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American Journal of Pharmaceutical... Jan 2020Attributes of rigor and quality and suggested best practices for qualitative research design as they relate to the steps of designing, conducting, and reporting... (Review)
Review
Attributes of rigor and quality and suggested best practices for qualitative research design as they relate to the steps of designing, conducting, and reporting qualitative research in health professions educational scholarship are presented. A research question must be clear and focused and supported by a strong conceptual framework, both of which contribute to the selection of appropriate research methods that enhance trustworthiness and minimize researcher bias inherent in qualitative methodologies. Qualitative data collection and analyses are often modified through an iterative approach to answering the research question. Researcher reflexivity, essentially a researcher's insight into their own biases and rationale for decision-making as the study progresses, is critical to rigor. This article reviews common standards of rigor, quality scholarship criteria, and best practices for qualitative research from design through dissemination.
Topics: Data Collection; Education, Pharmacy; Fellowships and Scholarships; Humans; Qualitative Research; Quality Indicators, Health Care; Research Design; Research Personnel
PubMed: 32292186
DOI: 10.5688/ajpe7120 -
Annual Review of Public Health Apr 2020Disease surveillance systems are a cornerstone of public health tracking and prevention. This review addresses the use, promise, perils, and ethics of social media- and... (Review)
Review
Disease surveillance systems are a cornerstone of public health tracking and prevention. This review addresses the use, promise, perils, and ethics of social media- and Internet-based data collection for public health surveillance. Our review highlights untapped opportunities for integrating digital surveillance in public health and current applications that could be improved through better integration, validation, and clarity on rules surrounding ethical considerations. Promising developments include hybrid systems that couple traditional surveillance data with data from search queries, social media posts, and crowdsourcing. In the future, it will be important to identify opportunities for public and private partnerships, train public health experts in data science, reduce biases related to digital data (gathered from Internet use, wearable devices, etc.), and address privacy. We are on the precipice of an unprecedented opportunity to track, predict, and prevent global disease burdens in the population using digital data.
Topics: Confidentiality; Data Collection; Humans; Internet; Public Health; Public Health Surveillance; Social Media; Wearable Electronic Devices
PubMed: 31905322
DOI: 10.1146/annurev-publhealth-040119-094402 -
American Journal of Public Health Dec 2021The National Health and Nutrition Examination Survey (NHANES) is a unique source of national data on the health and nutritional status of the US population, collecting...
The National Health and Nutrition Examination Survey (NHANES) is a unique source of national data on the health and nutritional status of the US population, collecting data through interviews, standard exams, and biospecimen collection. Because of the COVID-19 pandemic, NHANES data collection was suspended, with more than a year gap in data collection. NHANES resumed operations in 2021 with the NHANES 2021-2022 survey, which will monitor the health and nutritional status of the nation while adding to the knowledge of COVID-19 in the US population. This article describes the reshaping of the NHANES program and, specifically, the planning of NHANES 2021-2022 for data collection during the COVID-19 pandemic. Details are provided on how NHANES transformed its participant recruitment and data collection plans at home and at the mobile examination center to safely collect data in a COVID-19 environment. The potential implications for data users are also discussed. (. 2021;111(12):2149-2156. https://doi.org/10.2105/AJPH.2021.306517).
Topics: Adult; COVID-19; Communicable Disease Control; Data Collection; Female; Humans; Interviews as Topic; Male; Middle Aged; Nutrition Surveys; Nutritional Status; Pandemics; Physical Examination; SARS-CoV-2; United States; Young Adult
PubMed: 34878854
DOI: 10.2105/AJPH.2021.306517 -
Social Science & Medicine (1982) Jan 2022To review empirical studies that assess saturation in qualitative research in order to identify sample sizes for saturation, strategies used to assess saturation, and...
OBJECTIVE
To review empirical studies that assess saturation in qualitative research in order to identify sample sizes for saturation, strategies used to assess saturation, and guidance we can draw from these studies.
