Socioeconomic differences in waiting times for elective surgery: a population-based retrospective study

Attributing practice variation by its sources: the case of varicose veins treatments in the Netherlands

BACKGROUND

Unwarranted practice variation refers to regional differences in treatments that are not driven by patients' medical needs or preferences. Although it is the subject of numerous studies, most research focuses on variation at the end stage of treatment, i.e. the stage of the treating specialist, disregarding variation stemming from other sources (e.g. patient preferences, general practitioner referral patterns). In the present paper, we introduce a method that allows us to measure regional variation at different stages of the patient journey leading up to treatment.

METHODS

A series of logit regressions estimating the probability of (1) initial visit with the physician and (2) treatment correcting for patient needs and patient preferences. Calculating the coefficient of variation (CVU) at each stage of the patient journey.

RESULTS

Our findings show large regional variations in the probability of receiving an initial visit, The CVU, or the measure of dispersion, in the regional probability of an initial visit with a specialist was significantly larger (0.87-0.96) than at the point of treatment both conditional (0.14-0.25) and unconditional on an initial visit (0.65-0.74), suggesting that practice variation was present before the patient reached the specialist.

CONCLUSIONS

We present a new approach to attribute practice variation to different stages in the patient journey. We demonstrate our method using the clinically-relevant segment of varicose veins treatments. Our findings demonstrate that irrespective of the gatekeeping role of general practitioners (GPs), a large share of practice variation in the treatment of varicose veins is attributable to regional variation in primary care referrals. Contrary to expectation, specialists' decisions meaningfully diminish rather than increase the amount of regional variation.

The impact of deprivation on patients awaiting planned care

Aims

Deprivation underpins many societal and health inequalities. COVID-19 has exacerbated these disparities, with access to planned care falling greatest in the most deprived areas of the UK during 2020. This study aimed to identify the impact of deprivation on patients on growing waiting lists for planned care.

Methods

Questionnaires were sent to orthopaedic waiting list patients at the start of the UK’s first COVID-19 lockdown to capture key quantitative and qualitative aspects of patients’ health. A total of 888 respondents were divided into quintiles, with sampling stratified based on the Index of Multiple Deprivation (IMD); level 1 represented the ‘most deprived’ cohort and level 5 the ‘least deprived’.

Results

The least deprived cohort were older (mean 65.95 years (SD 13.33)) than the most deprived (mean 59.48 years (SD 13.85)). Mean symptom duration was lower in the least deprived areas (68.59 months (SD 112.26)) compared to the most deprived (85.85 months (SD 122.50)). Mean pain visual analogue scores (VAS) were poorer in the most compared to the least deprived cohort (7.11 (SD 2.01) vs 5.99 (SD 2.57)), with mean mood scores also poorer (6.06 (SD 2.65) vs 4.71 (SD 2.78)). The most deprived areas exhibited lower mean quality of life (QoL) scores than the least (0.37 (SD 0.30) vs 0.53 (SD 0.31)). QoL findings correlated with health VAS and Generalized Anxiety Disorder 2-item (GAD2) scores, with the most deprived areas experiencing poorer health (health VAS 50.82 (SD 26.42) vs 57.29 (SD 24.19); GAD2: 2.94 (SD 2.35) vs 1.88 (SD 2.07)). Least-deprived patients had the highest self-reported activity levels and lowest sedentary cohort, with the converse true for patients from the most deprived areas.

Conclusion

The most deprived patients experience poorer physical and mental health, with this most adversely impacted by lengthy waiting list delays. Interventions to address inequalities should focus on prioritizing the most deprived.

Cite this article: Bone Jt Open 2022;3(10):777–785.

Systematic Review: Impact of Social Determinants of Health on the Management and Prognosis of Gallstone Disease

Background:

Due to its prevalence, gallstone disease is a major public health issue. It affects diverse patient populations across various socioeconomic levels. Socioeconomic and geographic deprivation may impact both morbidity and mortality associated with digestive diseases, such as biliary tract disease.

Aim:

The aim of this systematic review was to review the available data on the impact of socioeconomic determinants and geographic factors on gallstone disease and its complications.

Methods:

This systematic review was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The MEDLINE and Web of Science databases were searched by two investigators to retrieve studies about the impact of income, insurance status, hospital status, education level, living areas, and deprivation indices on gallstone disease. Thirty-seven studies were selected for this review.

Results:

Socially disadvantaged populations appear to be more frequently affected by complicated or severe forms of gallstone disease. The prognosis of biliary tract disease is poor in these populations regardless of patient status, and increased morbidity and mortality were observed for acute cholangitis or subsequent cholecystectomy. Limited or delayed access and low-quality therapeutic interventions could be among the potential causes for this poor prognosis.

Conclusions:

This systematic review suggests that socioeconomic determinants impact the management of gallstone disease. Enhanced knowledge of these parameters could contribute to improved public health policies to manage these diseases.

Socioeconomic inequalities in waiting times for primary care across ten OECD countries

Waiting times for health care are a major policy concern across OECD countries. Waiting times are generally tolerated in publicly-funded health systems and perceived as equitable if access to care is not based on socioeconomic status. Although a growing literature has documented that socioeconomic status is negatively associated with waiting times for secondary care in several countries, less is known about waiting time inequalities in primary care, which is the focus of this study. We exploit the Commonwealth Fund's International Health Policy Survey of Adults in 2010, 2013 and 2016 and include ten OECD countries (Australia, Canada, France, Germany, Netherlands, New Zealand, Norway, Sweden, Switzerland, and the United Kingdom). Waiting time for primary care is measured by the time reported to get an appointment to see a doctor or a nurse. We employ interval regression models to investigate for each country whether socioeconomic status (household income and education) are associated with the waiting time for a primary care appointment. We control for age, gender, chronic conditions, and whether the individual holds private health insurance. We find a negative association between household income and waiting times in Canada, Germany, Norway and Sweden.

