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At least 19 recordsLinked to original sources
PubMedDate not supplied

Information partnerships--shared data, shared scale.

How can one company gain access to another's resources or customers without merging ownership, management, or plotting a takeover? The answer is found in new information partnerships, enabling diverse companies to develop strategic coalitions through the sharing of data. The key to cooperation is a quantum improvement in the hardware and software supporting relational databases: new computer speeds, cheaper mass-storage devices, the proliferation of fiber-optic networks, and networking architectures. Information partnerships mean that companies can distribute the technological and financial exposure that comes with huge investments. For the customer's part, partnerships inevitably lead to greater simplification on the desktop and more common standards around which vendors have to compete. The most common types of partnership are: joint marketing partnerships, such as American Airline's award of frequent flyer miles to customers who use Citibank's credit card; intraindustry partnerships, such as the insurance value-added network service (which links insurance and casualty companies to independent agents); customer-supplier partnerships, such as Baxter Healthcare's electronic channel to hospitals for medical and other equipment; and IT vendor-driven partnerships, exemplified by ESAB (a European welding supplies and equipment company), whose expansion strategy was premised on a technology platform offered by an IT vendor. Partnerships that succeed have shared vision at the top, reciprocal skills in information technology, concrete plans for an early success, persistence in the development of usable information for all partners, coordination on business policy, and a new and imaginative business architecture.

Economic Competition↗
PubMed1995

Data sharing in nursing research: advantages and challenges.

The sharing of data between investigators has received little attention in the nursing literature. Among other advantages, data sharing reinforces open scientific inquiry, encourages the development of multiple perspectives, and reduces respondent burden. However, ownership and control of the shared data, preservation of respondents' anonymity, and the costs of data sharing are among the issues that need to be addressed in agreements and contracts involving primary investigators, secondary investigators, and data repositories. The original researcher must spend time and energy to make data sharing possible. It is only when such efforts are acknowledged and rewarded that data sharing is likely to become a norm in the nursing profession. The authors argue that research data should be shared and nurse researchers should seek to have data from all publicly funded projects deposited in accessible data repositories. Nurse researchers need to incorporate plans for data sharing into their research programs and press for the infrastructures required to enable data sharing.

Authorship↗
PubMedDate not supplied

An Item Response analysis of the Hamilton Depression Rating Scale using shared data from two pharmaceutical companies.

Although the Hamilton Depression Rating Scale (HAMD) remains the most widely used outcome measure in clinical trials of Major Depressive Disorder, the psychometric properties of the individual HAMD items have not been extensively studied. In the present paper, data from four separate clinical trials conducted independently by two pharmaceutical companies were analyzed to determine the relationship between scores on the individual HAMD items and overall depressive severity in an outpatient population. Option characteristic curves (the probability of scoring a particular option in relation to overall HAMD scores) were generated in order to illustrate the relationship between scoring patterns for each item and the range of total HAMD scores. Results showed that Items 1 (Depressed Mood) and 7 (Work and Activities), and to a lesser degree, Items 2 (Guilt), 10 (Anxiety/Psychic), 11 (Anxiety/Somatic), and 13 (Somatic/General) demonstrated a good relationship between item responses and overall depressive severity. However, other items (e.g. Insight, Hypochondriasis) appeared to be more problematic with regard to their ability to discriminate over the full range of depression severity. The present results illustrate that co-operative data sharing between pharmaceutical companies can be a useful tool for improving clinical methods.

Clinical Trials as Topic↗
PubMed2026

Examining gaps in institutional policies for clinical genomic data sharing: A cross-jurisdictional study.

The sharing of data generated by clinical genetic and genomic testing without explicit consent is important for timely diagnosis and treatment. While many jurisdictions permit the sharing of identifiable data for direct clinical care, institutional policies vary in how clearly they specify key elements, including when sharing is permitted, what data are covered, and what safeguards apply. Greater clarity around these elements may support responsible data sharing while balancing timely care with transparency and appropriate protections. We conducted a mixed-methods content analysis of data-sharing and privacy policies from 33 clinical genomic institutions across 17 countries and regions. Using a predefined analytical framework, we assessed how policies document key governance elements relevant to sharing without explicit consent. Two independent reviewers extracted information about clinical contexts, data types, justifications, and protections. Although 70% of institutions described circumstances permitting data sharing without explicit consent, most policies did not clearly define the scope or governance of such sharing. Policies also rarely distinguished clinical from research or secondary use and inconsistently specified privacy and security safeguards. While sharing was commonly justified for clinical care (78.3%) or testing services (43.5%), data recipient roles and onward-sharing expectations were often left undefined. This uneven documentation could make it difficult for clinical teams and institutional decision-makers to identify and justify decisions about what is permitted and under what conditions. A guidance framework specifying core governance elements and corresponding protections could help institutions communicate their governance choices more clearly and support comparable baseline practices for responsible data sharing.

