User Preferences and Needs for Health Data Collection Using Research Electronic Data Capture: Survey Study.

BACKGROUND: Self-administered web-based questionnaires are widely used to collect health data from patients and clinical research participants. REDCap (Research Electronic Data Capture; Vanderbilt University) is a global, secure web application for building and managing electronic data capture. Unfortunately, stakeholder needs and preferences of electronic data collection via REDCap have rarely been studied. OBJECTIVE: This study aims to survey REDCap researchers and administrators to assess their experience with REDCap, especially their perspectives on the advantages, challenges, and suggestions for the enhancement of REDCap as a data collection tool. METHODS: We conducted a web-based survey with representatives of REDCap member organizations in the United States. The survey captured information on respondent demographics, quality of patient-reported data collected via REDCap, patient experience of data collection with REDCap, and open-ended questions focusing on the advantages, challenges, and suggestions to enhance REDCap's data collection experience. Descriptive and inferential analysis measures were used to analyze quantitative data. Thematic analysis was used to analyze open-ended responses focusing on the advantages, disadvantages, and enhancements in data collection experience. RESULTS: A total of 207 respondents completed the survey. Respondents strongly agreed or agreed that the data collected via REDCap are accurate (188/207, 90.8%), reliable (182/207, 87.9%), and complete (166/207, 80.2%). More than half of respondents strongly agreed or agreed that patients find REDCap easy to use (165/207, 79.7%), could successfully complete tasks without help (151/207, 72.9%), and could do so in a timely manner (163/207, 78.7%). Thematic analysis of open-ended responses yielded 8 major themes: survey development, user experience, survey distribution, survey results, training and support, technology, security, and platform features. The user experience category included more than half of the advantage codes (307/594, 51.7% of codes); meanwhile, respondents reported higher challenges in survey development (169/516, 32.8% of codes), also suggesting the highest enhancement suggestions for the category (162/439, 36.9% of codes). CONCLUSIONS: Respondents indicated that REDCap is a valued, low-cost, secure resource for clinical research data collection. REDCap's data collection experience was generally positive among clinical research and care staff members and patients. However, with the advancements in data collection technologies and the availability of modern, intuitive, and mobile-friendly data collection interfaces, there is a critical opportunity to enhance the REDCap experience to meet the needs of researchers and patients.

Smartphone App Designed to Collect Health Information in Older Adults: Usability Study.

BACKGROUND: Studies evaluating the usability of mobile-phone assessments in older adults are limited. OBJECTIVE: This study aims to identify design-based barriers and facilitators to mobile app survey completion among 2 samples of older adults; those in the Framingham Heart Study and a more diverse sample from a hospital-based setting. METHODS: We used mixed methods to identify challenging and beneficial features of the mobile app in participants from the electronic Framingham Heart Study (n=15; mean age of 72 years; 6/15, 40% women; 15/15, 100% non-Hispanic and White) and among participants recruited from a hospital-based setting (n=15; mean age of 71 years; 7/15, 47% women; 3/15, 20% Hispanic; and 8/15, 53% non-White). A variety of app-based measures with different response formats were tested, including self-reported surveys, pictorial assessments (to indicate body pain sites), and cognitive testing tasks (eg, Trail Making Test and Stroop). Participants completed each measure using a think-aloud protocol, while being audio- and video-recorded with a qualitative interview conducted at the end of the session. Recordings were coded for participant usability errors by 2 pairs of coders. Participants completed the Mobile App Rating Scale to assess the app (response range 1=inadequate to 5=excellent). RESULTS: In electronic Framingham Heart Study participants, the average total Mobile App Rating Scale score was 7.6 (SD 1.1), with no significant differences in the hospital-based sample. In general, participants were pleased with the app and found it easy to use. A large minority had at least 1 navigational issue, most committed only once. Most older adults did not have difficulty completing the self-reported multiple-choice measures unless it included lengthy instructions but participants had usability issues with the Stroop and Trail Making Test. CONCLUSIONS: Our methods and results help guide app development and app-based survey construction for older adults, while also giving consideration to sociodemographic differences.