METHODS
We conducted a systematic review of four databases to identify studies empirically assessing sample sizes for saturation in qualitative research, supplemented by searching citing articles and reference lists.
RESULTS
We identified 23 articles that used empirical data (n = 17) or statistical modeling (n = 6) to assess saturation. Studies using empirical data reached saturation within a narrow range of interviews (9-17) or focus group discussions (4-8), particularly those with relatively homogenous study populations and narrowly defined objectives. Most studies had a relatively homogenous study population and assessed code saturation; the few outliers (e.g., multi-country research, meta-themes, "code meaning" saturation) needed larger samples for saturation.
CONCLUSIONS
Despite varied research topics and approaches to assessing saturation, studies converged on a relatively consistent sample size for saturation for commonly used qualitative research methods. However, these findings apply to certain types of studies (e.g., those with homogenous study populations). These results provide strong empirical guidance on effective sample sizes for qualitative research, which can be used in conjunction with the characteristics of individual studies to estimate an appropriate sample size prior to data collection. This synthesis also provides an important resource for researchers, academic journals, journal reviewers, ethical review boards, and funding agencies to facilitate greater transparency in justifying and reporting sample sizes in qualitative research. Future empirical research is needed to explore how various parameters affect sample sizes for saturation.
Topics: Data Collection; Focus Groups; Humans; Qualitative Research; Research Design; Sample Size
PubMed: 34785096
DOI: 10.1016/j.socscimed.2021.114523 -
JMIR MHealth and UHealth Sep 2019Due to the adoption of electronic health records (EHRs) and legislation on meaningful use in recent decades, health systems are increasingly interdependent on EHR... (Review)
Review
BACKGROUND
Due to the adoption of electronic health records (EHRs) and legislation on meaningful use in recent decades, health systems are increasingly interdependent on EHR capabilities, offerings, and innovations to better capture patient data. A novel capability offered by health systems encompasses the integration between EHRs and wearable health technology. Although wearables have the potential to transform patient care, issues such as concerns with patient privacy, system interoperability, and patient data overload pose a challenge to the adoption of wearables by providers.
OBJECTIVE
This study aimed to review the landscape of wearable health technology and data integration to provider EHRs, specifically Epic, because of its prevalence among health systems. The objectives of the study were to (1) identify the current innovations and new directions in the field across start-ups, health systems, and insurance companies and (2) understand the associated challenges to inform future wearable health technology projects at other health organizations.
METHODS
We used a scoping process to survey existing efforts through Epic's Web-based hub and discussion forum, UserWeb, and on the general Web, PubMed, and Google Scholar. We contacted Epic, because of their position as the largest commercial EHR system, for information on published client work in the integration of patient-collected data. Results from our searches had to meet criteria such as publication date and matching relevant search terms.
RESULTS
Numerous health institutions have started to integrate device data into patient portals. We identified the following 10 start-up organizations that have developed, or are in the process of developing, technology to enhance wearable health technology and enable EHR integration for health systems: Overlap, Royal Philips, Vivify Health, Validic, Doximity Dialer, Xealth, Redox, Conversa, Human API, and Glooko. We reported sample start-up partnerships with a total of 16 health systems in addressing challenges of the meaningful use of device data and streamlining provider workflows. We also found 4 insurance companies that encourage the growth and uptake of wearables through health tracking and incentive programs: Oscar Health, United Healthcare, Humana, and John Hancock.
CONCLUSIONS
The future design and development of digital technology in this space will rely on continued analysis of best practices, pain points, and potential solutions to mitigate existing challenges. Although this study does not provide a full comprehensive catalog of all wearable health technology initiatives, it is representative of trends and implications for the integration of patient data into the EHR. Our work serves as an initial foundation to provide resources on implementation and workflows around wearable health technology for organizations across the health care industry.
