Wearable technology and the association of perioperative activity level with 30-day readmission among patients undergoing major colorectal surgery

Digital Tracking of Patients Undergoing Radical Cystectomy for Bladder Cancer: Daily Step Counts Before and After Surgery Within the iROC Randomised Controlled Trial

BACKGROUND

Efforts to improve recovery after radical cystectomy (RC) are needed.

OBJECTIVE

To investigate wrist-worn wearable activity trackers in RC participants.

DESIGN, SETTING, AND PARTICIPANTS

An observational cohort study was conducted within the iROC randomised trial.

INTERVENTION

Patients undergoing RC at nine cancer centres wore wrist-based trackers for 7 days (d) at intervals before and after surgery.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Step counts were compared with participant and operative features, and recovery outcomes.

RESULTS AND LIMITATIONS

Of 308 participants, 284 (92.2%) returned digital activity data at baseline (median 17 d [interquartile range: 8-32] before RC), and postoperatively (5 [5-6] d) and at weeks 5 (43 [38-43] d), 12 (94 [87-106] d), and 26 (192 [181-205] d) after RC. Compliance was affected by the time from surgery and a coronavirus disease 2019 pandemic lockdown (return rates fell to 0-7%, chi-square p < 0.001). Step counts dropped after surgery (mean of 28% of baseline), before recovering at 5 weeks (wk) (71% of baseline) and 12 wk (95% of baseline; all analysis of variance [ANOVA] p < 0.001). Baseline step counts were not associated with postoperative recovery or death. Patients with extended hospital stays had reduced postoperative step counts, with a difference of 2.2 d (95% confidence interval: 0.856-3.482 d) between the lowest third and highest two-third tertiles (linear regression analysis; p < 0.001). Additionally, they spent less time out of the hospital within 90 d of RC (80.3 vs 74.3 d, p = 0.013). Lower step counts at 5, 12, and 26 wk were seen in those seeking medical help and needing readmission (ANOVA p ≤ 0.002).

CONCLUSIONS

Baseline step counts were not associated with recovery. Lower postoperative step counts were associated with longer length of stay at the hospital and postdischarge readmissions. Studies are required to determine whether low step counts can identify patients at a risk of developing complications.

PATIENT SUMMARY

Postoperative step counts appear to be a promising tool to identify patients in the community needing medical help or readmission. More work is needed to understand which measures are most useful and how best to collect these.

Wearable Sensors as a Preoperative Assessment Tool: A Review

Surgery is a common first-line treatment for many types of disease, including cancer. Mortality rates after general elective surgery have seen significant decreases whilst postoperative complications remain a frequent occurrence. Preoperative assessment tools are used to support patient risk stratification but do not always provide a precise and accessible assessment. Wearable sensors (WS) provide an accessible alternative that offers continuous monitoring in a non-clinical setting. They have shown consistent uptake across the perioperative period but there has been no review of WS as a preoperative assessment tool. This paper reviews the developments in WS research that have application to the preoperative period. Accelerometers were consistently employed as sensors in research and were frequently combined with photoplethysmography or electrocardiography sensors. Pre-processing methods were discussed and missing data was a common theme; this was dealt with in several ways, commonly by employing an extraction threshold or using imputation techniques. Research rarely processed raw data; commercial devices that employ internal proprietary algorithms with pre-calculated heart rate and step count were most commonly employed limiting further feature extraction. A range of machine learning models were used to predict outcomes including support vector machines, random forests and regression models. No individual model clearly outperformed others. Deep learning proved successful for predicting exercise testing outcomes but only within large sample-size studies. This review outlines the challenges of WS and provides recommendations for future research to develop WS as a viable preoperative assessment tool.

Association between early mobilisation after abdominal cancer surgery and postoperative complications

INTRODUCTION

Postoperative complications and readmission to hospital after major cancer surgery are common. Early mobilisation in hospital is thought to reduce complications, and patients are recommended to mobilise for at least 2 h on the day of surgery, and thereafter at least 6 h per day. Evidence for early mobilisation is limited and therefore also how early mobilisation may influence the development of postoperative complications. The aim of this study was to evaluate the association between early mobilisation after abdominal cancer surgery and readmission to hospital due to postoperative complications.

