measures in clinical practice, and facilitate clinical research. Concerns have been raised about the increasing recruitment challenges in trials, burdensome and obtrusive data collection, and uncertain generalizability of the results. Leveraging electronic health records to counterbalance these trends is an area of intense interest. The initial applications of electronic health records, as the primary data source is envisioned for observational studies, embedded pragmatic or post-marketing registry-based randomized studies, or comparative effectiveness studies. Advancing this approach to randomized clinical trials, electronic health records may potentially be used to assess study feasibility, to facilitate patient recruitment, and streamline data collection at baseline and follow-up. Ensuring data security and privacy, overcoming the challenges associated with linking diverse systems and maintaining infrastructure for repeat use of high quality data, are some of the challenges associated with using electronic health records in clinical research. Collaboration between academia, industry, regulatory bodies, policy makers, patients, and electronic health record vendors is critical for the greater use of electronic health records in clinical research. This manuscript identifies the key steps required to advance the role of electronic health records in cardiovascular clinical research.

Experiences in running a complex electronic data capture system using mobile phones in a large-scale population trial in southern Nepal

Abstract: The increasing availability and capabilities of mobile phones make them a feasible means of data collection. Electronic Data Capture (EDC) systems have been used widely for public health monitoring and surveillance activities, but documentation of their use in complicated research studies requiring multiple systems is limited. This paper shares our experiences of designing and implementing a complex multi-component EDC system for a community-based four-armed cluster-Randomised Controlled Trial in the rural plains of Nepal, to help other researchers planning to use EDC for complex studies in low-income settings. We designed and implemented three interrelated mobile phone data collection systems to enrol and follow-up pregnant women (trial participants), and to support the implementation of trial interventions (women's groups, food and cash transfers). 720 field staff used basic phones to send simple coded text messages, 539 women's group facilitators used Android smartphones with Open Data Kit Collect, and 112 Interviewers, Coordinators and Supervisors used smartphones with CommCare. Barcoded photo ID cards encoded with participant information were generated for each enrolled woman. Automated systems were developed to download, recode and merge data for nearly real-time access by researchers. The systems were successfully rolled out and used by 1371 staff. A total of 25,089 pregnant women were enrolled, and 17,839 follow-up forms completed. Women's group facilitators recorded 5717 women's groups and the distribution of 14,647 food and 13,482 cash transfers. Using EDC sped up data collection and processing, although time needed for programming and set-up delayed the study inception. EDC using three interlinked mobile data management systems (FrontlineSMS, ODK and CommCare) was a feasible and effective method of data capture in a complex large-scale trial in the plains of Nepal. Despite challenges including prolonged set-up times, the systems met multiple data collection needs for users with varying levels of literacy and experience.

Mobile electronic versus paper case report forms in clinical trials: a randomized controlled trial.

Abstract: Regulations, study design complexity and amounts of collected and shared data in clinical trials render efficient data handling procedures inevitable. Recent research suggests that electronic data capture can be key in this context but evidence is insufficient. This randomized controlled parallel group study tested the hypothesis that time efficiency is superior when electronic (eCRF) instead of paper case report forms (pCRF) are used for data collection. We additionally investigated predictors of time saving effects and data integrity. This study was conducted on top of a clinical weight loss trial performed at a clinical research facility over six months. All study nurses and patients participating in the clinical trial were eligible to participate and randomly allocated to enter cross-sectional data obtained during routine visits either through pCRF or eCRF. A balanced randomization list was generated before enrolment commenced. 90 and 30 records were gathered for the time that 27 patients and 2 study nurses required to report 2025 and 2037 field values, respectively. The primary hypothesis, that eCRF use is faster than pCRF use, was tested by a two-tailed t-test. Analysis of variance and covariance were used to evaluate predictors of entry performance. Data integrity was evaluated by descriptive statistics. All randomized patients were included in the study (eCRF group n = 13, pCRF group n = 14). eCRF, as compared to pCRF, data collection was associated with significant time savings across all conditions (8.29 ± 5.15 min vs. 10.54 ± 6.98 min, p = .047). This effect was not defined by participant type, i.e. patients or study nurses (F(1,112) = .15, p = .699), CRF length (F(2,112) = .49, p = .609) or patient age (Beta = .09, p = .534). Additional 5.16 ± 2.83 min per CRF were saved with eCRFs due to data transcription redundancy when patients answered questionnaires directly in eCRFs. Data integrity was superior in the eCRF condition (0 versus 3 data entry errors). This is the first study to prove in direct comparison that using eCRFs instead of pCRFs increases time efficiency of data collection in clinical trials, irrespective of item quantity or patient age, and improves data quality. Clinical Trials NCT02649907 .

