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Original Investigation
October 28, 2019

Using Smartphones to Capture Novel Recovery Metrics After Cancer Surgery

Author Affiliations
  • 1Ariadne Labs, Brigham and Women’s Hospital, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
  • 2Department of Surgery, Massachusetts General Hospital, Boston
  • 3Montefiore Medical Center, Department of Surgery, Albert Einstein College of Medicine, Bronx, New York
  • 4Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
  • 5Department of Surgery, Brigham and Women’s Hospital, Boston, Massachusetts
JAMA Surg. Published online October 28, 2019. doi:10.1001/jamasurg.2019.4702
Key Points

Question  Can metrics derived from smartphone accelerometer data capture differences in physical recovery among patients after surgery?

Findings  In this cohort study, smartphone accelerometer data captured decreases in daily exertional activity in patients with a postoperative event (eg, complication, reoperation) compared with baseline at up to 6 weeks after surgery. Similarly, these data demonstrated that fewer of these patients achieved at least 60 minutes of daily exertional activity in the first 6 weeks after surgery compared with patients without a postoperative event.

Meaning  Physical activity measured passively through smartphone accelerometer data can be used to quantify differential recovery trends after surgery.


Importance  Patient-generated health data captured from smartphone sensors have the potential to better quantify the physical outcomes of surgery. The ability of these data to discriminate between postoperative trends in physical activity remains unknown.

Objective  To assess whether physical activity captured from smartphone accelerometer data can be used to describe postoperative recovery among patients undergoing cancer operations.

Design, Setting, and Participants  This prospective observational cohort study was conducted from July 2017 to April 2019 in a single academic tertiary care hospital in the United States. Preoperatively, adults (age ≥18 years) who spoke English and were undergoing elective operations for skin, soft tissue, head, neck, and abdominal cancers were approached. Patients were excluded if they did not own a smartphone.

Exposures  Study participants downloaded an application that collected smartphone accelerometer data continuously for 1 week preoperatively and 6 months postoperatively.

Main Outcomes and Measures  The primary end points were trends in daily exertional activity and the ability to achieve at least 60 minutes of daily exertional activity after surgery among patients with vs without a clinically significant postoperative event. Postoperative events were defined as complications, emergency department presentations, readmissions, reoperations, and mortality.

Results  A total of 139 individuals were approached. In the 62 enrolled patients, who were followed up for a median (interquartile range [IQR]) of 147 (77-179) days, there were no preprocedural differences between patients with vs without a postoperative event. Seventeen patients (27%) experienced a postoperative event. These patients had longer operations than those without a postoperative event (median [IQR], 225 [152-402] minutes vs 107 [68-174] minutes; P < .001), as well as greater blood loss (median [IQR], 200 [35-515] mL vs 25 [5-100] mL; P = .006) and more follow-up visits (median [IQR], 2 [2-4] visits vs 1 [1-2] visits; P = .002). Compared with mean baseline daily exertional activity, patients with a postoperative event had lower activity at week 1 (difference, −41.6 [95% CI, −75.1 to −8.0] minutes; P = .02), week 3 (difference, −40.0 [95% CI, −72.3 to −3.6] minutes; P = .03), week 5 (difference, −39.6 [95% CI, −69.1 to −10.1] minutes; P = .01), and week 6 (difference, −36.2 [95% CI, −64.5 to −7.8] minutes; P = .01) postoperatively. Fewer of these patients were able to achieve 60 minutes of daily exertional activity in the 6 weeks postoperatively (proportions: week 1, 0.40 [95% CI, 0.31-0.49]; P < .001; week 2, 0.49 [95% CI, 0.40-0.58]; P = .003; week 3, 0.39 [95% CI, 0.30-0.48]; P < .001; week 4, 0.47 [95% CI, 0.38-0.57]; P < .001; week 5, 0.51 [95% CI, 0.42-0.60]; P < .001; week 6, 0.73 [95% CI, 0.68-0.79] vs 0.43 [95% CI, 0.33-0.52]; P < .001).

Conclusions and Relevance  Smartphone accelerometer data can describe differences in postoperative physical activity among patients with vs without a postoperative event. These data help objectively quantify patient-centered surgical recovery, which have the potential to improve and promote shared decision-making, recovery monitoring, and patient engagement.

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