Cost-Utility Analysis of Major System Change in Specialist Cancer Surgery in London, England, Using Linked Patient-Level Electronic Health Records and Difference-in-Differences Analysis

Resource Allocation Efficiency of Urban Medical and Health Financial Expenditure Under the Background of Employees' Health

Introduction

The study proposes a method based on difference-in-differences (DID) to improve the resource allocation efficiency of medical and health financial expenditure to better guarantee the health level of enterprise employees. The DEA method is utilized to measure the comprehensive technology, pure technology, and scale as the resource allocation efficiency values of urban medical and health financial expenditure.

Methods

The proposed method includes the use of DEA to measure the resource allocation efficiency values of urban medical and health financial expenditure. The benchmark regression model and DID model are used to analyze the impact effect, robustness, and parallel trend of the policy.

Results

The study shows that the proposed method effectively evaluates and analyzes the impact of medical comprehensive reform on the resource allocation efficiency of urban medical and health financial expenditure. The comprehensive medical reform can improve the comprehensive efficiency and scale efficiency of urban medical and health financial expenditure, leading to improved resource allocation efficiency of urban employees' medical and health financial expenditure. The results also indicate a significant positive effect on the time trend, which can have a long-term impact and effectiveness.

Discussion

The proposed method can provide useful insights into the resource allocation efficiency of medical and health financial expenditure, which can help improve the health level of enterprise employees. The study suggests that comprehensive medical reform can be an effective way to improve resource allocation efficiency and guarantee the health of employees in urban areas. Further research can be conducted to evaluate the impact of medical reform on other aspects of health care, such as quality and accessibility.

Cost-Utility Analysis of Major System Change in Specialist Cancer Surgery in London, England, Using Linked Patient-Level Electronic Health Records and Difference-in-Differences Analysis

BACKGROUND

Studies have shown that centralising surgical treatment for some cancers can improve patient outcomes, but there is limited evidence of the impact on costs or health-related quality of life.

OBJECTIVES

We report the results of a cost-utility analysis of the RESPECT-21 study using difference-in-differences, which investigated the reconfiguration of specialist surgery services for four cancers in an area of London, compared to the Rest of England (ROE).

METHODS

Electronic health records data were obtained from the National Cancer Registration and Analysis Service for patients diagnosed with one of the four cancers of interest between 2012 and 2017. The analysis for each tumour type used a short-term decision tree followed by a 10-year Markov model with 6-monthly cycles. Costs were calculated by applying National Health Service (NHS) Reference Costs to patient-level hospital resource use and supplemented with published data. Cancer-specific preference-based health-related quality-of-life values were obtained from the literature to calculate quality-adjusted life-years (QALYs). Total costs and QALYs were calculated before and after the reconfiguration, in the London Cancer (LC) area and in ROE, and probabilistic sensitivity analysis was performed to illustrate the uncertainty in the results.

RESULTS

At a threshold of £30,000/QALY gained, LC reconfiguration of prostate cancer surgery services had a 79% probability of having been cost-effective compared to non-reconfigured services using difference-in-differences. The oesophago-gastric, bladder and renal reconfigurations had probabilities of 62%, 49% and 12%, respectively, of being cost-effective at the same threshold. Costs and QALYs per surgical patient increased over time for all cancers across both regions to varying degrees. Bladder cancer surgery had the smallest patient numbers and changes in costs, and QALYs were not significant. The largest improvement in outcomes was in renal cancer surgery in ROE, making the relative renal improvements in LC appear modest, and the probability of the LC reconfiguration having been cost-effective low.

CONCLUSIONS

Prostate cancer reconfigurations had the highest probability of being cost-effective. It is not clear, however, whether the prostate results can be considered in isolation, given the reconfigurations occurred simultaneously with other system changes, and healthcare delivery in the NHS is highly networked and collaborative. Routine collection of quality-of-life measures such as the EQ-5D-5L would have improved the analysis.

The cost-per-QALY threshold in England: Identifying structural uncertainty in the estimates

Introduction

There are increasing numbers of estimates of opportunity cost to inform the setting of thresholds as ceiling cost-per-quality-adjusted life year (QALY) ratios. To understand their ability to inform policy making, we need to understand the degree of uncertainty surrounding these estimates. In particular, do estimates provide sufficient certainty that the current policy "rules" or "benchmarks" need revision? Does the degree of uncertainty around those estimates mean that further evidence generation is required?

Methods

We analyse uncertainty and methods from three papers that focus on the use of data from the NHS in England to estimate opportunity cost. All estimate the impact of expenditure on mortality in cross-sectional regression analyses and then translate the mortality elasticities into cost-per-QALY thresholds using the same assumptions. All three discuss structural uncertainty around the regression analysis, and report parameter uncertainty derived from their estimated standard errors. However, only the initial, seminal, paper explores the structural uncertainty involved in moving from the regression analysis to a threshold. We discuss the elements of structural uncertainty arising from the assumptions that underpin the translation of elasticities to thresholds and seek to quantify the importance of some of the effects.

Results

We find several sets of plausible structural assumptions that would place the threshold estimates from these studies within the current National Institute for Health and Care Excellence (NICE) range of £20,000 to £30,000 per QALY. Heterogeneity, an additional source of uncertainty from variability, is also discussed and reported.

Discussion

Lastly, we discuss how decision uncertainty around the threshold could be reduced, setting out what sort of additional research is required, notably in improving estimates of disease burden and of the impact of health expenditure on quality of life. Given the likely value to policy makers of this research it should be a priority for health system research funding.