Analyzing regional variation in health care utilization using (rich) household microdata

Deprivation as a fundamental cause of morbidity and reduced life expectancy: an observational study using German statutory health insurance data

Across all developed countries, there is a steep life expectancy gradient with respect to deprivation. This paper provides a theoretical underpinning for this gradient in line with the Grossman model, indicating that deprivation affects morbidity and, consequently, life expectancy in three ways: directly from deprivation to morbidity, and indirectly through lower income and a trade-off between investments in health and social status. Using rich German claims data covering 6.3 million insured people over four years, this paper illustrates that deprivation increases morbidity and reduces life expectancy. It was estimated that highly deprived individuals had approximately two more chronic diseases and a life expectancy reduced by 15 years compared to the least deprived individuals. This mechanism of deprivation is identified as fundamental, as deprived people remain trapped in their social status, and this status results in health investment decisions that affect long-term morbidity. However, in the German setting, the income and investment paths of the effects of deprivation were of minor relevance due to the broad national coverage of its SHI system. The most important aspects of deprivation were direct effects on morbidity, which accumulate over the lifespan. In this respect, personal aspects, such as social status, were found to be three times more important than spatial aspects, such as area deprivation.

Subnational inequalities in years of life lost and associations with socioeconomic factors in pre-pandemic Europe, 2009-19: an ecological study

BACKGROUND

Health inequalities have been associated with shorter lifespans. We aimed to investigate subnational geographical inequalities in all-cause years of life lost (YLLs) and the association between YLLs and socioeconomic factors, such as household income, risk of poverty, and educational attainment, in countries within the European Economic Area (EEA) before the COVID-19 pandemic.

METHODS

In this ecological study, we extracted demographic and socioeconomic data from Eurostat for 1390 small regions and 285 basic regions for 32 countries in the EEA, which was complemented by a time-trend analysis of subnational regions within the EEA. Age-standardised YLL rates per 100 000 population were estimated from 2009 to 2019 based on methods from the Global Burden of Disease study. Geographical inequalities were assessed using the Gini coefficient and slope index of inequality. Socioeconomic inequalities were assessed by investigating the association between socioeconomic factors (educational attainment, household income, and risk of poverty) and YLLs in 2019 using negative binomial mixed models.

FINDINGS

Between Jan 1, 2009, and Dec 31, 2019, YLLs lowered in almost all subnational regions. The Gini coefficient of YLLs across all EEA regions was 14·2% (95% CI 13·6-14·8) for females and 17·0% (16·3 to 17·7) for males. Relative geographical inequalities in YLLs among women were highest in the UK (Gini coefficient 11·2% [95% CI 10·1-12·3]) and among men were highest in Belgium (10·8% [9·3-12·2]). The highest YLLs were observed in subnational regions with the lowest levels of educational attainment (incident rate ratio [IRR] 1·19 [1·13-1·26] for females; 1·22 [1·16-1·28] for males), household income (1·35 [95% CI 1·19-1·53]), and the highest poverty risk (1·25 [1·18-1·34]).

INTERPRETATION

Differences in YLLs remain within, and between, EEA countries and are associated with socioeconomic factors. This evidence can assist stakeholders in addressing health inequities to improve overall disease burden within the EEA.

FUNDING

Research Council of Norway; Development, and Innovation Fund of Hungary; Norwegian Institute of Public Medicine; and COST Action 18218 European Burden of Disease Network.

The role of mesolevel characteristics of the health care system and socioeconomic factors on health care use - results of a scoping review

BACKGROUND

Besides macrolevel characteristics of a health care system, mesolevel access characteristics can exert influence on socioeconomic inequalities in healthcare use. These reflect access to healthcare, which is shaped on a smaller scale than the national level, by the institutions and establishments of a health system that individuals interact with on a regular basis. This scoping review maps the existing evidence about the influence of mesolevel access characteristics and socioeconomic position on healthcare use. Furthermore, it summarizes the evidence on the interaction between mesolevel access characteristics and socioeconomic inequalities in healthcare use.

METHODS

We used the databases MEDLINE (PubMed), Web of Science, Scopus, and PsycINFO and followed the 'Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols extension for scoping reviews (PRISMA-ScR)' recommendations. The included quantitative studies used a measure of socioeconomic position, a mesolevel access characteristic, and a measure of individual healthcare utilisation. Studies published between 2000 and 2020 in high income countries were considered.

