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Indian Journal of Public Health 2022Containing expenditure and efficient resource use is essential to limit the increasing costs of health research. Electronic data collection (EDC) is thought to reduce...
BACKGROUND
Containing expenditure and efficient resource use is essential to limit the increasing costs of health research. Electronic data collection (EDC) is thought to reduce the costs compared to paper-based data collection (PDC).
OBJECTIVES
As economic evidence in this area is scanty, especially in low- and middle-income countries, the objectives of the study are to perform an economic evaluation and compare the cost between EDC and PDC.
METHODS
A cost-comparison study was conducted to compare between EDC and PDC from the institutional perspective for the year 2018, based on a community-based survey. Step-down cost accounting was adopted with a bottom-up approach for cost estimation. Total and unit costs were estimated with the base case comparison between EDC and PDC while using SPSS software (e-SPSS and p-SPSS, respectively). We conducted scenario analyses based on the usage of different software, R and STATA for both EDC and PDC (e-R, p-R, e-STATA, and p-STATA, respectively). One-way and probabilistic sensitivity analysis (PSA) was performed to examine the robustness of the observed results.
RESULTS
In the base-case analysis, total costs of EDC and PDC were ₹72,617 ($1060.9) and 87,717 ($1281.5), respectively, with estimated cost reduction of ₹15,100 ($220.6). In other scenarios, the estimated cost reduction for e-R, e-STATA, p-R, p-STATA was ₹-274 ($4.0), 98 ($1.4), 14826 ($216.6), and 15,002 ($219.2), respectively, when compared to EDC-SPSS. On one-way and PSA, the results of the cost-comparison analysis were robust.
CONCLUSION
EDC minimizes institutional cost for conducting health research. This finding will help researchers in efficiently planning for the budget for their research.
Topics: Humans; India; Cost-Benefit Analysis; Software; Surveys and Questionnaires
PubMed: 37039171
DOI: 10.4103/ijph.ijph_1271_21 -
Revista Gaucha de Enfermagem 2020To identify and map the online data collection strategies used in qualitative researches in the health field. (Review)
Review
OBJECTIVE
To identify and map the online data collection strategies used in qualitative researches in the health field.
METHODS
This is a scoping review guided by the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) from the Joanna Briggs Institute. We analyzed scientific articles, theses and dissertations from 12 databases. The analysis was made by descriptive statistics.
RESULTS
The final sample consisted of 121 researches. It was found that the number of publications increased sharply in the last five years, with predominance of studies from the United Kingdom. The highlight fields were psychology (28.1%), medicine (25.6%) and nursing (12.4%). The publications used 10 online data collection strategies: Online questionnaires, online forums, Facebook, websites, blogs, e-mail, online focus group, Twitter, chats, and YouTube.
CONCLUSIONS
Online data collection strategies are constantly expanding and increasingly used in the health area.
Topics: Data Collection; Databases, Factual; Humans; Internet; Qualitative Research
PubMed: 32555956
DOI: 10.1590/1983-1447.2020.20190297 -
Industrial Health Aug 2019Recent reviews of musicians' musculoskeletal symptoms (MSS) have reported heterogeneity in the outcomes reported and data collection tools used, making it difficult to... (Review)
Review
Recent reviews of musicians' musculoskeletal symptoms (MSS) have reported heterogeneity in the outcomes reported and data collection tools used, making it difficult to compare and synthesise findings. The purpose of this present review was to improve the consistency of future research, by documenting the outcomes reported in recent studies of musicians' MSS and the data collection tools used. All English language, peer-reviewed studies, published 2007-2016 that reported musicians' self-reported MSS outcomes were identified. Details of the types of outcomes reported and the tools used were extracted, and synthesised descriptively. A range of MSS outcomes were reported, including MSS with a temporal relationship to activities performed, and the consequences of symptoms. Only 24% of studies used standardised questionnaires, with the Nordic Musculoskeletal Questionnaire (NMQ) being the most commonly used. To improve the homogeneity of outcomes and data collection tools when investigating musicians' MSS, we recommend using the NMQ, where appropriate. Recall periods of 12-months and 7-d are the most appropriate for prevalence, and 7-d recall periods for ratings. Importantly, outcomes and the tools used to collect data should be reported in sufficient detail to ensure that the study can be replicated, critiqued, and accurately interpreted.
