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Presentation at the Workshop on Data Management
held at King Saud University Riyad Saudi Arabia on April 30th 2013 by Professor Omar Hasan Kasule Sr. MB
ChB (MUK), MPH (Harvard), DrPH (Harvard) Chairman Institutional Review Board
and Department of Bioethics King Fahad Medical City Riyadh EM: omarkasule@yahoo.com
Abstract
Data includes words, numbers, images, and voice most often in an
electronic form. Modern information technology handling large and multiple
datasets has spawned new ethical issues that researchers dealing with a single
research data base in one institution did not face. These issues are: data
costs, data ownership, data confidentiality, and patient safety based on data
validity. These ethical issues arise at the stages of data sourcing / collection,
data editing, and data storage and retrieval. They also arise in the processes
of data sharing and data integration. Data editing and validation can lead to
biases that will eventually impact on patient safety through wrong research
data and conclusions.
Operational data generated by
hospitals, health insurance companies, and administrative units is not
collected with due care to ensure research-quality accuracy (accuracy,
coverage) and lies unused in data banks while researchers apply for and get
grants to collect new data for their research purposes. The defects of these
data bases can be overcome by instituting quality control programs and using
multiple sources for cross validation. The data can be used for research by
permission of the legal owner; laws and regulations are not yet clear on this
issue because potential owners include the patients, the physicians, and the
institutions. The issue of ownership leads to another question whether
routinely collected data can be sold to researchers. A corollary to this is whether
researchers can engage in selling or buying data with other researchers or
commercial marketing and advertising agencies.
Data integration and data
sharing, facilitated by modern information technology, enable access to
more data in other institutions for analysis and standard setting. Information
technology provides the algorithms for fast integration. Data sharing
involves allowing other researchers to access data. Both integration and
sharing are an ethical imperative to advance knowledge that benefits patients.
Integration and sharing have been used mostly in genomic sequencing, nuclear
mapping, imaging, clinical trials, and organ transplantation research.
Integration and sharing enable researchers, present and future, to draw upon a
larger data base but are associated with ethical issues of intellectual
property, informed consent, privacy, and confidentiality are followed. Codes,
standards, policies and mapping at local and international levels are being
developed to address these issues. Owners of data collected at great expense
are reluctant to share or integrate it with others without proper
acknowledgement of intellectual property. Informed consent from patients is
needed for data sharing unless fully anonymised. Data privacy and
confidentiality are assured by use of secure data portals and cryptography.
Data processing within one research project has its
own ethical issues. The data manager could introduce biases, random or
non-random, in the processes of adjusting for missing data, data transformation,
and creation of derived variables. Data processing mistakes underlie several
types of bias: misclassification, selection bias, and sampling bias. Any
mistakes introduced at this stage will impact the final research results and
eventually affect patient safety due to clinical interventions based on false
research. The usual procedures for data privacy and data confidentiality must
be respected. As far as possible personal identifiers should not be accessible
except to a few selected members of the research team. The data should be kept
locked up or in password protected computers. If the computers are connected
online the institution should have policies and software to assure data
security.