Implementation and Feasibility of Electronic Patient-Reported Outcome (ePRO) Data Entry in the PRAEGNANT Real-Time Advanced and Metastatic Breast Cancer Registry

Abstract: Purpose Patient-reported outcomes (PROs) have been incorporated into clinical trials for many symptoms and medical conditions. A transition from paper-based capture of PROs to electronic PROs (ePROs) has recently started. This study reports on the feasibility of ePRO assessment in a prospective registry including molecular data for patients with advanced breast cancer. Methods As part of the PRAEGNANT network, patients were invited by clinical trial staff, physicians, and nurses to complete three standardized Internet-based questionnaires (EQ 5D 5 L, CES-D and IPAQ). Feasibility was assessed by the staff members who assigned the user accounts by the patients. The completeness of the questionnaires was also assessed. Results Fifteen of 17 patients who were asked agreed to participate to complete the PRO questionnaires (EQ-5D-5L and CES-D). However, the IPAQ (physical activity) questionnaire was only validly completed by 9 patients. Feasibility was ranked better by the physicians and dedicated clinical trial staff than by the nursing staff. Conclusions Incorporating ePRO questionnaires into an advanced breast cancer registry is feasible, and no major hurdles were reported. Involving stakeholders from the start, the application is tailored to the capacities and abilities of both patients and clinical staff. The patientsʼ compliance was better with some questionnaires, but others may present difficulties.

Electronic case report forms and electronic data capture within clinical trials and pharmacoepidemiology.

Abstract: Aims Researchers in clinical and pharmacoepidemiology fields have adopted information technology (IT) and electronic data capture, but these remain underused despite the benefits. This review discusses electronic case report forms and electronic data capture, specifically within pharmacoepidemiology and clinical research. Methods The review used PubMed and the Institute of Electrical and Electronic Engineers library. Search terms used were agreed by the authors and documented. PubMed is medical and health based, whereas Institute of Electrical and Electronic Engineers is technology based. The review focuses on electronic case report forms and electronic data capture, but briefly considers other relevant topics; consent, ethics and security. Results There were 1126 papers found using the search terms. Manual filtering and reviewing of abstracts further condensed this number to 136 relevant manuscripts. The papers were further categorized: 17 contained study data; 40 observational data; 27 anecdotal data; 47 covering methodology or design of systems; one case study; one literature review; two feasibility studies; and one cost analysis. Conclusion Electronic case report forms, electronic data capture and IT in general are viewed with enthusiasm and are seen as a cost-effective means of improving research efficiency, educating participants and improving trial recruitment, provided concerns about how data will be protected from misuse can be addressed. Clear operational guidelines and best practises are key for healthcare providers, and researchers adopting IT, and further work is needed on improving integration of new technologies with current systems. A robust method of evaluation for technical innovation is required.

Mobile Device-Based Electronic Data Capture System Used in a Clinical Randomized Controlled Trial: Advantages and Challenges.

