In end-of-life cancer care, nurse clinicians strive to deliver an effective care plan to minimise pain, manage debilitating symptoms, and improve patients' quality of life as they approach end of life. Sadly, existing research literature is replete with studies contesting that sub-optimal pain and symptom management remains the reality for many end-of-life cancer patients, resulting in unnecessary suffering and a diminished quality of life.
To begin to overcome the chasm between inadequate pain and symptom management currently delivered in end-of-life care, and the excellent standard of care that could be achieved, nurse clinicians need only leverage knowledge from existing knowledge resources. Researchers assert that clinical decision making for care planning in end-of-life cancer care can be improved by ensuring access to contextually relevant, medical knowledge resources at the point-of-care. Collectively, these medical knowledge resources represent a valuable asset which can improve clinical decisions and the delivery of best clinical practice, while reducing medical uncertainty, unnecessary clinical variation, and medical errors.
In this research we present a clinical decision support system to bridge the knowledge gap that currently impedes the planning, and delivery, of effective pain and symptom management in end-of-life cancer care. This system enables nurse clinicians to: (a) make informed clinical decisions based upon the patient's presenting situation, care priorities, preferences, and standards of care; and (b) create personalised care plans for effective pain and symptom management in end-of-life cancer care.
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