Level of attendance at the English National Health Service Diabetes Prevention Programme and risk of progression to type 2 diabetes.

BACKGROUND: We evaluated the dose-response relationship between the level of attendance at the English National Health Service Diabetes Prevention Programme (DPP) and risk of progression to type 2 diabetes amongst individuals participating in the programme. METHODS: We linked data on DPP attendance for 51,803 individuals that were referred to the programme between 1st June 2016 and 31st March 2018 and attended at least one programme session, with primary care records of type 2 diabetes diagnoses from the National Diabetes Audit up to 31st March 2020. Weibull survival regressions were used to estimate the association between the number of programme sessions attended and risk of progression to type 2 diabetes. RESULTS: Risk of developing type 2 diabetes declined significantly for individuals attending seven of the 13 programme sessions and continued to decline further up to 12 sessions. Attending the full 13 sessions was associated with a 45.5% lower risk (HR: 0.545 95% CI: 0.455 to 0.652). Compared to individuals that only partially attended the programme, attendance at 60% or more of the sessions was associated with a 30.7% lower risk of type 2 diabetes (HR: 0.693 95% CI: 0.645 to 0.745). CONCLUSIONS: Reducing the risk of progression to type 2 diabetes through diabetes prevention programmes requires a minimum attendance level at seven of the 13 programme sessions (54%). Retaining participants beyond this minimum level yields further benefits in diabetes risk reduction. Commissioners may wish to consider altering provider payment schedules to incentivise higher retention levels beyond 60% of programme sessions.

How do hospitals respond to payment unbundling for diagnostic imaging of suspected cancer patients?

Payments for some diagnostic scans undertaken in outpatient settings were unbundled from Diagnosis Related Group based payments in England in April 2013 to address under-provision. Unbundled scans attracted additional payments of between £45 and £748 directly following the reform. We examined the effect on utilization of these scans for patients with suspected cancer. We also explored whether any detected effects represented real increases in use of scans or better coding of activity. We applied difference-in-differences regression to patient-level data from Hospital Episodes Statistics for 180 NHS hospital Trusts in England, between April 2010 and March 2018. We also explored heterogeneity in recorded use of scans before and after the unbundling at hospital Trust-level. Use of scans increased by 0.137 scans per patient following unbundling, a 134% relative increase. This increased annual national provider payments by £79.2 million. Over 15% of scans recorded after the unbundling were at providers that previously recorded no scans, suggesting some of the observed increase in activity reflected previous under-coding. Hospitals recorded substantial increases in diagnostic imaging for suspected cancer in response to payment unbundling. Results suggest that the reform also encouraged improvements in recording, so the real increase in testing is likely lower than detected.

Age- and deprivation-related inequalities in identification of people at high risk of type 2 diabetes in England.

BACKGROUND: Early detection of intermediate hyperglycaemia, otherwise known as non-diabetic hyperglycaemia (NDH) is crucial to identify people at high risk of developing type 2 diabetes mellitus (T2DM) who could benefit from preventative interventions. Failure to identify NDH may also increase the risks of T2DM-related complications at the time of T2DM diagnosis. We investigate sociodemographic inequalities in identification of NDH in England. METHODS: We used nationwide data from the English National Health Service (NHS) National Diabetes Audit, which includes all people who were newly identified with NDH (N = 469,910) or diagnosed with T2DM (N = 222,795) between 1st April 2019 and 31st March 2020. We used regression models to explore inequalities in the under identification of NDH by area-level deprivation and age group. RESULTS: Of those with a new T2DM diagnosis, 67.3% had no previous record of NDH. The odds of no previous NDH being recorded were higher amongst people living in more deprived areas (Odds ratio (OR) 1.15 (95% confidence intervals (CI) [1.12, 1.19]) most deprived (Q1) compared to least deprived (Q5) quintile) and younger individuals (OR 4.02 (95% CI [3.79, 4.27] under 35s compared to age 75-84)). Deprivation-related inequalities persisted after stratification by age group, with the largest inequalities amongst middle and older age groups. People living in more deprived areas and younger people also had shorter recorded NDH duration before progression to T2DM, and higher T2DM severity at the time of diagnosis. CONCLUSIONS: There is under identification of NDH relative to diagnosis of T2DM amongst people living in more deprived areas and particularly amongst younger people, resulting in missed opportunities for targeted T2DM prevention efforts and potentially contributing to inequalities in T2DM prevalence and severity. More active NDH case-finding amongst these groups may be an important first step in helping to reduce inequalities in T2DM.

