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).

The effect of hospital spending on waiting times.

Long waiting times have been a persistent policy issue in the United Kingdom that the COVID-19 pandemic has exacerbated. This study analyses the causal effect of hospital spending on waiting times in England using a first-differences panel approach and an instrumental variable strategy to deal with residual concerns for endogeneity. We use data from 2014 to 2019 on waiting times from general practitioner referral to treatment (RTT) measured at the level of local purchasers (known as Clinical Commissioning Groups). We find that increases in hospital spending by local purchasers of 1% reduce median RTT waiting time for patients whose pathway ends with a hospital admission (admitted pathway) by 0.6 days but the effect is not statistically significant at 5% level (only at the 10% level). We also find that higher hospital spending does not affect the RTT waiting time for patients whose pathway ends with a specialist consultation (non-admitted pathway). Nor does higher spending have a statistically significant effect on the volume of elective activity for either pathway. Our findings suggest that higher spending is no guarantee of higher volumes and lower waiting times, and that additional mechanisms need to be put in place to ensure that increased spending benefits elective patients.

Socioeconomic inequalities in waiting times for planned and cancer surgery: Evidence from Spain.

Waiting times act as a non-price rationing mechanism to bring together the demand for and the supply of public healthcare services and ensure equal access independently of ability to pay. This study tests for the presence of socioeconomic inequalities in waiting times for ten publicly-funded planned and cancer surgeries in Catalonia (Spain) in 2015-2019. Socioeconomic status (SES), measured by four categories (very low, low, middle, high), is based on co-payment levels for medicines which depend on patient's income. Using administrative data, we estimate the association between SES and waiting times controlling for patient characteristics and hospital fixed effects. Compared to patients with low SES, patients with middle SES wait 2-6 fewer days for hip replacement, cataract surgery, and hysterectomy, and less than a day for breast cancer surgery. These inequalities arise within hospitals and are not explained by patient nor hospital characteristics. For some surgeries, the results also show that patients with higher SES are more likely to voluntarily exit the waiting list and have a lower probability of having a surgery canceled for medical reasons and dying while waiting.

What explains differences in waiting times for health care across socioeconomic status?

In publicly funded health systems, waiting times act as a rationing mechanism that should be based on need rather than socioeconomic status. However, several studies suggest that individuals with higher socioeconomic status wait less. Using individual-level data from administrative registers, we estimate and explain socioeconomic inequalities in access to publicly funded care for seven planned hospital procedures in Denmark. For each procedure, we first estimate the association between patients' waiting time for health care and their socioeconomic status as measured by income and education, controlling for patient severity. Then, we investigate how much of the association remains after controlling for (i) other individual characteristics (patients' family status, labor market status, and country of origin) that may be correlated with income and education, (ii) possible selection due to patients' use of a waiting time guarantee, and (iii) hospital factors which allow us to disentangle whether inequalities in waiting times arise across hospitals or within the hospital. Only for a few procedures, we find inequalities in waiting times related to income and education. These inequalities can be explained mostly by geographical and institutional factors across hospitals. But we also find inequalities for some procedures in relation to non-Western immigrants within hospitals.

Does hospital competition improve efficiency? The effect of the patient choice reform in England.

We use the 2006 relaxation of constraints on patient choice of hospital in the English NHS to investigate the effect of hospital competition on dimensions of efficiency including indicators of resource management (admissions per bed, bed occupancy rate, proportion of day cases, and cancelled elective operations) and costs (reference cost index for overall and elective activity, cleaning services costs, laundry and linen costs). We employ a quasi differences-in-differences approach and estimate seemingly unrelated regressions and unconditional quantile regressions with data on hospital trusts from 2002/2003 to 2010/2011. Our findings suggest that increased competition had mixed effects on efficiency. An additional equivalent rival increased admissions per bed by 1.1%, admissions per doctor by 0.9% and the proportion of day cases by 0.38 percentage points, but it also increased the number of cancelled elective operations by 2.5%.

Average-Cost Pricing and Dynamic Selection Incentives in the Hospital Sector.