RESULTS

Of the 9501 potentially eligible manuscripts, 158 studies were included after a two-stage screening process. The included studies contained a wide spectrum of outcomes and were thus summarised to the overarching categories: use of preventive services, use of curative services, and potentially avoidable service use. Exemplary outcomes were screening uptake, physician visits and avoidable hospitalisations. Access variables included healthcare system characteristics such as physician density or distance to physician. The effects of socioeconomic position on healthcare use as well as of mesolevel access characteristics were investigated by most studies. The results show that socioeconomic and access factors play a crucial role in healthcare use. However, the interaction between socioeconomic position and mesolevel access characteristics is addressed in only few studies.

CONCLUSIONS

Socioeconomic position and mesolevel access characteristics are important when examining variation in healthcare use. Additionally, studies provide initial evidence that moderation effects exist between the two factors, although research on this topic is sparse. Further research is needed to investigate whether adapting access characteristics at the mesolevel can reduce socioeconomic inequity in health care use.

Under-spending, over-spending or substitution among services? Spatial patterns of unexplained shares of health care expenditures

Using individual-level administrative data, we investigate the spatial patterns of unexplained shares of health care expenditures (HCE) at the municipality level. The focus is on the elderly population in the Italian Region Friuli-Venezia Giulia observed over the period 2017-2019. The empirical analysis comprises two steps. First, random-effects two-part models are estimated to analyze the effect of age, morbidity, and death on the probability and amount of positive individual total HCE and its components. Second, the unexplained shares of HCE at the municipality level are examined to identify areas with under- or over-spending and substitution among services. Results confirm the existing findings on the determinants of HCE and reveal geographic patterns in the unexplained shares of expenditures. We identify clusters of municipalities with observed HCE higher than predicted for each type of service and clusters with substitution between home care and all other services. These findings are associated with the degree of urbanization of these areas and, consequently, with the ease of access to health care. This is crucial from a policy perspective, as it indicates specific policy targets for public health intervention.

The level of countries' preparedness to health risks during Covid-19 and pre-pandemic: the differential response to health systems building blocks and socioeconomic indicators

The global health security (GHS) Index assesses countries' level of preparedness to health risks. However, there is no evidence on how and whether the effects of health systems building blocks and socioeconomic indicators on the level of preparedness differ for low and high prepared countries. The aim of this study was to examine the contributions of health systems building blocks and socioeconomic indicators to show differences in the level of preparedness to health risks. The study also aimed to examine trends in the level of preparedness and the World Health Organization (WHO) regional differences before and during the Covid-19 pandemic. We used the 2021 GHS index report data and employed quantile regression, log-linear, double-logarithmic, and time-fixed effects models. As robustness checks, these functional form specifications corroborated with one another, and interval validity tests confirmed. The results show that increases in effective governance, supply chain capacity in terms of medicines and technologies, and health financing had positive effects on countries' level of preparedness to health risks. These effects were considerably larger for countries with higher levels of preparedness to health risks. The positive gradient trends signaled a sense of capacity on the part of countries with higher global health security. However, the health workforce including doctors, and health services including hospital beds, were not statistically significant in explaining variations in countries' level of preparedness. While economic factors had positive effects on the level of preparedness to health risks, their impacts across the distribution of countries' level of preparedness to health risks were mixed. The effects of Social Development Goals (SDGs) were greater for countries with higher levels of preparedness to health risks. The effect of the Human Development Index (HDI) was greatest for countries whose overall GHS index lies at the midpoint of the distribution of countries' level of preparedness. High-income levels were associated with a negative effect on the level of preparedness, especially if countries were in the lower quantiles across the distributions of preparedness. Relative to poor countries, middle- and high-income groups had lower levels of preparedness to health risks, an indication of a sense of complacency. We find the pandemic period (year 2021) was associated with a decrease in the level of preparedness to health risks in comparison to the pre-pandemic period. There were significant WHO regional differences. Apart from the Eastern Mediterranean, the rest of the regions were more prepared to health risks compared to Africa. There was a negative trend in the level of preparedness to health risks from 2019 to 2021 although regional differences in changes over time were not statistically significant. In conclusion, attempts to strengthen countries' level of preparedness to health shocks should be more focused on enhancing essentials such as supply chain capacity in terms of medicines and technologies; health financing, and communication infrastructure. Countries should also strengthen their already existing health workforce and health services. Together, strengthening these health systems essentials will be beneficial to less prepared countries where their impact we find to be weaker. Similarly, boosting SDGs, particularly health-related sub-scales, will be helpful to less prepared countries. Moreover, there is a need to curb complacency in preparedness to health risks during pandemics by high-income countries. The negative trend in the level of preparedness to health risks would suggest that there is a need for better preparedness during pandemics by conflating national health with global health risks. This will ensure the imperative of having a synergistic response to global health risks, which is understood by and communicated to all countries and regions.