Usability of an Automated System for Real-Time Monitoring of Shared Decision-Making for Surgery: Mixed Methods Evaluation.

BACKGROUND: Improving shared decision-making (SDM) for patients has become a health policy priority in many countries. Achieving high-quality SDM is particularly important for approximately 313 million surgical treatment decisions patients make globally every year. Large-scale monitoring of surgical patients' experience of SDM in real time is needed to identify the failings of SDM before surgery is performed. We developed a novel approach to automating real-time data collection using an electronic measurement system to address this. Examining usability will facilitate its optimization and wider implementation to inform interventions aimed at improving SDM. OBJECTIVE: This study examined the usability of an electronic real-time measurement system to monitor surgical patients' experience of SDM. We aimed to evaluate the metrics and indicators relevant to system effectiveness, system efficiency, and user satisfaction. METHODS: We performed a mixed methods usability evaluation using multiple participant cohorts. The measurement system was implemented in a large UK hospital to measure patients' experience of SDM electronically before surgery using 2 validated measures (CollaboRATE and SDM-Q-9). Quantitative data (collected between April 1 and December 31, 2021) provided measurement system metrics to assess system effectiveness and efficiency. We included adult patients booked for urgent and elective surgery across 7 specialties and excluded patients without the capacity to consent for medical procedures, those without access to an internet-enabled device, and those undergoing emergency or endoscopic procedures. Additional groups of service users (group 1: public members who had not engaged with the system; group 2: a subset of patients who completed the measurement system) completed user-testing sessions and semistructured interviews to assess system effectiveness and user satisfaction. We conducted quantitative data analysis using descriptive statistics and calculated the task completion rate and survey response rate (system effectiveness) as well as the task completion time, task efficiency, and relative efficiency (system efficiency). Qualitative thematic analysis identified indicators of and barriers to good usability (user satisfaction). RESULTS: A total of 2254 completed surveys were returned to the measurement system. A total of 25 service users (group 1: n=9; group 2: n=16) participated in user-testing sessions and interviews. The task completion rate was high (169/171, 98.8%) and the survey response rate was good (2254/5794, 38.9%). The median task completion time was 3 (IQR 2-13) minutes, suggesting good system efficiency and effectiveness. The qualitative findings emphasized good user satisfaction. The identified themes suggested that the measurement system is acceptable, easy to use, and easy to access. Service users identified potential barriers and solutions to acceptability and ease of access. CONCLUSIONS: A mixed methods evaluation of an electronic measurement system for automated, real-time monitoring of patients' experience of SDM showed that usability among patients was high. Future pilot work will optimize the system for wider implementation to ultimately inform intervention development to improve SDM. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2023-079155.

Flexible approaches to eCOA administration in clinical trials: The site perspective.

The Critical Path Institute convened the Support Flexible Approaches to PRO Data Collection project as part of the eCOA: Getting Better Together Initiative which was instigated to identify and address common challenges and drive positive change with eCOA implementation in clinical trials. The project aimed to identify clinical trial stakeholders' concerns related to electronic PRO (ePRO) implementation and propose areas of improvement via simplification and flexibility. One workstream focused on patient-/site-centric approaches for simplification and surveyed representatives of clinical sites and site monitors for their perspectives. A semi-structured questionnaire was developed and distributed via snowball sampling to site professionals and clinical research associates (CRAs) that had ePRO experience who had been identified via representative groups or sponsor-led site networks. Responses were received from various site roles across a range of global regions; the largest contribution was from the United States. Topics raised included helpdesk capabilities, technical concerns, device types, and user interfaces among others and are discussed further in this paper. The feedback derived from the questionnaire provided the basis for concrete ideas that sponsors should consider incorporating into protocol design for participant visits, technology use, devices, and methods of back-up data collection.

Biometric linkage of longitudinally collected electronic case report forms and confirmation of subject identity: an open framework for ODK and related tools.

