Chapter 23 Waiting lists and medical treatment: Analysis and policies

How do family doctors respond to reduced waiting times for cancer diagnosis in secondary care?

Reducing waiting times is a priority in public health systems. Efforts of healthcare providers to shorten waiting times could be negated if they simultaneously induce substantial increases in demand. However, separating out the effects of changes in supply and demand on waiting times requires an exogenous change in one element. We examine the impact of a pilot programme in some English hospitals to shorten waiting times for urgent diagnosis of suspected cancer on family doctors' referrals. We examine referrals from 6,666 family doctor partnerships to 145 hospitals between 1st April 2012 and 31st March 2019. Five hospitals piloted shorter waiting times initiatives in 2017. Using continuous difference-in-differences regression, we exploit the pilot as a 'supply shifter' to estimate the effect of waiting times on referral volumes for two suspected cancer types: bowel and lung. The proportion of referred patients breaching two-week waiting times targets for suspected bowel cancer fell by 3.9 percentage points in pilot hospitals in response to the policy, from a baseline of 4.8%. Family doctors exposed to the pilot increased their referrals (demand) by 10.8%. However, the pilot was not successful for lung cancer, with some evidence that waiting times increased, and a corresponding reduction in referrals of -10.5%. Family doctor referrals for suspected cancer are responsive at the margin to waiting times. Healthcare providers may struggle to achieve long-term reductions in waiting times if supply-side improvements are offset by increases in demand.

Access to Healthcare and Health Literacy in Croatia: Empirical Investigation

Health literacy is related to different health-related outcomes. However, the nature of the relationship between health literacy and health outcomes is not well understood. One pathway may lead from health literacy to health outcomes by means of access to healthcare. The goal of the current study is to explore the association between health literacy and the particular measure of access to healthcare-unmet medical need-for the first time in Croatia and, to the best of our knowledge, for the first time in the EU context. We use data obtained from face-to-face interviews in a large nationally representative sample of the Croatian population (n = 1000) to estimate the level of health literacy and self-reported access to care and investigate the association between health literacy and self-perceived barriers to access. Our study showed that limited and problematic health literacy is prevalent and associated with higher rates of unmet medical need. Unmet need is largely caused by long waiting lists. It is therefore essential to design health services fitting the needs of those who have limited and/or problematic health literacy as well as enhance health education with the potential of improving the access to care and health outcomes as well as design policies that reduce waiting times.

The impact of a national formulary expansion on diabetics

This paper estimates the causal effect of the expansion of Colombia's national prescription drug formulary to include five new types of insulin on the healthcare utilization and costs of type I diabetics and explores the mechanisms through which outpatient cost reductions are realized. We find that expanded coverage generates an increase in the cost of insulin for type I diabetics equal to 17% of their baseline healthcare costs. At the same time, their annual outpatient care utilization falls by 1.9 claims. We devise tests to explore the relative importance of two mechanisms by which the expansion may have lowered type I diabetics' non-drug healthcare utilization: spillovers from drug to non-drug spending and rationing of care. We find no evidence that the formulary expansion reduces the rate of complications from diabetes and find substantial declines in non-drug costs even among the subset of diabetics with no scope for spillovers. We find large reductions in the utilization of discretionary care including diagnostic tests, but no such declines for the use of essential drugs, suggesting that rationing of care is the primary driver of observed cost savings.

The Value of Vaccines in Maintaining Health System Capacity in England

OBJECTIVES

In situations of excess demand for healthcare, treating one patient means losing the opportunity to treat another. Therefore, each decision bears an opportunity cost. Nevertheless, when assessing the value of health technologies, these opportunity costs are not always fully considered. We present a pragmatic approach for conceptualizing vaccines' health system capacity value when considering opportunity costs.

METHODS

Our approach proxies opportunity costs through the net monetary benefit forgone as scarce healthcare resources are used to treat a vaccine-preventable disease instead of a patient from the waiting list. We apply this approach to cost the resource "hospital beds" for 3 different scenarios of excess demand. Empirically, we estimate the opportunity costs saved for 4 selected vaccination programs from the national schedule in England during a hypothetical scenario of long-lasting excess demand induced by the pandemic.

