This pilot project was done in a single eye OT of a single surgical unit (operating twice-a-week) at a tertiary-care eye hospital. A team was formed consisting of a faculty member (team leader), a senior resident (Post-MD), a junior resident (Postgraduate student) and a member of the nursing staff.

The baseline process was studied (Fig. 1). The junior resident (JR) called all patients from the ward, and then called the Neonatal Intensive Care Unit (NICU) for arrangement of backup postoperative bed. The patients left the ward and arrived at the OT reception area and were shifted inside to the GA waiting area. If found fit by the anaesthesia team, they were shifted for surgery, else awaited confirmation by the JR, and exited from the OT.

Fig. 1 Baseline process flow chart depicting patient flow from ward to operation theatre till exit.

All eight patients posted for surgery were called much before the arrival time of the anaesthesia team i.e. 8.30 AM. Two of these patients were cancelled after five hours of waiting. An infected case posted for an intravitreal injection had to wait for over 6 ½ hours. two ‘plan do study act (PDSA)’ cycles were performed on two consecutive OT days.

Outcome Parameters - The waiting-time was defined as the time from the patient reporting to the OT reception area (outside the OT) to the time when the baby was shifted for surgery into the OT. The ‘average waiting- time was defined as the mathematical mean of waiting-time of all babies posted for surgery in that OT. The maximum waiting-time was the maximum time any baby had to wait before being shifted for surgery or out of the OT and was calculated from the record sheet. The data was collected across a total of six OT days to test the sustenance of changes.

The study was performed over six consecutive OT days over three weeks with baseline data being collected on the first day. The number of patients operated on these days were 3, 3, 4, 3, 4, 4, respectively. The Average waiting-time and Maximal waiting-time at baseline were recorded as 221 minutes and 390 minutes, respectively.

The Average waiting-time reduced to 123 minutes (44% reduction) after the first PDSA cycle and further maximally to 29 minutes (87% from baseline) after the second PDSA cycle. Similarly, the Maximum waiting-time reduced to 195 minutes (50% reduction) and further maximally to 52 minutes (87% reduction) after the first and second PDSA cycles, respectively (Fig. 2). The changes were sustained over next 3 days. Statistical analysis could not be performed due to small number of data points.

Fig. 2 Bar chart depicting sustained reduction in average and maximum waiting time following two Plan-Do-Study-Act cycles.

The need of effective and organized OT planning for continuous quality improvement has been a concern for hospital management. The communication gap among anaesthesiologists, surgeons and nursing staff is known to be a factor for start time delays and high waiting time in OT [1], and QI methodologies can significantly improve surgical care, from reducing infection to increasing OT efficiency [3].

This pilot QI project highlights the importance of collection of baseline data to detect notable waiting time issues. PDSA is a widely accepted method of quality improvement in healthcare systems [4]. Repeated PDSA cycles lead to better understanding of the process flow issues, with identification of new factors providing better than expected outcome. Rapid PDSA changes across 2 OT days led to quick reduction in waiting times, JR and this led to a less crowded GA waiting area, and more efficient workflow, which can indirectly lead to more cases being operated in the same OT day.

Since it was a pilot project, the waiting time was recorded only for six OT days. This is a limitation of the study and data collection over a longer period of time would have provided better insight into sustenance of quality improvement. These simple tweaks in process flow can be easily scaled and implemented across different operation theatres (not necessarily in eye OTs) to decrease waiting time. This project highlights how a common sense approach to tweak the system process flow can lead to improved patient quality of care at no extra cost.

Acknowledgements: This pilot project was conducted as part of QI training sessions at our center under the guidance of teams from IHI and USAID ASSIST.

Contributors: PC and RT: Conceptualization of research and interpretation of data; DD, YD and DK: Data collection; RT, DD and DK: Manuscript preparation; All authors were involved in critically revising the manuscript and approving the final manuscript. They agree to be accountable for all aspects of this research.

Funding: None; Competing interests: None stated.

1. Gupta B, Agrawal P, D’souza N, Soni KD. Start time delays in operating room: Different perspectives.　Saudi J Anaesth. 2011;5:286-8.

2. Ahmad BA, Khairatul K, Farnaza A. An assessment of patient waiting and consultation time in a primary healthcare clinic. Malays Fam Physician. 2017;12:14-21.

3. Nicolay CR, Purkayastha S, Greenhalgh A, Benn J, Chaturvedi S, Phillips N, Darzi A. Systematic review of the application of quality improvement methodologies from the manufacturing industry to surgical healthcare. Br J Surg. 2012;99:324-35.