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Life Sciences, Society and Policy Jan 2018Digital Epidemiology is a new field that has been growing rapidly in the past few years, fueled by the increasing availability of data and computing power, as well as by...
Digital Epidemiology is a new field that has been growing rapidly in the past few years, fueled by the increasing availability of data and computing power, as well as by breakthroughs in data analytics methods. In this short piece, I provide an outlook of where I see the field heading, and offer a broad and a narrow definition of the term.
Topics: Data Collection; Electronic Health Records; Epidemiologic Studies; Humans
PubMed: 29302758
DOI: 10.1186/s40504-017-0065-7 -
JMIR MHealth and UHealth Feb 2019Periodic demographic health surveillance and surveys are the main sources of health information in developing countries. Conducting a survey requires extensive use of... (Randomized Controlled Trial)
Randomized Controlled Trial
Evaluation of Electronic and Paper-Pen Data Capturing Tools for Data Quality in a Public Health Survey in a Health and Demographic Surveillance Site, Ethiopia: Randomized Controlled Crossover Health Care Information Technology Evaluation.
BACKGROUND
Periodic demographic health surveillance and surveys are the main sources of health information in developing countries. Conducting a survey requires extensive use of paper-pen and manual work and lengthy processes to generate the required information. Despite the rise of popularity in using electronic data collection systems to alleviate the problems, sufficient evidence is not available to support the use of electronic data capture (EDC) tools in interviewer-administered data collection processes.
OBJECTIVE
This study aimed to compare data quality parameters in the data collected using mobile electronic and standard paper-based data capture tools in one of the health and demographic surveillance sites in northwest Ethiopia.
METHODS
A randomized controlled crossover health care information technology evaluation was conducted from May 10, 2016, to June 3, 2016, in a demographic and surveillance site. A total of 12 interviewers, as 2 individuals (one of them with a tablet computer and the other with a paper-based questionnaire) in 6 groups were assigned in the 6 towns of the surveillance premises. Data collectors switched the data collection method based on computer-generated random order. Data were cleaned using a MySQL program and transferred to SPSS (IBM SPSS Statistics for Windows, Version 24.0) and R statistical software (R version 3.4.3, the R Foundation for Statistical Computing Platform) for analysis. Descriptive and mixed ordinal logistic analyses were employed. The qualitative interview audio record from the system users was transcribed, coded, categorized, and linked to the International Organization for Standardization 9241-part 10 dialogue principles for system usability. The usability of this open data kit-based system was assessed using quantitative System Usability Scale (SUS) and matching of qualitative data with the isometric dialogue principles.
RESULTS
From the submitted 1246 complete records of questionnaires in each tool, 41.89% (522/1246) of the paper and pen data capture (PPDC) and 30.89% (385/1246) of the EDC tool questionnaires had one or more types of data quality errors. The overall error rates were 1.67% and 0.60% for PPDC and EDC, respectively. The chances of more errors on the PPDC tool were multiplied by 1.015 for each additional question in the interview compared with EDC. The SUS score of the data collectors was 85.6. In the qualitative data response mapping, EDC had more positive suitability of task responses with few error tolerance characteristics.
CONCLUSIONS
EDC possessed significantly better data quality and efficiency compared with PPDC, explained with fewer errors, instant data submission, and easy handling. The EDC proved to be a usable data collection tool in the rural study setting. Implementation organization needs to consider consistent power source, decent internet connection, standby technical support, and security assurance for the mobile device users for planning full-fledged implementation and integration of the system in the surveillance site.
Topics: Adult; Cross-Over Studies; Data Accuracy; Data Collection; Ethiopia; Female; Health Surveys; Humans; Male; Prospective Studies; Surveys and Questionnaires; Technology Assessment, Biomedical
PubMed: 30741642
DOI: 10.2196/10995 -
Developmental Medicine and Child... Feb 2016To describe cerebral palsy (CP) surveillance programmes and identify similarities and differences in governance and funding, aims and scope, definition,...
