REDLetr: Workflow and tools to support the migration of legacy clinical data capture systems to REDCap

Automated oxygen administration versus manual control in acute cardiovascular care: a randomised controlled trial

BACKGROUND

Oxygen therapy is commonly administered to patients with acute cardiovascular conditions during hospitalisation. Both hypoxaemia and hyperoxia can cause harm, making it essential to maintain oxygen saturation (SpO2) within a target range. Traditionally, oxygen administration is manually controlled by nursing staff, guided by intermittent pulse oximetry readings. This study aimed to compare standard manual oxygen administration with automated oxygen administration (AOA) using the O2matic device.

METHODS

In this randomised controlled trial, 60 patients admitted to a cardiac department with an acute cardiovascular condition requiring oxygen therapy were randomised to either standard care (manual oxygen administration) or AOA via the O2matic device. The primary outcome was the percentage of time spent within the desired SpO2 range (92%-96% or 94%-98%) over 24 hours.

RESULTS

Patients had a mean age of 75.8±12.4 years, with an average SpO2 of 93%. Those in the AOA group (n=25) spent significantly more time within the target SpO2 range (median 87.0% vs 60.6%, p<0.001) compared with the standard care group (n=28). Time spent below the desired SpO2 range was significantly lower in the AOA group (7.9% vs 33.6%, p<0.001). No significant differences in time spent above the desired SpO2 range were observed between the two groups.

CONCLUSIONS

AOA with the O2matic device is superior to standard manual control in maintaining SpO2 within the target range in patients hospitalised with acute cardiovascular conditions. The automated systems significantly reduce the time spent in hypoxaemia without increasing hyperoxia.

TRIAL REGISTRATION NUMBER

NCT05452863.

Research Electronic Data Capture (REDCap) in an outpatient oncology surgery setting to securely email, collect, and manage survey data

BACKGROUND

Nursing interventions in the post-operative time period including psychological and emotional support, adverse event education, and instructions for follow-up care contribute patient satisfaction, safety, and quality of life. However, the time spent in the post-anesthesia care unit (PACU) and hospital continues to shorten around the world to reduce health care spending and improve patient outcomes. Nurses conducting research during the important post-operative recovery period need to utilize unique techniques and emerging technologies to contact, recruit and collect data outside of the hospital setting including the Research Electronic Data Capture (REDCap) platform.

AIMS

This paper describes the feasibility and acceptability, facilitators and barriers of the software application, REDCap, to complete a repeated-measures, descriptive correlational study in patients undergoing outpatient breast cancer surgeries.

METHODS & MATERIALS

The recruitment, data collection and storage were completed utilizing the secure REDCap Platform. The Institutional Research Board (IRB)-approved study was a repeated-measures, descriptive, correlational study with data collection at three time points. The data points aligned with important transitions and routine visits to improve data collection feasibility and increase relevance to clinical practice.

RESULTS

The sample consisted of women diagnosed with breast cancer undergoing breast conserving surgery between August 15 and October 15, 2020. There were 123 potential participants, of which 76 started the surveys and 75 participated (61%) responded and participated in the study on Post-operative Day 1. Fifty-nine participants (78%) completed the surveys on post-operative Day 14.

DISCUSSION

As the frequency of outpatient treatment increases, nurses conducting post-operative research will need to collect the data outside of the hospital setting.

CONCLUSION

Email provides a method of studying new phenomena by recruiting participants, providing information about the study, and collecting results in a non-traditional setting. REDCap provides a method to facilitate nursing research through a securely encrypted integrated process.

Integrating REDCap patient-reported outcomes with the HealtheIntent population health platform: proof of concept

Objective

Patient-reported outcome measures (PROMs) are critical to drive patient-centered care and to understanding patients' perspectives on their health status, quality of life, and the overall effectiveness of the care they receive. PROMs are increasingly being used in clinical and research settings, but the mechanisms to aggregate data from different systems can be cumbersome.