Abstract: Background: Electronic data capture (EDC) systems have been widely used in clinical research, but mobile device–based electronic data capture (mEDC) system has not been well evaluated. Objective: The aim of our study was to evaluate the feasibility, advantages, and challenges of mEDC in data collection, project management, and telemonitoring in a randomized controlled trial (RCT). Methods: We developed an mEDC to support an RCT called “Telmisartan and Hydrochlorothiazide Antihypertensive Treatment (THAT)” study, which was a multicenter, double-blinded, RCT, with the purpose of comparing the efficacy of telmisartan and hydrochlorothiazide (HCTZ) monotherapy in high-sodium-intake patients with mild to moderate hypertension during a 60 days follow-up. Semistructured interviews were conducted during and after the trial to evaluate the feasibility, advantage, and challenge of mEDC. Nvivo version 9.0 (QSR International) was used to analyze records of interviews, and a thematic framework method was used to obtain outcomes. Results: The mEDC was successfully used to support the data collection and project management in all the 14 study hospitals. A total of 1333 patients were recruited with support of mEDC, of whom 1037 successfully completed all 4 visits. Across all visits, the average time needed for 141 questions per patient was 53 min, which were acceptable to both doctors and patients. All the interviewees, including 24 doctors, 53 patients, 1 clinical research associate (CRA), 1 project manager (PM), and 1 data manager (DM), expressed their satisfaction to nearly all the functions of the innovative mEDC in randomization, data collection, project management, quality control, and remote monitoring in real time. The average satisfaction score was 9.2 (scale, 0-10). The biggest challenge came from the stability of the mobile or Wi-Fi signal although it was not a problem in THAT study. Conclusions: The innovative mEDC has many merits and is well acceptable in supporting data collection and project management in a timely manner in clinical trial. [J Med Internet Res 2017;19(3):e66]

Open-source mobile digital platform for clinical trial data collection in low-resource settings

Abstract: Background Governments, universities and pan-African research networks are building durable infrastructure and capabilities for biomedical research in Africa. This offers the opportunity to adopt from the outset innovative approaches and technologies that would be challenging to retrofit into fully established research infrastructures such as those regularly found in high-income countries. In this context we piloted the use of a novel mobile digital health platform, designed specifically for low-resource environments, to support high-quality data collection in a clinical research study. Objective Our primary aim was to assess the feasibility of a using a mobile digital platform for clinical trial data collection in a low-resource setting. Secondarily, we sought to explore the potential benefits of such an approach. Methods The investigative site was a research institute in Nairobi, Kenya. We integrated an open-source platform for mobile data collection commonly used in the developing world with an open-source, standard platform for electronic data capture in clinical trials. The integration was developed using common data standards (Clinical Data Interchange Standards Consortium (CDISC) Operational Data Model), maximising the potential to extend the approach to other platforms. The system was deployed in a pharmacokinetic study involving healthy human volunteers. Results The electronic data collection platform successfully supported conduct of the study. Multidisciplinary users reported high levels of satisfaction with the mobile application and highlighted substantial advantages when compared with traditional paper record systems. The new system also demonstrated a potential for expediting data quality review. Discussion and Conclusions This pilot study demonstrated the feasibility of using a mobile digital platform for clinical research data collection in low-resource settings. Sustainable scientific capabilities and infrastructure are essential to attract and support clinical research studies. Since many research structures in Africa are being developed anew, stakeholders should consider implementing innovative technologies and approaches.

Implementing electronic data capture at a well-established health and demographic surveillance site in rural northern Malawi

Abstract: This article aims to assess multiple issues of resources, staffing, local opinion, data quality, cost, and security while transitioning to electronic data collection (EDC) at a long-running community research site in northern Malawi. Levels of missing and error fields, delay from data collection to availability, and average number of interviews per day were compared between EDC and paper in a complex, repeated annual household survey. Three focus groups with field and data staff with experience using both methods, and in-depth interviews with participants were carried out. Cost for each method were estimated and compared. Missing data was more common on paper questionnaires than on EDC, and a similar number were carried out per day. Fieldworkers generally preferred EDC, but data staff feared for their employment. Most respondents had no strong preference for a method. The cost of the paper system was estimated to be higher than using EDC. The existing infrastructure and technical expertise could be adapted to using EDC, but changes have an impact on data processing jobs as fewer, and better qualified staff are required. EDC is cost-effective, and, for a long-running site, may offer further savings, as devices can be used in multiple studies and perform several other functions. EDC is accepted by fieldworkers and respondents, has good levels of quality and timeliness, and security can be maintained. EDC is well-suited for use in a well-established research site using and developing existing infrastructure and expertise.