AIM
To describe cerebral palsy (CP) surveillance programmes and identify similarities and differences in governance and funding, aims and scope, definition, inclusion/exclusion criteria, ascertainment and data collection, to enhance the potential for research collaboration.
METHOD
Representatives from 38 CP surveillance programmes were invited to participate in an online survey and submit their data collection forms. Descriptive statistics were used to summarize information submitted.
RESULTS
Twenty-seven surveillance programmes participated (25 functioning registers, two closed owing to lack of funding). Their aims spanned five domains: resource for CP research, surveillance, aetiology/prevention, service planning, and information provision (in descending order of frequency). Published definitions guided decision making for the definition of CP and case eligibility for most programmes. Consent, case identification, and data collection methods varied widely. Ten key data items were collected by all programmes and a further seven by at least 80% of programmes. All programmes reported an interest in research collaboration.
INTERPRETATION
Despite variability in methodologies, similarities exist across programmes in terms of their aims, definitions, and data collected. These findings will facilitate harmonization of data and collaborative research efforts, which are so necessary on account of the heterogeneity and relatively low prevalence of CP.
Topics: Cerebral Palsy; Data Collection; Humans; International Cooperation; Population Surveillance; Prevalence; Registries
PubMed: 26781543
DOI: 10.1111/dmcn.12999 -
Informatics in Primary Care 2012Health research using routinely collected National Health Service (NHS) data derived from electronic health records (EHRs) and health service information systems has...
INTRODUCTION
Health research using routinely collected National Health Service (NHS) data derived from electronic health records (EHRs) and health service information systems has been growing in both importance and quantity. Wide population coverage and detailed patient-level information allow this data to be applied to a variety of research questions. However, the sensitivity, complexity and scale of such data also hamper researchers from fully exploiting this potential.
OBJECTIVE
Here, we establish the current challenges preventing researchers from making optimal use of the data sets at their disposal, on both the legislative and practical levels, and give recommendations as to how these challenges can be overcome.
METHOD
A number of projects has recently been launched in the UK to address poor research data-management practices. Rapid Organisation of Healthcare Research Data (ROHRD) at Imperial College, London produced a useful prototype that provides local researchers with a one-stop index of available data sets together with relevant metadata.
FINDINGS
Increased transparency of data sets' availability and their provenance leads to better utilisation and facilitates compliance with regulatory requirements.
DISCUSSION
Research data resulting from NHS data is often not utilised fully, or is handled in a haphazard manner that prevents full auditability of the research. Furthermore, lack of informatics and data management skills in research teams act as a barrier to implementing more advanced practices, such as provenance capture and detailed, regularly updated, data management strategies. Only by a concerted effort at the levels of research organisations, funding bodies and publishers, can we achieve full transparency and reproducibility of the research.
Topics: Confidentiality; Data Collection; Electronic Health Records; Health Services Research; Humans; State Medicine; United Kingdom
PubMed: 23890333
DOI: 10.14236/jhi.v20i4.1 -
Health Policy and Planning Apr 2020High-quality data are essential to monitor and evaluate community health worker (CHW) programmes in low- and middle-income countries striving towards universal health...
High-quality data are essential to monitor and evaluate community health worker (CHW) programmes in low- and middle-income countries striving towards universal health coverage. This mixed-methods study was conducted in two purposively selected districts in Kenya (where volunteers collect data) and two in Malawi (where health surveillance assistants are a paid cadre). We calculated data verification ratios to quantify reporting consistency for selected health indicators over 3 months across 339 registers and 72 summary reports. These indicators are related to antenatal care, skilled delivery, immunization, growth monitoring and nutrition in Kenya; new cases, danger signs, drug stock-outs and under-five mortality in Malawi. We used qualitative methods to explore perceptions of data quality with 52 CHWs in Kenya, 83 CHWs in Malawi and 36 key informants. We analysed these data using a framework approach assisted by NVivo11. We found that only 15% of data were reported consistently between CHWs and their supervisors in both contexts. We found remarkable similarities in our qualitative data in Kenya and Malawi. Barriers to data quality mirrored those previously reported elsewhere including unavailability of data collection and reporting tools; inadequate training and supervision; lack of quality control mechanisms; and inadequate register completion. In addition, we found that CHWs experienced tensions at the interface between the formal health system and the communities they served, mediated by the social and cultural expectations of their role. These issues affected data quality in both contexts with reports of difficulties in negotiating gender norms leading to skipping sensitive questions when completing registers; fabrication of data; lack of trust in the data; and limited use of data for decision-making. While routine systems need strengthening, these more nuanced issues also need addressing. This is backed up by our finding of the high value placed on supportive supervision as an enabler of data quality.