Topics: Humans; Musculoskeletal Diseases; Music; Occupational Diseases; Occupational Medicine; Self Report; Surveys and Questionnaires; Symptom Assessment
PubMed: 30555103
DOI: 10.2486/indhealth.2018-0065 -
Revue Scientifique Et Technique... May 2023In 2015, the World Organisation for Animal Health (WOAH, founded as OIE) initiated the annual collection of data on antimicrobials intended for use in animals using a...
In 2015, the World Organisation for Animal Health (WOAH, founded as OIE) initiated the annual collection of data on antimicrobials intended for use in animals using a Microsoft Excel questionnaire. In 2022, WOAH initiated the migration to a customised interactive online system: ANIMUSE Global Database. This system enables national Veterinary Services not only to monitor and report data more easily and more accurately, but also to visualise, analyse and use data for surveillance purposes to their own benefit in the implementation of national action plans on antimicrobial resistance. This journey started seven years ago, with progressive improvements in the way data are collected, analysed and reported and continuous adaptations to overcome various challenges encountered (e.g. data confidentiality, training of civil servants, calculation of active ingredients, standardisation to enable fair comparisons and trend analyses, and data interoperability). Technical developments have been key in the success of this endeavour. However, it is important not to underestimate the importance of the human element: to listen to WOAH Members and their needs, and to exchange to solve issues, adapt tools, and gain and maintain trust. The journey is not over yet, and more developments are foreseen, such as to complement current data sources with data collected directly at the farm level; strengthen interoperability and integrated analysis with cross-sectoral databases; and facilitate institutionalisation of data collection and systematic use in monitoring, evaluation, lesson learning, reporting and, eventually, surveillance of antimicrobial use and antimicrobial resistance when implementing and updating national action plans. This paper describes how all these challenges were overcome and how future challenges will be addressed.
Topics: Animals; Humans; Anti-Infective Agents; Global Health; Data Collection
PubMed: 37232304
DOI: 10.20506/rst.42.3363 -
PLoS Biology Dec 2020Researchers face many, often seemingly arbitrary, choices in formulating hypotheses, designing protocols, collecting data, analyzing data, and reporting results....
Researchers face many, often seemingly arbitrary, choices in formulating hypotheses, designing protocols, collecting data, analyzing data, and reporting results. Opportunistic use of "researcher degrees of freedom" aimed at obtaining statistical significance increases the likelihood of obtaining and publishing false-positive results and overestimated effect sizes. Preregistration is a mechanism for reducing such degrees of freedom by specifying designs and analysis plans before observing the research outcomes. The effectiveness of preregistration may depend, in part, on whether the process facilitates sufficiently specific articulation of such plans. In this preregistered study, we compared 2 formats of preregistration available on the OSF: Standard Pre-Data Collection Registration and Prereg Challenge Registration (now called "OSF Preregistration," http://osf.io/prereg/). The Prereg Challenge format was a "structured" workflow with detailed instructions and an independent review to confirm completeness; the "Standard" format was "unstructured" with minimal direct guidance to give researchers flexibility for what to prespecify. Results of comparing random samples of 53 preregistrations from each format indicate that the "structured" format restricted the opportunistic use of researcher degrees of freedom better (Cliff's Delta = 0.49) than the "unstructured" format, but neither eliminated all researcher degrees of freedom. We also observed very low concordance among coders about the number of hypotheses (14%), indicating that they are often not clearly stated. We conclude that effective preregistration is challenging, and registration formats that provide effective guidance may improve the quality of research.