RESULTS

The opportunity cost avoided through vaccination rises with excess demand for treatment. When treating an acute vaccine-preventable outcome is a suboptimal choice compared with treating elective patients, preventing a vaccine-preventable disease from blocking a hospital bed generates opportunity cost savings of approximately twice the direct costs saved by avoiding vaccine-preventable hospitalizations.

CONCLUSIONS

Policy makers should be aware that, in addition to preventing the outcome of interest, vaccines and other preventative health technologies deliver value in maintaining regular healthcare services and clearing the pent-up demand from the pandemic. Therefore, health system capacity value should be a key-value element in health technology assessment. Existing and potential future vaccination programs deliver more value than hitherto quantified.

Provider supply and access to primary care

Resource-constrained delivery systems often have access issues, causing patients to wait a long time to see a provider. We develop theoretical and empirical models of wait times and apply them to primary care delivery by the U.S. Veterans Health Administration (VHA). Using instrumental variables to handle simultaneity issues, we estimate the effect of clinician supply on new patient wait times. We find that it has a sizable impact. A 10% increase in capacity reduces wait times by 2.1%. Wait times are also associated with clinician productivity, scheduling protocols, and patient access to alternative sources of care. The VHA has adopted our models to identify underserved areas as specified by the MISSION Act of 2018.

Dually-enrolled patients choose providers with lower wait times: Budgetary implications for the VHA

OBJECTIVE

To estimate the effect of wait times on patients' choice of provider and simulate changes in choice of provider due to compliance with VA MISSION Act wait time targets.

DATA SOURCES

We use nationwide administrative data (2014-2017) on Veterans who are enrolled in Medicare and the Veterans Health Administration (VHA), the Survey of VHA Enrollees, Area Health Resource Files, and other data provided by the Centers for Medicare & Medicaid Services.

STUDY DESIGN

We use an instrumental variables approach to identify the effect of VHA wait times on the proportion of total (Medicare and VHA) services that are paid for by the VHA ("reliance"). We exploit shocks to VHA provider supply to isolate supply-driven changes in wait times and estimate the effect on VHA reliance. We control for market and time fixed effects and local demand factors.

DATA COLLECTION/EXTRACTION METHODS

We use monthly aggregated data on 140 markets (groups of counties). VHA reliance is computed among patients aged 65 years or older who are dually enrolled in VHA and Medicare. VHA wait times and reliance are calculated for multiple specialties: cardiology, gastroenterology, orthopedics, urology, dermatology, and ophthalmology/optometry.

PRINCIPAL FINDINGS

A 10% increase in the mean wait time (+2.8 days) reduces VHA reliance by 2.3 percentage points (95% CI: 2.3, 2.7), or 7.9% of the sample mean. This implies that meeting the MISSION Act wait time targets may have multi-billion-dollar budgetary impacts. Effects vary across specialties. For example, a 10% increase in the mean wait time for cardiology services (+2.0 days) reduces reliance by 1.8 percentage points (95% CI: 1.6, 2.1), or 6.3% of the sample mean for cardiology services.

CONCLUSIONS

Meeting statutory wait time targets may have substantial unforeseen impacts on federal health care spending as patients sort to providers who have lower wait times.

Does waiting times decrease or increase operational costs in short and long-term? Evidence from Portuguese public hospitals

The Portuguese National Health System is composed of all public entities offering health services. There has been a successive increase in expenditure in recent years due to various factors that have contributed to a high degree of uncertainty about the evolution of operating costs in Public Business Hospitals. This research's main objective is to study the relationship between operational costs and waiting times as well as costs with healthcare professionals and waiting times in both external consultations and hospital surgeries. Furthermore, we will empirically assess the presence of U-shaped behaviour in both of these two relationships. We have included a sample of 38 hospitals considered in the Portuguese National Health System. We also included, in our analysis, five groups of public business hospitals, according to the Administrative Central Agency of Portugal's Health Service, considering the period between January 2015 and December 2019. To validate the two relationships proposed, the Autoregressive Distributed Lag panel model was used. This study highlights that longer waiting times for external consultation and surgery significantly affect hospital costs and suggest that longer waiting times do not merely increase absence rates. The study also proves that there are long-term effects that last beyond the short-term waiting period.