Topics: Community Health Workers; Data Accuracy; Data Collection; Female; Humans; Kenya; Malawi; Male; Maternal-Child Health Services; Qualitative Research; Quality Control; Trust; Volunteers
PubMed: 31977014
DOI: 10.1093/heapol/czz163 -
The Journals of Gerontology. Series B,... Nov 2014This report seeks to inform National Social Life, Health, and Aging Project (NSHAP) data users of the prevalence and predictors of missing data in the in-person...
OBJECTIVES
This report seeks to inform National Social Life, Health, and Aging Project (NSHAP) data users of the prevalence and predictors of missing data in the in-person interview (CAPI) and leave-behind questionnaire (LBQ) in Wave 2 of NSHAP, and methods to handle missingness.
METHOD
Missingness is quantified at the unit and item levels separately for CAPI and LBQ data, and at the item level is assessed within domains of conceptually related variables. Logistic and negative binomial regression analyses are used to model predictors of unit- and item-level nonresponse, respectively.
RESULTS
Unit-level nonresponse on the CAPI was 10.6% of those who responded at Wave 1, and LBQ nonresponse was 11.37% of those who completed the Wave 2 CAPI component. CAPI item-level missingness was less than 1% of items for most domains but 7.1% in the Employment and Finances domain. LBQ item-level missingness was 5% across domains but 8.3% in the Attitudes domain. Missingness was predicted by characteristics of the sample and features of the study design.
DISCUSSION
Multiple imputation is recommended to handle unit- and item-level missingness and can be readily and flexibly conducted with multiple imputation by chained equations, inverse probability weighting, and in some instances, full-information maximum-likelihood methods.
Topics: Age Factors; Aged; Aged, 80 and over; Aging; Data Collection; Data Interpretation, Statistical; Female; Health Status; Humans; Interviews as Topic; Longitudinal Studies; Male; Middle Aged; Prevalence; Socioeconomic Factors; Surveys and Questionnaires; United States
PubMed: 24809854
DOI: 10.1093/geronb/gbu044 -
Traffic Injury Prevention 2019The objective of this study was to evaluate and injury surveillance (IS) system's ability to monitor road traffic deaths and the coverage of road traffic injury and...
The objective of this study was to evaluate and injury surveillance (IS) system's ability to monitor road traffic deaths and the coverage of road traffic injury and death surveillance in Phuket, Thailand. U.S. Centers for Disease Control and Prevention guidelines on surveillance system evaluation were used to qualitatively and quantitatively evaluate IS. Interviews with key stakeholders focused on IS's usefulness, simplicity, flexibility, acceptability, and stability. Active case finding of 2014 road traffic deaths in all paper and electronic hospital record systems was used to assess system sensitivity, positive predictive value, and data quality. Electronic data matching software was used to determine the implications of combining IS data with other provincial-level data sources (e.g., death certificates, electronic vehicle insurance claim system). Evaluation results indicated that IS was useful, flexible, acceptable, and stable, with a high positive predictive value (99%). Simplicity was limited due to the burden of collecting data on all injuries and use of paper-based data collection forms. Sensitivity was low, with IS only identifying 55% of hospital road traffic death cases identified during active case finding; however, IS cases were representative of cases identified. Data accuracy and completeness varied across data fields. Combining IS with active case finding, death certificates, and the electronic vehicle insurance claim system more than doubled the number of road traffic death cases identified in Phuket. An efficient and comprehensive road traffic injury and death surveillance system is critical for monitoring Phuket's road traffic burden. The hospital-based IS system is a useful system for monitoring road traffic deaths and assessing risk behaviors. However, the complexity of data collection and limited coverage hinders the ability of IS to fully represent road traffic deaths in Phuket Province. Combining data sources could improve coverage and should be considered.