Topics: Data Collection; Humans; Quality Control; Registries; Research Design
PubMed: 33296358
DOI: 10.1371/journal.pbio.3000937 -
Journal of Medical Internet Research Mar 2023Digital phenotyping refers to near-real-time data collection from personal digital devices, particularly smartphones, to better quantify the human phenotype. Methodology...
Digital phenotyping refers to near-real-time data collection from personal digital devices, particularly smartphones, to better quantify the human phenotype. Methodology using smartphones is often considered the gold standard by many for passive data collection within the field of digital phenotyping, which limits its applications mainly to adults or adolescents who use smartphones. However, other technologies, such as wearable devices, have evolved considerably in recent years to provide similar or better quality passive physiologic data of clinical relevance, thus expanding the potential of digital phenotyping applications to other patient populations. In this perspective, we argue for the continued expansion of digital phenotyping to include other potential gold standards in addition to smartphones and provide examples of currently excluded technologies and populations who may uniquely benefit from this technology.
Topics: Adult; Adolescent; Humans; Smartphone; Wearable Electronic Devices; Data Collection; Phenotype; Data Accuracy
PubMed: 36917148
DOI: 10.2196/39546 -
BMC Research Notes Aug 2019Electronic data collection (EDC) has become a suitable alternative to paper based data collection (PBDC) in biomedical research even in resource poor settings. During a...
OBJECTIVE
Electronic data collection (EDC) has become a suitable alternative to paper based data collection (PBDC) in biomedical research even in resource poor settings. During a survey in Nepal, data were collected using both systems and data entry errors compared between both methods. Collected data were checked for completeness, values outside of realistic ranges, internal logic and date variables for reasonable time frames. Variables were grouped into 5 categories and the number of discordant entries were compared between both systems, overall and per variable category.
RESULTS
Data from 52 variables collected from 358 participants were available. Discrepancies between both data sets were found in 12.6% of all entries (2352/18,616). Differences between data points were identified in 18.0% (643/3580) of continuous variables, 15.8% of time variables (113/716), 13.0% of date variables (140/1074), 12.0% of text variables (86/716), and 10.9% of categorical variables (1370/12,530). Overall 64% (1499/2352) of all discrepancies were due to data omissions, 76.6% (1148/1499) of missing entries were among categorical data. Omissions in PBDC (n = 1002) were twice as frequent as in EDC (n = 497, p < 0.001). Data omissions, specifically among categorical variables were identified as the greatest source of error. If designed accordingly, EDC can address this short fall effectively.
Topics: Biomedical Research; Data Collection; Electronic Health Records; Humans; Nepal; Publications; Reproducibility of Results; Surveys and Questionnaires; Text Messaging
PubMed: 31439025
DOI: 10.1186/s13104-019-4574-8 -
Sensors (Basel, Switzerland) Dec 2022Hourly traffic volumes, collected by automatic traffic recorders (ATRs), are of paramount importance since they are used to calculate average annual daily traffic (AADT)...
Hourly traffic volumes, collected by automatic traffic recorders (ATRs), are of paramount importance since they are used to calculate average annual daily traffic (AADT) and design hourly volume (DHV). Hence, it is necessary to ensure the quality of the collected data. Unfortunately, ATRs malfunction occasionally, resulting in missing data, as well as unreliable counts. This naturally has an impact on the accuracy of the key parameters derived from the hourly counts. This study aims to solve this problem. ATR data from New South Wales, Australia was screened for irregularities and invalid entries. A total of 25% of the reliable data was randomly selected to test thirteen different imputation methods. Two scenarios for data omission, i.e., 25% and 100%, were analyzed. Results indicated that missForest outperformed other imputation methods; hence, it was used to impute the actual missing data to complete the dataset. AADT values were calculated from both original counts before imputation and completed counts after imputation. AADT values from imputed data were slightly higher. The average daily volumes when plotted validated the quality of imputed data, as the annual trends demonstrated a relatively better fit.