Information Dissemination↗
PubMed2006

Architecture of authorization mechanism for medical data sharing on the grid.

Data security is becoming increasingly important as the Grid matures. The advances of the Grid have allowed scientists and researchers to build a data grid where they can share and exchange research-related data and information. In reality, however, these specialists do not benefit enough from this data grid. The reason is that the current Grid does not have sufficiently robust and flexible data security. We investigate a medical data-sharing environment where medical doctors and scientists can securely share clinical and medical research data. We show medical data sharing that takes advantage of PERMIS, or an RBAC-based authorization system that achieves XML element level access control. We also describe the lessons learnt in designing the environment as well as a comparison with other existing authorization mechanisms.

Computer Security↗
PubMed2001

Data sharing and dissemination strategies for fostering competition in health care.

OBJECTIVES: To introduce the concept of common models for data sharing and dissemination, highlight the current operational, technical, and political issues surrounding existing data sharing and dissemination initiatives in a health care market, and suggest an ideal model for future data initiatives. DATA SOURCES/STUDY SETTING: A literature review and case studies of existing data sharing and dissemination initiatives that promote the collection and use of comparative information on provider cost and quality. PRINCIPAL FINDINGS: Three broad types of common models for data sharing and dissemination have evolved over the past decade or so: (1) provider-initiated initiatives developed through collaboration among providers of health care; (2) purchaser-initiated activities driven by a coalition of purchasers; and (3) indirect collaboration-data-sharing initiatives between providers and purchasers with a significant facilitating or regulating role by a third group of stakeholders. The success of a data-sharing and dissemination strategy is determined by how the complex operational, technical, and political issues are addressed. General principles by which a health data initiative might abide include the following: standardized databases as the physical foundation, indicators that reflect the changing market; linkages between and across data sets for comprehensive and complete data; economic value; policy relevance; use of evolving technologies to collect, integrate, and disseminate data; and stakeholder support. CONCLUSIONS: Regulatory solutions alone will not overcome the complex political and technical challenges to data sharing and dissemination. The "ideal" model or process nurturing a market for health care information will incorporate compromise and negotiation to address the issues of data ownership and proprietary concerns, therefore securing the necessary political and financial support of the private sector.

Cooperative Behavior↗
PubMed1992

Data disclosure and data sharing in scientific research.

Data sharing is examined for its bearing on (i) quality assurance and (ii) extensions of results in scientific research as well as (iii) part of a tradition of openness in science. It is suggested that sharing can be accomplished in a simple manner that is also sufficiently flexible to fit varying individual situations by asking authors of data dependent articles and grant proposals to footnote (a) whether they are willing to make their data available to others and, if so, (b) how the data may be accessed. Appendices report results from a survey of current policies and practices in professional societies and in Federal government fund granting agencies. Emphasis is on the social and management sciences.

Confidentiality↗
PubMed1996

Software breakthrough makes data sharing easy.

Technical barriers have made sharing health care data difficult among systems with different data collection tools and software; modifications to data collection tools also present difficulties when comparing new data with old. Software program standardizes indicators or questions so sharing data becomes easier. Data bank of thousands of indicators or questions are stored making survey development much easier.

Data Collection↗
PubMed1991

Issues in data sharing and access: an industry perspective.

Epidemiologic data sharing and access, and information sharing and access, are complex issues with no consensus within the industrial community. The purpose of this paper is to provide an introduction, as well as some personal perspectives, to the issues of data access and sharing. These perspectives include a discussion of types of data sharing, advantages and barriers to openness, and alternatives that lower the need for sharing of the raw data.