The Waiting Game - How Cooperation Between Public and Private Hospitals Can Help Reduce Waiting Lists

Prolonged waiting to access health care is a primary concern for nations aiming for comprehensive effective care, due to its adverse effects on mortality, quality of life, and government approval. Here, we propose two novel bargaining frameworks to reduce waiting lists in two-tier health care systems with local and regional actors. In particular, we assess the impact of 1) trading patients on waiting lists among hospitals, the 2) introduction of the role of private hospitals in capturing unfulfilled demand, and the 3) hospitals’ willingness to share capacity on the system performance. We calibrated our models with 2008–2018 Chilean waiting list data. If hospitals trade unattended patients, our game-theoretic models indicate a potential reduction of waiting lists of up to 37%. However, when private hospitals are introduced into the system, we found a possible reduction of waiting lists of up to 60%. Further analyses revealed a trade-off between diagnosing unserved demand and the additional expense of using private hospitals as a back-up system. In summary, our game-theoretic frameworks of waiting list management in two-tier health systems suggest that public–private cooperation can be an effective mechanism to reduce waiting lists. Further empirical and prospective evaluations are needed.

The effectiveness of different patient referral systems to shorten waiting times for elective surgeries: systematic review

BACKGROUND

Long waiting times for elective surgery are common to many publicly funded health systems. Inefficiencies in referral systems in high-income countries are more pronounced than lower and middle-income countries. Primary care practitioners play a major role in determining which patients are referred to surgeon and might represent an opportunity to improve this situation. With conventional methods of referrals, surgery clinics are often overcrowded with non-surgical referrals and surgical patients experience longer waiting times as a consequence. Improving the quality of referral communications should lead to more timely access and better cost-effectiveness for elective surgical care. This review summarises the research evidence for effective interventions within the scope of primary-care referral methods in the surgical care pathway that might shorten waiting time for elective surgeries.

METHODS

We searched PubMed, EMBASE, SCOPUS, Web of Science and Cochrane Library databases in December-2019 to January-2020, for articles published after 2013. Eligibility criteria included major elective surgery lists of adult patients, excluding cancer related surgeries. Both randomised and non-randomised controlled studies were eligible. The quality of evidence was assessed using ROBINS-I, AMSTAR 2 and CASP, as appropriate to the study method used. The review presentation was limited to a narrative synthesis because of heterogeneity. The PROSPERO registration number is CRD42019158455.

RESULTS

The electronic search yielded 7543 records. Finally, nine articles were considered as eligible after deduplication and full article screening. The eligible research varied widely in design, scope, reported outcomes and overall quality, with one randomised trial, two quasi-experimental studies, two longitudinal follow up studies, three systematic reviews and one observational study. All the six original articles were based on referral methods in high-income countries. The included research showed that patient triage and prioritisation at the referral stage improved timely access and increased the number of consultations of surgical patients in clinics.

CONCLUSIONS

The available studies included a variety of interventions and were of medium to high quality researches. Managing patient referrals with proper triaging and prioritisation using structured referral formats is likely to be effective in health systems to shorten the waiting times for elective surgeries, specifically in high-income countries.

Improving access to services for psychotic patients: does implementing a waiting time target make a difference

OBJECTIVE

In April 2015, the English National Health Service started implementing the first waiting time targets in mental health care. This study aims to investigate the effect of the 14-day waiting time target for early intervention in psychosis (EIP) services after the first six months of its implementation.

STUDY DESIGN

We analyse a cohort of first-episode psychosis patients from the English administrative Mental Health and Learning Disabilities Dataset 2011 to 2015. We compare patients being treated by EIP services (treatment) with those receiving care from standard community mental health services (control). We combine non-parametric matching with a difference-in-difference approach to account for observed and unobserved group differences. We analyse the probability of waiting below target and look at different percentiles of the waiting time distribution.