Regional differences in healthcare costs further explained: The contribution of health, lifestyle, loneliness and mastery

Healthcare costs in the Netherlands are rising and vary considerably among regions. Explaining regional differences in healthcare costs can help policymakers in targeting appropriate interventions in order to restrain costs. Factors usually taken into account when analyzing regional differences in healthcare costs are demographic structure and socioeconomic status (SES). However, health, lifestyle, loneliness and mastery have also been linked to healthcare costs. Therefore, this study analyzes the contribution of health, lifestyle factors (BMI, alcohol consumption, smoking and physical activity), loneliness, and mastery to regional differences in healthcare costs. Analyses are performed in a linked dataset (n = 334,721) from the Dutch Public Health Services, Statistics Netherlands, the National Institute for Public Health and the Environment (year 2016), and the healthcare claims database Vektis (year 2017) with Poisson and zero-inflated binomial regressions. Regional differences in general practitioner consult costs remain significant even after taking into account health, lifestyle, loneliness, and mastery. Regional differences in costs for mental, pharmaceutical, and specialized care are less pronounced and can be explained to a large extent. For total healthcare costs, regional differences are mostly explained through the factors included in this study. Hence, addressing lifestyle factors, loneliness and mastery can help policymakers in restraining healthcare costs. In this study, the region of Zuid-Limburg represents the reference region. Use compare regions for health and healthcare costs (Regiovergelijker gezondheid en zorgkosten) in order to select all other Dutch regions as reference region.

Supplementary Information

The online version of this article (10.1007/s12508-022-00369-4) contains supplementary material, which is available to authorized users.

The longitudinal NIHR ARC North West Coast Household Health Survey: exploring health inequalities in disadvantaged communities

Background

The Household Health Survey (HHS) was developed to understand the socioeconomic determinants of mental and physical health, and health inequalities in health and social care. This paper aims to provide a detailed rationale of the development and implementation of the survey and explore socio-economic variations in physical and mental health and health care.

Methods

This comprehensive longitudinal public health survey was designed and piloted in a disadvantaged area of England, comprising questions on housing, physical health, mental health, lifestyle, social issues, environment, work, and finances. After piloting, the HHS was implemented across 28 neighbourhoods – 10 disadvantaged neighbourhoods for learning (NfLs), 10 disadvantaged comparator sites, and eight relatively advantaged areas, in 2015 and 2018. Participants were recruited via random sampling of households in pre-selected neighbourhoods based on their areas of deprivation.

Results

7731 residents participated in Wave 1 (N = 4319) and 2 (n = 3412) of the survey, with 871 residents having participated in both. Mental health, physical health, employment, and housing quality were poorer in disadvantaged neighbourhoods than in relatively advantaged areas.

Conclusions

This survey provides important insights into socio-economic variations in physical and mental health, with findings having implications for improved care provision to enable residents from any geographical or socio-economic background to access suitable care.

Domain-specific effects of physical activity on the demand for physician visits

OBJECTIVES

To assess domain-specific effects of physical activity (PA) in the relationship with health care utilization and to investigate whether a measure that aggregates PA across domains (leisure, transport, work) is appropriate.

METHODS

Data were retrieved from a longitudinal cohort study conducted in Southern Germany (women n = 1330, men n = 766). The number of physician visits was regressed on total PA and on PA differentiated by the domains leisure time, travel time and working time in a negative binomial model.

RESULTS

For women, no association with physician visits is found for total PA, while high leisure time physical activity (LTPA) is associated with 22% more visits. The effect of high LTPA is statistically different from the effect of high total PA. For men, no significant associations are found for both measures.

CONCLUSIONS

The specific, positive effect of high LTPA on physician visits among women shows that using an aggregate measure of PA is inappropriate for analyzing the relation between PA and health care utilization. Further, the positive relationship should be considered in attempts to promote physical activity.

What explains the regional variation in the use of general practitioners in Australia?

BACKGROUND

Regional variation in the use of health care services is widespread. Identifying and understanding the sources of variation and how much variation is unexplained can inform policy interventions to improve the efficiency and equity of health care delivery.