Referral to the NHS Diabetes Prevention Programme and conversion from nondiabetic hyperglycaemia to type 2 diabetes mellitus in England: A matched cohort analysis.

BACKGROUND: The NHS Diabetes Prevention Programme (NDPP) is a behaviour change programme for adults who are at risk of developing type 2 diabetes mellitus (T2DM): people with raised blood glucose levels, but not in the diabetic range, diagnosed with nondiabetic hyperglycaemia (NDH). We examined the association between referral to the programme and reducing conversion of NDH to T2DM. METHODS AND FINDINGS: Cohort study of patients attending primary care in England using clinical Practice Research Datalink data from 1 April 2016 (NDPP introduction) to 31 March 2020 was used. To minimise confounding, we matched patients referred to the programme in referring practices to patients in nonreferring practices. Patients were matched based on age (≥3 years), sex, and ≥365 days of NDH diagnosis. Random-effects parametric survival models evaluated the intervention, controlling for numerous covariates. Our primary analysis was selected a priori: complete case analysis, 1-to-1 practice matching, up to 5 controls sampled with replacement. Various sensitivity analyses were conducted, including multiple imputation approaches. Analysis was adjusted for age (at index date), sex, time from NDH diagnosis to index date, BMI, HbA1c, total serum cholesterol, systolic blood pressure, diastolic blood pressure, prescription of metformin, smoking status, socioeconomic status, a diagnosis of depression, and comorbidities. A total of 18,470 patients referred to NDPP were matched to 51,331 patients not referred to NDPP in the main analysis. Mean follow-up from referral was 482.0 (SD = 317.3) and 472.4 (SD = 309.1) days, for referred to NDPP and not referred to NDPP, respectively. Baseline characteristics in the 2 groups were similar, except referred to NDPP were more likely to have higher BMI and be ever-smokers. The adjusted HR for referred to NDPP, compared to not referred to NDPP, was 0.80 (95% CI: 0.73 to 0.87) (p < 0.001). The probability of not converting to T2DM at 36 months since referral was 87.3% (95% CI: 86.5% to 88.2%) for referred to NDPP and 84.6% (95% CI: 83.9% to 85.4%) for not referred to NDPP. Associations were broadly consistent in the sensitivity analyses, but often smaller in magnitude. As this is an observational study, we cannot conclusively address causality. Other limitations include the inclusion of controls from the other 3 UK countries, data not allowing the evaluation of the association between attendance (rather than referral) and conversion. CONCLUSIONS: The NDPP was associated with reduced conversion rates from NDH to T2DM. Although we observed smaller associations with risk reduction, compared to what has been observed in RCTs, this is unsurprising since we examined the impact of referral, rather than attendance or completion of the intervention.

The effects of structure, process and outcome incentives on primary care referrals to a national prevention programme.

Despite widespread use, evidence is sparse on whether financial incentives in healthcare should be linked to structure, process or outcome. We examine the impact of different incentive types on the quantity and effectiveness of referrals made by general practices to a new national prevention programme in England. We measured effectiveness by the number of referrals resulting in programme attendance. We surveyed local commissioners about their use of financial incentives and linked this information to numbers of programme referrals and attendances from 5170 general practices between April 2016 and March 2018. We used multivariate probit regressions to identify commissioner characteristics associated with the use of different incentive types and negative binomial regressions to estimate their effect on practice rates of referral and attendance. Financial incentives were offered by commissioners in the majority of areas (89%), with 38% using structure incentives, 69% using process incentives and 22% using outcome incentives. Compared to practices without financial incentives, neither structure nor process incentives were associated with statistically significant increases in referrals or attendances, but outcome incentives were associated with 84% more referrals and 93% more attendances. Outcome incentives were the only form of pay-for-performance to stimulate more participation in this national disease prevention programme.