The availability of low-cost biometric hardware sensors and software makes it possible to rapidly, affordably and securely sample and store a unique and invariant biological signature (or biometric "template") for the purposes of identification. This has applications in research and trials, particularly for purposes of consent, linkage of case reporting forms collected at different times, and in the confirmation of participant identity for purposes of safety monitoring and adherence to international data laws. More broadly, these methods are applicable to the needs of the billion people who live in resource-restricted settings without identification credentials. The use of mobile electronic data collection software has recently become commonplace in clinical trials, research and actions for public good. A raft of tools based on the open-source ODK project now provide diverse options for data management that work consistently in resource-restricted settings, but none have built-in functionality for capturing biometric templates. In this study, we report the development and validation of a novel open-source app and associated method for capturing and matching biometric fingerprint templates during data collection with the popular data platforms ODK, KoBoToolbox, SurveyCTO, Ona and CommCare. Using data from more than 1,000 fingers, we show that fingerprint templates can be used to link data records with high accuracy. The accuracy of this process increases through the linkage of multiple fingerprints to each data record. By focussing on publishing open-source code and documentation, and by using an affordable (<£50) and mass-produced model of fingerprint sensor, we are able to make this platform freely available to the large global user community that utilises ODK and related data collection systems.

Determining Inaccurate Coordinates in Electronic Data Collection for Surveillance and Immunization Supportive Supervision: A Case Study of Nigeria EPI Supportive Supervision Module.

The mobile phone global positioning system (GPS) is used to reconnaissance a mobile phone user's location, e.g., at work, home, shops, etc. Such information can be used to feed data gathering expeditions, the actual position of the interviewer/surveyor using the mobile phone inert settings of location mode via GPS, WIFI, and Mobile networks. Mobile devices are becoming progressively erudite and now integrate diverse and robust sensors. The new generation of smartphones is multi-laden with sensors, including GPS sensors. The study describes and evaluates a data-gathering process used by the World Health Organization (WHO-Nigeria, EPI Program) that uses phone-based in-built GPS sensors to identify the position of users while they undergo supportive supervision. This form of spatial data is collected intrinsically using the Open Data Kit (ODK) GPS interface, which interlaces with the mobile phone GPS sensor to fetch the geo-coordinates during the process. It represents a step in building a methodology of matching places on the map with the geo-coordinates received from the mobile phones to investigate deviation patterns by devices and location mode. The empirical results can help us to understand the variation in geospatial data collation across devices and highlight critical criteria for choosing mobile phones for mobile surveys and data campaigns. This study reviewed the existing data gathered inadvertently from 10 brands of smartphones over 1 year of using the mobile data collection with over 80,000 field visits to predict the deviation pattern for spatial data acquisition via mobile phones by different brands.

Quality improvement in juvenile idiopathic arthritis: a mixed-methods implementation pilot of the CAPTURE-JIA dataset.

BACKGROUND: A significant proportion of children and young people with juvenile idiopathic arthritis (JIA) do not achieve inactive disease during the first two years following diagnosis. Refinements to clinical care pathways have the potential to improve clinical outcomes but a lack of consistent and contemporaneous clinical data presently precludes standard setting and implementation of meaningful quality improvement programmes. This study was the first to pilot clinical data collection and analysis using the CAPTURE-JIA dataset, and to explore patient and clinician-reported feasibility and acceptability data. METHODS: A multiphase mixed-methods approach enabled prospective collection of quantitative data to examine the feasibility and efficacy of dataset collection and of qualitative data informing the context and processes of implementation. An initial paper pilot informed the design of a bespoke electronic data collection system (the Agileware system), with a subsequent electronic pilot informing the final CAPTURE-JIA data collection tool. RESULTS: Paper collection of patient data was feasible but time-consuming in the clinical setting. Phase 1 paper pilot data (121 patients) identified three themes: problematic data items (14/62 data items received >40% missing data), formatting of data collection forms and a clinician-highlighted need for digital data collection, informing Phase 2 electronic data collection tool development. Patients and families were universally supportive of the collection and analysis of anonymised patient data to inform clinical care. No apparent preference for paper / electronic data collection was reported by families. Phase 3 electronic pilot data (38 patients) appeared complete and the system reported to be easy to use. Analysis of the study dataset and a dummy longitudinal dataset confirmed that all eleven JIA national audit questions can be answered using the electronic system. CONCLUSIONS: Multicentre CAPTURE-JIA data collection is feasible and acceptable, with a bespoke data collection system highlighted as the most satisfactory solution. The study is informing ongoing work towards a streamlined and flexible national paediatric data collection system to drive quality improvement in clinical care.

