Informed consent in palliative care clinical trials: Challenging but possible
- Publication Type:
- Journal Article
- Citation:
- Journal of Palliative Medicine, 2013, 16 (5), pp. 485 - 491
- Issue Date:
- 2013-05-01
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Obtaining informed consent is a key protection that should be afforded universally to people using health services and the basis around which any participation in clinical trials is built. Randomized controlled effectiveness studies are necessary to answer key questions in hospice and palliative care, in order to help systematically improve the quality of care. In order to be properly generalizable, such trials need to have broad inclusion criteria to reflect the population most likely to be affected by the condition. The inclusion of patients who are seriously ill, and therefore potentially vulnerable, requires careful exploration of ethical and legal principles that underpin informed consent. Specific challenges in obtaining informed consent for randomised clinical trials (RCTs) in clinically unstable populations such as hospice and palliative care include higher rates of people with impaired cognitive capacity as well as interventional studies in clinical situations which may present as a sudden change in condition. None of these challenges is unique to hospice and palliative care research, but the combination and frequency with which they are encountered require systematic and considered solutions. This article outlines five different ethically valid consent approaches and discusses their applicability to hospice and palliative care research trials. These include: consent by the patient (at the time of enrolment, in advance of the study, or delayed until after the study has commenced); a proxy (or legally authorised representative); or a consent waiver. Increased use of the less traditional modes of informed consent may lead to greater participation rates in hospice and palliative care trials, thereby improving the evidence base more rapidly in part by better reflecting the population served and hence improving generalizability. © Mary Ann Liebert, Inc.
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