Estimating (quality-adjusted) life-year losses associated with deaths: With application to COVID-19.

Many epidemiological models of the COVID-19 pandemic have focused on preventing deaths. Questions have been raised as to the frailty of those succumbing to the COVID-19 infection. In this paper we employ standard life table methods to illustrate how the potential quality-adjusted life-year (QALY) losses associated with COVID-19 fatalities could be estimated, while adjusting for comorbidities in terms of impact on both mortality and quality of life. Contrary to some suggestions in the media, we find that even relatively elderly patients with high levels of comorbidity can still lose substantial life years and QALYs. The simplicity of the method facilitates straightforward international comparisons as the pandemic evolves. In particular, we compare five different countries and show that differences in the average QALY losses for each COVID-19 fatality is driven mainly by differing age distributions for those dying of the disease.

The older prisoner health and social care assessment and plan (OHSCAP) versus treatment as usual: a randomised controlled trial.

BACKGROUND: Older people are the fastest-growing demographic group among prisoners in England and Wales and they have complex health and social care needs. Their care is frequently ad hoc and uncoordinated. No previous research has explored how to identify and appropriately address the needs of older adults in prison. We hypothesised that the Older prisoner Health and Social Care Assessment and Plan (OHSCAP) would significantly increase the proportion of met health and social care needs 3 months after prison entry, compared to treatment as usual (TAU). METHODS: The study was a parallel randomised controlled trial (RCT) recruiting male prisoners aged 50 and over from 10 prisons in northern England. Participants received the OHSCAP or TAU. A clinical trials unit used minimisation with a random element as the allocation procedure. Data analysis was conducted blind to allocation status. The intervention group had their needs assessed using the OHSCAP tool and care plans were devised; processes that lasted approximately 30 min in total per prisoner. TAU included the standard prison health assessment and care. The intention to treat principle was followed. The trial was registered with the UK Clinical Research Network Portfolio (ISRCTN ID: 11841493) and was closed on 30 November 2016. RESULTS: Data were collected between 28 January 2014 and 06 April 2016. Two hundred and forty nine older prisoners were assigned TAU of which 32 transferred prison; 12 were released; 2 withdrew and 1 was deemed unsafe to interview. Two hundred and fifty three 3 prisoners were assigned the OHSCAP of which 33 transferred prison; 11 were released; 6 withdrew and 1 was deemed unsafe to interview. Consequently, data from 202 participants were analysed in each of the two groups. There were no significant differences in the number of unmet needs as measured by the Camberwell Assessment of Needs - Forensic Short Version (CANFOR-S). The mean number of unmet needs for the OHSCAP group at follow-up was 2.03 (SD = 2.07) and 2.06 (SD = 2.11) for the TAU group (mean difference = 0.088; 95% CI - 0.276 to 0.449, p = 0.621). No adverse events were reported. CONCLUSION: The OHSCAP was fundamentally not implemented as planned, partly due to the national prison staffing crisis that ensued during the study period. Therefore, those receiving the OHSCAP did not experience improved outcomes compared to those who received TAU. TRIAL REGISTRATION: Current Controlled Trials: ISRCTN11841493 , 25/10/2012.

How do hospitals respond to price changes in emergency departments?

Little is known about how prospective provider payment affects the provision of services led by unpredictable demand. We investigate hospital responses to a 32% increase in price for two treatments in emergency departments in England in April 2011 using data on 11,532,304 attendances (79 hospitals) between 2009/2010 and 2013/2014. We compare changes in the volumes of these two treatments to a treatment not attracting additional reimbursement using a difference-in-differences framework. Additional reimbursement led to 76% and 152% increases in the volumes of the two incentivised treatments. Hospitals received an additional £64.4 M between April 2011 and March 2014 for providing these treatments, of which 40% (£25.9 M) was attributable to the unanticipated hospital response to the price increase. We use time in treatment to distinguish real increases in treatment from reductions in undercoding or increases in upcoding. The association between the recorded receipt of these treatments and time spent in treatment was the same before and after the price increase, and there was no association between hospital-specific increases in recorded treatment volumes and changes in treatment times. The persistence of the treatment time increment suggests the increase in recorded treatment was a real increase in provision of treatments.