This study investigates dynamic incentives to select patients for hospitals that are remunerated according to a prospective payment system of the diagnosis-related group (DRG) type. Using a model with patients differing in severity within a DRG, we show that price dynamics depend on the extent of hospital altruism and the relation between patients' severity and benefit. Upwards and downwards price movements over time are both possible. In a steady state, DRG prices are unlikely to give optimal incentives to treat patients. Depending on the level of altruism, too few or too many patients are treated. DRG pricing may also give incentives to treat low-severity patients even though high-severity patients should be treated. Copyright © 2016 John Wiley & Sons, Ltd.

The effect of waiting times on demand and supply for elective surgery: Evidence from Italy.

Waiting times are a major policy concern in publicly funded health systems across OECD countries. Economists have argued that, in the presence of excess demand, waiting times act as nonmonetary prices to bring demand for and supply of health care in equilibrium. Using administrative data disaggregated by region and surgical procedure over 2010-2014 in Italy, we estimate demand and supply elasticities with respect to waiting times. We employ linear regression models with first differences and instrumental variables to deal with endogeneity of waiting times. We find that demand is inelastic to waiting times while supply is more elastic. Estimates of demand elasticity are between -0.15 to -0.24. Our results have implications on the effectiveness of policies aimed at increasing supply and their ability to reduce waiting times.

Do hospitals respond to rivals' quality and efficiency? A spatial panel econometric analysis.

We investigate whether hospitals in the English National Health Service change their quality or efficiency in response to changes in quality or efficiency of neighbouring hospitals. We first provide a theoretical model that predicts that a hospital will not respond to changes in the efficiency of its rivals but may change its quality or efficiency in response to changes in the quality of rivals, though the direction of the response is ambiguous. We use data on eight quality measures (including mortality, emergency readmissions, patient reported outcome, and patient satisfaction) and six efficiency measures (including bed occupancy, cancelled operations, and costs) for public hospitals between 2010/11 and 2013/14 to estimate both spatial cross-sectional and spatial fixed- and random-effects panel data models. We find that although quality and efficiency measures are unconditionally spatially correlated, the spatial regression models suggest that a hospital's quality or efficiency does not respond to its rivals' quality or efficiency, except for a hospital's overall mortality that is positively associated with that of its rivals. The results are robust to allowing for spatially correlated covariates and errors and to instrumenting rivals' quality and efficiency.

Do public hospitals respond to changes in DRG price regulation? The case of birth deliveries in the Italian NHS.

We study how changes in Diagnosis-Related Group price regulation affect hospital behaviour in quasi-markets with exclusive provision by public hospitals. Exploiting a quasi-natural experiment, we use a difference-in-differences approach to test whether public hospitals respond to an exogenous change in Diagnosis-Related Group tariffs by increasing C-section rates and/or by upcoding. Controlling for a detailed set of mother characteristics, we find that price changes did not affect the probability of a C-section. We do however find evidence of upcoding: Conditional on the birth delivery method (either a C-section or a vaginal delivery), public hospitals experiencing the largest price change exhibit a higher probability of treating patients coded as complicated. This finding suggests that even public hospitals may be sensitive to market incentives.

How do Hospitals Respond to Price Changes? Evidence from Norway.

Many publicly funded health systems use activity-based financing to increase hospital production and efficiency. The aim of this study is to investigate whether price changes for different treatments affect the number of patients treated and the mix of activity provided by hospitals. We exploit the variations in prices created by the changes in the national average treatment cost per diagnosis-related group (DRG) offered to Norwegian hospitals over a period of 5 years (2003-2007). We use the data from Norwegian Patient Register, containing individual-level information on age, gender, type of treatment, diagnosis, number of co-morbidities and the national average treatment costs per DRG. We employ fixed-effect models to examine the changes in the number of patients treated within the DRGs over time. The results suggest that a 10% increase in price leads to about 0.8-1.3% increase in the number of patients treated for DRGs, which are medical (for both emergency and elective patients). In contrast, we find no price effect for DRGs that are surgical (for both emergency and elective patients). Moreover, we find evidence of upcoding. A 10% increase in the ratio of prices between patients with and without complications increases the proportion of patients coded with complications by 0.3-0.4 percentage points.

Location, quality and choice of hospital: Evidence from England 2002-2013.