RESULTS

EIP patients had an 11.6-18.4 percentage point higher chance of waiting below target post-policy compared to standard care patients. However, post-policy trends at different percentiles of the waiting time distribution were not different between groups.

CONCLUSIONS

Mental health providers seem to respond to waiting time targets in a similar way as physical health providers. The increased proportion waiting below target did not, however, result in an overall improvement across the waiting time distribution.

Outpatient Waiting Time at Vietnam Health Facilities: Policy Implications for Medical Examination Procedure

Our study aims to measure outpatient waiting times at Vietnam health facilities according to the socioeconomic characteristics. We employed the 2015 Vietnam District and Commune Health Facility Survey which was a cross-sectional study designed by the World Bank in collaboration with the Vietnam Health Strategy and Policy Institute. This survey was designed to be representative of six provinces (Dien Bien, Hanoi, Binh Dinh, Dak Lak, Dong Nai, and Dong Thap) drawn from six distinct geographical regions of Vietnam. Data from 4949 outpatients at district hospitals (DHs) and 1724 outpatients at commune health centers (CHCs) were extracted for final analysis. We recorded average outpatient waiting times of 32.58 min at DHs and of 11.58 min at CHCs. Four hundred and forty-five outpatients at DHs (9.0%) and 720 those at CHCs (42.8%) were examined immediately (waiting time = 0 min). Outpatient waiting times were various in six distinct geographical regions. With an investigation according to several socioeconomic characteristics, significant differences in outpatient waiting times were observed at both two levels of health facilities as measured by province, age, self-reported health status, patient’s wealth, ethnicity, and health insurance. Conclusions. Outpatient waiting times from arrival at health facility until receiving care were significantly distinct amongst two health facility levels, revealing longer at DHs compared to at CHCs. There was significantly higher proportion of outpatients examined immediately at CHCs compared to at DHs. Our study suggests that, vulnerable populations, with longer outpatient waiting time, should be dealt with in appropriate models towards each medical facility according to key socioeconomic factors to contribute to simplify the process of medical examination and treatment for outpatients.

Optimal hospital payment rules under rationing by waiting

We derive optimal rules for paying hospitals for non-emergency care when providers choose quality and capacity, and patient demand is rationed by waiting time. Waiting for treatment is costly for patients, so that hospital payment rules should take account of their effect on waiting time as well as on quality. Since deterministic waiting time models imply that profit maximising hospitals will never choose to have both positive quality and positive waiting time, we develop a stochastic model of rationing by waiting in which both quality and expected waiting are positive in equilibrium. We use it to show that, although a prospective output price gives hospitals an incentive to attract patients by raising quality and reducing waiting times, it must be supplemented by a price attached to hospital decisions on quality or capacity or to a performance indicator which depends on those decisions (such as average waiting time, or average length of stay). A prospective output price by itself can support the optimal quality and waiting time distribution only if the welfare function respects patient preferences over quality and waiting time, if patients' marginal rates of substitution between quality and waiting time are independent of income, and if waiting for treatment does not reduce the productivity of patients. If these conditions do not hold, supplementing the output price with a reward linked to the hospital's cost can increase welfare, though it is possible that costs should be taxed rather than subsidised.

Priority access to health care: Evidence from an exogenous policy shock

Access to care is an important issue in public health care systems. Unlike private systems, in which price equilibrates supply and demand, public systems often ration medical services through wait times. Access that is given on a first come, first served basis might not yield an allocation of resources that maximizes the health of a population, potentially creating suboptimal heterogeneity in wait times. In this study, we examine an access disparity between two groups of patients-established patients and new patients. We exploit an exogenous policy change-implemented by the U.S. Veterans Health Administration-that removed the disparity and homogenized the wait time. We find strong evidence that without such a policy, established patients have priority access over new patients. We discuss whether this is a suboptimal allocation of resources. We additionally find that established patient priority access is an important determinant of access for new patients; accounting for it increased the explanatory power of our statistical model of new patient wait times by a factor of five. The findings imply that policy and management decisions may be more effective in achieving the optimal distribution of access if access heterogeneity is recognized and accounted for explicitly.