METHODS

We examined the regional variation in the use of general practitioners (GPs) using data from the Social Health Atlas of Australia by Statistical Local Area (SLAs). 756 SLAs were included in the analysis. The outcome variable of GP visits per capita by SLAs was regressed on a series of demand-side factors measuring population health status and demographic characteristics and supply-side factors measuring access to physicians. Each group of variables was entered into the model sequentially to assess their explanatory share on regional differences in GP usage.

RESULTS

Both demand-side and supply-side factors were found to influence the frequency of GP visits. Specifically, areas in urban regions, areas with a higher percentage of the population who are obese, who have profound or severe disability, and who hold concession cards, and areas with a smaller percentage of the population who reported difficulty in accessing services have higher GP usage. The availability of more GPs led to higher use of GP services while the supply of more specialists reduced use. 30.56% of the variation was explained by medical need. Together, both need-related and supply-side variables accounted for 32.24% of the regional differences as measured by the standard deviation of adjusted GP-consultation rate.

CONCLUSIONS

There was substantial variation in GP use across Australian regions with only a small proportion of them being explained by population health needs, indicating a high level of unexplained clinical variation. Supply factors did not add a lot to the explanatory power. There was a lot of variation that was not attributable to the factors we could observe. This could be due to more subtle aspects of population need or preferences and therefore warranted. However, it could be due to practice patterns or other aspects of supply and be unexplained. Future work should try to explain the remaining unexplained variation.

Sources of regional variation in healthcare utilization in Germany

We examine sources of regional variation in ambulatory care utilization in Germany. We exploit patient migration to examine which share of regional variation in ambulatory care utilization can be attributed to demand factors and to supply factors, respectively. Based on administrative claim-level data we find that regional variation can be overwhelmingly explained by patient characteristics. Our results contrast with previous results for other countries, and they suggest that institutional rules in Germany successfully constrain supply-side variation in ambulatory care use between German regions for most patients. Furthermore, we find that both demographics and other patient characteristics substantially contribute to regional variation and that causes of regional variation vary when comparing different regions within Germany.

Spatial risk adjustment between health insurances: using GWR in risk adjustment models to conserve incentives for service optimisation and reduce MAUP

This paper presents a new approach to deal with spatial inequalities in risk adjustment between health insurances. The shortcomings of non-spatial and spatial fixed effects in risk adjustment models are analysed and opposed against spatial kernel estimators. Theoretical and empirical evidence suggests that a reasonable choice of the spatial kernel could limit the spatial uncertainty of the modifiable area unit problem under heavy-tailed claims data, leading to more precise predictions and economically positive incentives on the healthcare market. A case study of the German risk adjustment shows a spatial risk spread of 86 Euro p.c., leading to incentives for spatial risk selection. The proposed estimator eliminates this issue and conserves incentives for services optimisation.

[Primary and secondary data on dementia care as an example of regional health planning]

BACKGROUND

Health service planning that takes into account as far as possible the regional needs and regional discrepancies is a controversial health issue in Germany.

OBJECTIVES

In a pilot scheme, we tested a planning process for regional healthcare services, based on the example of dementia care. The aim of this article is to present the strengths and limitations of this planning process.

MATERIALS AND METHODS

We developed an indicator set for dementia care based on routine regional data obtained from two German statutory health insurance companies. Additionally, primary data based on a questionnaire sent to all GPs in the area were evaluated. These data were expanded through the addition of official socio-demographic population data. Procedures and evaluation strategies, discussion of the results and the derivation of planning measures followed, in close agreement with a group of local experts.

RESULTS

Few epidemiological data on regional variations in health care planning are publicly available. Secondary data from statutory health insurance companies can be assessed to support the estimation of regional health care needs, but interpretation is difficult. The use of surveys to collect primary data, and the assessment of results by the local health board may facilitate interpretation and may contribute towards more valid statements regarding regional health planning.

CONCLUSIONS

Despite the limited availability of data and the considerable efforts involved in data analysis, the project demonstrates how needs-based health service planning can be carried out in a small region, taking into account the increasing demands of the local health care providers and the special local features.

An investigation of the effect of accessibility to General Practitioner services on healthcare utilisation among older people

Equity in access to healthcare services is regarded as an important policy goal in the organisation of modern healthcare systems. Physical accessibility to healthcare services is recognised as a key component of access. Older people are more frequent and intensive users of healthcare, but reduced mobility and poorer access to transport may negatively influence patterns of utilisation. We investigate the extent to which supply-side factors in primary healthcare are associated with utilisation of General Practitioner (GP) services for over 50s in Ireland. We explore the effect of network distance on GP visits, and two novel access variables: an estimate of the number of addresses the nearest GP serves, and the number of providers within walking distance of a person's home. The results indicate that geographic accessibility to GP services does not in general explain differences in the utilisation of GP services in Ireland. However, we find that the effect of the number of GPs is significant for those who can exercise choice in selecting a GP, i.e., those without public health insurance. For these individuals, the number of GPs within walking distance exerts a positive and significant effect on the utilisation of GP services.

