Association of Wearable Activity Monitors With Assessment of Daily Ambulation and Length of Stay Among Patients Undergoing Major Surgery

Abstract

Importance: Early postoperative ambulation is vital to minimizing length of stay (LOS), but few hospitals objectively measure ambulation to predict outcomes. Wearable activity monitors have the potential to transform assessment of postoperative ambulation, but key implementation data, including whether digitally monitored step count can identify patients at risk for poor efficiency outcomes, are lacking.

Objectives: To define the distribution of digitally measured daily step counts after major inpatient surgical procedures, to assess the accuracy of physician assessment and ordering of ambulation, and to quantify the association of digitally measured step count with LOS.

Design, setting, and participants: Prospective cohort study at Cedars-Sinai Medical Center, an urban tertiary referral center. Participants were patients undergoing 8 inpatient operations (lung lobectomy, gastric bypass, hip replacement, robotic cystectomy, open colectomy, abdominal hysterectomy, sleeve gastrectomy, and laparoscopic colectomy) from July 11, 2016, to August 30, 2017.

Interventions: Use of activity monitors to measure daily postoperative step count.

Main outcomes and measures: Operation-specific daily step count, daily step count by physician orders and assessment, and a prolonged LOS (>70th percentile for each operation).

Results: Among 100 patients (53% female), the mean (SD) age was 53 (18) years, and the median LOS was 4 days (interquartile range, 3-6 days). There was a statistically significant increase in daily step count with successive postoperative days in aggregate (r = 0.55; 95% bootstrapped CI, 0.47-0.62; P < .001) and across individual operations. Ninety-five percent (356 of 373) of daily ambulation orders were "ambulate with assistance," although daily step counts ranged from 0 to 7698 steps (0-5.5 km) under this order. Physician estimation of ambulation was predictive of the median step count (r = 0.66; 95% bootstrapped CI, 0.59-0.72; P < .001), although there was substantial variation within each assessment category. For example, daily step counts ranged from 0 to 1803 steps (0-1.3 km) in the "out of bed to chair" category. Higher step count on postoperative day 1 was associated with lower odds of prolonged LOS from 0 to 1000 steps (odds ratio [OR], 0.63; 95% CI, 0.45-0.84; P = .003), with no further decrease in odds after 1000 steps (OR, 0.99; 95% CI, 0.75-1.30; P = .80).

Conclusions and relevance: In this study, digitally measured step count up to 1000 steps on postoperative day 1 was associated with lower probability of a prolonged LOS. Wearable activity monitors improved the accuracy of assessment of daily step count over the current standard of care, providing an opportunity to identify patients at risk for poor efficiency outcomes.

Conflict of interest statement

Conflict of Interest Disclosures: Drs Daskivich and Spiegel reported having a patent pending for a wearable technology feedback system to monitor postoperative ambulation and reported having a working relationship with 2 companies (SONIFI Health and Fitabase) for further testing and development of this technology. Dr Daskivich reported receiving support from Fitabase. Dr Walsh reported receiving support from Merck, Alligent, and Clovis Oncology. Dr Spitzer reported consulting for Flexion, Sanofi, and DePuy and reported receiving research grants from DePuy and Flexion. No other disclosures were reported.

Figures

Figure 1.. Digitally Monitored Step Count by Postoperative Day Across All Surgical Procedures

Boxes show the first quartile (lower border of the box), median (thick horizontal line within the box), and third quartile (top border of the box). Whiskers extending from the top and bottom borders of the box show the range of nonoutlier values. The individual points outside the whisker boundaries indicate outlier values that are less than the first quartile or greater than the third quartile by 1.5 times the interquartile range.

Figure 2.. Digitally Monitored Step Count by Postoperative Day and Operation Type

Boxes show the first quartile (lower border of the box), median (thick horizontal line within the box), and third quartile (top border of the box). Whiskers extending from the top and bottom borders of the box show the range of nonoutlier values. The individual points outside the whisker boundaries indicate outlier values that are less than the first quartile or greater than the third quartile by 1.5 times the interquartile range.

Figure 3.. Digitally Monitored Step Count by Ordered Ambulation Regimen and Surgeon-Estimated Ambulation

Boxes show the first quartile (lower border of the box), median (thick horizontal line within the box), and third quartile (top border of the box). Whiskers extending from the top and bottom borders of the box show the range of nonoutlier values. The individual points outside the whisker boundaries indicate outlier values that are less than the first quartile or greater than the third quartile by 1.5 times the interquartile range. OOB indicates out of bed.

Figure 4.. Predicted Probabilities of Prolonged Length of Stay by Postoperative Day 1 Step Count

A, Operation-specific length of stay longer than the 70th percentile (data include all operations). B, Operation-specific length of stay longer than the 80th percentile (data include all operations). C, Operation-specific length of stay longer than the 70th percentile (by operation). D, Operation-specific length of stay longer than the 80th percentile (by operation). Shaded areas represent 95% CIs.