Case Report Form Reporter: A Key Component for the Integration of Electronic Medical Records and the Electronic Data Capture System.

Abstract: To improve the efficiency of clinical research, we developed a system to integrate electronic medical records (EMRs) and the electronic data capture system (EDC) EDC is divided into case report form (CRF) reporter and CDMS with CRF receiver with data communication using the operational data model (ODM) The CRF reporter is incorporated into the EMR to share data witth the EMR In the data transcription type, doctors enter data using a progress note template, which are transmitted to the reporter template It then generates the ODM In the direct record type, reporter templates open from the progress note and generate narrative text to make record in the progress note The configuration files for a study are delivered from the contents server to minimize the setup This system has been used for 15 clinical studies including 3 clinical trials This system can save labor and financial costs in clinical research

Validation Relaxation: A Quality Assurance Strategy for Electronic Data Collection.

Abstract: Background: The use of mobile devices for data collection in developing world settings is becoming increasingly common and may offer advantages in data collection quality and efficiency relative to paper-based methods. However, mobile data collection systems can hamper many standard quality assurance techniques due to the lack of a hardcopy backup of data. Consequently, mobile health data collection platforms have the potential to generate datasets that appear valid, but are susceptible to unidentified database design flaws, areas of miscomprehension by enumerators, and data recording errors. Objective: We describe the design and evaluation of a strategy for estimating data error rates and assessing enumerator performance during electronic data collection, which we term “validation relaxation.” Validation relaxation involves the intentional omission of data validation features for select questions to allow for data recording errors to be committed, detected, and monitored. Methods: We analyzed data collected during a cluster sample population survey in rural Liberia using an electronic data collection system (Open Data Kit). We first developed a classification scheme for types of detectable errors and validation alterations required to detect them. We then implemented the following validation relaxation techniques to enable data error conduct and detection: intentional redundancy, removal of “required” constraint, and illogical response combinations. This allowed for up to 11 identifiable errors to be made per survey. The error rate was defined as the total number of errors committed divided by the number of potential errors. We summarized crude error rates and estimated changes in error rates over time for both individuals and the entire program using logistic regression. Results: The aggregate error rate was 1.60% (125/7817). Error rates did not differ significantly between enumerators (P=.51), but decreased for the cohort with increasing days of application use, from 2.3% at survey start (95% CI 1.8%-2.8%) to 0.6% at day 45 (95% CI 0.3%-0.9%; OR=0.969; P<.001). The highest error rate (84/618, 13.6%) occurred for an intentional redundancy question for a birthdate field, which was repeated in separate sections of the survey. We found low error rates (0.0% to 3.1%) for all other possible errors. Conclusions: A strategy of removing validation rules on electronic data capture platforms can be used to create a set of detectable data errors, which can subsequently be used to assess group and individual enumerator error rates, their trends over time, and categories of data collection that require further training or additional quality control measures. This strategy may be particularly useful for identifying individual enumerators or systematic data errors that are responsive to enumerator training and is best applied to questions for which errors cannot be prevented through training or software design alone. Validation relaxation should be considered as a component of a holistic data quality assurance strategy. [J Med Internet Res 2017;19(8):e297]

Data Management and Data Quality in PERCH, a Large International Case-Control Study of Severe Childhood Pneumonia.

Abstract: The Pneumonia Etiology Research for Child Health (PERCH) study is the largest multicountry etiology study of pediatric pneumonia undertaken in the past 3 decades. The study enrolled 4232 hospitalized cases and 5325 controls over 2 years across 9 research sites in 7 countries in Africa and Asia. The volume and complexity of data collection in PERCH presented considerable logistical and technical challenges. The project chose an internet-based data entry system to allow real-time access to the data, enabling the project to monitor and clean incoming data and perform preliminary analyses throughout the study. To ensure high-quality data, the project developed comprehensive quality indicator, data query, and monitoring reports. Among the approximately 9000 cases and controls, analyzable laboratory results were available for ≥96% of core specimens collected. Selected approaches to data management in PERCH may be extended to the planning and organization of international studies of similar scope and complexity.