Regional variation in health care utilization in Sweden - the importance of demand-side factors

BACKGROUND

Differences in health care utilization across geographical areas are well documented within several countries. If the variation across areas cannot be explained by differences in medical need, it can be a sign of inefficiency or misallocation of public health care resources.

METHODS

In this observational, longitudinal panel study we use regional level data covering the 21 Swedish regions (county councils) over 13 years and a random effects model to assess to what degree regional variation in outpatient physician visits is explained by observed demand factors such as health, demography and socio-economic factors.

RESULTS

The results show that regional mortality, as a proxy for population health, and demography do not explain regional variation in visits to primary care physicians, but explain about 50% of regional variation in visits to outpatient specialists. Adjusting for socio-economic and basic supply-side factors explains 33% of the regional variation in primary physician visits, but adds nothing to explaining the variation in specialist visits.

CONCLUSION

50-67% of regional variation remains unexplained by a large number of observable regional characteristics, indicating that omitted and possibly unobserved factors contribute substantially to the regional variation. We conclude that variations in health care utilization across regions is not very well explained by underlying medical need and demand, measured by mortality, demographic and socio-economic factors.

Geographic health inequalities in Norway: a Gini analysis of cross-county differences in mortality from 1980 to 2014

Background

This study aims at quantifying the level and changes over time of inequality in age-specific mortality and life expectancy between the 19 Norwegian counties from 1980 to 2014.

Methods

Data on population and mortality by county was obtained from Statistics Norway for 1980–2014. Life expectancy and age-specific mortality rates (0–4, 5–49 and 50–69 age groups) were estimated by year and county. Geographic inequality was described by the absolute Gini index annually.

Results

Life expectancy in Norway has increased from 75.6 to 82.0 years, and the risk of death before the age of 70 has decreased from 26 to 14% from 1980 to 2014. The absolute Gini index decreased over the period 1980 to 2014 from 0.43 to 0.32 for life expectancy, from 0.012 to 0.0057 for the age group 50–69 years, from 0.0038 to 0.0022 for the age group 5–49 years, and from 0.0009 to 0.0006 for the age group 0–4 years. It will take between 2 and 32 years (national average 7 years) until the counties catch up with the life expectancy in the best performing county if their annual rates of increase remain unchanged.

Conclusion

Using the absolute Gini index as a metric for monitoring changes in geographic inequality over time may be a valuable tool for informing public health policies. The absolute inequality in mortality and life expectancy between Norwegian counties has decreased from 1980 to 2014.

Electronic supplementary material

The online version of this article (10.1186/s12939-018-0771-7) contains supplementary material, which is available to authorized users.

General practitioners' perception of being a doctor in urban vs. rural regions in Germany - A focus group study

BACKGROUND

Inadequate recruitment numbers for GPs in rural regions give cause for concern. Working in rural regions is less attractive among medical students because of strong associations concerning a higher workload, restriction of privacy and demands exceeding their competences. We aimed to explore perceptions of GPs working in urban versus rural regions to contrast these prejudices.

METHODS

We conducted nine focus groups with GPs [female = 21, male = 44] from urban and rural regions, using a semi-structured guideline. Transcripts were content analyzed using deductive and inductive categories.

RESULTS

Urban GPs perceived themselves as a provider of medical services and rural GPs as being a medical companion. Compared to urban GPs, GPs from non-urban regions portray themselves more strongly as a family physician that accompanies patients 'from the cradle to the grave' and is responsible for the treatment of any medical issue. They emphasized their close relationship with their patients. Rural GPs establish a close relationship with their patients and considered this as beneficial for the treatment relationship. This aspect seems to play a subordinate role for urban GPs.

CONCLUSIONS

GPs enjoy their work and the role they play in their patients' lives. Being a rural GP was described very positively. Greater emphasis should be made on positive aspects of being a GP in rural regions, e.g. by university lectures given by rural GPs, campaigns emphasizing the positive aspects of working as a GP [in rural regions], promotion of work placements or incentives for working in rural general practices.

