Capturing intraoperative process deviations using a direct observational approach: the glitch method

Abstract

ObjectivesTo develop a sensitive, reliable tool for enumerating and evaluating technical process imperfections during surgical operations.DesignProspective cohort study with direct observation.SettingOperating theatres on five sites in three National Health Service Trusts.ParticipantsStaff taking part in elective and emergency surgical procedures in orthopaedics, trauma, vascular and plastic surgery; including anaesthetists, surgeons, nurses and operating department practitioners.Outcome measuresReliability and validity of the glitch count method; frequency, type, temporal pattern and rate of glitches in relation to site and surgical specialty.ResultsThe glitch count has construct and face validity, and category agreement between observers is good (κ=0.7). Redundancy between pairs of observers significantly improves the sensitivity over a single observation. In total, 429 operations were observed and 5742 glitches were recorded (mean 14 per operation, range 0–83). Specialty-specific glitch rates varied from 6.9 to 8.3/h of operating (ns). The distribution of glitch categories was strikingly similar across specialties, with distractions the commonest type in all cases. The difference in glitch rate between specialty teams operating at different sites was larger than that between specialties (range 6.3–10.5/h, p<0.001). Forty per cent of glitches occurred in the first quarter of an operation, and only 10% occurred in the final quarter.ConclusionsThe glitch method allows collection of a rich dataset suitable for analysing the changes following interventions to improve process safety, and appears reliable and sensitive. Glitches occur more frequently in the early stages of an operation. Hospital environment, culture and work systems may influence the operative process more strongly than the specialty.

Effectiveness of facilitated introduction of a standard operating procedure into routine processes in the operating theatre: a controlled interrupted time series

“…Our dual observation method allowed us to demonstrate reliability across observers 4 15 18. We also attempted to separate those involved in delivering the training and supporting the intervention (SN) from those evaluating the interventions effects, though in practice, this was logistically difficult.…”

“…We assessed the effect of the intervention with three observational measures of work processes and three measures of clinical outcome: we evaluated team non-technical skills using Oxford Non-Technical Skills (NOTECHS) II,14 technical process deviations using the glitch count15 and compliance with the WHO checklist using a simple 3-point check 16. We also recorded the duration of the operations.…”

“…Glitches are defined as deviations from the recognised process with the potential to reduce quality or speed, including interruptions, omissions and changes, whether these actually affected the outcome of the procedure 15 20. Glitches were recorded, timed and classified independently by each observer, before being agreed by discussion and entered into a secure database following the completion of the operation.…”

A combined teamwork training and work standardisation intervention in operating theatres: controlled interrupted time series study

“…This measure of the technical quality of surgical team performance records deviations from the recognised process with the potential to reduce quality or speed, including interruptions, omissions and changes, whether or not these actually affected the outcome of the procedure, and is expressed as a glitch rate per hour 17. Glitches, their details (eg, ‘equipment not available when requested’) and time of occurrence were recorded independently by each observer.…”

The dichotomy of the application of a systems approach in UK healthcare the challenges and priorities for implementation

“…The diffusion of HFE in UK healthcare can be seen through a steady rise in publications reflecting the application and benefit of HFE within different healthcare contexts (Bowie et al 2015, Hignett et al 2011, Lang et al 2013, Morgan et al 2013.…”