The Impact of Commercialisation and Genetic Data Sharing Arrangements on Public Trust and the Intention to Participate in Biobank Research

2015 ◽  
Vol 18 (3) ◽  
pp. 160-172 ◽  
Author(s):  
Christine Critchley ◽  
Dianne Nicol ◽  
Margaret Otlowski
Keyword(s):  
Data Sharing ◽  
Genetic Data ◽  
Public Trust ◽  
Biobank Research ◽  
Intention To Participate ◽  
The Impact

scholarly journals Mental health professional perspectives on health data sharing: Mixed methods study

2020 ◽  
Vol 26 (3) ◽  
pp. 2067-2082 ◽  
Author(s):  
Adela Grando ◽  
Julia Ivanova ◽  
Megan Hiestand ◽  
Hiral Soni ◽  
Anita Murcko ◽  
...  
Keyword(s):  
Health Information ◽  
Data Sharing ◽  
Health Professionals ◽  
Mixed Methods Study ◽  
Qualitative And Quantitative Analysis ◽  
Qualitative And Quantitative ◽  
Patient Comprehension ◽  
Professional Perspectives ◽  
The Impact ◽  
Perceived Reasons

This study explores behavioral health professionals’ perceptions of granular data. Semi-structured in-person interviews of 20 health professionals were conducted at two different sites. Qualitative and quantitative analysis was performed. While most health professionals agreed that patients should control who accesses their personal medical record (70%), there are certain types of health information that should never be restricted (65%). Emergent themes, including perceived reasons that patients might share or withhold certain types of health information (65%), care coordination (12%), patient comprehension (11%), stigma (5%), trust (3%), sociocultural understanding (3%), and dissatisfaction with consent processes (1%), are explored. The impact of care role (prescriber or non-prescriber) on data-sharing perception is explored as well. This study informs the discussion on developing technology that helps balance provider and patient data-sharing and access needs.

Project HALO: A Post-Market, Observational Registry of Data Derived from Serenity LiquidTM, Serenity GenomeTM, and Clinical Parameters (Preprint)

2021 ◽  
Author(s):  
Monika Hagen ◽  
Danette Newton ◽  
Jonathan Richina ◽  
Petra Gambon Stow ◽  
Jonathan Douissard
Keyword(s):  
Clinical Data ◽  
Clinical Course ◽  
Genetic Data ◽  
Data Repository ◽  
Research Database ◽  
Clinical Parameters ◽  
Real World Setting ◽  
Post Market ◽  
Initial Dataset ◽  
The Impact

BACKGROUND Registries are a valuable tool for data collection and observation of medical innovations in a real-world setting. Serenity LiquidTM and Serenity GenomeTM are newly launched diagnostic platforms analyzing large genetic datasets in combination with clinical data to deliver precision preventative medicine. To this point, no systematic data is available to observe the use and clinical implementations of these platforms. OBJECTIVE To create a data repository collecting data from Serenity LiquidTM, Serenity GenomeTM, and clinical parameters for analyses. METHODS Individuals receiving Serenity LiquidTM or Serenity GenomeTM are solicited to participate in this registry. In addition to the initial dataset, a clinical update is secured every six months. Data from the registry participants are pseudo-anonymized and archived in a HIPPA-compliant research database for regular analyses. RESULTS Includes but is not limited to correlations between genetic and clinical data, the impact of genetic data on the clinical course of patients, comparisons between specific cohorts (within this database and against historical cohorts) on an ongoing basis. CONCLUSIONS This is a prospective registry collecting genetic and clinical data to gather important information, provide novel insights by continuously analyzing the data in this registry.

scholarly journals The Changing Nature of Clinical Decision Support Systems: a Focus on Consumers, Genomics, Public Health and Decision Safety

2009 ◽  
Vol 18 (01) ◽  
pp. 84-95 ◽  
Author(s):  
A. Y. S. Lau ◽  
G. Tsafnat ◽  
V. Sintchenko ◽  
F. Magrabi ◽  
E. Coiera
Keyword(s):  
Public Health ◽  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Genetic Data ◽  
Clinical Decision ◽  
Translational Bioinformatics ◽  
The Impact