We investigate (a) how patient choice of hospital for elective hip replacement is influenced by distance, quality and waiting times, (b) differences in choices between patients in urban and rural locations, (c) the relationship between hospitals' elasticities of demand to quality and the number of local rivals, and how these changed after relaxation of constraints on hospital choice in England in 2006. Using a data set on over 500,000 elective hip replacement patients over the period 2002 to 2013 we find that patients became more likely to travel to a provider with higher quality or lower waiting times, the proportion of patients bypassing their nearest provider increased from 25% to almost 50%, and hospital elasticity of demand with respect to own quality increased. By 2013 average hospital demand elasticity with respect to readmission rates and waiting times were - 0.2 and - 0.04. Providers facing more rivals had demand that was more elastic with respect to quality and waiting times. Patients from rural areas have smaller disutility from distance.

Testing the bed-blocking hypothesis: does nursing and care home supply reduce delayed hospital discharges?

Hospital bed-blocking occurs when hospital patients are ready to be discharged to a nursing home, but no place is available, so that hospital care acts as a more costly substitute for long-term care. We investigate the extent to which greater supply of nursing home beds or lower prices can reduce hospital bed-blocking using a new Local Authority (LA) level administrative data from England on hospital delayed discharges in 2009-2013. The results suggest that delayed discharges respond to the availability of care home beds, but the effect is modest: an increase in care home beds by 10% (250 additional beds per LA) would reduce social care delayed discharges by about 6-9%. We also find strong evidence of spillover effects across LAs: more care home beds or fewer patients aged over 65 years in nearby LAs are associated with fewer delayed discharges.

The effects of taxing sugar-sweetened beverages across different income groups.

This paper investigates the impact of sugar-sweetened beverages (SSB) taxes on consumption, bodyweight and tax burden for low-income, middle-income and high-income groups using an Almost Ideal Demand System and 2011 Household level scanner data. A significant contribution of our paper is that we compare two types of SSB taxes recently advocated by policy makers: A 20% flat rate sales (valoric) tax and a 20 cent/L volumetric tax. Censored demand is accounted for using a two-step procedure. We find that the volumetric tax would result in a greater per capita weight loss than the valoric tax (0.41 kg vs. 0.29 kg). The difference between the change in weight is substantial for the target group of heavy purchasers of SSBs in low-income households, with a weight reduction of up to 3.20 kg for the volumetric and 2.06 kg for the valoric tax. The average yearly per capita tax burden on low-income households is $17.87 (0.21% of income) compared with $15.17 for high-income households (0.07% of income) for the valoric tax, and $13.80 (0.15%) and $10.10 (0.04%) for the volumetric tax. Thus, the tax burden is lower, and weight reduction is higher under a volumetric tax.

Does a hospital's quality depend on the quality of other hospitals? A spatial econometrics approach.

We examine whether a hospital's quality is affected by the quality provided by other hospitals in the same market. We first sketch a theoretical model with regulated prices and derive conditions on demand and cost functions which determine whether a hospital will increase its quality if its rivals increase their quality. We then apply spatial econometric methods to a sample of English hospitals in 2009-10 and a set of 16 quality measures including mortality rates, readmission, revision and redo rates, and three patient reported indicators, to examine the relationship between the quality of hospitals. We find that a hospital's quality is positively associated with the quality of its rivals for seven out of the sixteen quality measures. There are no statistically significant negative associations. In those cases where there is a significant positive association, an increase in rivals' quality by 10% increases a hospital's quality by 1.7% to 2.9%. The finding suggests that for some quality measures a policy which improves the quality in one hospital will have positive spillover effects on the quality in other hospitals.

Patient choice, mobility and competition among health care providers.

Policymakers are increasingly designing policies that encourage patient choice and therefore mobility across providers. Since prices are regulated (fixed) in most countries, providers need to compete on quality to attract patients. This chapter reviews the current theoretical and empirical literature on patient choice and quality competition in health markets. The theoretical literature identifies key factors affecting incentives to provide quality. These include: altruistic motives, cost structure, number of providers, demand responsiveness, GP gatekeeping, degree of specialization, profit constraints and soft budgets. We also review the theoretical literature on choice across different countries (e.g. within the EU) or regions within the same countries. The chapter reviews selected empirical studies that investigate whether demand responds to quality and waiting times, the role of patient's mobility and the effect of competition on quality.