Improving data collection, documentation, and workflow in a dementia screening study

Abstract: Background: A clinical study team performing three multicultural dementia screening studies identified the need to improve data management practices and facilitate data sharing. A collaboration was initiated with librarians as part of the National Library of Medicine (NLM) informationist supplement program. The librarians identified areas for improvement in the studies’ data collection, entry, and processing workflows. Case Presentation: The librarians’ role in this project was to meet needs expressed by the study team around improving data collection and processing workflows to increase study efficiency and ensure data quality. The librarians addressed the data collection, entry, and processing weaknesses through standardizing and renaming variables, creating an electronic data capture system using REDCap, and developing well-documented, reproducible data processing workflows. Conclusions: NLM informationist supplements provide librarians with valuable experience in collaborating with study teams to address their data needs. For this project, the librarians gained skills in project management, REDCap, and understanding of the challenges and specifics of a clinical research study. However, the time and effort required to provide targeted and intensive support for one study team was not scalable to the library’s broader user community.

Validity of mobile electronic data capture in clinical studies: a pilot study in a pediatric population

Abstract: Clinical studies in children are necessary yet conducting multiple visits at study centers remains challenging. The success of “care-at-home” initiatives and remote clinical trials suggests their potential to facilitate conduct of pediatric studies. This pilot aimed to study the feasibility of remotely collecting valid (i.e. complete and correct) saliva samples and clinical data utilizing mobile technology. Single-center, prospective pilot study in children undergoing elective tonsillectomy at the University of Basel Children’s Hospital. Data on pain scores and concomitant medication and saliva samples were collected by caregivers on two to four inpatient study days and on three consecutive study days at home. A tailored mobile application developed for this study supported data collection. The primary endpoint was the proportion of complete and correct caregiver-collected data (pain scale) and saliva samples in the at-home setting. Secondary endpoints included the proportion of complete and correct saliva samples in the inpatient setting, subjective feasibility for caregivers, and study cost. A total number of 23 children were included in the study of which 17 children, median age 6.0 years (IQR 5.0, 7.4), completed the study. During the at-home phase, 71.9% [CI = 64.4, 78.6] of all caregiver-collected pain assessments and 53.9% [CI = 44.2, 63.4] of all saliva samples were complete and correct. Overall, 64.7% [CI = 58.7, 70.4] of all data collected by caregivers at home was complete and correct. The predominant reason for incorrectness of data was adherence to the timing of predefined patient actions. Participating caregivers reported high levels of satisfaction and willingness to participate in similar trials in the future. Study costs for a potential sample size of 100 patients were calculated to be 20% lower for the at-home than for a traditional in-patient study setting. Mobile device supported studies conducted at home may provide a cost-effective approach to facilitate conduct of clinical studies in children. Given findings in this pilot study, data collection at home may focus on electronic data capture rather than biological sampling.

Generalizable Middleware to Support Use of REDCap Dynamic Data Pull for Integrating Clinical and Research Data.

Abstract: To support integration of clinical and research data, the makers of REDCap, a widely-used electronic data capture system, released the Dynamic Data Pull (DDP) module Although DDP is a standard module in REDCap, institutions must develop custom middleware web services to exchange data between REDCap and local source systems The lack of middleware is a barrier to institutional adoption and use by investigators To overcome this gap, we developed a REDCap DDP web service middleware (accessible at https://githubcom/wcmc-research-informatics/redcap-ddp) that minimizes developer effort, relies on configuration by non-developers, and can generalize to other settings Early findings suggest the approach is successful

Exploring Organizational Culture for Information Security in Healthcare Organizations: A Literature Review