The effects of immigration on NHS waiting times

This paper analyzes the effects of immigration on waiting times for the National Health Service (NHS) in England. Linking administrative records from Hospital Episode Statistics (2003-2012) with immigration data drawn from the UK Labour Force Survey, we find that immigration reduced waiting times for outpatient referrals and did not have significant effects on waiting times in accident and emergency departments (A&E) and elective care. The reduction in outpatient waiting times can be explained by the fact that immigration increases natives' internal mobility and that immigrants tend to be healthier than natives who move to different areas. Finally, we find evidence that immigration increased waiting times for outpatient referrals in more deprived areas outside of London. The increase in average waiting times in more deprived areas is concentrated in the years immediately following the 2004 EU enlargement and disappears in the medium term (e.g., 3-4 years).

Pent-up demand for surgery in the Manaus metropolitan region: A population-based cross-sectional study

Waiting lines in healthcare reflect an imbalance between the availability and the demand for medical services. This study aimed to analyze the prevalence and factors associated with the pent-up demand for surgical procedures in the Manaus metropolitan region.We performed a population-based cross-sectional study in 2015. Pent-up demand was based on self-report by the participants; those who reported waiting were contacted by phone to clarify the nature and reasons for the experienced delay.We interviewed 4001 adults in their households. The pent-up demand for surgical procedures in the Manaus metropolitan region was 14% (95% confidence interval: 13-15%). The surgical specialties with the highest demand included orthopedics (18.1%), gynecology (17.0%), ophthalmology (12.4%), neurosurgery (10.8%), and general surgery (10.2%). The main reason for not accessing services was their lack of availability in the public health system, leading some patients to pay for procedures in private facilities. The populations most affected by pent-up demand included elderly individuals, women, and housewives.Pent-up demand for surgical procedures is a common problem in the Manaus metropolitan region and thus requires coordinated actions to optimize access to and capacity of the healthcare system.

Public Provision and Cross-Border Health Care

We study how the optimal public provision of health care depends on whether or not individuals have an option to seek publicly financed treatment in other regions. We find that, relative to the first-best solution, the government has an incentive to over-provide health care to low-income individuals. When cross-border health care takes place, this incentive is solely explained by that over-provision facilitates redistribution. The reason why more health care facilitates redistribution is that high-ability individuals mimicking low-ability individuals benefit the least from health care when health and labor supply are complements. Without cross-border health care, higher demand for health care among high-income individuals also contributes to the over-provision given that high-income individuals do not work considerably less than low-income individuals and that the government cannot discriminate between the income groups by giving them different access to health care.

Do waiting times affect health outcomes? Evidence from coronary bypass

Long waiting times for non-emergency services are a feature of several publicly-funded health systems. A key policy concern is that long waiting times may worsen health outcomes: when patients receive treatment, their health condition may have deteriorated and health gains reduced. This study investigates whether patients in need of coronary bypass with longer waiting times are associated with poorer health outcomes in the English National Health Service over 2000-2010. Exploiting information from the Hospital Episode Statistics (HES), we measure health outcomes with in-hospital mortality and 28-day emergency readmission following discharge. Our results, obtained combining hospital fixed effects and instrumental variable methods, find no evidence of waiting times being associated with higher in-hospital mortality and weak association between waiting times and emergency readmission following a surgery. The results inform the debate on the relative merits of different types of rationing in healthcare systems. They are to some extent supportive of waiting times as an acceptable rationing mechanism, although further research is required to explore whether long waiting times affect other aspects of individuals' life.

Difficulties in access and estimates of public beds in intensive care units in the state of Rio de Janeiro

OBJECTIVE

To estimate the required number of public beds for adults in intensive care units in the state of Rio de Janeiro to meet the existing demand and compare results with recommendations by the Brazilian Ministry of Health.

METHODS

The study uses a hybrid model combining time series and queuing theory to predict the demand and estimate the number of required beds. Four patient flow scenarios were considered according to bed requests, percentage of abandonments and average length of stay in intensive care unit beds. The results were plotted against Ministry of Health parameters. Data were obtained from the State Regulation Center from 2010 to 2011.

