Quality Improvement in Juvenile Idiopathic Arthritis: a Mixed-methods Implementation Pilot of the CAPTURE-JIA Dataset

BackgroundA 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.MethodsA 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. ResultsPaper 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. ConclusionsMulticentre 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.

Going digital: added value of electronic data collection in 2018 Afghanistan Health Survey

Background Through a nationally representative household survey in Afghanistan, we conducted an operational study in two relatively secure provinces comparing effectiveness of computer-aided personal interviewing (CAPI) with paper-and-pencil interviewing (PAPI). Methods In Panjshir and Parwan provinces, household survey data were collected using paper questionnaires in 15 clusters, and OpenDataKit (ODK) software on electronic tablets in 15 other clusters. Added value was evaluated from three perspectives: efficient implementation, data quality, and acceptability. Efficiency was measured through financial expenditures and time stamped data. Data quality was measured by examining completeness. Acceptability was studied through focus group discussions with survey staff. Results Survey costs were 68% more expensive in CAPI clusters compared to PAPI clusters, due primarily to the upfront one-time investment for survey programming. Enumerators spent significantly less time administering surveys in CAPI cluster households (248 min survey time) compared to PAPI (289 min), for an average savings of 41 min per household (95% CI 25–55). CAPI offered a savings of 87 days for data management over PAPI. Among 49 tracer variables (meaning responses were required from all respondents), small differences were observed between PAPI and CAPI. 2.2% of the cleaned dataset’s tracer data points were missing in CAPI surveys (1216/ 56,073 data points), compared to 3.2% in PAPI surveys (1953/ 60,675 data points). In pre-cleaned datasets, 3.9% of tracer data points were missing in CAPI surveys (2151/ 55,092 data points) compared to 3.2% in PAPI surveys (1924/ 60,113 data points). Enumerators from Panjsher and Parwan preferred CAPI over PAPI due to time savings, user-friendliness, improved data security, and less conspicuity when traveling; however approximately half of enumerators trained from all 34 provinces reported feeling unsafe due to Taliban presence. Community and household respondent skepticism could be resolved by enumerator reassurance. Enumerators shared that in the future, they prefer collecting data using CAPI when possible. Conclusions CAPI offers clear gains in efficiency over PAPI for data collection and management time, although costs are relatively comparable even without the programming investment. However, serious field staff concerns around Taliban threats and general insecurity mean that CAPI should only be conducted in relatively secure areas.

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.

Information and analytical tools for monitoring the prices of material and technical resources (MTR) of construction

The article deals with features and principles of the price monitoring system for material and technical resources operating now in the road industry. To improve the process of information collection, processing, and analysis concerning the cost of building materials, products, and structures, as well as other types of resources, it is proposed to reinforce a centralized single database of material and technical resources on the basis of regional data. Minimization of costs for data collection, storage, processing and use is possible only with the maximum automation of electronic data collection and exchange, which is realized during the implementation of elements of the centralized monitoring system (CMS) in practice. The architecture, algorithm, and regulations for the formation of a CMS are proposed.

Applications for data collection: AppDatCol

Health surveillance or routine health surveys are the main sources of health-related information in developing countries. The need to support the paper process and the recent advanced popularity of mobile devices fortified the development and use of electronic data collection methods in community health and clinical research works. Data collection apps are mobile applications that make it possible to collect data from a smartphone, tablet, or iPad. The main objective of this article is to explore different type of applications easily available for using as a tool for data collection purpose. This article will brief about software’s that are easily available to be customized and can be used for data collection. Mobile data collection apps are becoming integral to secure, reliable, and scalable research. The efficiency and dependability of these mobile survey apps, even in offline settings, open doors to new research possibilities. It begins with the freedom and adaptability of designing research-specific forms that work even in the most challenging environments. Sharing experiences of the barriers and distinct benefits of this technology will help future users to be better informed and allow for the swifter adoption of these and similar technologies. Although any digital form may suffice for the purpose of data gathering, not every data collection system may be used for sensitive, clinical or research data. We believe that Teamscope and CSPro stands out in the mobile data collection landscape and is the best choice for research purposes. No other application combines data encryption, passcode lock, cross-device compatibility with iOS and android, support for both cross sectional and longitudinal studies, like these applications does.

