JMIR Publications

ABSTRACT

Background:

Minimally invasive thoracic surgery (MITS) has improved lung cancer outcomes but requires enhanced postoperative care. Traditionally episodic care model has limited timely and multi-dimensional monitoring of patients. Recent technological advances in multimodal digital devices, including wearable device and electronic patient reported outcomes (ePROs), offer a promising solution to these challenges. However, current studies focus on only a few parameters and limited application in thoracic surgery.

Objective:

We propsed a self-controlled study to evaluate the feasibility and reliability of multimodal digital devices, including wearables and ePROs, for continuous perioperative monitoring to enhance revovery after thoracic surgery.

Methods:

We included 288 non-small cell lung cancer (NSCLC) patients from the GMU cohort, which includes 2,757 participants with various lung diseases. Digital data were collected during hospitalization using a commercial smartwatch combined an electronic patient-reported outcomes (ePROs) questionnaire, while clinical data was obtained from electronic health record (EHR). Agreement between the digital device and EHR was evaluated via Bland-Altman analysis. Time-series data were normalized for continuous outlier monitoring and threshold analysis of ePROs scores was used to explore associations across different modules.

Results:

Throughout hospitalization, digital devices provided a subjective overview of the patients’ recovery trajectories. Results of Bland-Altman analysis demonstrated a high level of agreement between the digital device and the HER, for body temperature, the analysis revealed a minimal bias of 0.02°C (95% CI: -0.01°C to 0.05°C), the agreement for HR showed a bias of 0.26 beats per minute (bpm) (95% CI: -0.49 bpm to 1.01 bpm), for oxygen saturation, the bias was -0.06% (95% CI: -0.27% to 0.15%)indicating close alignment between the two measurement methods. Meanwhile, wearable devices demonstrate significant potential in outlier detection compared to episodic care model, offering accurate and sensitive monitoring of outliers between traditional measurement intervals. Using a thresholding method, we found that wearable metrics was correlated with the severity of ePROs.

Conclusions:

These findings highlight the reliability and clinical potential of digital device-based multimodal system within the enhanced recovery after surgery (ERAS) framework, offering a novel approach for continuous perioperative monitoring. Clinical Trial: This prospective study was registered with clinical trial registry (Clinical trial number: NCT06118229).