Implementing a national diabetes prevention programme in England: lessons learned.

BACKGROUND: Type 2 diabetes mellitus is preventable through lifestyle intervention. Diabetes prevention programmes (DPPs) aim to deliver prevention-based behaviour change interventions to reduce incidence. Such programmes vary from usual primary care in terms of where, how, and by whom they are delivered. Implementation is therefore likely to face new commissioning, incentive and delivery challenges. We report on the implementation of a national DPP in NHS England, and identify lessons learned in addressing the implementation challenges. METHODS: In 2017/18, we conducted 20 semi-structured telephone interviews covering 16 sampled case sites with the designated lead(s) responsible for local implementation of the programme. Interviews explored the process of implementation, including organisation of the programme, expectations and attitudes to the programme, funding, target populations and referral and clinical pathways. We drew on constant comparative methods to analyse the data and generate over-arching themes. We complemented our qualitative data with a survey focused on variation in the financial incentives used across sites to ensure usual primary care services recruited patients to new providers. RESULTS: We identified five over-arching areas of learning for implementing this large-scale programme: 1) managing new providers; 2) promoting awareness of services; 3) recruiting patients; 4) incentive payments; and 5) mechanisms for sharing learning. In general, tensions appeared to be caused by a lack of clear roles/responsibilities between hierarchical actors, and lack of communication. Both local sites and the national NHS coordination team gained experience through learning by doing. Initial tensions with roles and expectations have been worked out during implementation. CONCLUSIONS: Implementing a national disease prevention programme is a major task, and one that will be increasingly faced by health systems globally as they aim to adjust to demand pressures. We provide practical learning opportunities for the wider uptake and sustainability of prevention programmes. Future implementers might wish to define clear responsibilities for each actor prior to implementation, ensure early engagement with new providers, offer mechanisms/forums for sharing learning, generate evidence and provide advice on incentive payments, and prioritise public and professional awareness of the programme.

Is telephone health coaching a useful population health strategy for supporting older people with multimorbidity? An evaluation of reach, effectiveness and cost-effectiveness using a 'trial within a cohort'.

BACKGROUND: Innovative ways of delivering care are needed to improve outcomes for older people with multimorbidity. Health coaching involves 'a regular series of phone calls between patient and health professional to provide support and encouragement to promote healthy behaviours'. This intervention is promising, but evidence is insufficient to support a wider role in multimorbidity care. We evaluated health coaching in older people with multimorbidity. METHODS: We used the innovative 'Trials within Cohorts' design. A cohort was recruited, and a trial was conducted using a 'patient-centred' consent model. A randomly selected group within the cohort were offered the intervention and were analysed as the intervention group whether they accepted the offer or not. The intervention sought to improve the skills of patients with multimorbidity to deal with a range of long-term conditions, through health coaching, social prescribing and low-intensity support for low mood. RESULTS: We recruited 4377 older people, and 1306 met the eligibility criteria (two or more long-term conditions and moderate 'patient activation'). We selected 504 for health coaching, and 41% consented. More than 80% of consenters received the defined 'dose' of 4+ sessions. In an intention-to-treat analysis, those selected for health coaching did not improve on any outcome (patient activation, quality of life, depression or self-care) compared to usual care. We examined health care utilisation using hospital administrative and self-report data. Patients selected for health coaching demonstrated lower levels of emergency care use, but an increase in the use of planned services and higher overall costs, as well as a quality-adjusted life year (QALY) gain. The incremental cost per QALY was £8049, with a 70-79% probability of being cost-effective at conventional levels of willingness to pay. CONCLUSIONS: Health coaching did not lead to significant benefits on the primary measures of patient-reported outcome. This is likely related to relatively low levels of uptake amongst those selected for the intervention. Demonstrating effectiveness in this design is challenging, as it estimates the effect of being selected for treatment, regardless of whether treatment is adopted. We argue that the treatment effect estimated is appropriate for health coaching, a proactive model relevant to many patients in the community, not just those seeking care. TRIAL REGISTRATION: International Standard Randomised Controlled Trial Number ( ISRCTN12286422 ).