Summary Objectives To review the recent research literature in clinical decision support systems (CDSS). Methods A review of recent literature was undertaken, focussing on CDSS evaluation, consumers and public health, the impact of translational bioinformatics on CDSS design, and CDSS safety. Results In recent years, researchers have concentrated much less on the development of decision technologies, and have focussed more on the impact of CDSS in the clinical world. Recent work highlights that traditional process measures of CDSS effectiveness, such as document relevance are poor proxy measures for decision outcomes. Measuring the dynamics of decision making, for example via decision velocity, may produce a more accurate picture of effectiveness. Another trend is the broadening of user base for CDSS beyond front line clinicians. Consumers are now a major focus for biomedical informatics, as are public health officials, tasked with detecting and managing disease outbreaks at a health system, rather than individual patient level. Bioinformatics is also changing the nature of CDSS. Apart from personalisation of therapy recommendations, translational bioinformatics is creating new challenges in the interpretation of the meaning of genetic data. Finally, there is much recent interest in the safety and effectiveness of computerised physicianorderentry (CPOE) systems, given that prescribing and administration errors are a significant cause of morbidity and mortality. Of note, there is still much controversy surrounding the contention that poorly designed, implemented or used CDSS may actually lead to harm. Conclusions CDSS research remains an active and evolving area of research, as CDSS penetrate more widely beyond their traditional domain into consumer decision support, and as decisions become more complex, for example by involving sequence level genetic data.

scholarly journals Australia: regulating genomic data sharing to promote public trust

2018 ◽  
Vol 137 (8) ◽  
pp. 583-591 ◽  
Author(s):  
Lisa Eckstein ◽  
Donald Chalmers ◽  
Christine Critchley ◽  
Ruthie Jeanneret ◽  
Rebekah McWhirter ◽  
...  
Keyword(s):  
Data Sharing ◽  
Genomic Data ◽  
Public Trust

scholarly journals Archaeological documentation and data sharing: digital surveying and open data approach applied to archaeological fieldworks

2019 ◽  
Vol 10 (20) ◽  
pp. 17 ◽  
Author(s):  
Mattia Previtali ◽  
Riccardo Valente
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Data Sharing ◽  
Open Data ◽  
Geographic Information ◽  
Published Data ◽  
Archaeological Data ◽  
Disciplinary Expertise ◽  
Large Level ◽  
The Impact

<p>The open data paradigm is changing the research approach in many fields such as remote sensing and the social sciences. This is supported by governmental decisions and policies that are boosting the open data wave, and in this context archaeology is also affected by this new trend. In many countries, archaeological data are still protected or only limited access is allowed. However, the strong political and economic support for the publication of government data as open data will change the accessibility and disciplinary expertise in the archaeological field too. In order to maximize the impact of data, their technical openness is of primary importance. Indeed, since a spreadsheet is more usable than a PDF of a table, the availability of digital archaeological data, which is structured using standardised approaches, is of primary importance for the real usability of published data. In this context, the main aim of this paper is to present a workflow for archaeological data sharing as open data with a large level of technical usability and interoperability. Primary data is mainly acquired through the use of digital techniques (e.g. digital cameras and terrestrial laser scanning). The processing of this raw data is performed with commercial software for scan registration and image processing, allowing for a simple and semi-automated workflow. Outputs obtained from this step are then processed in modelling and drawing environments to generate digital models, both 2D and 3D. These crude geometrical data are then enriched with further information to generate a Geographic Information System (GIS) which is finally published as open data using Open Geospatial Consortium (OGC) standards to maximise interoperability.</p><p><strong>Highlights:</strong></p><ul><li><p>Open data will change the accessibility and disciplinary expertise in the archaeological field.</p></li><li><p>The main aim of this paper is to present a workflow for archaeological data sharing as open data with a large level of interoperability.</p></li><li><p>Digital acquisition techniques are used to document archaeological excavations and a Geographic Information System (GIS) is generated that is published as open data.</p></li></ul>

scholarly journals The Evolution of Data Sharing Practices in the Psychological Literature