National Implementation of an Electronic Patient-Reported Outcome Measures Program for Joint Replacement Surgery: Pilot Study.

BACKGROUND: There is a global emphasis on expanding data collection for joint replacement procedures beyond implant attributes and progression to revision surgery. Patient-reported outcome measures (PROMs) are increasingly considered as an important measure of surgical outcomes from a patient's perspective. However, a major limitation preventing wider use of PROMs data in national data collection has been the inability to systematically collect and share electronic information with relevant stakeholders in a comprehensive and financially sustainable manner. OBJECTIVE: This study reports on the development of an electronic data capture and reporting system by a national registry for the collection of PROMs and the processes used to identify and overcome barriers to implementation and uptake. The study also aims to provide a cost breakdown of establishing and maintaining a nationwide electronic PROMs program. METHODS: Between 2018 and 2020, 3 governance and advisory committees were established to develop and implement a PROMs pilot program nested within a nationwide joint replacement registry. The program involved electronic collection of preoperative and 6-month postoperative data for hip, knee, or shoulder replacement surgery from 44 Australian hospitals. Resource requirements for the program included a project manager, software developers, data manager, and statistician. An online platform was tested, refined, and implemented for electronic PROMs collection with scalability considered for future expansion to all Australian hospitals and additional data fields. Technical capabilities included different access for multiple user types, patient registration, automatic reminders via SMS text messages and email, online consent, and patient outcome real-time dashboards accessible for different user groups (surgeons, patients, hospitals, and project stakeholders). RESULTS: During the PROMs pilot period there were 19,699 primary procedures undertaken with 10,204 registered procedures in the electronic system. This equated to 51.80% of people who had a joint replacement at participating hospitals during this period. Patient registration and data collection were efficient (20-30 seconds and 10-12 minutes, respectively). Engagement with the reporting dashboards (as a proportion of those who viewed their dashboard) varied by user group: 197/277 (71.1%) hospital administrators, 68/129 (52.7%) project stakeholders, 177/391 (45.3%) surgeons, and 1138/8840 patients (12.9%). Cost analysis determined an overall cost per patient of Aus $7-15 (approximately US $5-12) for 2 PROMs collections per joint replacement procedure once the program was established. CONCLUSIONS: Successful implementation of an orthopedic PROMs program with planned scalability for a broader national rollout requires significant funding and staffing resources. However, this expenditure can be considered worthwhile, given that collection and reporting of PROMs can drive health care improvement processes. Further consideration of strategies to improve stakeholder engagement with electronic reporting dashboards (particularly for patients and surgeons) will be critical to the ongoing success of a national PROMs program.

The Strategies for Quantitative and Qualitative Remote Data Collection: Lessons From the COVID-19 Pandemic.

The COVID-19 pandemic has necessitated a rapid shift to web-based or blended design models for both ongoing and future clinical research activities. Research conducted virtually not only has the potential to increase the patient-centeredness of clinical research but may also further widen existing disparities in research participation among underrepresented individuals. In this viewpoint, we discuss practical strategies for quantitative and qualitative remote research data collection based on previous literature and our own ongoing clinical research to overcome challenges presented by the shift to remote data collection. We aim to contribute to and catalyze the dissemination of best practices related to remote data collection methodologies to address the opportunities presented by this shift and develop strategies for inclusive research.

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.

Electronic Data Management for Vaccine Trials in Low Resource Settings: Upgrades, Scalability, and Impact of ODK.

