How much surplus capacity is required to maintain low waiting times?

Simulation as a tool to model potential workflow enhancements in radiotherapy treatment pathways - A systematic review

This systematic review aimed to synthesize and summarize the use of simulation of radiotherapy pathways. The objective was to establish the suitability of those simulations in modeling the potential introduction of processes and technologies to speed up radiotherapy pathways. A systematic literature search was carried out using PubMed and Scopus databases to evaluate the use of simulation in radiotherapy pathways. Full journal articles and conference proceedings were considered, and the search was limited to the English language only. To be eligible for inclusion, articles had to model multiple sequential processes in the radiotherapy pathway concurrently to demonstrate the suitability of simulation modeling in typical pathways. Papers solely modeling scheduling, capacity, or queuing strategies were excluded. In total, 151 potential studies were identified and screened to find 18 relevant studies in October 2022. Studies showed that various pathways could be modeled, including the entire pathway from referral to end of treatment or the constituent phases such as pre-treatment, treatment, or other subcomponents. The data required to generate models varied from study to study, but at least 3 months of data were needed. This review demonstrates that modeling and simulation of radiotherapy pathways are feasible and that model output matches real-world systems. Validated models give researchers confidence to modify models with potential workflow enhancements to assess their potential effect on real-world systems. It is recommended that researchers follow best practice guidelines when building models to ensure that they are fit for purpose and to enable decision makers to have confidence in their results.

The occurrence of adverse events in relation to time after registration for coronary artery bypass surgery: a population-based observational study

Background

Our objective was to evaluate the effect of delays on adverse events while waiting for coronary artery bypass grafting (CABG).

Methods

An observational study that prospectively followed patients from registration on a wait list to removal for planned surgery, death while waiting, or unplanned emergency surgery. The population-based registry provided data on 12,030 patients with a record of registration on a wait list for first-time isolated CABG surgery between 1992 and 2005.

Results

In total, 104 patients died and 382 patients underwent an emergency surgery before planned CABG. The death rate was 0.5 per 1000 patient-weeks in the semiurgent group and 0.6 per 1000 patient-weeks the nonurgent group, adjusted OR = 1.07 (95% confidence interval [CI] 0.69—1.65). The emergency surgery rate of 1.2 per 1000 patient-weeks in the nonurgent group was lower compared to 2.1 per 1000 patient-weeks in the semiurgent group (adjusted OR = 0.72, 95% CI 0.54–0.97). However, the nonurgent group had a greater cumulative incidence of preoperative death than the semiurgent group for almost all weeks on the wait list, adjusted OR = 1.92 (95% CI 1.25–2.95). The surgery rate was 1.2 per 1000 patient-weeks in the nonurgent group and 2.1 per 1000 patient-weeks in the semiurgent group, adjusted OR = 0.72 (95% CI 0.54–0.97). The cumulative incidence of emergency surgery before planned CABG was similar in the semiurgent and nonurgent groups, adjusted OR = 0.88, (95% CI 0.64–1.20).

Conclusion

Despite similar death rates in the semiurgent and nonurgent groups, the longer waiting times in the nonurgent group result in a greater cumulative incidence of death on the wait list compared to that in the semiurgent group. These longer waiting times also offset the lower rate of emergency surgery before planned admission in the nonurgent group so that the cumulative incidence of the emergency surgery was similar in both groups.

Modelling the throughput capacity of a single-accelerator multitreatment room proton therapy centre

OBJECTIVE

We describe a model for evaluating the throughput capacity of a single-accelerator multitreatment room proton therapy centre with the aims of (1) providing quantitative estimates of the throughput and waiting times and (2) providing insight into the sensitivity of the system to various physical parameters.

METHODS

A Monte Carlo approach was used to compute various statistics about the modelled centre, including the throughput capacity, fraction times for different groups of patients and beam waiting times. A method of quantifying the saturation level is also demonstrated.

RESULTS

Benchmarking against the MD Anderson Cancer Center showed good agreement between the modelled (140 ± 4 fractions per day) and reported (133 ± 35 fractions per day) throughputs. A sensitivity analysis of that system studied the impact of beam switch time, the number of treatment rooms, patient set-up times and the potential benefit of having a second accelerator. Finally, scenarios relevant to a potential UK facility were studied, finding that a centre with the same four-room, single-accelerator configuration as the MD Anderson Cancer Center but handling a more complex UK-type caseload would have a throughput reduced by approximately 19%, but still be capable of treating in excess of 100 fractions per 16-h treatment day.

CONCLUSIONS

The model provides a useful tool to aid in understanding the operating dynamics of a proton therapy facility, and for investigating potential scenarios for prospective centres.

ADVANCES IN KNOWLEDGE

The model helps to identify which technical specifications should be targeted for future improvements.

