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Mammalian Genome : Official Journal of... Sep 2023Experiments in which data are collected by multiple independent resources, including multicentre data, different laboratories within the same centre or with different...
Experiments in which data are collected by multiple independent resources, including multicentre data, different laboratories within the same centre or with different operators, are challenging in design, data collection and interpretation. Indeed, inconsistent results across the resources are possible. In this paper, we propose a statistical solution for the problem of multi-resource consensus inferences when statistical results from different resources show variation in magnitude, directionality, and significance. Our proposed method allows combining the corrected p-values, effect sizes and the total number of centres into a global consensus score. We apply this method to obtain a consensus score for data collected by the International Mouse Phenotyping Consortium (IMPC) across 11 centres. We show the application of this method to detect sexual dimorphism in haematological data and discuss the suitability of the methodology.
Topics: Mice; Animals; Consensus; Data Collection
PubMed: 37154937
DOI: 10.1007/s00335-023-09993-0 -
American Journal of Public Health Jul 2021To assess the quality of population-level US mortality data in the US Census Bureau Numerical Identification file (Numident) and describe the details of the mortality... (Comparative Study)
Comparative Study
OBJECTIVES
To assess the quality of population-level US mortality data in the US Census Bureau Numerical Identification file (Numident) and describe the details of the mortality information as well as the novel person-level linkages available when using the Census Numident.
METHODS
We compared all-cause mortality in the Census Numident to published vital statistics from the Centers for Disease Control and Prevention. We provide detailed information on the linkage of the Census Numident to other Census Bureau survey, administrative, and economic data.
RESULTS
Death counts in the Census Numident are similar to those from published mortality vital statistics. Yearly comparisons show that the Census Numident captures more deaths since 1997, and coverage is slightly lower going back in time. Weekly estimates show similar trends from both data sets.
CONCLUSIONS
The Census Numident is a high-quality and timely source of data to study all-cause mortality. The Census Bureau makes available a vast and rich set of restricted-use, individual-level data linked to the Census Numident for researchers to use.
PUBLIC HEALTH IMPLICATIONS
The Census Numident linked to data available from the Census Bureau provides infrastructure for doing evidence-based public health policy research on mortality.
Topics: Cause of Death; Censuses; Centers for Disease Control and Prevention, U.S.; Data Collection; Forecasting; Humans; Mortality; United States; Vital Statistics
PubMed: 34314212
DOI: 10.2105/AJPH.2021.306217 -
International Journal of Environmental... Nov 2021We aimed to assess Centers for Disease Control and Prevention (CDC) data systems on the extent of data collection on sex, sexual orientation, and gender identity as well...
We aimed to assess Centers for Disease Control and Prevention (CDC) data systems on the extent of data collection on sex, sexual orientation, and gender identity as well as on age and race/ethnicity. Between March and September 2019, we searched 11 federal websites to identify CDC-supported or -led U.S. data systems active between 2015 and 2018. We searched the systems' website, documentation, and publications for evidence of data collection on sex, sexual orientation, gender identity, age, and race/ethnicity. We categorized each system by type (disease notification, periodic prevalence survey, registry/vital record, or multiple sources). We provide descriptive statistics of characteristics of the identified systems. Most (94.1%) systems we assessed collected data on sex. All systems collected data on age, and approximately 80% collected data on race/ethnicity. Only 17.7% collected data on sexual orientation and 5.9% on gender identity. Periodic prevalence surveys were the most common system type for collecting all the variables we assessed. While most U.S. public health data and monitoring systems collect data disaggregated by sex, age, and race/ethnicity, far fewer do so for sexual orientation or gender identity. Standards and examples exist to aid efforts to collect and report these vitally important data. Additionally important is increasing accessibility and appropriately tailored dissemination of reports of these data to public health professionals and other collaborators.