Background: ODK provides software and standards that are popular solutions for off-grid electronic data collection and has substantial code overlap and interoperability with a number of related software products including CommCare, Enketo, Ona, SurveyCTO, and KoBoToolbox. These tools provide open-source options for off-grid use in public health data collection, management, analysis, and reporting. During the 2018-2020 Ebola epidemic in the North Kivu and Ituri regions of Democratic Republic of Congo, we used these tools to support the DRC Ministère de la Santé RDC and World Health Organization in their efforts to administer an experimental vaccine (VSV-Zebov-GP) as part of their strategy to control the transmission of infection. Method: New functions were developed to facilitate the use of ODK, Enketo and R in large scale data collection, aggregation, monitoring, and near-real-time analysis during clinical research in health emergencies. We present enhancements to ODK that include a built-in audit-trail, a framework and companion app for biometric registration of ISO/IEC 19794-2 fingerprint templates, enhanced performance features, better scalability for studies featuring millions of data form submissions, increased options for parallelization of research projects, and pipelines for automated management and analysis of data. We also developed novel encryption protocols for enhanced web-form security in Enketo. Results: Against the backdrop of a complex and challenging epidemic response, our enhanced platform of open tools was used to collect and manage data from more than 280,000 eligible study participants who received VSV-Zebov-GP under informed consent. These data were used to determine whether the VSV-Zebov-GP was safe and effective and to guide daily field operations. Conclusions: We present open-source developments that make electronic data management during clinical research and health emergencies more viable and robust. These developments will also enhance and expand the functionality of a diverse range of data collection platforms that are based on the ODK software and standards.

Smartphone assisted oral health data recording - an android based software application development.

BACKGROUND: Smartphone compared to the traditional pen-paper method could enhance oral health data recording procedure by reducing the cost of data collection, risk of data loss, early detection of errors and reducing data entry time. The present research developed a mobile/tablet-based software application to capture oral health data and test its adaptability and operations in oral health surveys. METHODS: A comparative cross-sectional study was conducted among the general population of Sanwer town, Indore district. The initial testing of the application was done on 120 individuals. A random sampling (lottery method) followed by a systematic sampling strategy was employed to select 120 households. A "one per household" design was implemented for the survey. The initial oral health data collection was done using mobile-assisted software application followed by a second examination scheduled after 15 days on the same participants using the conventional Pen-paper method to collect oral health data. RESULTS: Six Investigator Recorder (IR) teams conducted the oral health data collection. Data collection through Smartphone-based application displayed less meantime (3.57 minutes) in comparison to pen-paper method (4.87 minutes) (p≤0.001). Survey team response showed the majority of investigators having strong agreement on user satisfaction and speed of data entry using software application. CONCLUSION: The initial testing of mobile-assisted recording system (MARS) efficiently captured oral health data among the general population with wide variations in oral disease level. The application facilitated minimal or no wastage of paper and had a high level of user-satisfaction, accuracy, speed of entry and low potential for any data loss.

The use of electronic PROMs provides same outcomes as paper version in a spine surgery registry. Results from a prospective cohort study.

BACKGROUND AND PURPOSE: Patient-Reported Measured Outcomes (PROMs) are essential to gain a full understanding of a patient's condition, and in spine surgery, these questionnaires are of help when tailoring a surgical strategy. Electronic registries allow for a systematic collection and storage of PROMs, making them readily available for clinical and research purposes. This study aimed to investigate the reliability between the electronic and paper form of ODI (Oswestry Disability Index), SF-36 (Short Form Health Survey 36) and COMI-back (Core Outcome Measures Index for the back) questionnaires. METHODS: A prospective analysis was performed of ODI, SF-36 and COMI-back questionnaires collected in paper and electronic format in two patients' groups: Pre-Operatively (PO) or at follow-up (FU). All patients, in both groups, completed the three questionnaires in paper and electronic form. The correlation between both methods was assessed with the Intraclass Correlation Coefficients (ICC). RESULTS: The data from 100 non-consecutive, volunteer patients with a mean age of 55.6 ± 15.0 years were analysed. For all of the three PROMs, the reliability between paper and electronic questionnaires results was excellent (ICC: ODI = 0.96; COMI = 0.98; SF36-MCS = 0.98; SF36-PCS = 0.98. For all p < 0.001). CONCLUSIONS: This study proved an excellent reliability between the electronic and paper versions of ODI, SF-36 and COMI-back questionnaires collected using a spine registry. This validation paves the way for stronger widespread use of electronic PROMs. They offer numerous advantages in terms of accessibility, storage, and data analysis compared to paper questionnaires.