Elevated mortality among weekend hospital admissions is not associated with adoption of seven day clinical standards.

INTRODUCTION: Patients admitted to hospital in an emergency at weekends have been found to experience higher mortality rates than those admitted during the week. The National Health Service (NHS) in England has introduced four priority clinical standards for emergency hospital care with the objective of reducing deaths associated with this 'weekend effect'. This study aimed to determine whether adoption of these clinical standards is associated with the extent to which weekend mortality is elevated. METHODS: We used publicly available data on performance against the four priority clinical standards in 2015 and estimates of Trusts' weekend effects between 2013/2014 and 2015/2016 for 123 NHS Trusts in England. We examined whether adoption of the priority clinical standards was associated with the extent to which weekend mortality was elevated, and changes over a 3 year period in the extent to which mortality was elevated. RESULTS: Levels of achievement of two of the four clinical standards (ongoing review and access to diagnostic services) had small positive associations with the magnitude of the weekend effect in 2015/2016. Levels of achievement of the remaining two standards (time to first consultant review and access to consultant directed interventions) had small negative associations with the magnitude of the weekend effect in 2015/2016. No association was statistically significant. The same pattern was observed in the associations between achievement of the standards and changes in the magnitudes of the weekend effect between 2013/2014 and 2015/2016. DISCUSSION: We found no association between Trusts' performance against any of the four standards and the current magnitude of their weekend effects, or the change in their weekend effects over the past 3 years. These findings cast doubt on whether adoption of seven day clinical standards in the delivery of emergency hospital services will be successful in reducing the weekend effect.

Long-term effect of hospital pay for performance on mortality in England.

BACKGROUND: A pay-for-performance program based on the Hospital Quality Incentive Demonstration was introduced in all hospitals in the northwest region of England in 2008 and was associated with a short-term (18-month) reduction in mortality. We analyzed the long-term effects of this program, called Advancing Quality. METHODS: We analyzed 30-day in-hospital mortality among 1,825,518 hospital admissions for eight conditions, three of which were covered by the financial-incentive program. The hospitals studied included the 24 hospitals in the northwest region that were participating in the program and 137 elsewhere in England that were not participating. We used difference-in-differences regression analysis to compare risk-adjusted mortality for an 18-month period before the program was introduced with subsequent mortality in the short term (the first 18 months of the program) and the longer term (the next 24 months). RESULTS: Throughout the short-term and the long-term periods, the performance of hospitals in the incentive program continued to improve and mortality for the three conditions covered by the program continued to fall. However, the reduction in mortality among patients with these conditions was greater in the control hospitals (those not participating in the program) than in the hospitals that were participating in the program (by 0.7 percentage points; 95% confidence interval [CI], 0.3 to 1.2). By the end of the 42-month follow-up period, the reduced mortality in the participating hospitals was no longer significant (-0.1 percentage points; 95% CI, -0.6 to 0.3). From the short term to the longer term, the mortality for conditions not covered by the program fell more in the participating hospitals than in the control hospitals (by 1.2 percentage points; 95% CI, 0.4 to 2.0), raising the possibility of a positive spillover effect on care for conditions not covered by the program. CONCLUSIONS: Short-term relative reductions in mortality for conditions linked to financial incentives in hospitals participating in a pay-for-performance program in England were not maintained.

Understanding the 'Weekend Effect'.

Weekends are not unusual because of more deaths, but because hospitals apply a stricter admission threshold.

The humanistic and economic burden of juvenile idiopathic arthritis in the era of biologic medication.

