Socioeconomic inequalities in waiting times for breast cancer surgery.

Prompt access to cancer care is a policy priority in several OECD countries, because delayed access can exacerbate deleterious health outcomes. Access to care based on need remains a key pillar of publicly-funded health systems. This study tests for the presence of inequalities in waiting times by socioeconomic status for patients receiving breast cancer surgery (mastectomy or breast conserving surgery) in England using the Hospital Episode Statistics. We investigate separately the pre-COVID-19 period (April 2015-January 2020), and the COVID-19 period (February 2020-March 2022). We use linear regression models to study the association between waiting times and income deprivation measured at the patient's area of residence. We control for demographic factors, type and number of comorbidities, past emergency admissions and Healthcare Resource Groups, and supply-level factors through hospital fixed effects. In the pre-COVID-19 period, we do not find statistically significant associations between income deprivation in the patient's area of residence and waiting times for surgery. In the COVID-19 period, we find that patients living in the most deprived areas have longer waiting times by 0.7 days (given a mean waiting time of 20.6 days).

Mixed Methods EvAluation of the high-volume low-complexity Surgical hUb pRogrammE (MEASURE): a mixed methods study protocol.

INTRODUCTION: The waiting list for elective surgery in England recently reached over 7.8 million people and waiting time targets have been missed since 2010. The high-volume low complexity (HVLC) surgical hubs programme aims to tackle the backlog of patients awaiting elective surgery treatment in England. This study will evaluate the impact of HVLC surgical hubs on productivity, patient care and the workforce. METHODS AND ANALYSIS: This 4-year project consists of six interlinked work packages (WPs) and is informed by the Consolidated Framework for Implementation Research. WP1: Mapping current and future HVLC provision in England through document analysis, quantitative data sets (eg, Hospital Episodes Statistics) and interviews with national service leaders. WP2: Exploring the effects of HVLC hubs on key performance outcomes, primarily the volume of low-complexity patients treated, using quasi-experimental methods. WP3: Exploring the impact and implementation of HVLC hubs on patients, health professionals and the local NHS through approximately nine longitudinal, multimethod qualitative case studies. WP4: Assessing the productivity of HVLC surgical hubs using the Centre for Health Economics NHS productivity measure and Lord Carter's operational productivity measure. WP5: Conducting a mixed-methods appraisal will assess the influence of HVLC surgical hubs on the workforce using: qualitative data (WP3) and quantitative data (eg, National Health Service (NHS) England's workforce statistics and intelligence from WP2). WP6: Analysing the costs and consequences of HVLC surgical hubs will assess their achievements in relation to their resource use to establish value for money. A patient and public involvement group will contribute to the study design and materials. ETHICS AND DISSEMINATION: The study has been approved by the East Midlands-Nottingham Research Ethics Committee 23/EM/0231. Participants will provide informed consent for qualitative study components. Dissemination plans include multiple academic and non-academic outputs (eg, Peer-reviewed journals, conferences, social media) and a continuous, feedback-loop of findings to key stakeholders (eg, NHS England) to influence policy development. TRIAL REGISTRATION: Research registry: Researchregistry9364 (https://www.researchregistry.com/browse-the-registry%23home/registrationdetails/64cb6c795cbef8002a46f115/).

COVID-19, deaths at home and end-of-life cancer care.

During the COVID-19 pandemic there was a period of high excess deaths from cancer at home as opposed to in hospitals or in care homes. In this paper we aim to explore whether healthcare utilisation trajectories of cancer patients in the final months of life during the COVID-19 pandemic reveal any potential unmet healthcare need. We use English hospital records linked to data on all deaths in and out of hospital which identifies the cause and location of death. Our analysis shows that during the periods of peak COVID-19 caseload, patients dying of cancer experienced up to 42% less hospital treatment in their final month of life compared to historical controls. We find reductions in end-of-life hospital care for cancer patients dying in hospitals, care homes/hospices and at home, however the effect is amplified by the shift to more patients dying at home. Through the first year of the pandemic in England, we estimate the number of inpatient bed-days for end-of-life cancer patients in their final month reduced by approximately 282,282, or 25%. For outpatient appointments in the final month of life we find a reduction in face-to-face appointments and an increase in remote appointments which persists through the pandemic year and is not confined only to the periods of peak COVID-19 caseload. Our results suggest reductions in care provision during the COVID-19 pandemic may have led to unmet need, and future emergency reorganisations of health care systems must ensure consistent care provision for vulnerable groups such as cancer patients.