2021 ◽  
Author(s):  
Judith Neve ◽  
Guillaume A Rousselet
Keyword(s):  
Data Sharing ◽  
Linear Models ◽  
Generalized Additive Models ◽  
Additive Models ◽  
Future Research ◽  
Science Data ◽  
Editorial Policies ◽  
Psychological Science ◽  
The Impact

Sharing data has many benefits. However, data sharing rates remain low, for the most part well below 50%. A variety of interventions encouraging data sharing have been proposed. We focus here on editorial policies. Kidwell et al. (2016) assessed the impact of the introduction of badges in Psychological Science; Hardwicke et al. (2018) assessed the impact of Cognition’s mandatory data sharing policy. Both studies found policies to improve data sharing practices, but only assessed the impact of the policy for up to 25 months after its implementation. We examined the effect of these policies over a longer term by reusing their data and collecting a follow-up sample including articles published up until December 31st, 2019. We fit generalized additive models as these allow for a flexible assessment of the effect of time, in particular to identify non-linear changes in the trend. These models were compared to generalized linear models to examine whether the non-linearity is needed. Descriptive results and the outputs from generalized additive and linear models were coherent with previous findings: following the policies in Cognition and Psychological Science, data sharing statement rates increased immediately and continued to increase beyond the timeframes examined previously, until reaching close to 100%. In Clinical Psychological Science, data sharing statement rates started to increase only two years following the implementation of badges. Reusability rates jumped from close to 0% to around 50% but did not show changes within the pre-policy nor the post-policy timeframes. Journals that did not implement a policy showed no change in data sharing rates or reusability over time. There was variability across journals in the levels of increase, so we suggest future research should examine a larger number of policies to draw conclusions about their efficacy. We also encourage future research to investigate the barriers to data sharing specific to psychology subfields to identify the best interventions to tackle them.

Patient Experiences, Trust, and Preferences for Health Data Sharing

2021 ◽  
Author(s):  
Rochelle D. Jones ◽  
Chris Krenz ◽  
Kent A. Griffith ◽  
Rebecca Spence ◽  
Angela R. Bradbury ◽  
...  
Keyword(s):  
Health Care ◽  
Data Sharing ◽  
Health Care System ◽  
Lived Experiences ◽  
Care Delivery ◽  
Group Discussion ◽  
Final Analysis ◽  
Secondary Use ◽  
The Impact ◽  
Care System

PURPOSE: Scholars have examined patients' attitudes toward secondary use of routinely collected clinical data for research and quality improvement. Evidence suggests that trust in health care organizations and physicians is critical. Less is known about experiences that shape trust and how they influence data sharing preferences. MATERIALS AND METHODS: To explore learning health care system (LHS) ethics, democratic deliberations were hosted from June 2017 to May 2018. A total of 217 patients with cancer participated in facilitated group discussion. Transcripts were coded independently. Finalized codes were organized into themes using interpretive description and thematic analysis. Two previous analyses reported on patient preferences for consent and data use; this final analysis focuses on the influence of personal lived experiences of the health care system, including interactions with providers and insurers, on trust and preferences for data sharing. RESULTS: Qualitative analysis identified four domains of patients' lived experiences raised in the context of the policy discussions: (1) the quality of care received, (2) the impact of health care costs, (3) the transparency and communication displayed by a provider or an insurer to the patient, and (4) the extent to which care coordination was hindered or facilitated by the interchange between a provider and an insurer. Patients discussed their trust in health care decision makers and their opinions about LHS data sharing. CONCLUSION: Additional resources, infrastructure, regulations, and practice innovations are needed to improve patients' experiences with and trust in the health care system. Those who seek to build LHSs may also need to consider improvement in other aspects of care delivery.

