Proxy-Reported Quality of Life and Family Impact for Children Followed Longitudinally by a Pediatric Palliative Care Team

Abstract

Abstract

Background:

One goal of pediatric palliative care is to maintain quality of life for children and their families. Quality-of-life investigations may be enhanced by considering clinically important metrics in addition to statistical significance.

Objective:

The purpose of this study was to longitudinally evaluate the effect of time on quality of life and family impact for pediatric palliative care patients across all diagnoses and ages.

Design:

This prospective quality-of-life study included administration of a 23-item PedsQL™ Measurement Model to evaluate for physical, emotional, social, and cognitive dimensions of the child's quality of life and a 36-item PedsQL Family Impact Module to assess for the familial impact at time of initial palliative care consultation, Month 6, and Month 12.

Setting/Subjects:

All pediatric patients who received a palliative care consultation in our Midwestern free-standing children's hospital over a five-year period were included in the longitudinal study (n = 87).

Measurements:

Repeated measures ANOVA was used to investigate how proxy-reported quality of life and family impact changed with time with attentiveness to also follow trends in minimal clinically important difference (MCID) metrics.

Results:

The emotional domain showed a statistically significant positive trend over the first six months of palliative care involvement (p = 0.049), while the physical domain (p = 0.028) and daily activity (p = 0.039) showed a positive improvement for the full year. In using a standard of MCID, the physical, emotional, and cognitive domains improved in the quality-of-life scale and the communication, worry, and daily activity domains improved in the family impact scale over 12 months.

Conclusions:

In considering quality-of-life analyses for pediatric palliative care programmatic improvements, providers may consider analyzing not only for statistical significance in collective data sets but also for clinically important difference over time.