Juvenile idiopathic arthritis (JIA) is a poorly understood, heterogeneous, incurable, inflammatory syndrome. Long-term outcomes are uncertain, and this painful condition can result in lifelong disability. JIA is associated with considerable financial and humanistic burden for those affected and the healthcare system. Early diagnosis and effective treatment are indicated to optimise outcomes. Modern treatment aims to achieve remission and preserve joint function by using disease-modifying antirheumatic drugs (DMARDs) early. DMARDs can be classified as conventional/traditional or biologic. Biologic medications may be more effective but cost approximately ten times more than traditional DMARDs. Decision-makers in healthcare are increasingly comparing the cost and consequences of alternative treatment strategies to guide resource allocation decisions. There have been few economic evaluations to date to guide medicines optimisation in JIA. This systematic review highlights the lack of existing evidence relating to the humanistic and economic burden of JIA in the era of biologic medication.

What are the Costs and Benefits of Providing Comprehensive Seven-day Services for Emergency Hospital Admissions?

The English National Health Service is moving towards providing comprehensive 7-day hospital services in response to higher death rates for emergency weekend admissions. Using Hospital Episode Statistics between 1st April 2010 and 31st March 2011 linked to all-cause mortality within 30 days of admission, we estimate the number of excess deaths and the loss in quality-adjusted life years associated with emergency weekend admissions. The crude 30-day mortality rate was 3.70% for weekday admissions and 4.05% for weekend admissions. The excess weekend death rate equates to 4355 (risk adjusted 5353) additional deaths each year. The health gain of avoiding these deaths would be 29 727-36 539 quality-adjusted life years per year. The estimated cost of implementing 7-day services is £1.07-£1.43 bn, which exceeds by £339-£831 m the maximum spend based on the National Institute for Health and Care Excellence threshold of £595 m-£731 m. There is as yet no clear evidence that 7-day services will reduce weekend deaths or can be achieved without increasing weekday deaths. The planned cost of implementing 7-day services greatly exceeds the maximum amount that the National Health Service should spend on eradicating the weekend effect based on current evidence. Policy makers and service providers should focus on identifying specific service extensions for which cost-effectiveness can be demonstrated.

Mapping the disease-specific LupusQoL to the SF-6D.

PURPOSE: To derive a mapping algorithm to predict SF-6D utility scores from the non-preference-based LupusQoL and test the performance of the developed algorithm on a separate independent validation data set. METHOD: LupusQoL and SF-6D data were collected from 320 patients with systemic lupus erythematosus (SLE) attending routine rheumatology outpatient appointments at seven centres in the UK. Ordinary least squares (OLS) regression was used to estimate models of increasing complexity in order to predict individuals' SF-6D utility scores from their responses to the LupusQoL questionnaire. Model performance was judged on predictive ability through the size and pattern of prediction errors generated. The performance of the selected model was externally validated on an independent data set containing 113 female SLE patients who had again completed both the LupusQoL and SF-36 questionnaires. RESULTS: Four of the eight LupusQoL domains (physical health, pain, emotional health, and fatigue) were selected as dependent variables in the final model. Overall model fit was good, with R(2) 0.7219, MAE 0.0557, and RMSE 0.0706 when applied to the estimation data set, and R(2) 0.7431, MAE 0.0528, and RMSE 0.0663 when applied to the validation sample. CONCLUSION: This study provides a method by which health state utility values can be estimated from patient responses to the non-preference-based LupusQoL, generalisable beyond the data set upon which it was estimated. Despite concerns over the use of OLS to develop mapping algorithms, we find this method to be suitable in this case due to the normality of the SF-6D data.

The cost-effectiveness of using financial incentives to improve provider quality: a framework and application.

Despite growing adoption of pay-for-performance (P4P) programmes in health care, there is remarkably little evidence on the cost-effectiveness of such schemes. We review the limited number of previous studies and critique the frameworks adopted and the narrow range of costs and outcomes considered, before proposing a new more comprehensive framework, which we apply to the first P4P scheme introduced for hospitals in England. We emphasise that evaluations of cost-effectiveness need to consider who the residual claimant is on any cost savings, the possibility of positive and negative spillovers, and whether performance improvement is a transitory or investment activity. Our application to the Advancing Quality initiative demonstrates that the incentive payments represented less than half of the £ 13 m total programme costs. By generating approximately 5200 quality-adjusted life years and £ 4.4 m of savings in reduced length of stay, we find that the programme was a cost-effective use of resources in its first 18 months.

Free-for-all: Does crowding impact outcomes because hospital emergency departments do not prioritise effectively?