Electronic data collection for multi-country, hospital-based, clinical observation of maternal and newborn care: EN-BIRTH study experiences.

BACKGROUND: Observation of care at birth is challenging with multiple, rapid and potentially concurrent events occurring for mother, newborn and placenta. Design of electronic data (E-data) collection needs to account for these challenges. The Every Newborn Birth Indicators Research Tracking in Hospitals (EN-BIRTH) was an observational study to assess measurement of indicators for priority maternal and newborn interventions and took place in five hospitals in Bangladesh, Nepal and Tanzania (July 2017-July 2018). E-data tools were required to capture individually-linked, timed observation of care, data extraction from hospital register-records or case-notes, and exit-survey data from women. METHODS: To evaluate this process for EN-BIRTH, we employed a framework organised around five steps for E-data design, data collection and implementation. Using this framework, a mixed methods evaluation synthesised evidence from study documentation, standard operating procedures, stakeholder meetings and design workshops. We undertook focus group discussions with EN-BIRTH researchers to explore experiences from the three different country teams (November-December 2019). Results were organised according to the five a priori steps. RESULTS: In accordance with the five-step framework, we found: 1) Selection of data collection approach and software: user-centred design principles were applied to meet the challenges for observation of rapid, concurrent events around the time of birth with time-stamping. 2) Design of data collection tools and programming: required extensive pilot testing of tools to be user-focused and to include in-built error messages and data quality alerts. 3) Recruitment and training of data collectors: standardised with an interactive training package including pre/post-course assessment. 4) Data collection, quality assurance, and management: real-time quality assessments with a tracking dashboard and double observation/data extraction for a 5% case subset, were incorporated as part of quality assurance. Internet-based synchronisation during data collection posed intermittent challenges. 5) Data management, cleaning and analysis: E-data collection was perceived to improve data quality and reduce time cleaning. CONCLUSIONS: The E-Data system, custom-built for EN-BIRTH, was valued by the site teams, particularly for time-stamped clinical observation of complex multiple simultaneous events at birth, without which the study objectives could not have been met. However before selection of a custom-built E-data tool, the development time, higher training and IT support needs, and connectivity challenges need to be considered against the proposed study or programme's purpose, and currently available E-data tool options.

Electronic data collection in a multi-site population-based survey: EN-INDEPTH study.

BACKGROUND: Electronic data collection is increasingly used for household surveys, but factors influencing design and implementation have not been widely studied. The Every Newborn-INDEPTH (EN-INDEPTH) study was a multi-site survey using electronic data collection in five INDEPTH health and demographic surveillance system sites. METHODS: We described experiences and learning involved in the design and implementation of the EN-INDEPTH survey, and undertook six focus group discussions with field and research team to explore their experiences. Thematic analyses were conducted in NVivo12 using an iterative process guided by a priori themes. RESULTS: Five steps of the process of selecting, adapting and implementing electronic data collection in the EN-INDEPTH study are described. Firstly, we reviewed possible electronic data collection platforms, and selected the World Bank's Survey Solutions® as the most suited for the EN-INDEPTH study. Secondly, the survey questionnaire was coded and translated into local languages, and further context-specific adaptations were made. Thirdly, data collectors were selected and trained using standardised manual. Training varied between 4.5 and 10 days. Fourthly, instruments were piloted in the field and the questionnaires finalised. During data collection, data collectors appreciated the built-in skip patterns and error messages. Internet connection unreliability was a challenge, especially for data synchronisation. For the fifth and final step, data management and analyses, it was considered that data quality was higher and less time was spent on data cleaning. The possibility to use paradata to analyse survey timing and corrections was valued. Synchronisation and data transfer should be given special consideration. CONCLUSION: We synthesised experiences using electronic data collection in a multi-site household survey, including perceived advantages and challenges. Our recommendations for others considering electronic data collection include ensuring adaptations of tools to local context, piloting/refining the questionnaire in one site first, buying power banks to mitigate against power interruption and paying attention to issues such as GPS tracking and synchronisation, particularly in settings with poor internet connectivity.