Materials and methods

As part of an FDA Real-World Evidence demonstration project, we enriched routine care clinical data from our Cerner electronic health record (EHR) with PROMs collected using REDCap. We used SSIS, sFTP, and the REDCap Application Programming Interface to aggregate both data sources into the Cerner HealtheIntent Population Health Platform.

Results

We successfully built dashboards, reports, and datasets containing both REDCap and EHR data collected prospectively.

Discussion

This technically straightforward approach using commonly available clinical and research tools can be readily adopted and adapted by others to better integrate PROMs with clinical data sources.

Migrating a Well-Established Longitudinal Cohort Database From Oracle SQL to Research Electronic Data Entry (REDCap): Data Management Research and Design Study

BACKGROUND

Providing user-friendly electronic data collection tools for large multicenter studies is key for obtaining high-quality research data. Research Electronic Data Capture (REDCap) is a software solution developed for setting up research databases with integrated graphical user interfaces for electronic data entry. The Swiss Mother and Child HIV Cohort Study (MoCHiV) is a longitudinal cohort study with around 2 million data entries dating back to the early 1980s. Until 2022, data collection in MoCHiV was paper-based.

OBJECTIVE

The objective of this study was to provide a user-friendly graphical interface for electronic data entry for physicians and study nurses reporting MoCHiV data.

METHODS

MoCHiV collects information on obstetric events among women living with HIV and children born to mothers living with HIV. Until 2022, MoCHiV data were stored in an Oracle SQL relational database. In this project, R and REDCap were used to develop an electronic data entry platform for MoCHiV with migration of already collected data.

RESULTS

The key steps for providing an electronic data entry option for MoCHiV were (1) design, (2) data cleaning and formatting, (3) migration and compliance, and (4) add-on features. In the first step, the database structure was defined in REDCap, including the specification of primary and foreign keys, definition of study variables, and the hierarchy of questions (termed "branching logic"). In the second step, data stored in Oracle were cleaned and formatted to adhere to the defined database structure. Systematic data checks ensured compliance to all branching logic and levels of categorical variables. REDCap-specific variables and numbering of repeated events for enabling a relational data structure in REDCap were generated using R. In the third step, data were imported to REDCap and then systematically compared to the original data. In the last step, add-on features, such as data access groups, redirections, and summary reports, were integrated to facilitate data entry in the multicenter MoCHiV study.

CONCLUSIONS

By combining different software tools-Oracle SQL, R, and REDCap-and building a systematic pipeline for data cleaning, formatting, and comparing, we were able to migrate a multicenter longitudinal cohort study from Oracle SQL to REDCap. REDCap offers a flexible way for developing customized study designs, even in the case of longitudinal studies with different study arms (ie, obstetric events, women, and mother-child pairs). However, REDCap does not offer built-in tools for preprocessing large data sets before data import. Additional software is needed (eg, R) for data formatting and cleaning to achieve the predefined REDCap data structure.

Usability Evaluation of an Offline Electronic Data Capture App in a Prospective Multicenter Dementia Registry (digiDEM Bayern): Mixed Method Study

BACKGROUND

Digital registries have been shown to provide an efficient way of gaining a better understanding of the clinical complexity and long-term progression of diseases. The paperless method of electronic data capture (EDC) during a patient interview saves both time and resources. In the prospective multicenter project "Digital Dementia Registry Bavaria (digiDEM Bayern)," interviews are also performed on site in rural areas with unreliable internet connectivity. It must be ensured that EDC can still be performed in such a context and that there is no need to fall back on paper-based questionnaires. In addition to a web-based data collection solution, the EDC system REDCap (Research Electronic Data Capture) offers the option to collect data offline via an app and to synchronize it afterward.

OBJECTIVE

The aim of this study was to evaluate the usability of the REDCap app as an offline EDC option for a lay user group and to examine the necessary technology acceptance of using mobile devices for data collection. The feasibility of the app-based offline data collection in the digiDEM Bayern dementia registry project was then evaluated before going live.

METHODS

An exploratory mixed method design was employed in the form of an on-site usability test with the "Thinking Aloud" method combined with an online questionnaire including the System Usability Scale (SUS). The acceptance of mobile devices for data collection was surveyed based on five categories of the technology acceptance model.