RESULTS

There were 33,101 medical requests for 268 regulated intensive care unit beds in Rio de Janeiro. With an average length of stay in regulated ICUs of 11.3 days, there would be a need for 595 active beds to ensure system stability and 628 beds to ensure a maximum waiting time of six hours. Deducting current abandonment rates due to clinical improvement (25.8%), these figures fall to 441 and 417. With an average length of stay of 6.5 days, the number of required beds would be 342 and 366, respectively; deducting abandonment rates, 254 and 275. The Brazilian Ministry of Health establishes a parameter of 118 to 353 beds. Although the number of regulated beds is within the recommended range, an increase in beds of 122.0% is required to guarantee system stability and of 134.0% for a maximum waiting time of six hours.

CONCLUSIONS

Adequate bed estimation must consider reasons for limited timely access and patient flow management in a scenario that associates prioritization of requests with the lowest average length of stay.

The effect of in-office waiting time on physician visit frequency among working-age adults

Disparities in unmet health care demand resulting from socioeconomic, racial, and financial factors have received a great deal of attention in the United States. However, out-of-pocket costs alone do not fully reflect the total opportunity cost that patients must consider as they seek medical attention. While there is an extensive literature on the price elasticity of demand for health care, empirical evidence regarding the effect of waiting time on utilization is sparse. Using the nationally representative 2003 Community Tracking Study Household Survey, the most recent iteration containing respondents' physician office visit frequency and estimated in-office waiting time in the United States (N = 23,484), we investigated the association between waiting time and calculated time cost with the number of physician visits among a sample of working-age adults. To avoid the bias that literature suggests would result from excluding respondents with zero physician visits, we imputed waiting time for the essential inclusion of such individuals. On average, respondents visited physician offices 3.55 times, during which time they waited 28.7 min. The estimates from a negative binomial model indicated that a doubling of waiting time was associated with a 7.7 percent decrease (p-value < 0.001) in physician visit frequency. For women and unemployed respondents, who visited physicians more frequently, the decrease was even larger, suggesting a stronger response to greater waiting times. We believe this finding reflects the discretionary nature of incremental visits in these groups, and a consequent lower perceived marginal benefit of additional visits. The results suggest that in-office waiting time may have a substantial influence on patients' propensity to seek medical attention. Although there is a belief that expansions in health insurance coverage increase health care utilization by reducing financial barriers to access, our results suggest that unintended consequences may arise if in-office waiting time increases.

Waiting times and socioeconomic status: evidence from England

Waiting times for elective surgery, like hip replacement, are often referred to as an equitable rationing mechanism in publicly-funded healthcare systems because access to care is not based on socioeconomic status. Previous work has established that that this may not be the case and there is evidence of inequality in NHS waiting times favouring patients living in the least deprived neighbourhoods in England. We advance the literature by explaining variations of inequalities in waiting times in England in four different ways. First, we ask whether inequalities are driven by education rather than income. Our analysis shows that education and income deprivation have distinct effects on waiting time. Patients in the first quintile with least deprivation in education wait 9% less than patients in the second quintile and 14% less than patients in the third-to-fifth quintile. Patients in the fourth and fifth most income-deprived quintile wait about 7% longer than patients in the least deprived quintile. Second, we investigate whether inequalities arise "across" hospitals or "within" the hospital. The analysis provides evidence that most inequalities occur within hospitals rather than across hospitals. Moreover, failure to control for hospital fixed effects results in underestimation of the income gradient. Third, we explore whether inequalities arise across the entire waiting time distribution. Inequalities between better educated patients and other patients occur over large part of the waiting time distribution. Moreover we find that the education gradient becomes smaller for very long waiting. Fourth, we investigate whether the gradient may reflect the fact that patients with higher socioeconomic status have a different severity as proxied through a range of types and the number of diagnoses (in addition to age and gender) compared to those with lower socioeconomic status. We find no evidence that differences in severity explain the social gradient in waiting times.