Variation in attendance at emergency departments in England across local areas: A system under unequal pressure.

BACKGROUND: Crowding in Accident and Emergency Departments (AEDs) and long waiting times are critical issues contributing to adverse patient outcomes and system inefficiencies. These challenges are exacerbated by varying levels of AED attendance across different local areas, which may reflect underlying disparities in primary care provision and population characteristics. METHOD: We used regression analysis to determine how much variation across local areas in England of attendance at emergency departments remained after controlling for population risk factors and alternative urgent care provision. FINDINGS: There is substantial residual variation of the order of 3 to 1 (highest to lowest) in per person attendance rate across different areas. This is not related to in-hospital capacity as proxied by the per person number of hospital emergency doctors in an area. CONCLUSION: Some areas in England have emergency departments that are under much greater pressure than others, and this cannot be explained in terms of their population characteristics or the availability of alternative treatment options. It is imperative to better understand the drivers of this variation so that effective interventions to address utilisation can be designed.

Competition, quality and integrated health care.

Integration of health care services has been promoted in several countries to improve the quality and coordination of care. We investigate the effects of such integration in a model where providers compete on quality to attract patients under regulated prices. We identify countervailing effects of integration on quality of care. While integration makes coordination of care more profitable for providers due to bundled payments, it also softens competition as patient choice is restricted. We also identify circumstances due to asymmetries across providers and/or services under which integration either increases or reduces the quality of services provided. In the absence of synergies, integration generally leads to increases in quality for some services and reductions for others. The corresponding effect on health benefits depends largely on whether integration leads to quality dispersion or convergence across services. If the softening of competition effect is weak, integration is likely to improve quality and patient outcomes.

Differences in length of stay for hip replacement between public hospitals, specialised treatment centres and private providers: selection or efficiency?

We investigate differences in patients' length of stay between National Health Service (NHS) public hospitals, specialised public treatment centres and private treatment centres that provide elective (non-emergency) hip replacement to publicly funded patients. We find that the specialised public treatment centres and private treatment centres have, on average, respectively 18% and 40% shorter length of stay compared with NHS public hospitals, even after controlling for differences in age, gender, number and type of diagnoses, deprivation and regional variation. Therefore, we interpret such differences as because of efficiency as opposed to selection of less complex patients. Quantile regression suggests that the proportional differences between different provider types are larger at the higher conditional quantiles of length of stay.

Contracts for primary and secondary care physicians and equity-efficiency trade-offs.

We analyse how payment systems for general practitioners (GPs) and hospital specialists affect inequalities in healthcare treatments, referrals, and patient health. We present a model of contracting with two providers, a GP and a hospital specialist, with patients differing in severity and socioeconomic status, and the GP only receiving an informative signal on severity. We investigate four health system configurations depending on whether the GP refers and the specialist treats only high-severity patients or patients with any severity. We show that an increase in the GP fee, which induces GPs to refer only high-severity patients, increases utilitarian welfare but also increases inequities in access to specialist visits. A reduction in the DRG reimbursement to hospital specialists, which induces specialists to treat only high-severity patients, increases utilitarian welfare but also increases inequities in access to specialist visits when the GP refers only high-severity patients.

The association between bed occupancy rates and hospital quality in the English National Health Service.

We study whether hospitals that exhibit systematically higher bed occupancy rates are associated with lower quality in England over 2010/11-2017/18. We develop an economic conceptual framework to guide our empirical analysis and run regressions to inform possible policy interventions. First, we run a pooled OLS regression to test if high bed occupancy is associated with, and therefore acts as a signal of, lower quality, which could trigger additional regulation. Second, we test whether this association is explained by exogenous demand-supply factors such as potential demand, and unavoidable costs. Third, we include determinants of bed occupancy (beds, length of stay, and volume) that might be associated with quality directly, rather than indirectly through bed occupancy. Last, we use a within-between random-effects specification to decompose these associations into those due to variations in characteristics between hospitals and variations within hospitals. We find that bed occupancy rates are positively associated with overall and surgical mortality, negatively associated with patient-reported health gains, but not associated with other indicators. These results are robust to controlling for demand-supply shifters, beds, and volume. The associations reduce by 12%-25% after controlling for length of stay in most cases and are explained by variations in bed occupancy between hospitals.