Topics: Data Collection; Ethnicity; Female; Gender Identity; Humans; Male; Prevalence; Public Health; Sexual Behavior
PubMed: 34831945
DOI: 10.3390/ijerph182212189 -
The American Journal of Hospice &... Jun 2020Hospices provide multidimensional care. In the Netherlands, patients with <3 months estimated life expectancy have access to hospice care. Insight into patients admitted...
BACKGROUND
Hospices provide multidimensional care. In the Netherlands, patients with <3 months estimated life expectancy have access to hospice care. Insight into patients admitted to hospices and the care provided is lacking. In preparation for a national multicenter study, a pilot study was performed.
OBJECTIVE
The primary objective was to test the appropriateness of the study procedures and the availability of hospice patient records (HPRs), and patient and care characteristics.
METHOD
A cross-sectional pilot study was performed using a descriptive exploratory design. Sixteen hospices were invited to participate, and HPRs from 8 deceased patients per hospice were selected. Data were collected using self-developed electronic case report forms.
OUTCOMES
(1). Appropriateness of procedures: availability of HPRs and identified barriers and strategies. (2) Availability of patient and care characteristics in HPRs.
RESULTS
In total, 104 HPRs of patients from 13 hospices were enrolled. Various types of HPRs were found with different availabilities: nurses' records were most available (98%) compared to volunteers' records (62%). Overarching barriers were as follows: ethical issues, lack of knowledge, and lack of communication. Information about the illness was most available (97%), whereas descriptions of experienced symptoms were least available (10%).
CONCLUSION
Collecting HPRs is difficult and time-consuming. Specifically, data from separate records of home care nurses and general practitioners were difficult to come by. Patient and care characteristics were alternately present, which led to an extension of data collection in HPRs to 3 time periods. Piloting is essential to adjust study procedures and outcome measures to ensure a feasible national multicenter hospice study.
Topics: Aged; Aged, 80 and over; Communication; Cross-Sectional Studies; Data Collection; Female; Health Knowledge, Attitudes, Practice; Health Personnel; Health Records, Personal; Health Services Accessibility; Hospice Care; Hospices; Humans; Male; Middle Aged; Palliative Care; Pilot Projects; Volunteers
PubMed: 31835931
DOI: 10.1177/1049909119889004 -
Advances in Nutrition (Bethesda, Md.) Nov 2017Dietary surveys in low-income countries (LICs) are hindered by low investment in the necessary research infrastructure, including a lack of basic technology for data... (Review)
Review
Dietary surveys in low-income countries (LICs) are hindered by low investment in the necessary research infrastructure, including a lack of basic technology for data collection, links to food composition information, and data processing. The result has been a dearth of dietary data in many LICs because of the high cost and time burden associated with dietary surveys, which are typically carried out by interviewers using pencil and paper. This study reviewed innovative dietary assessment technologies and gauged their suitability to improve the quality and time required to collect dietary data in LICs. Predefined search terms were used to identify technologies from peer-reviewed and gray literature. A total of 78 technologies were identified and grouped into 6 categories: ) computer- and tablet-based, ) mobile-based, ) camera-enabled, ) scale-based, ) wearable, and ) handheld spectrometers. For each technology, information was extracted on a number of overarching factors, including the primary purpose, mode of administration, and data processing capabilities. Each technology was then assessed against predetermined criteria, including requirements for respondent literacy, battery life, requirements for connectivity, ability to measure macro- and micronutrients, and overall appropriateness for use in LICs. Few technologies reviewed met all the criteria, exhibiting both practical constraints and a lack of demonstrated feasibility for use in LICs, particularly for large-scale, population-based surveys. To increase collection of dietary data in LICs, development of a contextually adaptable, interviewer-administered dietary assessment platform is recommended. Additional investments in the research infrastructure are equally important to ensure time and cost savings for the user.
