OBJECTIVES: Understanding Quality of Life (QoL) between clinical visits is challenging. One reason is that collecting QoL data in the home is often seen as a burden to patients. Digital technologies exist that can administer pulse surveys, but patient response rates are typically low. This research aims to explore whether a combination of brief pulse surveys administered over a series of days can provide valid time-varying QoL estimates with high response rates.

METHODS: We administered a QoL survey to 100 patients using a smart hub, where questions were scheduled to be answered intermittently. Response rate was determined and compared to existing technologies. Using a 50/50 train/test split, a state space model was fit using the training data and QoL trajectories computed using the test data. To assess the ability of the procedure to detect QoL signal and smooth noise, we tested the hypothesis of random questionnaire response using the parametric bootstrap. The average trajectory variance of the holdout was used as a test statistic and is expected to be low for random responses and high for time-varying response patterns.

RESULTS: There was a 94% response rate to questions administered on the smart hubs. The average variance of the real patient trajectories was greater than the maximum of a parametric bootstrap sample of size 200 (p < .005). The procedure detected time-varying trajectories from the intermittent QoL data.

CONCLUSIONS: A survey delivered via at-home smart hub resulted in high response rates and enabled estimation of continuous QoL trajectories. These trajectories contained QoL signal suggesting both a baseline level of data quality and methodological promise. Further work includes validating trajectory trends against known outcomes and incorporating this survey design and analysis into ongoing health outcome studies.