MATERIAL AND METHODS

Adult patients who had abdominal cancer surgery due to ovarian, colorectal, or urinary bladder cancer between January 2017 and May 2018 were included in the study. Exposure was set to the mean number of steps taken over the first three postoperative days, measured with an activity monitor. Primary outcome was readmission to hospital within 30 days after discharge, and secondary outcome was severity of complications. Data were obtained from medical records. Logistic regression was used to investigate the association between exposure and outcomes.

RESULTS

Of 133 patients included in the study, 25 were readmitted to the hospital within 30 days after discharge. The analysis showed no association between early mobilisation and readmission or severity of complications.

CONCLUSION

Early mobilisation does not seem to increase the odds of readmission, nor the severity of complications. This study contributes to the limited research on the association between early mobilisation and postoperative complications after abdominal cancer surgery.

Predicting Hospital Readmission among Patients with Sepsis Using Clinical and Wearable Data

Sepsis is a life-threatening condition that occurs due to a dysregulated host response to infection. Recent data demonstrate that patients with sepsis have a significantly higher readmission risk than other common conditions, such as heart failure, pneumonia and myocardial infarction and associated economic burden. Prior studies have demonstrated an association between a patient's physical activity levels and readmission risk. In this study, we show that distribution of activity level prior and post-discharge among patients with sepsis are predictive of unplanned rehospitalization in 90 days (P-value<1e-3). Our preliminary results indicate that integrating Fitbit data with clinical measurements may improve model performance on predicting 90 days readmission.Clinical relevance Sepsis, Activity level, Hospital readmission, Wearable data.

Frailty Assessment and Prehabilitation as Part of a PeRioperative Evaluation and Planning (PREP) Program for Patients Undergoing Colorectal Surgery

Frailty assessment and prehabilitation can be incrementally implemented in a multidisciplinary, multiphase pathway to improve patient care. To start, modifications can be made to a surgeon's practice with existing resources while adapting standard pathways for frail patients. Frailty screening can identify patients in need of additional assessment and optimization. Personalized utilization of frailty data for optimization through prehabilitation can improve postoperative outcomes and identify patients who would benefit from adapted care. Additional utilization of the multidisciplinary team can lead to improved outcomes and a strong business case to add additional members of the team.

Readiness for implementation of novel digital health interventions for postoperative monitoring: a systematic review and clinical innovation network analysis

An increasing number of digital health interventions (DHIs) for remote postoperative monitoring have been developed and evaluated. This systematic review identifies DHIs for postoperative monitoring and evaluates their readiness for implementation into routine health care. Studies were defined according to idea, development, exploration, assessment, and long-term follow-up (IDEAL) stages of innovation. A novel clinical innovation network analysis used coauthorship and citations to examine collaboration and progression within the field. 126 DHIs were identified, with 101 (80%) being early stage innovations (IDEAL stage 1 and 2a). None of the DHIs identified had large-scale routine implementation. There is little evidence of collaboration, and there are clear omissions in the evaluation of feasibility, accessibility, and the health-care impact. Use of DHIs for postoperative monitoring remains at an early stage of innovation, with promising but generally low-quality supporting evidence. Comprehensive evaluation within high-quality, large-scale trials and real-world data are required to definitively establish readiness for routine implementation.

Predicting Hospital Readmission among Patients with Sepsis using Clinical and Wearable Data

Sepsis is a life-threatening condition that occurs due to a dysregulated host response to infection. Recent data demonstrate that patients with sepsis have a significantly higher readmission risk than other common conditions, such as heart failure, pneumonia and myocardial infarction and associated economic burden. Prior studies have demonstrated an association between a patient's physical activity levels and readmission risk. In this study, we show that distribution of activity level prior and post-discharge among patients with sepsis are predictive of unplanned rehospitalization in 90 days (P-value<1e-3). Our preliminary results indicate that integrating Fitbit data with clinical measurements may improve model performance on predicting 90 days readmission.

Accelerometer-measured Inpatient Physical Activity and Associated Outcomes after Major Abdominal Surgery: A Systematic Review (Preprint)

BACKGROUND

It remains unclear how inpatient physical activity after major abdominal surgery affects outcomes. Accelerometer research may provide further evidence for postoperative mobilization.

