JMIR Publications

ABSTRACT

Background:

The integration of high technology into healthcare systems is intended to provide new treatment options and improve the quality, safety, and efficiency of care. Robotic-assisted surgery (RAS) is an example of high technology integration in healthcare that has become ubiquitous in many surgical disciplines.

Objective:

The goal of the project is to understand and measure current RAS processes in a systematic, quantitative, and replicable way; identify latent systemic threats and opportunities for improvement based on our observations; and implement and evaluate interventions. This five-year study will take a human factors engineering approach to improve the safety and efficiency of RAS across four US hospitals.

Methods:

The study uses a stepped wedge crossover design with three interventions - introduced in different sequences at each of the four hospitals over four 8-month phases. RAS procedures will be observed in urogynecology, gynecology, general and colorectal surgery, bariatric, and urology. We intend to evaluate attitudes towards each intervention; safety culture; subjective workload for each case; effectiveness of each intervention (including through direct observation of a sample of surgeries in each observational phase); OR duration, length of stay, and patient safety incident reports. Analytic methods will include statistical data analysis, point process analysis, and thematic content analysis.

Results:

The study was funded in September 2018 and approved by the Institutional Review Board of each institution in May and June of 2019 (CSMC and MDRH: Pro00056245; VCMC: STUDY 270; MUSC: Pro00088741). After refining our three interventions in phase one, data collection for phase two (baseline data) began in November 2019 and was scheduled to continue through June 2020. However, data collection was suspended in March 2019 due to the COVID-19 pandemic. We have collected a total of 65 observations across the four sites thus far and anticipate resuming phase two data collection in October 2020.

Conclusions:

This will be the largest direct observational study of surgery ever conducted with data collected on 680 robotic surgery procedures at four different institutions. Proposed interventions will be evaluated using individual (workload and attitude), process (perioperative duration and flow disruption), and organizational (safety culture and complications) level measures. Analytic methods includes statistical analysis, point process analysis, and thematic analysis to study the effect of interventions on a variety of outcomes and examine causation. An implementation science framework is used to investigate the causes of success, or failure, of each intervention at each site and understand potential spread of the interventions.