Time is money: outpatient waiting times and health insurance choices of elderly veterans in the United States

Growth in the number of days between an appointment request and the actual appointment reduces demand. Although such waiting times are relatively low in the US, current policy initiatives could cause them to increase. We estimate multiple-equation models of physician utilization and insurance plan choice for Medicare-eligible veterans. We find that a 10% increase in VA waiting times increases demand for Medigap insurance by 5%, implying that a representative patient would be indifferent between waiting an average of 5 more days for VA appointments and paying $300 more in annual premium.

Rendering hospital budgets volume based and open ended to reduce waiting lists: does it work?

In the past decades fixed budgets for hospitals were replaced by reimbursement based on outputs in several countries in order to bring down waiting lists. This was also the case in the Netherlands where fixed global budgets were replaced by budgets that are to a large extent volume based and in practice open-ended. The objective of this study was to examine the effectiveness of this Dutch policy measure, which was implemented in 2001. We carried out a statistical analysis and interpretation of trends in Dutch hospital admission rates. We observed a significant turn in the development of in-patient admission rates after the abolition of budget caps in 2001: decreasing admission rates turned into an internationally exceptional increase of more than 3% per year. Day care admissions had already been rising explosively for two decades, but the pace increased after 2001. The increase in the number of admissions includes a broad range of patient categories that were not in the first place associated with long waiting times. The growth was attributable for a large part to admissions for observation of the patient and the evaluation of symptoms, not resulting in a definite medical diagnosis. We considered several factors, other than the availability of more resources, to explain the growth: the ageing of the population, making up for waiting list arrears, ditto for "under consumption" of unplanned care and, as to the growth of day care, substitution for inpatient care. However, these factors were all found to fall short as an explanation. Although waiting times have dropped since the change in the budget system, they continue to be long for several procedures. Our study indicates that making available more resources to admit patients, or otherwise an increase in hospital activity, do not in itself lead to equilibrium between demand and supply because the volume and composition of demand are partly induced by supply. We conclude that abolishing budget caps to solve waiting list problems is not efficient. Instead of a generic measure, a more focused approach is necessary. We suggest ingredients for such an approach.

Disparidades nas filas para transplantes de órgãos nos estados brasileiros

Avaliamos alguns aspectos dos transplantes de órgãos nas Unidades da Federação brasileira, nos anos de 2004, 2005 e 2006. Estimamos, com base em um modelo de teoria das filas, os tempos de espera para transplantes de coração, córnea, fígado, pulmão, rim, pâncreas, e transplante simultâneo de rim e pâncreas. Os resultados indicam redução na espera por alguns órgãos (córnea, e pâncreas); elevação em outros (fígado, coração, rim/pâncreas); e ligeiras flutuações, sem tendência muito definida, nos transplantes de rim e nos transplantes de pulmão ao longo do período estudado. Os estados das regiões Sul e Sudeste (com a exceção do Rio de Janeiro) e Centro-oeste têm os menores tempos de espera e as maiores taxas de atendimento do país.

Waiting-time targets in the healthcare sector: how long are we waiting?

Waiting-time targets are used by policy makers to monitor providers' performance. Such targets are based on the distribution of the patients on the list. We compare and link such distribution with the distribution of waiting time of patients treated, as opposed to on the list, which is a better measure of total disutility from waiting (although can only be calculated retrospectively). We show that the latter can be calculated from the former, and vice versa. We also show that, depending on how the hazard rate varies with time waited, the proportion of patients on the list waiting more than x periods can be higher or lower than the proportion of patients treated waiting more than x periods. However, empirically we find that the proportion of patients waiting on the list more than x months is smaller than our estimate of the proportion of patients treated waiting more than x months.

Do waiting times reduce hospital costs?

Using a sample of 137 hospitals over the period 1998-2002 in the English National Health Service, we estimate the elasticity of hospital costs with respect to waiting times. Our cross-sectional and panel-data results suggest that at the sample mean (103 days), waiting times have no significant effect on hospitals' costs or, at most, a positive one. If significant, the elasticity of cost with respect to waiting time from our cross-sectional estimates is in the range 0.4-1. The elasticity is still positive but lower in our fixed-effects specifications (0.2-0.4). In all specifications, the effect of waiting time on cost is non-linear, suggesting a U-shaped relationship between hospital costs and waiting times. However, the level of waiting time which minimises total costs is always below ten days.