Staff Attitudes Towards Electronic Data Collection for a National Take-Home Naloxone Program

Background During the scaling-up of a national Norwegian take-home naloxone (THN) program, data collection methods shifted from paper-based to electronic. The aim of this study was to explore staff attitudes and preferences towards the shift in data collection. Methods In January-February 2020, a survey was sent out via email to personnel involved with the THN program (n=200). The survey included 17 questions, and covered staff demographics, experiences distributing THN, attitudes towards data collection (both paper and electronically), and an open response section. Descriptive statistics were performed for the survey results. The open response section was recorded from each questionnaire and was coded into major themes by the authors. Main findings In total, 122 staff completed the survey. Of these, 62% had experience with both electronic and paper-based forms, and there was a near unanimous preference towards electronic data collection over paper-based forms. From the free-text responses, staff found the electronic form to be a useful tool for conversation and overdose prevention education, and that the electronic form was easier to manage than the paper forms. Conclusion The shift towards electronic data collection was necessary for the feasibility of the Norwegian national THN program. This study found that staff not only tolerated the shift, but in most cases preferred this organizational change.

Electronic data collection to enhance disease surveillance at the slaughterhouse in a smallholder production system

Globally, meat inspection provides data for animal health surveillance. However, paper-based recording of data is often not reported through to higher authorities in sufficient detail. We trialled the use of an electronic meat inspection form in Kenyan slaughterhouses, in lieu of the currently used paper-based format. Meat inspectors in two ruminant slaughterhouses completed and submitted an electronic report for each animal slaughtered at their facility. The reports, which captured information on the animal demographics and any eventual condemnations, were stored in a central database and available in real-time. A stakeholder meeting was held towards the end of the study. Over the 2.75 year study period, 16,386 reports were submitted; a downward linear trend in the monthly submissions was noted. There was a week effect, whereby more reports were submitted on the market day. Of the slaughtered animals, 23% had at least a partial condemnation. The most frequently condemned organs were the liver, lungs and intestines; the primary reasons for condemnations were parasitic conditions. Lack of feedback and difficulty capturing animal origin information were the primary challenges highlighted. The study demonstrated that electronic data capture is feasible in such challenging environments, thereby improving the timeliness and resolution of the data collected.

Electronic data collection, management and analysis tools used for outbreak response in low- and middle-income countries: a systematic review and stakeholder survey

Background Use of electronic data collection, management and analysis tools to support outbreak response is limited, especially in low income countries. This can hamper timely decision-making during outbreak response. Identifying available tools and assessing their functions in the context of outbreak response would support appropriate selection and use, and likely more timely data-driven decision-making during outbreaks. Methods We conducted a systematic review and a stakeholder survey of the Global Outbreak Alert and Response Network and other partners to identify and describe the use of, and technical characteristics of, electronic data tools used for outbreak response in low- and middle-income countries. Databases included were MEDLINE, EMBASE, Global Health, Web of Science and CINAHL with publications related to tools for outbreak response included from January 2010–May 2020. Software tool websites of identified tools were also reviewed. Inclusion and exclusion criteria were applied and counts, and proportions of data obtained from the review or stakeholder survey were calculated. Results We identified 75 electronic tools including for data collection (33/75), management (13/75) and analysis (49/75) based on data from the review and survey. Twenty-eight tools integrated all three functionalities upon collection of additional information from the tool developer websites. The majority were open source, capable of offline data collection and data visualisation. EpiInfo, KoBoCollect and Open Data Kit had the broadest use, including for health promotion, infection prevention and control, and surveillance data capture. Survey participants highlighted harmonisation of data tools as a key challenge in outbreaks and the need for preparedness through training front-line responders on data tools. In partnership with the Global Health Network, we created an online interactive decision-making tool using data derived from the survey and review. Conclusions Many electronic tools are available for data -collection, −management and -analysis in outbreak response, but appropriate tool selection depends on knowledge of tools’ functionalities and capabilities. The online decision-making tool created to assist selection of the most appropriate tool(s) for outbreak response helps by matching requirements with functionality. Applying the tool together with harmonisation of data formats, and training of front-line responders outside of epidemic periods can support more timely data-driven decision making in outbreaks.