Unexpected peaks in volumes of attendances at hospital emergency departments (EDs) have been found to affect waiting times, intensity of care and outcomes. We ask whether these effects of ED crowding on patients are caused by poor clinical prioritisation or a quality-quantity trade-off generated by a binding capacity constraint. We study the effects of crowding created by lower-severity patients on the outcomes of approximately 13 million higher-severity patients attending the 140 public EDs in England between April 2016 and March 2017. Our identification approach relies on high-dimensional fixed effects to account for planned capacity. Unexpected demand from low-severity patients has very limited effects on the care provided to higher-severity patients throughout their entire pathway in ED. Detrimental effects of crowding caused by low-severity patients materialise only at very high levels of unexpected demand, suggesting that binding resource constraints impact patient care only when demand greatly exceeds the ED's expectations. These effects are smaller than those caused by crowding induced by higher-severity patients, suggesting an efficient prioritisation of incoming patients in EDs.

The effect of local hospital waiting times on GP referrals for suspected cancer.

INTRODUCTION: Reducing waiting times is a major policy objective in publicly-funded healthcare systems. However, reductions in waiting times can produce a demand response, which may offset increases in capacity. Early detection and diagnosis of cancer is a policy focus in many OECD countries, but prolonged waiting periods for specialist confirmation of diagnosis could impede this goal. We examine whether urgent GP referrals for suspected cancer patients are responsive to local hospital waiting times. METHOD: We used annual counts of referrals from all 6,667 general practices to all 185 hospital Trusts in England between April 2012 and March 2018. Using a practice-level measure of local hospital waiting times based on breaches of the two-week maximum waiting time target, we examined the relationship between waiting times and urgent GP referrals for suspected cancer. To identify whether the relationship is driven by differences between practices or changes over time, we estimated three regression models: pooled linear regression, a between-practice estimator, and a within-practice estimator. RESULTS: Ten percent higher rates of patients breaching the two-week wait target in local hospitals were associated with higher volumes of referrals in the pooled linear model (4.4%; CI 2.4% to 6.4%) and the between-practice estimator (12.0%; CI 5.5% to 18.5%). The relationship was not statistically significant using the within-practice estimator (1.0%; CI -0.4% to 2.5%). CONCLUSION: The positive association between local hospital waiting times and GP demand for specialist diagnosis was caused by practices with higher levels of referrals facing longer local waiting times. Temporal changes in waiting times faced by individual practices were not related to changes in their referral volumes. GP referrals for diagnostic cancer services were not found to respond to waiting times in the short-term. In this setting, it may therefore be possible to reduce waiting times by increasing supply without consequently increasing demand.

Do Informal Care Recipients Internalise Carer Burden? Examining the Impact of Informal Care Receipt on Health Behaviours.

BACKGROUND: Providing informal care has a negative effect on the caregiver's health and well-being, but little is known about how individuals respond to receiving informal care. Care recipients may improve their health behaviours to minimise the onerousness of caregiving and the stress faced by their carer from seeing a loved one in ill-health. OBJECTIVE: We aimed to examine whether informal care recipients internalise the potential for carer spillovers through changes in health behaviours. METHODS: We used data from 3250 older adults with care needs who took part in the UK Household Longitudinal Study between 2017 and 2019. We examined the response to informal care receipt in terms of the probability of engaging in four health behaviours: healthy diet, physical activity, smoking and alcohol consumption. We estimated average treatment effects using regression adjustment with inverse probability treatment weights, comparing individuals that received informal care to those receiving either formal or no care. RESULTS: We found that informal care receipt increased the probability of refraining from negative health behaviours (smoking and alcohol consumption) but reduced the probability of engaging in positive health behaviours (eating fruits and/or vegetables and physical activity). CONCLUSIONS: The asymmetric effects detected suggest that the underlying mechanisms are different, and care recipients may be engaging in risk and effort compensation between negative and positive health behaviours. Failure to account for the behavioural responses from informal care recipients may lead to under-estimation or over-estimation of the extent of caregiving burden and the effectiveness of interventions impacting informal carers.