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This paper sets out to investigate whether demand for gynaecological theatre time could be described in terms of the time required to undertake elective operations booked for surgery, and so help match the capacity to this.

A questionnaire assessed the estimates for total operation time for seven common operations, sent to surgeons, anaesthetists and nursing staff in one tertiary referral and one district general hospital (total 49 staff; response rate 58 per cent), and estimates were obtained from theatre computer logs. Average timings for each operation were then applied to cases added from clinics to the waiting list at the district general, to yield the mean demand for elective surgery, and were also applied to emergencies to estimate emergency workload. Finally these demand estimates were compared with the theatre capacity available.

The paper found no difference between the estimates of the three staff groups or between these and the theatre logs (p=0.669), nor did it find that estimates differed between the two centers (p=0.628). Including emergencies, the mean (95 per cent confidence intervals) demand at the district general was 2,438 (1,952‐2,924) min/week.

Although the paper modelled the variation in demand using the relevant variation in operation times, any additional variation caused by differences in booking rates from clinics over time was not nodelled. The minimum period over which data should be collected was not established.

The paper finds that the existing capacity of 1,680 min/week did not match these needs and, unless it was increased, a rise in waiting lists was predictable.

The paper concludes that time estimates for scheduled operations can be better used to assess the need for surgical operating capacity than current measures of demand or capacity.

Anecdotally, many hospitals experience shortfalls in anaesthetic consultant staffing. This paper aims to investigate whether these subjective experiences are confirmed objectively.

The paper hypothesises that a simple model that estimated service delivery capability using consultant entitlements to annual and other types of leave would not (null hypothesis) accurately predict the magnitude of any shortfall that existed. It also hypothesises that excessive leave‐taking was an important cause of any shortfall. A comparison is made between the model predictions for total leave taken and service delivery with results from a real data set from a large university teaching hospital's department of anaesthetics.

The model prediction for leave (median total 45 days absence in a year per consultant, range (30‐59)) closely matched the reality (median 41 days (tenth‐ninetieth deciles 30‐69)). Consequently, both model predictions and the real data for annual elective service delivery agreed: median 228 sessions (193‐266) vs 232 (183‐266) per consultant respectively. Taking into account likely service delivery by trainees (2,304‐4,140 elective sessions in total annually) the predicted shortfall of 2,220 sessions was very close to the true elective service shortfall of 2,148 sessions for the department as a whole over the year.

Rejecting the null hypothesis, it is concluded that a simple model that estimates elective service delivery using leave entitlements as the main factor can accurately predict actual service capability for a department. There is no evidence that excessive leave‐taking occurs.

The paper computes an estimate that 2.2‐2.6 consultants per functional operating theatre are necessary to ensure that staffing matches the elective workload.