Predictors and Prospective Course of PANS: A Pilot Study Using Electronic Platforms for Data Collection.

Objectives: Little is known about the longitudinal course of pediatric acute-onset neuropsychiatric syndrome (PANS) because existing literature is primarily cross-sectional. To begin to address this gap, two digital platforms were used to prospectively monitor neuropsychiatric symptoms in children with PANS. The aim was to identify baseline clinical characteristics that would predict the course of neuropsychiatric symptoms over 12 weeks. We compared relative compliance between two electronic data acquisition platforms and evaluated agreement between parent-child ratings of symptoms. Methods: For 12 weeks, 20 children with PANS and their parents completed weekly rating scales of neuropsychiatric symptoms on Research Electronic Data Capture (REDCap) and concurrently parents completed tri-weekly ratings on My Pediatric Autoimmune Neuropsychiatric Disorders Associated with Streptococcal Infections (PANDAS) Chart, a symptom monitoring website. Longitudinal data were analyzed by using regression analyses. Results: Greater duration of time between onset of PANS and study enrollment was associated with worsening of parent-rated neuropsychiatric symptoms over 12 weeks (p = 0.05). Higher scores on parents' Caregiver Burden Inventory at baseline predicted that children would report more severe symptoms over the 12-week period (p = 0.01). Compliance rates for parents were 86.3% for the weekly REDCap PANS Symptoms Rating Scale compared with 53.8% for the tri-weekly My PANDAS Chart ratings. There was moderate agreement between children and parents on the PANS Symptom Rating Scale (r = 0.55, p < 0.0001). Conclusion: Our study highlights the utility of electronic methods for tracking longitudinal symptoms in children with PANS and suggests that particular baseline characteristics (e.g., delay in identification and treatment of PANS, greater caregiver burden) may be indicative of a differential trajectory of PANS course, with more severe symptoms over the short term. clinicaltrials.gov NCT04382716.

Data Quality and Cost-effectiveness Analyses of Electronic and Paper-Based Interviewer-Administered Public Health Surveys: Systematic Review.

BACKGROUND: A population-level survey (PLS) is an essential and standard method used in public health research that supports the quantification of sociodemographic events, public health policy development, and intervention designs. Data collection mechanisms in PLS seem to be a significant determinant in avoiding mistakes. Using electronic devices such as smartphones and tablet computers improves the quality and cost-effectiveness of public health surveys. However, there is a lack of systematic evidence to show the potential impact of electronic data collection tools on data quality and cost reduction in interviewer-administered surveys compared with the standard paper-based data collection system. OBJECTIVE: This systematic review aims to evaluate the impact of the interviewer-administered electronic data collection methods on data quality and cost reduction in PLS compared with traditional methods. METHODS: We conducted a systematic search of MEDLINE, CINAHL, PsycINFO, the Web of Science, EconLit, Cochrane CENTRAL, and CDSR to identify relevant studies from 2008 to 2018. We included randomized and nonrandomized studies that examined data quality and cost reduction outcomes, as well as usability, user experience, and usage parameters. In total, 2 independent authors screened the title and abstract, and extracted data from selected papers. A third author mediated any disagreements. The review authors used EndNote for deduplication and Rayyan for screening. RESULTS: Our search produced 3817 papers. After deduplication, we screened 2533 papers, and 14 fulfilled the inclusion criteria. None of the studies were randomized controlled trials; most had a quasi-experimental design, for example, comparative experimental evaluation studies nested on other ongoing cross-sectional surveys. A total of 4 comparative evaluations, 2 pre-post intervention comparative evaluations, 2 retrospective comparative evaluations, and 4 one-arm noncomparative studies were included. Meta-analysis was not possible because of the heterogeneity in study designs, types, study settings, and level of outcome measurements. Individual paper synthesis showed that electronic data collection systems provided good quality data and delivered faster compared with paper-based data collection systems. Only 2 studies linked cost and data quality outcomes to describe the cost-effectiveness of electronic data collection systems. Field data collectors reported that an electronic data collection system was a feasible, acceptable, and preferable tool for their work. Onsite data error prevention, fast data submission, and easy-to-handle devices were the comparative advantages offered by electronic data collection systems. Challenges during implementation included technical difficulties, accidental data loss, device theft, security concerns, power surges, and internet connection problems. CONCLUSIONS: Although evidence exists of the comparative advantages of electronic data collection compared with paper-based methods, the included studies were not methodologically rigorous enough to combine. More rigorous studies are needed to compare paper and electronic data collection systems in public health surveys considering data quality, work efficiency, and cost reduction. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/10678.