Abstract: The healthcare sector has generally been a late adopter of information technology solutions. As a result of the American Recovery and Reinvestment Act of 2009, the Centers for Medicare and Medicaid Services implemented a program whereby financial incentives were made available for eligible healthcare entities and healthcare providers implementing health information technology solutions. These healthcare entities and providers were required to attest to "meaningful use" (e.g. electronic data capture of clinical data, provision of electronic health records to patients) in order to receive the financial incentives. This program, more than any other key driver, has transformed the utilization of health information technology (HIT) in clinical settings. Health IT is now ubiquitous. With the advent of these HIT solutions has come large caches of private and protected health information which must be guarded from both accidental disclosure and nefarious criminal activity. Compliance monitoring efforts by the Department of Health and Human Service's Office for Civil Rights have increased dramatically in recent years with multi-million dollar fines being levied across the country for security gaps. As a result of this increased risk, many healthcare organization are revisiting their information security position and culture in the age of electronic medical records. This paper will review the current state of that culture.

Innovative Use of the Electronic Health Record to Support Harm Reduction Efforts.

Abstract: BACKGROUND AND OBJECTIVES: Awareness of the impact of preventable harm on patients and families has resulted in extensive efforts to make our health care systems safer. We determined that, in our hospital, patients experienced 1 of 9 types of preventable harm approximately every other day. In an effort to expedite early identification of patients at risk and provide timely intervention, we used the electronic health record’s (EHR) documentation to enable decision support, data capture, and auditing and implemented reporting tools to reduce rates of harm. METHODS: Harm reduction strategies included aggregating data to generate a risk profile for hospital-acquired conditions (HACs) for all inpatients. The profile includes links to prevention bundles and available care guidelines. Additionally, lists of patients at risk for HACs autopopulate electronic audit tools contained within Research Electronic Data Capture, and data from observational audits and EHR documentation populate real-time dashboards of bundle compliance. Patient population summary reports promote the discussion of relevant HAC prevention measures during patient care and unit leadership rounds. RESULTS: The hospital has sustained a >30% reduction in harm for 9 types of HAC since 2012. In 2014, the number of HACs with >80% bundle adherence doubled coincident with the progressive rollout of these EHR-based interventions. CONCLUSIONS: Existing EHR documentation and reporting tools may be effective adjuncts to harm reduction initiatives. Additional study should include an evaluation of scalability across organizations, ongoing bundle adherence, and individual tests of change to isolate interventions with the highest impact on our results.

Measuring Clinical Decision-Making and Clinical Skills in DPT Students Across a Curriculum: Validating A New Survey Tool.

Abstract: BACKGROUND Healthcare is a fast-paced, dynamic atmosphere. Clinical decision-making and clinical skills have been identified as necessary skills for autonomous practitioners in physical therapy. However, there are limited tools to measure these skills, which are cumbersome to implement and not validated. PURPOSE To validate a survey tool across three cohorts of DPT students and one cohort of physical therapy interns. DESIGN A cross-sectional, descriptive study. METHODS A 25-item survey tool was used to measure clinical decision-making and clinical skills. The survey tool was sent and data collected online via REDCap (Research Electronic Data Capture). RESULTS The survey response rates were between 19% and 47%. The Cronbach's alpha was ≥0.964 across domains and the total scale. Mann-Whitney U-tests demonstrated significant differences between all cohorts except between the second- and third-year students. The interns demonstrated less variance in their answers than students earlier in the curriculum. CONCLUSIONS The survey demonstrated excellent internal consistency and construct and face validity. The psychometric properties of the tool and the possibility of a ceiling effect need to be studied further.

S2O – A software tool for integrating research data from general purpose statistic software into electronic data capture systems

