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Capturing intraoperative process deviations using a direct observational approach: the glitch method
  1. Lauren Morgan1,
  2. Eleanor Robertson1,
  3. Mohammed Hadi2,
  4. Ken Catchpole3,
  5. Sharon Pickering2,
  6. Steve New4,
  7. Gary Collins5,
  8. Peter McCulloch1
  1. 1Quality, Reliability, Safety and Teamwork Unit, Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
  2. 2Warwick Orthopaedics, Warwick Medical School, Coventry, UK
  3. 3Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, California, USA
  4. 4Saïd Business School, University of Oxford, Oxford, UK
  5. 5Centre for Statistics in Medicine, University of Oxford, Oxford, UK
  1. Correspondence to Dr Peter McCulloch; peter.mcculloch{at}


Objectives To develop a sensitive, reliable tool for enumerating and evaluating technical process imperfections during surgical operations.

Design Prospective cohort study with direct observation.

Setting Operating theatres on five sites in three National Health Service Trusts.

Participants Staff taking part in elective and emergency surgical procedures in orthopaedics, trauma, vascular and plastic surgery; including anaesthetists, surgeons, nurses and operating department practitioners.

Outcome measures Reliability and validity of the glitch count method; frequency, type, temporal pattern and rate of glitches in relation to site and surgical specialty.

Results The 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.

Conclusions The 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.

  • patient safety
  • quality improvement
  • process of care

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