The Acceptability and Efficacy of Electronic Data Collection in a Hospital Neurodevelopmental Clinic: Pilot Questionnaire Study.

BACKGROUND: There is a growing need for cost-efficient and patient-centered approaches to support families in hospital- and community-based neurodevelopmental services. For such purposes, electronic data collection (EDC) may hold advantages over paper-based data collection. Such EDC approaches enable automated data collection for scoring and interpretation, saving time for clinicians and services and promoting more efficient service delivery. OBJECTIVE: This pilot study evaluated the efficacy of EDC for the Child Development Unit, a hospital-based diagnostic assessment clinic in the Sydney Children's Hospital Network. Caregiver response rates and preference for EDC or paper-based methods were evaluated as well as the moderating role of demographic characteristics such as age, level of education, and ethnic background. METHODS: Families were sent either a paper-based questionnaire via post or an electronic mail link for completion before attending their first on-site clinic appointment for assessment. A total of 62 families were provided a paper version of the questionnaire, while 184 families were provided the online version of the same questionnaire. RESULTS: Completion rates of the questionnaire before the first appointment were significantly higher for EDC (164/184, 89.1%) in comparison to paper-based methods (24/62, 39%; P<.001). Within the EDC group, a vast majority of respondents indicated a preference for completing the questionnaire online (151/173, 87.3%), compared to paper completion (22/173, 12.7%; P<.001). Of the caregiver demographic characteristics, only the respondent's level of education was associated with modality preference, such that those with a higher level of education reported a greater preference for EDC (P=.04). CONCLUSIONS: These results show that EDC is feasible in hospital-based clinics and has the potential to offer substantial benefits in terms of centralized data collation, time and cost savings, efficiency of service, and resource allocation. The results of this study therefore support the continued use of electronic methods to improve family-centered care in clinical practices.

Using implementation science to inform the integration of electronic patient-reported experience measures (ePREMs) into healthcare quality improvement: description of a theory-based application in primary care.

BACKGROUND: Collecting and monitoring the information from patients through patient-reported experience measures (PREMs) about the quality of care they receive is important for tracking changes in healthcare quality, stimulate innovation, and enhance person-centred care. The objective of this theoretical paper is to discuss the use of implementation science theories, models, and frameworks to inform and evaluate the integration of the electronic collection of PREMs (ePREMs) in healthcare quality improvement for primary care in Canada. METHODS: To assess potential knowledge-to-practice gaps in implementing ePREMs in primary care in Alberta, the overarching implementation model that will be used is the Knowledge to Action Cycle. An integrated knowledge translation approach will ensure ongoing engagement of key stakeholders (e.g. primary care providers, patients) throughout the study. ePREM implementation will be informed by the identification of barriers and facilitators to implementation using the Consolidated Framework for Implementation Research (CFIR). The CFIR brings an organizational perspective providing an opportunity to explore the intervention characteristics, the context of implementation, individual factors, and the processes that influence implementation of ePREMs in healthcare. Identified barriers and facilitators to ePREM implementation will be mapped to evidence-based implementation strategies and prioritized by stakeholders. The RE-AIM framework will be used to guide the evaluation of ePREM implementation outcomes after six months of implementation by assessing Reach, Effectiveness, Adoption, Implementation, and Maintenance (sustainability). DISCUSSION: Consultations with stakeholders affirm the importance of using integrated knowledge translation approaches and the need to better understand how to integrate ePREMs in primary care. Using an implementations science approach, this study can provide guidance for mitigating important ePREM implementation challenges and promote the successful uptake and use of ePREMs for quality improvement in healthcare.