Topics: Data Collection; Decision Making, Computer-Assisted; Developing Countries; Diet Surveys; Humans; Nutrition Assessment
PubMed: 29141974
DOI: 10.3945/an.116.014308 -
BMJ Global Health Jan 2021In-person interactions have traditionally been the gold standard for qualitative data collection. The COVID-19 pandemic required researchers to consider if remote data... (Review)
Review
In-person interactions have traditionally been the gold standard for qualitative data collection. The COVID-19 pandemic required researchers to consider if remote data collection can meet research objectives, while retaining the same level of data quality and participant protections. We use four case studies from the Philippines, Zambia, India and Uganda to assess the challenges and opportunities of remote data collection during COVID-19. We present lessons learned that may inform practice in similar settings, as well as reflections for the field of qualitative inquiry in the post-COVID-19 era. Key challenges and strategies to overcome them included the need for adapted researcher training in the use of technologies and consent procedures, preparation for abbreviated interviews due to connectivity concerns, and the adoption of regular researcher debriefings. Participant outreach to allay suspicions ranged from communicating study information through multiple channels to highlighting associations with local institutions to boost credibility. Interviews were largely successful, and contained a meaningful level of depth, nuance and conviction that allowed teams to meet study objectives. Rapport still benefitted from conventional interviewer skills, including attentiveness and fluency with interview guides. While differently abled populations may encounter different barriers, the included case studies, which varied in geography and aims, all experienced more rapid recruitment and robust enrollment. Reduced in-person travel lowered interview costs and increased participation among groups who may not have otherwise attended. In our view, remote data collection is not a replacement for in-person endeavours, but a highly beneficial complement. It may increase accessibility and equity in participant contributions and lower costs, while maintaining rich data collection in multiple study target populations and settings.
Topics: Africa South of the Sahara; COVID-19; Data Accuracy; Data Collection; Humans; India; Internet; Interpersonal Relations; Pandemics; Philippines; Physical Distancing; Qualitative Research; SARS-CoV-2
PubMed: 33419929
DOI: 10.1136/bmjgh-2020-004193 -
Journal of Clinical Epidemiology Nov 2017Pragmatic trials can improve our understanding of how treatments will perform in routine practice. In a series of eight papers, the GetReal Consortium has evaluated the...
Pragmatic trials can improve our understanding of how treatments will perform in routine practice. In a series of eight papers, the GetReal Consortium has evaluated the challenges in designing and conducting pragmatic trials and their specific methodological, operational, regulatory, and ethical implications. The present final paper of the series discusses the operational and methodological challenges of data collection in pragmatic trials. A more pragmatic data collection needs to balance the delivery of highly accurate and complete data with minimizing the level of interference that data entry and verification induce with clinical practice. Furthermore, it should allow for the involvement of a representative sample of practices, physicians, and patients who prescribe/receive treatment in routine care. This paper discusses challenges that are related to the different methods of data collection and presents potential solutions where possible. No one-size-fits-all recommendation can be given for the collection of data in pragmatic trials, although in general the application of existing routinely used data-collection systems and processes seems to best suit the pragmatic approach. However, data access and privacy, the time points of data collection, the level of detail in the data, and the lack of a clear understanding of the data-collection process were identified as main challenges for the usage of routinely collected data in pragmatic trials. A first step should be to determine to what extent existing health care databases provide the necessary study data and can accommodate data collection and management. When more elaborate or detailed data collection or more structured follow-up is required, data collection in a pragmatic trial will have to be tailor-made, often using a hybrid approach using a dedicated electronic case report form (eCRF). In this case, the eCRF should be kept as simple as possible to reduce the burden for practitioners and minimize influence on routine clinical practice.
Topics: Data Collection; Electronic Health Records; Evidence-Based Medicine; Humans; Pragmatic Clinical Trials as Topic
PubMed: 28716504
DOI: 10.1016/j.jclinepi.2017.07.003 -
Journal of Healthcare Engineering 2021It is important to promote the development and application of hospital information system, community health service system, etc. However, it is difficult to realize the...