[Rationing through waiting lists: measuring improvement and possible implications]

This paper analyzes the main policy initiatives for improving waiting lists in health care. The authors begin by describing strategies to reduce either waiting time or length of the list. They distinguish between demand-side and supply-side strategies. They proceed to discuss policies for improving the "quality" of waiting time. For each policy, they present both the expected effect and the indirect effects that can reduce its effectiveness for improving waiting list conditions.

The market for elective surgery: joint estimation of supply and demand

This paper develops models of the demand for and supply of elective (non-emergency) surgery using a panel of quarterly data for 200 English hospitals over the period 1995-2002. Unusually, distinct measures of supply (outpatients seen and inpatient admissions) and demand (outpatient referrals and decisions to admit) are available for each observation. These offer the opportunity to estimate separate empirical models of supply and demand using ordinary least squares (OLS) regression methods. However, the strong correlation between the residuals of these models suggests some merit in the deployment of seemingly unrelated regression (SUR) methods. Although both static and dynamic SUR estimations leave the results largely qualitatively unchanged, SUR estimation can have a considerable quantitative effect relative to the OLS results. For example, SUR estimation generates a lower elasticity of inpatient demand with respect to waiting time than that obtained via OLS. The results offer an important justification for more careful econometric modelling of hospital behaviour than has traditionally been employed in the health economics literature.

[A study on organ transplantation waiting lines in Brazil's Unified National Health System]

This study analyzes the waiting lines for solid organ transplants in Brazil's Unified National Health System. By using a queuing theory model, we estimate the waiting times for different organs under alternative scenarios. The model reveals the elasticity of various waiting times with respect to arrival and service rates for organ transplantation within the system. Average waiting time for a solid organ transplant is very long and highly elastic in Brazil. The article discusses some important possibilities for reducing such waiting times.

The Norwegian hospital reform of 2002: Central government takes over ownership of public hospitals

Starting in January 2002, the majority of the Norwegian Parliament transferred the ownership of all public hospitals from the county governments to the central state. This round of reforms represents the most recent attempt by the central government to resolve major problems in the Norwegian health care system. In this paper, we describe these reforms and the problems they are intended to remedy. We also indicate further proposals that we believe need to be accomplished to ensure that the reforms become successful. The main lesson to be learned from the Norwegian experiment is that central government involvement in local and county government decision-making can lead to ambiguous responsibilities and a lack of transparency. This appears to be particularly the case when central government involvement implies shared responsibilities for the financing of particular services.

Comparing the welfare effects of public and private health care subsidies in the United Kingdom

We use a calibrated analytical model to compare the welfare costs (gross of externalities) of increasing subsidies for public and private health care in the UK. The model incorporates wait costs for rationed public care, burdens that subsidies impose on the tax system, and distributional weights for different households. Welfare costs are significantly higher for expanding public health care over a range of parameter scenarios. Both policies reduce average wait times, but for public health care this is offset by new waiting costs incurred on extra treatments. And the burden on the tax system is much larger for expanding public health care.

Influence of waiting time on cost-effectiveness

Economic evaluations of health care programs are intended to support policy decisions and therefore should incorporate elements of the health care environment such as waiting lists. We explore possible relationships between waiting time and the cost-effectiveness of health care programs. The impact of waiting on cost-effectiveness is very scenario dependent and may be substantial, especially if health loss while waiting is partly or completely non-reversible. We argue that economic evaluations of health care programs in countries with waiting lists should consider the possible impact of waiting on costs and health effects.

The demand for elective surgery in a public system: time and money prices in the UK National Health Service

We construct a model of the admission process for patients from general practices for elective surgery in the UK National Health Service. Public patients face a positive waiting time, but a zero money price. Fundholding practices faced a positive money price for each patient admitted. The model is tested with data on general practice admission rates for cataract procedures in an English Health Authority. Admission rates are negatively related to waiting times and distance to hospital. Practices respond to financial incentives as predicted by the model: fundholding practices have lower admission rates than non-fundholders and respond differently to changes in waiting times and patient characteristics.