The effect of financial incentives on the quality of health care provided by primary care physicians.

BACKGROUND: The use of blended payment schemes in primary care, including the use of financial incentives to directly reward 'performance' and 'quality' is increasing in a number of countries. There are many examples in the US, and the Quality and Outcomes Framework (QoF) for general practitioners (GPs) in the UK is an example of a major system-wide reform. Despite the popularity of these schemes, there is currently little rigorous evidence of their success in improving the quality of primary health care, or of whether such an approach is cost-effective relative to other ways to improve the quality of care. OBJECTIVES: The aim of this review is to examine the effect of changes in the method and level of payment on the quality of care provided by primary care physicians (PCPs) and to identify:i) the different types of financial incentives that have improved quality;ii) the characteristics of patient populations for whom quality of care has been improved by financial incentives; andiii) the characteristics of PCPs who have responded to financial incentives. SEARCH STRATEGY: We searched the Cochrane Effective Practice and Organisation of Care (EPOC) Trials Register, Cochrane Central Register of Controlled Trials (CENTRAL) and Cochrane Database of Systematic Reviews (CDSR) (The Cochrane Library), MEDLINE, HealthSTAR, EMBASE, CINAHL, PsychLIT, and ECONLIT. Searches of Internet-based economics and health economics working paper collections were also conducted. Finally, studies were identified through the reference lists of retrieved articles, websites of key organisations, and from direct contact with key authors in the field. Articles were included if they were published from 2000 to August 2009. SELECTION CRITERIA: Randomised controlled trials (RCT), controlled before and after studies (CBA), and interrupted time series analyses (ITS) evaluating the impact of different financial interventions on the quality of care delivered by primary healthcare physicians (PCPs). Quality of care was defined as patient reported outcome measures, clinical behaviours, and intermediate clinical and physiological measures. DATA COLLECTION AND ANALYSIS: Two review authors independently extracted data and assessed study quality, in consultation with two other review authors where there was disagreement. For each included study, we reported the estimated effect sizes and confidence intervals. MAIN RESULTS: Seven studies were included in this review. Three of the studies evaluated single-threshold target payments, one examined a fixed fee per patient achieving a specified outcome, one study evaluated payments based on the relative ranking of medical groups' performance (tournament-based pay), one study examined a mix of tournament-based pay and threshold payments, and one study evaluated changing from a blended payments scheme to salaried payment. Three cluster RCTs examined smoking cessation; one CBA examined patients' assessment of the quality of care; one CBA examined cervical screening, mammography screening, and HbA1c; one ITS focused on four outcomes in diabetes; and one controlled ITS (a difference-in-difference design) examined cervical screening, mammography screening, HbA1c, childhood immunisation, chlamydia screening, and appropriate asthma medication. Six of the seven studies showed positive but modest effects on quality of care for some primary outcome measures, but not all. One study found no effect on quality of care. Poor study design led to substantial risk of bias in most studies. In particular, none of the studies addressed issues of selection bias as a result of the ability of primary care physicians to select into or out of the incentive scheme or health plan. AUTHORS' CONCLUSIONS: The use of financial incentives to reward PCPs for improving the quality of primary healthcare services is growing. However, there is insufficient evidence to support or not support the use of financial incentives to improve the quality of primary health care. Implementation should proceed with caution and incentive schemes should be more carefully designed before implementation. In addition to basing incentive design more on theory, there is a large literature discussing experiences with these schemes that can be used to draw out a number of lessons that can be learned and that could be used to influence or modify the design of incentive schemes. More rigorous study designs need to be used to account for the selection of physicians into incentive schemes. The use of instrumental variable techniques should be considered to assist with the identification of treatment effects in the presence of selection bias and other sources of unobserved heterogeneity. In randomised trials, care must be taken in using the correct unit of analysis and more attention should be paid to blinding. Studies should also examine the potential unintended consequences of incentive schemes by having a stronger theoretical basis, including a broader range of outcomes, and conducting more extensive subgroup analysis. Studies should more consistently describe i) the type of payment scheme at baseline or in the control group, ii) how payments to medical groups were used and distributed within the groups, and iii) the size of the new payments as a percentage of total revenue. Further research comparing the relative costs and effects of financial incentives with other behaviour change interventions is also required.