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Bulletin Du Cancer Feb 2017The concept of big data indicates a change of scale in the use of data and data aggregation into large databases through improved computer technology. One of the current... (Review)
Review
The concept of big data indicates a change of scale in the use of data and data aggregation into large databases through improved computer technology. One of the current challenges in the creation of big data in the context of radiation therapy is the transformation of routine care items into dark data, i.e. data not yet collected, and the fusion of databases collecting different types of information (dose-volume histograms and toxicity data for example). Processes and infrastructures devoted to big data collection should not impact negatively on the doctor-patient relationship, the general process of care or the quality of the data collected. The use of big data requires a collective effort of physicians, physicists, software manufacturers and health authorities to create, organize and exploit big data in radiotherapy and, beyond, oncology. Big data involve a new culture to build an appropriate infrastructure legally and ethically. Processes and issues are discussed in this article.
Topics: Data Collection; Data Mining; Databases, Factual; Diagnostic Imaging; Genomics; Humans; Neoplasms; Organs at Risk; Physician-Patient Relations; Radiation Oncology; Radiotherapy
PubMed: 27914589
DOI: 10.1016/j.bulcan.2016.10.018 -
Revista Brasileira de Enfermagem 2018construct and validate the content of an instrument to collect data from patients with head and neck cancer (HNC) served in a specialty clinic.
OBJECTIVE
construct and validate the content of an instrument to collect data from patients with head and neck cancer (HNC) served in a specialty clinic.
METHOD
methodological study consisting of four steps. The first step consisted in the preparation of the instrument using databases and the theoretical model of Marjory Gordon. In the second and third steps the content was validated by eight nursing judges. The evaluation used the Content Validity Index (CVI). The fourth step consisted in a pilot test with seventeen HNC patients.
RESULTS
of the 88 questions formulated and organized on the dimensions of structure and process submitted to validation, items with CVI lower than 0.80 were excluded. The final instrument was composed of 56 items, with global CVI calculated as 0.87.
CONCLUSION
the final instrument presented content validity for data collection in head and neck clinic.
Topics: Adult; Data Collection; Female; Head and Neck Neoplasms; Humans; Male; Middle Aged; Psychometrics; Reproducibility of Results; Surveys and Questionnaires
PubMed: 30156675
DOI: 10.1590/0034-7167-2017-0227 -
The International Journal of Artificial... Oct 2016Dialysis is a highly quantitative therapy involving large volumes of both clinical and technical data. While automated data collection has been implemented for chronic... (Review)
Review
PURPOSE
Dialysis is a highly quantitative therapy involving large volumes of both clinical and technical data. While automated data collection has been implemented for chronic dialysis, this has not been done for acute kidney injury patients treated with continuous renal replacement therapy (CRRT).
METHODS
After a brief review of the fundamental aspects of electronic medical records (EMRs), a new tool designed to provide clinicians with individualized CRRT treatment data is analyzed, with emphasis on its quality assurance capabilities.
RESULTS
The first platform addressing the problem of data collection and management with current CRRT machines (Sharesource system; Baxter Healthcare) is described. The system provides connectivity for the Prismaflex CRRT machine and enables both EMR connectivity and therapy analytics with 2 basic components: the connect module and the report module.
CONCLUSIONS
The enormous amount of data in CRRT should be collected and analyzed to enable adequate clinical decisions. Current CRRT technology presents significant limitations with consequent lack of rigorous analysis of technical data and relevant feedback. From a quality assurance perspective, these limitations preclude any systematic assessment of prescription and delivery trends that may be adversely affecting clinical outcomes. A detailed assessment of current practice limitations is provided together with several possible ways to address such limitations by a new technical tool.
Topics: Acute Kidney Injury; Data Collection; Humans; Renal Replacement Therapy
PubMed: 27748946
DOI: 10.5301/ijao.5000522 -
Emergency Medicine Australasia : EMA Dec 2017
Topics: Data Accuracy; Data Collection; Humans; Research; Sepsis
PubMed: 29178275
DOI: 10.1111/1742-6723.12898 -
BMC Health Services Research Apr 2021The International Classification of Diseases (ICD) is the reference standard for reporting diseases and health conditions globally. Variations in ICD use and data...
BACKGROUND
The International Classification of Diseases (ICD) is the reference standard for reporting diseases and health conditions globally. Variations in ICD use and data collection across countries can hinder meaningful comparisons of morbidity data. Thus, we aimed to characterize ICD and hospital morbidity data collection features worldwide.
METHODS
An online questionnaire was created to poll the World Health Organization (WHO) member countries that were using ICD. The survey included questions focused on ICD meta-features and hospital data collection systems, and was distributed via SurveyMonkey using purposive and snowball sampling. Accordingly, senior representatives from organizations specialized in the topic, such as WHO Collaborating Centers, and other experts in ICD coding were invited to fill out the survey and forward the questionnaire to their peers. Answers were collated by country, analyzed, and presented in a narrative form with descriptive analysis.