Topics: Biomedical Technology; Data Collection; Electronic Health Records; Humans; Wearable Electronic Devices
PubMed: 31512582
DOI: 10.2196/12861 -
PloS One 2020Data saturation is the most commonly employed concept for estimating sample sizes in qualitative research. Over the past 20 years, scholars using both empirical research...
Data saturation is the most commonly employed concept for estimating sample sizes in qualitative research. Over the past 20 years, scholars using both empirical research and mathematical/statistical models have made significant contributions to the question: How many qualitative interviews are enough? This body of work has advanced the evidence base for sample size estimation in qualitative inquiry during the design phase of a study, prior to data collection, but it does not provide qualitative researchers with a simple and reliable way to determine the adequacy of sample sizes during and/or after data collection. Using the principle of saturation as a foundation, we describe and validate a simple-to-apply method for assessing and reporting on saturation in the context of inductive thematic analyses. Following a review of the empirical research on data saturation and sample size estimation in qualitative research, we propose an alternative way to evaluate saturation that overcomes the shortcomings and challenges associated with existing methods identified in our review. Our approach includes three primary elements in its calculation and assessment: Base Size, Run Length, and New Information Threshold. We additionally propose a more flexible approach to reporting saturation. To validate our method, we use a bootstrapping technique on three existing thematically coded qualitative datasets generated from in-depth interviews. Results from this analysis indicate the method we propose to assess and report on saturation is feasible and congruent with findings from earlier studies.
Topics: Data Collection; Humans; Qualitative Research; Research Design; Sample Size
PubMed: 32369511
DOI: 10.1371/journal.pone.0232076 -
The Lancet. Global Health Aug 2021
Topics: COVID-19; Data Collection; Disabled Persons; Global Health; Humans
PubMed: 34297946
DOI: 10.1016/S2214-109X(21)00312-0 -
Journal of the American Medical... Mar 2021
Topics: Data Collection; Electronic Health Records; Health Records, Personal; Humans; Machine Learning; Natural Language Processing; Patient Access to Records; Surveys and Questionnaires
PubMed: 33677514
DOI: 10.1093/jamia/ocab040 -
Ugeskrift For Laeger Jan 2024Qualitative studies are adept at exploring individuals' routines, practices, thoughts, and values, as well as interaction and collaboration. As a doctor, you encounter... (Review)
Review
Qualitative studies are adept at exploring individuals' routines, practices, thoughts, and values, as well as interaction and collaboration. As a doctor, you encounter qualitative research questions daily: Why do patients hesitate to follow recommendations? How do doctors broach sensitive topics with patients? How do fellow physicians experience cross-sector collaboration? This review provides a quick guide to qualitative studies, covering research question formulation, data collection, analysis, and transparency criteria. We critically assess a qualitative study on chronic disease management.
Topics: Humans; Physicians; Qualitative Research; Data Collection
PubMed: 38235777
DOI: 10.61409/V08230491 -
Lakartidningen Sep 2019According to the Swedish National Board of Health and Welfare, about 3200 people a year die due to accidents. Around 900 of these are classified as "Accidental exposure...
According to the Swedish National Board of Health and Welfare, about 3200 people a year die due to accidents. Around 900 of these are classified as "Accidental exposure to other and unspecified factors". A more precise classification with the board has not been recorded in these cases due to incomplete death certificates. This study examined the death certificates for this group in 2016 and compared it to patient records. This study showed that most cases of incomplete classification are in instances of elderly persons who sustained a fall and subsequently died due to complications of the resulting injury. The doctor has in most cases not perceived the death as accidental.This study showed that there is a lack of knowledge among doctors in how to accurately complete a death certificate.
Topics: Accidental Falls; Age Distribution; Aged; Aged, 80 and over; Cause of Death; Clinical Competence; Data Collection; Death Certificates; Documentation; Female; Humans; Male; Medical Records; Middle Aged; Physicians; Sex Distribution; Sweden; Time Factors
PubMed: 31503322
DOI: No ID Found