OBJECTIVE

We aimed to summarize the current literature evaluating the impact of accelerometer-measured postoperative physical activity on outcomes after major abdominal surgery.

METHODS

We searched PubMed and Google Scholar in October 2021 to conduct a systematic review. Studies were included if they used accelerometers to measure inpatient physical behaviors immediately after major abdominal surgery, defined as any nonobstetric procedures performed under general anesthesia requiring hospital admission. Studies were eligible only if they evaluated the effects of physical activity on postoperative outcomes such as postoperative complications, return of gastrointestinal function, hospital length of stay, discharge destination, and readmissions. We excluded studies involving participants aged <18 years. Risk of bias was assessed using the risk-of-bias assessment tool for nonrandomized studies (RoBANS) for observational studies and the revised Cochrane risk-of-bias tool for randomized trials (RoB 2) for randomized controlled trials (RCTs). Findings were summarized by qualitative synthesis.

RESULTS

We identified 15 studies. Risk of bias was high in 14 (93%) of the 15 studies. Most of the studies (11/15, 73%) had sample sizes of <100. Of the 15 studies, 13 (87%) included the general surgery population, 1 (7%) was a study of patients who had undergone gynecologic surgery, and 1 (7%) included a mixed (abdominal, thoracic, gynecologic, and orthopedic) surgical population. Of the 15 studies, 12 (80%) used consumer-grade accelerometers to measure physical behaviors. Step count was the most commonly reported physical activity outcome (12/15, 80%). In the observational studies (9/15, 60%), increased physical activity during the immediate postoperative period was associated with earlier return of gastrointestinal function, fewer surgical and pulmonary complications, shorter hospital length of stay, and fewer readmissions. In the RCTs (6/15, 40%), only 1 (17%) of the 6 studies demonstrated improved outcomes (shorter time to flatus and hospital length of stay) when a mobility-enhancing intervention was compared with usual care. Notably, mobility-enhancing interventions used in 4 (67%) of the 6 RCTs did not result in increased postoperative physical activity.

CONCLUSIONS

Although observational studies show strong associations between postoperative physical activity and outcomes after major abdominal surgery, RCTs have not proved the benefit of mobility-enhancing interventions compared with usual care. The overall risk of bias was high, and we could not synthesize specific recommendations for postoperative mobilization. Future research would benefit from improving study design, increasing methodologic rigor, and measuring physical behaviors beyond step counts to understand the impact of postoperative mobilization on outcomes after major abdominal surgery.

Determining the Reliable Measurement Period for Preoperative Baseline Values With Telemonitoring Before Major Abdominal Surgery: Pilot Cohort Study

BACKGROUND

Preoperative telemonitoring of vital signs, physical activity, and well-being might be able to optimize prehabilitation of the patient's physical and mental condition prior to surgery, support setting alarms during in-hospital monitoring, and allow personalization of the postoperative recovery process.

OBJECTIVE

The primary aim of this study was to evaluate when and how long patients awaiting major abdominal surgery should be monitored to get reliable preoperative individual baseline values of heart rate (HR), daily step count, and patient-reported outcome measures (PROMs). The secondary aim was to describe the perioperative course of these measurements at home.

METHODS

In this observational single-center cohort study, patients used a wearable sensor during waking hours and reported PROMs (pain, anxiety, fatigue, nausea) on a tablet twice a day. Intraclass correlation coefficients (ICCs) were used to evaluate the reliability of mean values on 2 specific preoperative days (the first day of telemonitoring and the day before hospital admission) and randomly selected preoperative periods compared to individual reference values. Mean values of HR, step count, and PROMs per day were visualized in a boxplot from 14 days before hospital admission until 30 days after surgery.

RESULTS

A total of 16 patients were included in the data analyses. The ICCs of mean values on the first day of telemonitoring were 0.91 for HR, 0.71 for steps, and at least 0.86 for PROMs. The day before hospital admission showed reliability coefficients of 0.76 for HR, 0.71 for steps, and 0.92-0.99 for PROMs. ICC values of randomly selected measurement periods increased over the continuous period of time from 0.68 to 0.99 for HR and daily step counts. A lower bound of the 95% CI of at least 0.75 was determined after 3 days of measurements. The ICCs of randomly selected PROM measurements were 0.89-0.94. Visualization of mean values per day mainly showed variable preoperative daily step counts (median 2409, IQR 1735-4661 steps/day) and lower postoperative daily step counts (median 884, IQR 474-1605 steps/day). In addition, pain was visually reduced until 30 days after surgery at home.