RESULTS
Responses from 47 participants were collected, representing 26 different countries using ICD. Results indicated worldwide disparities in the ICD meta-features regarding the maximum allowable coding fields for diagnosis, the definition of main condition, and the mandatory type of data fields in the hospital morbidity database. Accordingly, the most frequently reported answers were "reason for admission" as main condition definition (n = 14), having 31 or more diagnostic fields available (n = 12), and "Diagnoses" (n = 26) and "Patient demographics" (n = 25) for mandatory data fields. Discrepancies in data collection systems occurred between but also within countries, thereby revealing a lack of standardization both at the international and national level. Additionally, some countries reported specific data collection features, including the use or misuse of ICD coding, the national standards for coding or lack thereof, and the electronic abstracting systems utilized in hospitals.
CONCLUSIONS
Harmonizing ICD coding standards/guidelines should be a common goal to enhance international comparisons of health data. The current international status of ICD data collection highlights the need for the promotion of ICD and the adoption of the newest version, ICD-11. Furthermore, it will encourage further research on how to improve and standardize ICD coding.
Topics: Hospitals; Humans; International Classification of Diseases; Morbidity; Surveys and Questionnaires; World Health Organization
PubMed: 33827567
DOI: 10.1186/s12913-021-06302-w -
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 -
Cancer Epidemiology Dec 2016This article reports on the methods and framework we have developed to guide economic evaluation of noncommunicable disease registries.
BACKGROUND
This article reports on the methods and framework we have developed to guide economic evaluation of noncommunicable disease registries.
METHODS
We developed a cost data collection instrument, the Centers for Disease Control and Prevention's (CDC's) International Registry Costing Tool (IntRegCosting Tool), based on established economics methods We performed in-depth case studies, site visit interviews, and pilot testing in 11 registries from multiple countries including India, Kenya, Uganda, Colombia, and Barbados to assess the overall quality of the data collected from cancer and cardiovascular registries.
RESULTS
Overall, the registries were able to use the IntRegCosting Tool to assign operating expenditures to specific activities. We verified that registries were able to provide accurate estimation of labor costs, which is the largest expenditure incurred by registries. We also identified several factors that can influence the cost of registry operations, including size of the geographic area served, data collection approach, local cost of living, presence of rural areas, volume of cases, extent of consolidation of records to cases, and continuity of funding.
CONCLUSION
Internal and external registry factors reveal that a single estimate for the cost of registry operations is not feasible; costs will vary on the basis of factors that may be beyond the control of the registries. Some factors, such as data collection approach, can be modified to improve the efficiency of registry operations. These findings will inform both future economic data collection using a web-based tool and cost and cost-effectiveness analyses of registry operations in low- and middle-income countries (LMICs) and other locations with similar characteristics.
Topics: Cardiovascular Diseases; Cost-Benefit Analysis; Costs and Cost Analysis; Data Collection; Humans; Neoplasms; Registries
PubMed: 27726980
DOI: 10.1016/j.canep.2016.10.003 -
Recenti Progressi in Medicina Oct 2018
Topics: Data Collection; Databases, Factual; Humans; Research Design
PubMed: 30394409
DOI: 10.1701/3010.30090 -
BMC Medical Informatics and Decision... Apr 2022Electronic sources (eSources) can improve data quality and reduce clinical trial costs. Our team has developed an innovative eSource record (ESR) system in China. This...
BACKGROUND
Electronic sources (eSources) can improve data quality and reduce clinical trial costs. Our team has developed an innovative eSource record (ESR) system in China. This study aims to evaluate the efficiency, quality, and system performance of the ESR system in data collection and data transcription.
METHODS
The study used time efficiency and data transcription accuracy indicators to compare the eSource and non-eSource data collection workflows in a real-world study (RWS). The two processes are traditional data collection and manual transcription (the non-eSource method) and the ESR-based source data collection and electronic transmission (the eSource method). Through the system usability scale (SUS) and other characteristic evaluation scales (system security, system compatibility, record quality), the participants' experience of using ESR was evaluated.
RESULTS
In terms of the source data collection (the total time required for writing electronic medical records (EMRs)), the ESR system can reduce the time required by 39% on average compared to the EMR system. In terms of data transcription (electronic case report form (eCRF) filling and verification), the ESR can reduce the time required by 80% compared to the non-eSource method (difference: 223 ± 21 s). The ESR accuracy in filling the eCRF field is 96.92%. The SUS score of ESR is 66.9 ± 16.7, which is at the D level and thus very close to the acceptable margin, indicating that optimization work is needed.
CONCLUSIONS
This preliminary evaluation shows that in the clinical medical environment, the ESR-based eSource method can improve the efficiency of source data collection and reduce the workload required to complete data transcription.
Topics: Data Accuracy; Data Collection; Electronic Health Records; Humans; Research Design; Workflow
PubMed: 35410214
DOI: 10.1186/s12911-022-01824-7 -
European Heart Journal Mar 2016Big Data promises to change cardiology through a massive increase in the data gathered and analysed; but its impact goes beyond improving incrementally existing methods. (Review)
Review
AIM
Big Data promises to change cardiology through a massive increase in the data gathered and analysed; but its impact goes beyond improving incrementally existing methods.
METHODS AND RESULTS
The potential of comprehensive data sets for scientific discovery is examined, and its impact on the scientific method generally and cardiology in particular is posited, together with likely consequences for research and practice.
CONCLUSION
Big Data in cardiology changes how new insights are being discovered. For it to flourish, significant modifications in the methods, structures, and institutions of the profession are necessary.
Topics: Cardiology; Causality; Data Collection; Humans; Inventions; Science
PubMed: 26705386
DOI: 10.1093/eurheartj/ehv648