Topics: Data Collection; Australia
PubMed: 36560244
DOI: 10.3390/s22249876 -
BMC Emergency Medicine Mar 2022Delivery of major trauma care is complex and often fast paced. Clear and comprehensive documentation is paramount to support effective communication during complex... (Randomized Controlled Trial)
Randomized Controlled Trial
BACKGROUND
Delivery of major trauma care is complex and often fast paced. Clear and comprehensive documentation is paramount to support effective communication during complex clinical care episodes, and to allow collection of data for audit, research and continuous improvement. Clinical events are typically recorded on paper-based records that are developed for individual centres or systems. As one of the priorities laid out by the Scottish Trauma Network project was to develop an electronic data collection system, the TraumaApp was created as a data collection tool for major trauma that could be adopted worldwide.
METHODS
The study was performed as a service evaluation based at the Queen Elizabeth University Hospital Emergency Department. Fifty staff members were recruited in pairs and listened to five paired major trauma standby and handover recordings. Participants were randomised to input data to the TraumaApp and one into the existing paper proforma. The time taken to input data add into was measured, along with time for clarifications and any errors made. Those using the app completed a System Usability Score.
RESULTS
No statistically significant difference was demonstrated between times taken for data entry for the digital and paper documentation, apart from the Case 5 Handover (p < 0.05). Case 1 showed a significantly higher time for clarifications and number of errors with digital data collection (p = 0.01 and p = 1.79E-05 respectively). There were no other differences between data for the app and the proforma. The mean System Usability score for this cohort was 75 out of 100, with a standard deviation of 17 (rounded to nearest integer).
CONCLUSION
Digital real-time recording of clinical events using a tool such as the TraumaApp is comparable to completion of paper proforma. The System Usability Score for the TraumaApp was above the internationally validated standard of acceptable usability. There was no evidence of improvement in use over time or familiarity, most likely due to the brevity of the assessments and the refined user interface. This would benefit from further research, exploring data completeness and a potential mixed methods approach to explore training requirements for use of the TraumaApp.
Topics: Data Collection; Documentation; Humans
PubMed: 35279070
DOI: 10.1186/s12873-022-00578-9 -
Journal of Injury & Violence Research Jul 2021Sufficient data should be gathered and analyzed to increase awareness and attention of the community and policymakers in the field of road traffic injury (RTI)...
BACKGROUND
Sufficient data should be gathered and analyzed to increase awareness and attention of the community and policymakers in the field of road traffic injury (RTI) prevention. While various organizations and stakeholders are involved in road traffic crashes, there is no clear lead agency for data collection system in RTIs. Exploring stakeholders' perspective is one of the key sources for understanding this system. The purpose of this study is to identify the process of RTI data collection system based on stakeholders' experience.
METHODS
This qualitative study was conducted employing grounded theory approach since September 2017 to December 2018 in Iran. Participants in this study were the authorities of the Emergency organizations, police, Ministry of Health and Medical Education, faculty members, as well as executive staff and road users who were involved in collecting and recording data (n=15). Data collection was carried out through face-to-face interviews using purposeful and theoretical sampling. Data analysis was performed based on Strauss and Corbin 2008.
RESULTS
The core category was identified as "separated registration" explaining the process of collecting and recording road traffic injury data. Other variables obtained using the Strauss and Corbin Paradigm model were categorized as context, casual, intervening, strategies, and outcomes factors. The findings were classified into five groups including lack of trust in road safety promotion, process factors, management and organizational factors, failure of quality assurance, and administrative and organizational culture.
CONCLUSIONS
The most important theory is "separated registration" and non-systematic registry system of road traffic injury data which is shown in a conceptual model. The findings of this study will help policymakers for better understanding the collecting and recording of RTI information.
Topics: Accidents, Traffic; Data Collection; Grounded Theory; Humans; Iran; Registries; Wounds and Injuries
PubMed: 33875628
DOI: 10.5249/jivr.v13i2.1406