||5R01CA201356-04 Interpret this number
||University Of Michigan At Ann Arbor
||Patient Perspectives on the Ethical Implementation of an Oncology Learning System
Abstract: The development of learning health systems is causing radical transformation of the environment
within which the NCI pursues its mission; understanding the ethical and social implications of these changes is
of paramount importance. In rapid learning systems (RLS), routinely collected patient data drive the process of
discovery, which in turn becomes a natural outgrowth of clinical care. As the Institute of Medicine has noted,
such systems have substantial promise for improving the quality of care and research, and ultimately the value
of health care. As such systems develop, the blurring of the current distinction between clinical practice, quality
of care, and research necessitates careful consideration of ethical implications. As RLSs are in their infancy, it
is critical to conduct research to generate informed and considered patient perceptions of the ethical
implementation of such systems, particularly regarding ways to ensure respect for patient autonomy and
privacy, including best approaches for informing participants and governance of data use, in order to realize
the potential benefits of these systems. Therefore, we propose an innovative study that uses cutting edge
methods of deliberative democracy to generate considered and informed opinions of cancer patients,
leveraging a unique opportunity to evaluate patient experiences during the roll-out of a real-world RLS.
Specifically, the American Society of Clinical Oncology (ASCO) has developed a real-world oncology RLS
known as CancerLinQ. CancerLinQ is being implemented in 15 vanguard practices over the next year, and the
approach to patient notification/consent and data governance in this system is actively evolving. We propose
an empirical investigation with two distinct approaches and aims, in collaboration with ASCO and its vanguard
practices. First, we will use a deliberative democracy approach to determine the range of informed and
considered individual and group opinions and recommendations of cancer patients on the optimal approach for
obtaining consent and appropriate uses of information routinely collected in the course of medical care as part
of a RLS that seeks to improve quality and advance research. Second, following CancerLinQ roll-out, we will
survey patients experiencing the real-world implementation of this RLS in order to evaluate their knowledge
and perceptions of that system. Conducting the proposed work in parallel with the development of a real-world
RLS provides an opportunity to directly inform the development and implementation of a national learning
system that will ultimately impact tens of thousands of patients, and it also allows for the consideration of real-
life rather than purely hypothetical scenarios in ways that increase the likelihood that these investigations will
yield insights that are directly applicable in other settings. The findings will have substantial relevance to the
research mission of the NCI, as oncology learning systems are fundamentally altering the context for research
across the spectrum of cancer causation, diagnosis, prevention, treatment, and survivorship care.
Big data, ethics, and regulations: Implications for consent in the learning health system.
, Jagsi R.
Medical physics, 2018 Oct; 45(10), p. e845-e847.
Perspectives of Patients With Cancer on the Ethics of Rapid-Learning Health Systems.
, Griffith K.A.
, Sabolch A.
, Jones R.
, Spence R.
, De Vries R.
, Grande D.
, Bradbury A.R.
Journal of clinical oncology : official journal of the American Society of Clinical Oncology, 2017-07-10; 35(20), p. 2315-2323.
Estimating the Risks of Breast Cancer Radiotherapy: Evidence From Modern Radiation Doses to the Lungs and Heart and From Previous Randomized Trials.
, Correa C.
, Duane F.K.
, Aznar M.C.
, Anderson S.J.
, Bergh J.
, Dodwell D.
, Ewertz M.
, Gray R.
, Jagsi R.
, et al.
Journal of clinical oncology : official journal of the American Society of Clinical Oncology, 2017-05-20; 35(15), p. 1641-1649.