Simulating the impact of centralization of prostate cancer surgery services on travel burden and equity in the English National Health Service: A national population based model for health service re‐design

Abstract

Introduction:There is limited evidence on the impact of centralization of cancer treatment services on patient travel burden and access to treatment. Using prostate cancer surgery as an example, this national study analysis aims to simulate the effect of different centralization scenarios on the number of center closures, patient travel times, and equity in access. Methods:We used patient-level data on all men (n = 19,256) undergoing radical prostatectomy in the English National Health Service between January 1, 2010 and December 31, 2014, and considered three scenarios for centralization of prostate cancer surgery services A: procedure volume, B: availability of specialized services, and C: optimization of capacity. The probability of patients travelling to each of the remaining centers in the choice set was predicted using a conditional logit model, based on preferences revealed through actual hospital selections. Multivariable linear regression analysed the impact on travel time according to patient characteristics. Results: Scenarios A, B, and C resulted in the closure of 28, 24, and 37 of the 65 radical prostatectomy centers, respectively, affecting 3993 (21%), 5763 (30%), and 7896 (41%) of the men in the study. Despite similar numbers of center closures the expected average increase on travel time was very different for scenario B (+15 minutes) and A (+28 minutes). A distance minimization approach, assigning patients to their next nearest center, with patient preferences not considered, estimated a lower impact on travel burden in all scenarios. The additional travel burden on older, sicker, less affluent patients was evident, but where significant, the absolute difference was very small. Conclusion:The study provides an innovative simulation approach using national patient-level datasets, patient preferences based on actual hospital selections, and personal characteristics to inform health service planning. With this approach, we demonstrated for prostate cancer surgery that three different centralization scenarios

Health service planning to assess the expected impact of centralising specialist cancer services on travel times, equity, and outcomes: a national population-based modelling study

“…The cancer service planning tool can be used for different types of common cancers or modalities of treatment, and has been used for considering the travel burden and equity implications of the centralisation of prostate cancer surgery. 9 However, the model will be less applicable to very rare cancer types for which few patients are treated annually or where the service is already highly centralised. It could also be applied to the planning of the location of advanced treatment modalities (eg, the location of proton therapy, MRI-guided linear accelerator, and chimeric antigen receptor [CAR] T-cell units).…”

“…In our model, patients affected by each centralisation scenario (ie, the hospital where they are treated is planned to close) were reallocated to alternative hospitals by use of two main methods. 9 The first approach reallocated patients affected by the closure to their nearest available hospital following its closure, and was termed the distance minimisation approach. Expected changes in travel time were estimated as the difference between travel times to the actual centre used before centralisation and the nearest available hospital following its closure.…”

“…[4][5][6][7][8] This fine balance between travel burden, equitable access to services, and outcomes means that it is important to estimate the expected impact of service centralisation before implementation. [7][8][9][10] An established empirical template to define the optimal configuration of cancer services is currently lacking. Without such health service planning tools, decisions about the closure of cancer centres might instead be driven by political reasons rather than by a transparent assessment of the expected consequences of central isation of services for patients and providers.…”

What Really Matters for Cancer Care – Health Systems Strengthening or Technological Innovation?

“…Evidence for a volumeeoutcome relationship exists for some cancer surgical procedures, but there is little evidence in radiation and systemic therapies and there is very limited research to support how and where services should be centralised within a health system to improve quality and prevent the inequities in access that have been observed [55,56]. Clearly understanding this trade-off in a contextspecific manner will ensure that the organisation of services will protect the most vulnerable and act to reduce access disparities [57].…”

Influence of travel burden on tumor classification and survival of head and neck cancer patients

“…Centralization of the healthcare system supports the formation of such high-volume centers, but which also implicates that the mean travel distance of associated patients is inevitably rising [11,12]. Older and sicker patients, when living in rural areas, are consequently affected to a greater extent [12,13]. These circumstances may result in more advanced disease status at diagnosis and may interfere with optimal treatment, compliance, and follow-up care [2,14].…”