Randomized Controlled Trial Shows Efficacy of Caregiver mHealth Support for Patient Symptom Treatment at End of Life

By Teresa Hagan Thomas, PhD, RN - March 16, 2023

When individuals with cancer approach the end of life (EOL), they commonly experience multiple distressing symptoms that require attention and care. Family caregivers must help care for symptoms and decide when to contact the hospice team or another health care professional. However, support for caregivers in helping ease patients’ symptom burdens are lacking, and they are often left to provide intense levels of care with little instruction.

A new study demonstrated that an automated symptom monitoring system significantly improved patient symptom burden over time compared to usual care. The study team, led by Dr. Kathi Mooney, PhD, RN, at the University of Utah College of Nursing, published their results in the Journal of Pain and Symptom Management.

The intervention–Symptom Care at Home–consisted of 3 components: (1) caregivers making daily calls to an interactive voice response system where they reported their care recipient’s presence and severity of 11 common EOL symptoms, (2) caregivers receiving coaching based on the patient’s symptoms, and (3) hospice nurses being notified of any moderate to severe symptoms (eg, 4 out of 10 or greater on a 0-10 scale). Participants randomized to usual care still completed daily calls but received no coaching or automated calls to hospice nurses. Caregivers and patients were recruited across 12 hospices in 4 states.

The final sample included 298 caregivers, about half (53%) of whom were spouses/partners and 36% of whom were adult children. Caregiver calls to the interactive voice response system were between 9 and 11 minutes, and most caregivers completed the majority of daily calls to the system (66% and 75% of expected days for the usual care and Symptom Care at Home groups, respectively). The top 3 most frequently reported symptoms were fatigue, pain, and poor appetite.

Group comparisons at each timepoint from 1, 2, 4, and 8 weeks after enrollment indicated that patients’ symptoms in the Symptom Care at Home were lower than the usual care group. The researchers concluded that the intervention benefit was an overall 4.9-point reduction in symptom severity on a 0-10 scale. The biggest symptom reduction was at week 1 (5.1 points) but remained high even at week 8 (4.1 points). These results had a moderate effect size of d=0.55, so the intervention’s effect was meaningful. Moreover, the intervention decreased the incidence of moderate to severe symptoms, including fatigue, pain, and poor appetite (20%, 33%, and 43% reduction, respectively).

These results demonstrate that this automated symptom monitoring and coaching system significantly reduced caregiver reports of patients’ symptoms at EOL. Unlike prior reports indicating that face-to-face or clinically embedded symptom interventions were preferable, this study demonstrated that an automated symptom coaching intervention was engaging and efficacious. Oncology nurses can support such caregiver interventions and ensure their symptom management suggestions are evidence-based.

References

Technology-assisted mHealth caregiver support to manage cancer patient symptoms: A randomized controlled trial.

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