RESULTS

Using the "Thinking Aloud" method, usability issues were identified and solutions were accordingly derived. Evaluation of the REDCap app resulted in a SUS score of 74, which represents "good" usability. After evaluating the technology acceptance questionnaire, it can be concluded that the lay user group is open to mobile devices as interview tools.

CONCLUSIONS

The usability evaluation results show that a lay user group generally agree that data collecting partners in the digiDEM project can handle the REDCap app well. The usability evaluation provided statements about positive aspects and could also identify usability issues relating to the REDCap app. In addition, the current technology acceptance in the sample showed that heterogeneous groups of different ages with diverse experiences in handling mobile devices are also ready for the use of app-based EDC systems. Based on these results, it can be assumed that the offline use of an app-based EDC system on mobile devices is a viable solution for collecting data in a decentralized registry-based research project.

Improving hypertension surveillance from a data management prospective: Data requirements for implementation of population-based registry

BACKGROUND

Hypertension (HTN) has become a major public health problem which can cause serious complications when it is not well-controlled. Prevention and effective care of HTN require a population-based registry. Thus, establishing this registry can be used to collect comprehensive, timely, and reliable data on epidemiology cases. The aim is to create a registry for the collection of highly required prospective data that will present an in-depth analysis of the characteristics of all individuals with HTN and track them over a particular chronological interval.

MATERIALS AND METHODS

The study was divided into three phases: At first, a comprehensive literature review was conducted to determine the proposed data classes and data fields. Then, the final minimum data set was designed by a two-round Delphi consensus approach of 20 experts of cardiologists, nephrologists, nutritionist, and health information management. Finally, a web-based registry system was developed by a Structured Query Language environment.

RESULTS

A total of two clinical and nonclinical data categories with nine data classes and 68 data fields were selected for their inclusion in the registry following the consensus phase. A web-based registry was designed with a modular and layered architecture.

CONCLUSIONS

This study provides an appropriate information infrastructure for active tracing and monitoring of individuals with HTN. It has provided a practical information system allowing quality improvement, aggregate reporting for planning, and research purposes.

Validation of a multisubstance online Timeline Followback assessment

OBJECTIVES

The Timeline Followback (TLFB) was originally developed to assess alcohol consumption patterns (American Journal of Public Health, 86, 1996, 966) and has been increasingly modified for Web-based use. Additionally, new modes of substance use administration have emerged, creating a need for an adaptable TLFB tool than can capture data such as cannabis product potency or prescription drug use. Our goal was to validate an online TLFB that reliably assesses a wide range of substances in greater detail.

METHODS

Using a within-subjects counterbalanced design, daily substance use data were collected from 50 college students over a 14-day retrospective period using both the traditional in-person TLFB and online TLFB (O-TLFB).

RESULTS

All substance use variables, including detailed measures of cannabis metrics, correlated significantly (r's ranged from .653 to .944, p < .001) between TLFB versions. Further, results demonstrated that both the online TLFB and in-person TLFB demonstrated concurrent validity with both the Alcohol Use Disorders Identification Test (AUDIT) and Marijuana Dependence Scale (MDS).

CONCLUSION

Overall, the data suggest that this new O-TLFB demonstrates strong reliability and delivers a versatile and secure tool for substance use assessment that is relevant to a variety of biomedical and psychological research contexts.

The transformation of a gold standard in-person substance use assessment to a web-based, REDCap integrated data capture tool

The adoption of computer systems for gathering, managing, and analyzing health data is resulting in the replacement of pen-and-paper methods for collecting data and managing health records by computerized methods. One classic "pen-and-paper" assessment in health and substance use research is the Timeline Follow-Back (TLFB), the gold standard in self-reported substance use developed in 1996 by Sobell et al. to assess alcohol consumption patterns and later other substances such as marijuana or tobacco over discreet timeframes [1-7]. The TLFB has been modified by some research groups for use as a web-based assessment [8-10], but not without significant limitations. As such, this paper describes the team-oriented, interdisciplinary process by which a new online TLFB (O-TLFB) was conceptualized, the technical details of development towards a dynamic data capture tool fully integrated with REDCap via application programming interface (API), and the potential for this optimized O-TLFB to be leveraged broadly across the domains of substance use, health, and behavioral research.