The intention of South Africans to engage in collaborative consumption: The case of Uber

Orientation: The idea of collaborative consumption is developing among consumers, where underutilised or excess resources, skills and money are shared among peers for compensation. Collaborative consumption involves sharing, and as such, Uber, an app-based transport service enables those with spare vehicle capacity to provide a fee-based transport solution.Research purpose: This study investigates the intention to use this service in a South African context, specifically through the Technology Acceptance Model (TAM) and Theory of Planned Behaviour (TPB) because of the suitability of these models in this context. Differences between regular and seldom users are also examined.Motivation for the study: With the widespread use of Uber in South Africa, understanding the factors contributing to the intention to use Uber requires examination.Research design, approach and method: Data were collected using a quantitative survey among panel respondents of South Africans, using electronic data collection. The research instrument comprised pre-existing items measured on a 6-point Likert scale. A total of 367 usable responses were received. Data analysis included testing for differences in means (t-test, Satterthwaite-Welch t-test, Anova F-test, Welch F-test) as well as regression analysis (by means of multiple regressions and two-stage least squares).Main findings: The findings indicate that South Africans intend to use the service largely due to their positive attitude towards the service, the perceived usefulness (PU) of the app and perceived behavioural (PB) control associated with the service. The value of the app has been highlighted in this research, and the importance of its functioning is evident.Practical/managerial implications: The importance of providing a positive service experience impacts the intention to use the service in the future. This emphasises the importance of the service itself and the functioning of the app.Contribution/value-add: Understanding the intention to use this service enables further development of this app and associated services.

Going Digital: Added Value of Electronic Data Collection In 2018 Afghanistan Health Survey

Background: Through a nationally representative household survey in Afghanistan, we conducted an operational study in two relatively secure provinces comparing effectiveness of computer-aided personal interviewing (CAPI) with paper-and-pencil interviewing (PAPI). Methods: In Panjshir and Parwan provinces, household survey data were collected using paper questionnaires in 15 clusters, and OpenDataKit (ODK) software on electronic tablets in 15 other clusters. Added value was evaluated from three perspectives: efficient implementation, data quality, and acceptability. Efficiency was measured through financial expenditures and time stamped data. Data quality was measured by examining completeness. Acceptability was studied through focus group discussions with survey staff.Results: Survey costs were 68% more expensive in CAPI clusters compared to PAPI clusters, due primarily to the upfront one-time investment for survey programming. Enumerators spent significantly less time administering surveys in CAPI cluster households (248 minutes survey time) compared to PAPI (289 minutes), for an average savings of 41 minutes per household (95% CI: 25 – 55). CAPI offered a savings of 87 days for data management over PAPI.Among 49 tracer variables (meaning responses were required from all respondents), small differences were observed between PAPI and CAPI. 2.2% of the cleaned dataset’s tracer data points were missing in CAPI surveys (1,216/ 56,073 data points), compared to 3.2% in PAPI surveys (1,953/ 60,675 data points). In pre-cleaned datasets, 3.9% of tracer data points were missing in CAPI surveys (2,151/ 55,092 data points) compared to 3.2% in PAPI surveys (1,924/ 60,113 data points). Enumerators from Panjsher and Parwan preferred CAPI over PAPI due to time savings, user-friendliness, improved data security, and less conspicuity when traveling; however approximately half of enumerators trained from all 34 provinces reported feeling unsafe due to Taliban presence. Community and household respondent skepticism could be resolved by enumerator reassurance. Enumerators shared that in the future, they prefer collecting data using CAPI when possible.Conclusions: CAPI offers clear gains in efficiency over PAPI for data collection and management time, although costs are relatively comparable even without the programming investment. However, serious field staff concerns around Taliban threats and general insecurity mean that CAPI should only be conducted in relatively secure areas.