Consent for Use of Genetic Data among US Hispanics/Latinos: Results from the Hispanic Community Health Study/ Study of Latinos

2021 ◽  
Vol 31 (4) ◽  
pp. 547-558
Author(s):  
Sara Gonzalez ◽  
Garrett Strizich ◽  
Carmen R. Isasi ◽  
Simin Hua ◽  
Betsy Comas ◽  
...  
Keyword(s):  
Community Health ◽  
Data Sharing ◽  
Genetic Data ◽  
Genomic Research ◽  
Health Study ◽  
Medicine Research ◽  
For Profit ◽  
Hispanic Community ◽  
Precision Medicine Research

Inclusion of historically underrepresented populations in biomedical research is critical for large precision medicine research initia­tives. Among 13,721 Hispanic Community Health Study/Study of Latinos (HCHS/SOL) enrollees, we used multivariable-adjusted prevalence ratios to describe characteristics associated with participants’ willingness to consent to different levels of biospecimen and genetic data analysis and sharing. At baseline (2008-2011), HCHS/SOL par­ticipants almost universally consented to the use of biospecimens and genetic data by study investigators and their collabora­tors (97.6%; 95%CI: 97.1, 98.0). Fewer consented to biospecimen and genetic data sharing with investigators not affiliated with the HCHS/SOL research team (81%, 95%CI: 80, 82) or any data sharing with commer­cial/for-profit entities (75%, 95%CI: 74, 76). Those refusing to share their data beyond the study investigators group were more often females, Spanish language-speakers and non-US born individuals. As expected, participants who were retained and recon­sented at the six-year follow up visit tended to embrace broader data sharing, although this varied by group. Over time, Puerto Ricans and Dominicans were more likely to convert to broader data sharing than individuals of a Mexican background. Our analysis suggests that acculturation and im­migration status of specific Hispanic/Latino communities may influence decisions about participation in genomic research projects and biobanks. Ethn Dis. 2021;31(4):547- 558; doi:10.18865/ed.31.4.547

scholarly journals Mental health professionals’ perceptions on patients control of data sharing

2020 ◽  
Vol 26 (3) ◽  
pp. 2011-2029 ◽  
Author(s):  
Julia Ivanova ◽  
Adela Grando ◽  
Anita Murcko ◽  
Michael Saks ◽  
Mary Jo Whitfield ◽  
...  
Keyword(s):  
Mental Health ◽  
Health Information ◽  
Data Sharing ◽  
Mental Health Professionals ◽  
Health Professionals ◽  
Health Care Professionals ◽  
Health Data ◽  
Structured Interviews ◽  
Timely Access ◽  
The Impact

Integrated mental and physical care environments require data sharing, but little is known about health professionals’ perceptions of patient-controlled health data sharing. We describe mental health professionals’ views on patient-controlled data sharing using semi-structured interviews and a mixed-method analysis with thematic coding. Health information rights, specifically those of patients and health care professionals, emerged as a key theme. Behavioral health professionals identified patient motivations for non-sharing sensitive mental health records relating to substance use, emergency treatment, and serious mental illness (94%). We explore conflicts between professional need for timely access to health information and patient desire to withhold some data categories. Health professionals’ views on data sharing are integral to the redesign of health data sharing and informed consent. As well, they seek clarity about the impact of patient-controlled sharing on health professionals’ roles and scope of practice.

Personal Data Sharing and Legal Issues of Human Rights in the Era of Artificial Intelligence

2019 ◽  
Vol 15 (3) ◽  
pp. 21-36
Author(s):  
Sheshadri Chatterjee ◽  
Sreenivasulu N.S.
Keyword(s):  
Artificial Intelligence ◽  
Human Rights ◽  
Data Sharing ◽  
Personal Data ◽  
Security And Privacy ◽  
Human Right ◽  
Public And Private ◽  
Analyse Data ◽  
Regulatory Controls ◽  
The Impact

Personal data sharing has become an important issue in public and private sectors of our society. However, data subjects are perceived to be always unwilling to share their data on security and privacy reasons. They apprehend that those data will be misused at the cost of their privacy jeopardising their human rights. Thus, personal data sharing is closely associated with human right issues. This concern of data subjects has increased manifolds owing to the interference of Artificial Intelligence (AI) since AI can analyse data without human intervention. In this background, this article has taken an attempt to investigate how applications of AI and imposition of regulatory controls with appropriate governance can influence the impact of personal data sharing on the issues of human right abuses.

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