Abstract: Data capture for clinical registries or pilot studies is often performed in spreadsheet-based applications like Microsoft Excel or IBM SPSS. Usually, data is transferred into statistic software, such as SAS, R or IBM SPSS Statistics, for analyses afterwards. Spreadsheet-based solutions suffer from several drawbacks: It is generally not possible to ensure a sufficient right and role management; it is not traced who has changed data when and why. Therefore, such systems are not able to comply with regulatory requirements for electronic data capture in clinical trials. In contrast, Electronic Data Capture (EDC) software enables a reliable, secure and auditable collection of data. In this regard, most EDC vendors support the CDISC ODM standard to define, communicate and archive clinical trial meta- and patient data. Advantages of EDC systems are support for multi-user and multicenter clinical trials as well as auditable data. Migration from spreadsheet based data collection to EDC systems is labor-intensive and time-consuming at present. Hence, the objectives of this research work are to develop a mapping model and implement a converter between the IBM SPSS and CDISC ODM standard and to evaluate this approach regarding syntactic and semantic correctness. A mapping model between IBM SPSS and CDISC ODM data structures was developed. SPSS variables and patient values can be mapped and converted into ODM. Statistical and display attributes from SPSS are not corresponding to any ODM elements; study related ODM elements are not available in SPSS. The S2O converting tool was implemented as command-line-tool using the SPSS internal Java plugin. Syntactic and semantic correctness was validated with different ODM tools and reverse transformation from ODM into SPSS format. Clinical data values were also successfully transformed into the ODM structure. Transformation between the spreadsheet format IBM SPSS and the ODM standard for definition and exchange of trial data is feasible. S2O facilitates migration from Excel- or SPSS-based data collections towards reliable EDC systems. Thereby, advantages of EDC systems like reliable software architecture for secure and traceable data collection and particularly compliance with regulatory requirements are achievable.

Automated Transformation of CDISC ODM to OpenClinica.

Abstract: Due to the increasing use of electronic data capture systems for clinical research, the interest in saving resources by automatically generating and reusing case report forms in clinical studies is growing. OpenClinica, an open-source electronic data capture system enables the reuse of metadata in its own Excel import template, hampering the reuse of metadata defined in other standard formats. One of these standard formats is the Operational Data Model for metadata, administrative and clinical data in clinical studies. This work suggests a mapping from Operational Data Model to OpenClinica and describes the implementation of a converter to automatically generate OpenClinica conform case report forms based upon metadata in the Operational Data Model.

Deriving meaningful insights from clinical trial and postmarketing safety data: Perspectives from India.

Abstract: Today, drug safety data collection in India is both manual and electronic with reporting of potential overlapping and duplicate data, which is likely incomplete for further review and analysis. Furthermore, standardized data collection and timelines are not aligned with international standards. Complete coverage of safety data from all sources throughout the life of the drug cannot be ensured. There is no requirement to submit periodic safety data in clinical trials to regulatory authority. There is clearly a lack of emphasis on deriving meaningful safety data insights for ensuring patient safety. Efforts toward the early detection of drug safety issues are minimal. There is no mandate to publicly disclose drug safety findings. Benefit-risk evaluation of investigational and marketed products cannot be assured merely through annual status reports and periodic safety update reports, respectively. Focused initiatives involving stakeholders from regulatory, health-care, and pharmaceutical industries are required to change the current situation and enable derivation of meaningful insights from safety data. Equal emphasis on assessing real-time safety of the drugs and protection of patients' rights, safety, and well-being is required. Periodic safety data reporting in clinical trials, proactive safety data collection related to potential safety concerns, electronic medical records, electronic expedited reporting, collection of targeted data from stakeholders, and standardized and harmonized data collection aligned to the International Council for Harmonization guidelines are required. The Central Drugs Standard Control Organization should implement requirements to submit Development Safety Update Reports, Periodic Benefit-Risk Evaluation Reports, and Risk Management Plans. Access to clinical trials and postmarketing safety data through central repository would enable researchers to explore the data for application in clinical practice.

Developing a Practical Method for Validation of Computerized Systems Integrated With Smart and/or Wearable Devices for Regulatory Compliance of Clinical Trials.

Abstract: Background:The use of smart and/or wearable devices for collection of electronic data in clinical trials has recently become a strong tool with which to collect patients’ data in a timely manner. E...

The assumptions of data capture

Abstract: Within the field of clinical research, there has been, for many years, a move away from the use of paper as a form of data capture, in favour of electronic data capture, particularly within industry. The advent of the use of electronic case record forms (eCRFs) is nothing new from that perspective: what remains a challenge is the use of electronic data capture (EDC) at site. This article will, I hope, with some broad generalisation, raise awareness of the issues from the sites’ perspective