Reducing access times for an endoscopy department by an iterative combination of computer simulation and linear programming

To reduce the access times of an endoscopy department, we developed an iterative combination of Discrete Event simulation and Integer Linear Programming. We developed the method in the Endoscopy Department of the Academic Medical Center in Amsterdam and compared different scenarios to reduce the access times for the department. The results show that by a more effective allocation of the current capacity, all procedure types will meet their corresponding performance targets in contrast to the current situation. This improvement can be accomplished without requiring additional equipment and staff. Currently, our recommendations are implemented.

Reducing access times for an endoscopy department by an iterative combination of computer simulation and linear programming

To reduce the access times of an endoscopy department, we developed an iterative combination of Discrete Event simulation and Integer Linear Programming. We developed the method in the Endoscopy Department of the Academic Medical Center in Amsterdam and compared different scenarios to reduce the access times for the department. The results show that by a more effective allocation of the current capacity, all procedure types will meet their corresponding performance targets in contrast to the current situation. This improvement can be accomplished without requiring additional equipment and staff. Currently, our recommendations are implemented.

Does wait-list size at registration influence time to surgery? Analysis of a population-based cardiac surgery registry

OBJECTIVE

To determine whether the probability of undergoing coronary bypass surgery within a certain time was related to the number of patients on the wait list at registration for the operation in a publicly funded health system.

METHODS

A prospective cohort study comparing waiting times among patients registered on wait lists at the hospitals delivering adult cardiac surgery. For each calendar week, the list size, the number of new registrations, and the number of direct admissions immediately after angiography characterized the demand for surgery.

RESULTS

The length of delay in undergoing treatment was associated with list size at registration, with shorter times for shorter lists (log-rank test 1,198.3, p<.0001). When the list size at registration required clearance time over 1 week patients had 42 percent lower odds of undergoing surgery compared with lists with clearance time less than 1 week (odds ratio [OR] 0.58 percent, 95 percent, confidence interval [CI] 0.53-0.63), after adjustment for age, sex, comorbidity, period, and hospital. The weekly number of new registrations exceeding weekly service capacity had an independent effect toward longer service delays when the list size at registration required clearance time less than 1 week (OR 0.56 percent, 95 percent CI 0.45-0.71), but not for longer lists. Every time the operation was performed for a patient requiring surgery without registration on wait lists, the odds of surgery for listed patients were reduced by 6 percent (OR 0.94, CI 0.93-0.95).

CONCLUSION

For wait-listed patients, time to surgery depends on the list size at registration, the number of new registrations, as well as on the weekly number of patients who move immediately from angiography to coronary bypass surgery without being registered on a wait list. Hospital managers may use these findings to improve resource planning and to reduce uncertainty when providing advice on expected treatment delays.

Presumptive coding. A preliminary study of the aggregation of input diagnoses to determine their relevance to clinical governance and urological resourcing

OBJECTIVE

To determine the validity of a system for coding the reason for urological referral from primary care, using ICD10, and thus enable benchmarking of urological outpatient activity.

PATIENTS AND METHODS

Four studies were conducted: (i) A pilot study to aggregate information into a few input diagnosis codes (925 patients); (ii) Validation of the aggregated codes using input diagnoses from a second centre (928 patients); (iii) A prospective study by three urologists to determine the system's generic utility (918 patients); (iv) A study to aggregate the presumptive codes for 2771 patients to gain an insight into the case-mix of patients referred to a general urological service via the outpatient department.

RESULTS

The aggregation of input diagnoses from general practice referrals into 36 'presumptive codes' was possible and could be validated. Prospective coding, for 96% of eligible patients, was possible with < 1% of referral diagnoses not being codable. Further aggregation of the data for 2771 patients showed that 31% were referred with urological malignancy whilst 69% had symptoms suggesting benign urological disease.

CONCLUSIONS

This preliminary study of presumptive coding suggests that it is a feasible and valid method of recording the input diagnoses for patients presented to a urological service. The information it provides has relevance for the structuring, benchmarking, resourcing and manpower requirements of that service, essential components for clinical governance. It also has relevance to the prospective collection of patient data for research and audit.

Waiting for radiation therapy: does it matter?

The aim of this study was to determine the direct and indirect effects of prolonged waiting times for radiation therapy. We used the Medline, CancerNet and EMBASE databases to search the international research using the keywords radiotherapy, waiting times and delay. The negative effects of prolonged waiting times for radiation therapy can be broken down into direct and indirect effects. Direct effects include tumour control factors and patient factors. Indirect effects include changes in referral patterns and change in management of tumours. The precise effects of prolonged waiting times for radiation therapy are difficult to define. Evidence exists for some tumour sites, such as postoperative head and neck, small-cell lung cancer and high-grade cerebral gliomas, that tumour control might be adversely affected. The effect on other tumour sites is less established. Patient factors are likely to be consistent across all tumour types and indirect effects are hard to quantify.