Confidentiality↗
PubMed2005

Reducing duplicate patient creation using a probabilistic matching algorithm in an open-access community data sharing environment.

In an open-access community data sharing environment, Intermountain Health Care (IHC) is managing the creation of duplicate patient records through a probabilistic matching algorithm that allows the threshold limits for the returned set to be dynamically assigned to the source system. For internal hospital systems, the rate of duplicate creation was cut 30% in the first 6 months. For IHC's first community data sharing partner, the rate of duplicate creation has been maintained below the acceptable range for the internal Health Plans rate.

Algorithms↗
PubMed2025

"It just feels morally not right to Sell the data": Ethical and social perspectives on human genomic data sharing in Uganda-A phenomenological qualitative study.

While genomic data sharing enhances transparency and research efficiency, it also raises significant ethical and social challenges. This study explored stakeholders' perspectives on these issues, particularly around privacy, confidentiality, and equity in collaborative research. A phenomenological qualitative study was conducted between August and December 2023 at Makerere University College of Health Sciences, other research-intensive institutions, and national regulatory bodies. The study engaged 86 participants: 47 key informants (16 researchers, 14 ethics committee members, nine community advisory board members, and eight research regulators) and four deliberative focus group discussions with 39 participants. Interviews were transcribed verbatim, and thematic analysis was conducted using NVivo 14. Three major themes emerged: (1) stakeholders' experiences in genomic research, including their roles as participants, implementers, or overseers; (2) ethical concerns, such as informed consent, third-party data access, inequities between high-income and low- and middle-income country (LMIC) researchers and participants, and the lack of benefit-sharing frameworks; and (3) social implications, including stigma, discrimination, labeling, community perceptions of fairness, and the need for meaningful engagement. Participants emphasized the importance of protecting participant rights, promoting equity, and ensuring robust data governance and security. The theoretical frameworks of principlism and distributive justice provided a valuable lens for examining these concerns, particularly by highlighting the need to safeguard privacy and fairly distribute responsibilities and benefits in global collaborations. Participants also noted that perceptions of fairness are shaped by trust, local context, and past experiences with research factors that are critical for building equitable and respectful partnerships. This study underscores the urgent need to strengthen protections for research participants and promote fairness in genomic data sharing. Policies should, if adopted, emphasize culturally contextualized consent, active community engagement, restricted third-party data access, and strong data protection mechanisms to address existing inequities and prevent misuse.

LMICs↗
PubMed2001

Data sharing in medical research: an empirical investigation.

BACKGROUND: Scientific research entails systematic investigation. Publishing the findings of research in peer reviewed journals implies a high level of confidence by the authors in the veracity of their interpretation. Therefore it stands to reason that researchers should be prepared to share their raw data with other researchers, so that others may enjoy the same level of confidence in the findings. METHOD: In a prospective study, 29 corresponding authors of original research articles in a medical journal (the British Medical Journal) were contacted to ascertain their preparedness to share the data from their research. The email contact was in one of two forms, a general request and a specific request. The type of request a researcher received was randomly allocated. FINDINGS: Researchers receiving specific requests for data were less likely, and slower, to respond than researchers receiving general requests. Only one researcher released data. Most researchers were reluctant to release their data. Some required further information, clarification, or authorship. INTERPRETATION: The general reluctance of researchers to consider requests for their data is of concern. It raises questions about the level of confidence that should be placed on their interpretations of the data. It also highlights an unfortunate situation where researchers are more concerned with losing an advantage than advancing science.

Authorship↗
PubMed2006

Data sharing and intellectual property in a genomic epidemiology network: policies for large-scale research collaboration.

Genomic epidemiology is a field of research that seeks to improve the prevention and management of common diseases through an understanding of their molecular origins. It involves studying thousands of individuals, often from different populations, with exacting techniques. The scale and complexity of such research has required the formation of research consortia. Members of these consortia need to agree on policies for managing shared resources and handling genetic data. Here we consider data-sharing and intellectual property policies for an international research consortium working on the genomic epidemiology of malaria. We outline specific guidelines governing how samples and data are transferred among its members; how results are released into the public domain; when to seek protection for intellectual property; and how intellectual property should be managed. We outline some pragmatic solutions founded on the basic principles of promoting innovation and access.

Access to Information↗