The role of regional health systems on the waiting time inequalities in health care services: Evidences from Italy

Inequalities in effective access to healthcare are present among countries and within the same country. Despite in Italy exist the principle of equity in access to health system, there are evidence of different access rates in the form of unequal waiting time within the country. Waiting times are an instruments to ration healthcare services dealing with resource scarsity. Theoretically, it is a fair tool because waiting times should depend only on health needs and not on the ability to pay. However, a growing literature has pointed out that belonging to a particular socioeconomic status leads to waiting times inequalities for healthcare services. Many countries have socioeconomic disparities among regions, and healthcare organizations need to take into account these differences. The increasing power of Regional Health Authorities in decentralized health systems, as in the case of Italy, has generated different organizational ways to provide health care, possibly leading to different access rates in the form of unequal waiting time within the country. This paper aims to understand if the administrative area (Regional Health Authorities) in charge of health services affects waiting times lowering or strengthening health care access inequalities. Using a series of logistic regression models, this work suggests the presence of two vectors: socioeconomic inequalities and regional inequalities. Health organizations need to implement different kinds of answers for each vectors of inequalities.

Socioeconomic Status and Waiting Times for Health Services: Current Evidences and Next Area of Research

Waiting times are an issue in many countries, excessive waiting for treatments may deteriorate patient's health status and reduce treatment effectiveness potentially, becoming a barrier in the access to health care services. Waiting time to be equitable should be related only to the health need, people with the same health need have to wait the same time, without any difference due to socioeconomic status. In the commentary, the results of the extensive literature review and policy implications are discussed.

Socioeconomic status and waiting times for health services: An international literature review and evidence from the Italian National Health System

In the absence of priority criteria, waiting times are an implicit rationing instrument where the absence or limited use of prices creates an excess of demand. Even in the presence of priority criteria, waiting times may be unfair because they reduce health care demand of patients in lower socio-economic conditions due to high opportunity costs of time or a decay in their health level. Significant evidence has shown a relationship between socioeconomic status and the length of waiting time. The first phase of the study involved an extensive review of the existent literature for the period of 2002-2016 in the main databases (Scopus, PubMed and Science Direct). Twenty-eight met the eligibility criteria. The 27 papers were described and classified. The e mpirical objective of this study was to determine whether socioeconomic characteristics affect waiting time for different health services in the Italian national health system. The services studied were specialist visits, diagnostics tests and elective surgeries. A classification tree and logistic regression models were implemented. Data from the 2013 Italian Health National Survey were used. The analysis found heterogeneous results for different types of service. Individuals with lower education and economic resources have a higher risk of experiencing excessive waiting times for diagnostic and specialist visits. For elective surgery, socioeconomic inequalities are present but appear to be lower.

The intertwined relationship between patient education, hospital waiting times and hospital utilization

Background Hospital waiting times are established instruments to ration healthcare when resources are scarce. However, higher educated patients may be better able to influence access to, and exit from, hospital care when waiting times are long. Methods Based on a representative sample of 11 European countries from the Survey of Health, Ageing and Retirement in Europe (SHARE) collected in 2004/2005, this paper investigates whether the relationship between individual educational background and hospital utilization depends on the prevalent hospital waiting times in a country. Logistic regression with interaction effects between individual education and average waiting times per country are conducted. Results Primary education is significantly associated with a lower probability of visiting a hospital overnight (OR = 0.88) compared to secondary and tertiary education. Patients in countries with long waiting times had shorter stays (OR = 0.92), and the significant interaction effect indicates that lower educated patients have longer hospital stays than higher educated patients in countries where waiting times tend to be long (OR = 1.06). Conclusions While the findings imply that educational differences exist with regard to hospital care, future research should investigate potential underlying mechanisms, i.e. patients' perceived access barriers and the perceived quality of hospital treatment.

The relationship between educational attainment and waiting time among the elderly in Norway

We investigate whether educational attainment affects waiting time of elderly patients in somatic hospitals. We consider three distinct pathways; that patients with different educational attainment have different disease patterns, that patients with different levels of education receive treatments at different hospitals, and that patient choice and supply of local health services within hospital catchment areas explain unequal waiting time of different educational groups. We find evidence of an educational gradient in waiting time for male patients, but not for female patients. Conditional on age, male patients with tertiary education wait 45% shorter than male patients with secondary or primary education. The first pathway is not quantitatively important as controlling for disease patters has little effect on relative waiting times. The second pathway is important. Relative to patients with primary education, variation in waiting time and education level across local hospitals contributes to higher waiting time for male patients with secondary education and female patients with secondary or tertiary education and lower waiting time for male patients with tertiary education. These effects are in the order of 15-20%. The third pathway is also quantitatively important. The educational gradients within catchment areas disappear when we control for travel distance and supply of private specialists.

Inequalities in waiting times by socioeconomic status

Waiting times for elective care are a major health policy issue in many developed countries. Recent empirical studies suggest that inequalities in waiting times by socioeconomic status are present within publicly-funded systems in several countries. In this short commentary I discuss alternative approaches regarding data, methods and interpretation of results. Further work in this research area is needed.