Research Electronic Data Capture (REDCap®) used as an audit tool with a built-in database

The aim of this study was to develop an audit tool with a built-in database using Research Electronic Data Capture (REDCap®) as part of an antimicrobial stewardship program at a regional hospital in the Central Denmark Region, and to analyse the need, if any, to involve more than one expert in the evaluation of cases of antimicrobial treatment, and the level of agreement among the experts. Patients treated with systemic antimicrobials in the period from 1 September 2015 to 31 August 2016 were included, in total 722 cases. Data were collected retrospectively and entered manually. The audit was based on seven flow charts regarding: (1) initiation of antimicrobial treatment (2) infection (3) prescription and administration of antimicrobials (4) discontinuation of antimicrobials (5) reassessment within 48 h after the first prescription of antimicrobials (6) microbiological sampling in the period between suspicion of infection and the first administration of antimicrobials (7) microbiological results. The audit was based on automatic calculations drawing on the entered data and on expert assessments. Initially, two experts completed the audit, and in the cases in which they disagreed, a third expert was consulted. In 31.9% of the cases, the two experts agreed on all elements of the audit. In 66.2%, the two experts reached agreement by discussing the cases. Finally, 1.9% of the cases were completed in cooperation with a third expert. The experts assessed 3406 flow charts of which they agreed on 75.8%. We succeeded in creating an audit tool with a built-in database that facilitates independent expert evaluation using REDCap. We found a large inter-observer difference that needs to be considered when constructing a project based on expert judgements. Our two experts agreed on most of the flow charts after discussion, whereas the third expert's intervention did not have any influence on the overall assessment.

Using Digital Technologies in Clinical HIV Research: Real-World Applications and Considerations for Future Work

BACKGROUND

Digital technologies, especially if used in novel ways, provide a number of potential advantages to clinical research in trials related to human immunodeficiency virus (HIV) and acquired immune deficiency syndrome (AIDS) and may greatly facilitate operations as well as data collection and analysis. These technologies may even allow answering questions that are not answerable with older technologies. However, they come with a variety of potential concerns for both the participants and the trial sponsors. The exact challenges and means for alleviation depend on the technology and on the population in which it is deployed, and the rapidly changing landscape of digital technologies presents a challenge for creating future-proof guidelines for technology application.

OBJECTIVE

The aim of this study was to identify and summarize some common themes that are frequently encountered by researchers in this context and highlight those that should be carefully considered before making a decision to include these technologies in their research.

METHODS

In April 2016, the Global HIV Vaccine Enterprise surveyed the field for research groups with recent experience in novel applications of digital technologies in HIV clinical research and convened these groups for a 1-day meeting. Real-world uses of various technologies were presented and discussed by 46 attendees, most of whom were researchers involved in the design and conduct of clinical trials of biomedical HIV prevention and treatment approaches. After the meeting, a small group of organizers reviewed the presentations and feedback obtained during the meeting and categorized various lessons-learned to identify common themes. A group of 9 experts developed a draft summary of the findings that was circulated via email to all 46 attendees for review. Taking into account the feedback received, the group finalized the considerations that are presented here.

RESULTS

Meeting presenters and attendees discussed the many successful applications of digital technologies to improve research outcomes, such as those for recruitment and enrollment, participant identification, informed consent, data collection, data quality, and protocol or treatment adherence. These discussions also revealed unintended consequence of technology usage, including risks to study participants and risks to study integrity.

CONCLUSIONS

Key lessons learned from these discussions included the need to thoroughly evaluate systems to be used, the idea that early success may not be sustained throughout the study, that some failures will occur, and considerations for study-provided devices. Additionally, taking these key lessons into account, the group generated recommendations on how to move forward with the use of technology in HIV vaccine and biomedical prevention trials.