It is important to promote the development and application of hospital information system, community health service system, etc. However, it is difficult to realize the intercommunication between various information systems because it is not enough to realize the in-depth management of health information. To address these issues, we design the 5G edge computing-assisted architecture for medical community. Then, we formulate the directional data collection (DDC) problem to gather the EMR/HER data from the medical community to minimize the service error under the deadline constraint of data collection deadline. Moreover, we design the data direction prediction algorithm (DDPA) to predict the data collection direction and propose the data collection planning algorithm (DCPA) to minimize the data collecting time cost. Through the numerical simulation experiments, we demonstrate that our proposed algorithms can decrease the total time cost by 62.48% and improve the data quality by 36.47% through the designed system, respectively.
Topics: Algorithms; Computer Simulation; Data Collection; Electronic Health Records; Hospital Information Systems; Humans
PubMed: 34336158
DOI: 10.1155/2021/5598077 -
European Journal of Medical Genetics Dec 2023knowledge on the natural history of rare diseases is necessary to improve outcomes. Disease registries may play a key role in covering these unmet needs in the rare bone...
BACKGROUND
knowledge on the natural history of rare diseases is necessary to improve outcomes. Disease registries may play a key role in covering these unmet needs in the rare bone and mineral community.
OBJECTIVE
to map existing bone and mineral conditions registries in Europe and their characteristics.
METHODS
online survey about the use of registries/databases and their characteristics. This survey was disseminated among members of the European Reference Network on Rare Bone Diseases (ERN BOND) and non-ERN experts in the field of bone and mineral conditions as well as patient organisations.
RESULTS
sixty-three responses from health care providers (HCPs) and 10 responses from patient groups (PGs) were collected. The response rate for ERN BOND members was 55%. Of 63 HCPs, 37 declared using a registry. Osteogenesis imperfecta (OI) was the most registered condition. We mapped 3 international registries, all were disease-specific.
CONCLUSIONS
There is a need for developing a common high-quality platform for registering rare bone and mineral conditions.
Topics: Humans; Registries; Europe; Rare Diseases; Databases, Factual; Bone Diseases; Data Collection; Osteogenesis Imperfecta
PubMed: 38832910
DOI: 10.1016/j.ejmg.2023.104868 -
BMC Medical Research Methodology Jan 2020Researchers and clinicians use text messages to collect data with the advantage of real time capture when compared with standard data collection methods. This article... (Review)
Review
BACKGROUND
Researchers and clinicians use text messages to collect data with the advantage of real time capture when compared with standard data collection methods. This article reviews project setup and management for successfully collecting patient-reported data through text messages.
METHODS
We review our experience enrolling over 2600 participants in six clinical trials that used text messages to relay information or collect data. We also reviewed the literature on text messages used for repeated data collection. We classify recommendations according to common themes: the text message, the data submitted and the phone used.
RESULTS
We present lessons learned and discuss how to create text message content, select a data collection platform with practical features, manage the data thoughtfully and consistently, and work with patients, participants and their phones to protect privacy. Researchers and clinicians should design text messages to include short, simple prompts and answer choices. They should decide whether and when to send reminders if participants do not respond and set parameters regarding when and how often to contact patients for missing data. Data collection platforms send, receive, and store messages. They can validate responses and send error messages. Researchers should develop a protocol to append and correct data in order to improve consistency with data handling. At the time of enrollment, researchers should ensure that participants can receive and respond to messages. Researchers should address privacy concerns and plan for service interruptions by obtaining alternate participant contact information and providing participants with a backup data collection method.
CONCLUSIONS
Careful planning and execution can reward clinicians and investigators with complete, timely and accurate data sets.
Topics: Clinical Trials as Topic; Data Collection; Health Communication; Humans; Physician-Patient Relations; Reminder Systems; Text Messaging
PubMed: 31900108
DOI: 10.1186/s12874-019-0891-9