CONCLUSIONS

In this prospective pilot study, for patients awaiting major abdominal surgery, baseline values for HR and daily step count could be measured reliably by a wearable sensor worn for at least 3 consecutive days and PROMs during any preoperative day. No clear conclusions were drawn from the description of the perioperative course by showing mean values of HR, daily step count, and PROM values over time in the home situation.

Gamification for Machine Learning in Surgical Patient Engagement

Patients and their surgeons face a complex and evolving set of choices in the process of shared decision making. The plan of care must be tailored to individual patient risk factors and values, though objective estimates of risk can be elusive, and these risk factors are often modifiable and can alter the plan of care. Machine learning can perform real-time predictions of outcomes, though these technologies are limited by usability and interpretability. Gamification, or the use of game elements in non-game contexts, may be able to incorporate machine learning technology to help patients optimize their pre-operative risks, reduce in-hospital complications, and hasten recovery. This article proposes a theoretical mobile application to help guide decision making and provide evidence-based, tangible goals for patients and surgeons with the goal of achieving the best possible operative outcome that aligns with patient values.

OUP accepted manuscript

Background

Wearable devices have been proposed as a novel method for monitoring patients after surgery to track recovery, identify complications early, and improve surgical safety. Previous studies have used a heterogeneous range of devices, methods, and analyses. This review aimed to examine current methods and wearable devices used for monitoring after abdominal surgery and identify knowledge gaps requiring further investigation.

Methods

A scoping review was conducted given the heterogeneous nature of the evidence. MEDLINE, EMBASE, and Scopus databases were systematically searched. Studies of wearable devices for monitoring of adult patients within 30 days after abdominal surgery were eligible for inclusion.

Results

A total of 78 articles from 65 study cohorts, with 5153 patients were included. Thirty-one different wearable devices were used to measure vital signs, physiological measurements, or physical activity. The duration of postoperative wearable device use ranged from 15 h to 3 months after surgery. Studies mostly focused on physical activity metrics (71.8 per cent). Continuous vital sign measurement and physical activity tracking both showed promise for detecting postoperative complications earlier than usual care, but conclusions were limited by poor device precision, adherence, occurrence of false alarms, data transmission problems, and retrospective data analysis. Devices were generally well accepted by patients, with high levels of acceptance, comfort, and safety.

Conclusion

Wearable technology has not yet realized its potential to improve postoperative monitoring. Further work is needed to overcome technical limitations, improve precision, and reduce false alarms. Prospective assessment of efficacy, using an intention-to-treat approach should be the focus of further studies.

Consumer Wearables for Patient Monitoring in Otolaryngology: A State of the Art Review

OBJECTIVE

Consumer wearables, such as the Apple Watch or Fitbit devices, have become increasingly commonplace over the past decade. The application of these devices to health care remains an area of significant yet ill-defined promise. This review aims to identify the potential role of consumer wearables for the monitoring of otolaryngology patients.

DATA SOURCES

PubMed.

REVIEW METHODS

A PubMed search was conducted to identify the use of consumer wearables for the assessment of clinical outcomes relevant to otolaryngology. Articles were included if they described the use of wearables that were designed for continuous wear and were available for consumer purchase in the United States. Articles meeting inclusion criteria were synthesized into a final narrative review.

CONCLUSIONS

In the perioperative setting, consumer wearables could facilitate prehabilitation before major surgery and prediction of clinical outcomes. The use of consumer wearables in the inpatient setting could allow for early recognition of parameters suggestive of poor or declining health. The real-time feedback provided by these devices in the remote setting could be incorporated into behavioral interventions to promote patients' engagement with healthy behaviors. Various concerns surrounding the privacy, ownership, and validity of wearable-derived data must be addressed before their widespread adoption in health care.

IMPLICATIONS FOR PRACTICE

Understanding how to leverage the wealth of biometric data collected by consumer wearables to improve health outcomes will become a high-impact area of research and clinical care. Well-designed comparative studies that elucidate the value and clinical applicability of these data are needed.