The use of smartphone-derived location data to evaluate participation following critical illness: A pilot observational cohort study

• Published in: Australian critical care Vol. 35; no. 3; pp. 225 - 232
• Main Authors: Gluck, Samuel, Andrawos, Alice, Summers, Matthew J., Lange, Jarrod, Chapman, Marianne J., Finnis, Mark E., Deane, Adam M.
• Format: Journal Article
• Language: English
• Published: Australia Elsevier Ltd 01.05.2022
• Subjects: Adult; Cohort Studies; Critical Illness; Global position system; Humans; Intensive Care Units; Outcomes; Patient Discharge; Prospective Studies; Quality of Life; Smartphone; Technology; Critical illness; Global position system; Technology; Smartphone; Outcomes
• ISSN: 1036-7314; 1878-1721
• DOI: 10.1016/j.aucc.2021.05.007

Disability is common following critical illness, impacting the quality of life of survivors, and is difficult to measure. ‘Participation’ can be quantified as involvement in life outside of their home requiring movement from their home to other locations. Participation restriction is a key element of disability, and following critical illness, participation may be diminished. It may be possible to quantify this change using pre-existing smartphone data. The feasibility of extracting location data from smartphones of survivors of intensive care unit (ICU) admission and assessing participation, using location-based outcomes, during recovery from critical illness was evaluated. Fifty consecutively admitted, consenting adult survivors of non-elective admission to ICU of greater than 48-h duration were recruited to a prospective observational cohort study where they were followed up at 3 and 6 months following discharge. The feasibility of extracting location data from survivors' smartphones and creating location-derived outcomes assessing participation was investigated over three 28-d study periods: pre-ICU admission and at 3 and 6 months following discharge. The following were calculated: time spent at home; the number of destinations visited; linear distance travelled; and two ‘activity spaces’, a minimum convex polygon and standard deviation ellipse. Results are median [interquartile range] or n (%). The number of successful extractions was 9/50 (18%), 12/39 (31%), and 13/33 (39%); the percentage of time spent at home was 61 [56–68]%, 77 [66–87]%, and 67 [58–77]% (P = 0.16); the number of destinations visited was 34 [18–64], 38 [22–63], and 65 [46–88] (P = 0.02); linear distance travelled was 367 [56–788], 251 [114–323], and 747 [326–933] km over 28 d (P = 0.02), pre-ICU admission and at 3 and 6 months following ICU discharge, respectively. Activity spaces were successfully created. Limited smartphone ownership, missing data, and time-consuming data extraction limit current implementation of mass extraction of location data from patients’ smartphones to aid prognostication or measure outcomes. The number of journeys taken and the linear distance travelled increased between 3 and 6 months, suggesting participation may improve over time.