Topics: Accidents, Traffic; Data Collection; Humans; Thailand
PubMed: 31050566
DOI: 10.1080/15389588.2019.1581924 -
British Journal of Anaesthesia Nov 2017
Topics: Airway Management; Data Collection; Humans; Infant; Infant, Newborn; Pediatrics; Statistics as Topic
PubMed: 29028951
DOI: 10.1093/bja/aex362 -
Bulletin of the World Health... Jan 2016To analyse the design and operational status of India's civil registration and vital statistics system and facilitate the system's development into an accurate and...
OBJECTIVE
To analyse the design and operational status of India's civil registration and vital statistics system and facilitate the system's development into an accurate and reliable source of mortality data.
METHODS
We assessed the national civil registration and vital statistics system's legal framework, administrative structure and design through document review. We did a cross-sectional study for the year 2013 at national level and in Punjab state to assess the quality of the system's mortality data through analyses of life tables and investigation of the completeness of death registration and the proportion of deaths assigned ill-defined causes. We interviewed registrars, medical officers and coders in Punjab state to assess their knowledge and practice.
FINDINGS
Although we found the legal framework and system design to be appropriate, data collection was based on complex intersectoral collaborations at state and local level and the collected data were found to be of poor quality. The registration data were inadequate for a robust estimate of mortality at national level. A medically certified cause of death was only recorded for 965,992 (16.8%) of the 5,735,082 deaths registered.
CONCLUSION
The data recorded by India's civil registration and vital statistics system in 2011 were incomplete. If improved, the system could be used to reliably estimate mortality. We recommend improving political support and intersectoral coordination, capacity building, computerization and state-level initiatives to ensure that every death is registered and that reliable causes of death are recorded - at least within an adequate sample of registration units within each state.
Topics: Cause of Death; Cross-Sectional Studies; Data Accuracy; Data Collection; Death Certificates; Humans; India; Life Expectancy; Life Tables; Vital Statistics
PubMed: 26769992
DOI: 10.2471/BLT.15.153585 -
International Journal of Environmental... Sep 2015Water quality monitoring is important for identifying public health risks and ensuring water safety. However, even when water sources are tested, many institutions...
When Are Mobile Phones Useful for Water Quality Data Collection? An Analysis of Data Flows and ICT Applications among Regulated Monitoring Institutions in Sub-Saharan Africa.
Water quality monitoring is important for identifying public health risks and ensuring water safety. However, even when water sources are tested, many institutions struggle to access data for immediate action or long-term decision-making. We analyzed water testing structures among 26 regulated water suppliers and public health surveillance agencies across six African countries and identified four water quality data management typologies. Within each typology, we then analyzed the potential for information and communication technology (ICT) tools to facilitate water quality information flows. A consistent feature of all four typologies was that testing activities occurred in laboratories or offices, not at water sources; therefore, mobile phone-based data management may be most beneficial for institutions that collect data from multiple remote laboratories. We implemented a mobile phone application to facilitate water quality data collection within the national public health agency in Senegal, Service National de l'Hygiène. Our results indicate that using the phones to transmit more than just water quality data will likely improve the effectiveness and sustainability of this type of intervention. We conclude that an assessment of program structure, particularly its data flows, provides a sound starting point for understanding the extent to which ICTs might strengthen water quality monitoring efforts.
Topics: Africa; Africa South of the Sahara; Cell Phone; Data Collection; Humans; Mobile Applications; Public Health; Senegal; Water Quality
PubMed: 26404343
DOI: 10.3390/ijerph120910846