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Ethical standards are the backbone of nursing practice, guiding nurses as they interact with patients, families, and colleagues. These standards are crucial for providing safe, empathetic care centered on the patient's needs.
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Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different...
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Area of Science:

  • Health Informatics
  • Data Science
  • Research Policy

Background:

  • The National Institutes of Health (NIH) implemented a Data Management and Sharing Policy in January to utilize data from NIH-funded research.
  • The COVID-19 pandemic highlighted the importance of data sharing for patient research and mitigating analytical biases.
  • The pandemic revealed challenges in research reproducibility and validity, with data sharing often remaining "Open Data in Appearance Only" (ODIAO).

Purpose of the Study:

  • To propose a framework detailing risks associated with data sharing.
  • To systematically present risk mitigation strategies for data sharing.
  • To provide healthcare-specific examples of data sharing risks and mitigation.

Main Methods:

  • The framework development was informed by guidelines from the Open Data Institute.
  • The framework incorporated critical aspects of the NIH's 2023 Data Management and Sharing Policy.
  • Analysis involved examining legal, technical, reputational, and commercial categories of data sharing barriers.

Main Results:

  • Barriers to data sharing include misinterpretation of the General Data Privacy Rule and insufficient technical expertise for large data transfers.
  • Current disincentives hinder data sharing from becoming a standard practice across various stages.
  • Identified risks span legal, technical, reputational, and commercial domains.

Conclusions:

  • Moving towards true Open Data requires creating robust incentivization mechanisms.
  • Re-centering data sharing on patient benefits is crucial for encouraging participation.
  • Additional grant requirements and dedicated committees can promote adherence to data reporting practices.