[Implementation of models to ensure healthcare in rural areas: Development of a consultancy service]

INTRODUCTION

The combination of an ageing population and unequal distribution of healthcare capacity between rural and urban regions requires the development of innovative healthcare models, especially in rural areas, thus increasing the need to involve community representatives. The aim of this study was to ascertain the need for support and advice among municipalities and family doctors planning and implementing regional projects to ensure the provision of healthcare, and to develop a support and consultancy service on that basis.

METHODS

Using semi-structured telephone interviews, 16 local representatives of the target groups (representatives from rural districts, mayors of rural municipalities and communities, doctors in private practice) were asked to identify the kind of support and advice they needed. The interviews were evaluated using the framework approach, a form of qualitative content analysis, and the results used to develop modules of a support and consultancy service. We discussed and finalized the concept during several workshops involving different representatives of the target groups (another 36 general practitioners, 19 mayors and representatives from rural districts).

RESULTS

After taking into account the expressed need for advice and support, the developed consultancy service included the following modules: local situation/needs analysis, financial support options (e. g., grant application), concept/project development (including presentation of best practice examples), networks, assessment and evaluation, junior staff recruitment and introduction to other experts (for legal or IT-related advice, mediation, etc.).

DISCUSSION

The study showed that local representatives have a substantial need for advice and support for which no nationwide consultancy service is yet available. Future practice tests should establish the extent to which local participants and projects can benefit from the consultancy service we have developed.

Regional variations of perceived problems in ambulatory care from the perspective of general practitioners and their patients - an exploratory focus group study in urban and rural regions of northern Germany

BACKGROUND

Patients from rural and urban regions should have equitable access to health care. In Germany, the physician-patient-ratio and the supply of medical services vary greatly between urban and rural areas. The aim of our study was to explore the regional variations of the perceived health care problems in ambulatory care from the perspective of affected professionals and laypersons i.e. general practitioners and their patients.

METHODS

We conducted 27 focus groups with general practitioners (n = 65) and patients (n = 145) from urban areas, environs and rural areas in northern Germany. Discussions were facilitated by two researchers using a semi-structured guideline. The transcripts were content analyzed using deductive and inductive categories.

RESULTS

General practitioners and patients reported problems due to demographic change and patient behaviour, through structural inequalities and the ambulatory reimbursement system as well as with specialist care and inpatient care. A high physician density, associated with high competition between general practitioners, a high fluctuation of patients and a low status of general practitioners were the main problems reported in urban areas. In contrast, participants from rural areas reported an insufficient physician density, a lack of young recruits in primary care and a resulting increased workload as problematic. All regions are concerned with subjectively inadequate general practitioners' budgets, insufficiently compensated consultations and problems in the cooperation with specialists and inpatient care institutions. Most problems were mentioned by GPs and patients alike, but some (e.g. high competition rates in urban regions and problems with inpatient care) were only mentioned by GPs.

CONCLUSIONS

While many problems arise in urban regions as well as in rural regions, our results support the notion that there is an urgent need for action in rural areas. Possible measures include the support of telemedicine, delegation of medical services and reoccupation of vacant practices. The attractiveness of working in rural areas for general practitioners, specialists and clinicians must be increased by consolidating and expanding rural infrastructure (e.g. child care and cultural life). The above mentioned results also indicate that the ambulatory reimbursement system should be examined regarding the reported inequalities. Measures to further enhance the cooperation between general practitioners, specialists and inpatient care should be taken to solve supra-regionally reported problems. Problems showing regional variations indicate the need for measures to balance these variations between the regions. This is the first German study to analyze subjective views of the stakeholders concerned on regionally variating problems in ambulatory care. Further studies are needed to quantify the extent of the identified problems and differences. A corresponding survey is currently under way.

Regional variation of patient behaviour and reasons for consultation in the general practice of Northern Germany: protocol for an observational study

INTRODUCTION

Inappropriate supply and an increasing demand on the healthcare system have been of concern for health policy in Germany for at least 15 years. In the primary care setting, this especially relates to an undersupply of general practitioners (GPs) in the countryside. In addition, there seem to be other regional differences, for example, a difference in accessing primary and secondary care between rural and urban areas. Despite these findings, regional differences in health services have not been studied extensively in Germany. Therefore, this study aims to explore regional variations of patient populations and reasons for accessing primary medical care.

METHODS AND ANALYSIS

We will conduct a cross-sectional observational study based on standardised interviews with 240 GPs and ∼1200 patients. Data collection started on 10 June 2015 and will probably be completed by 31 October 2016. We will include all districts and cities within 100 km from Hamburg and assign them according to the type of regions: rural, urban and environs. All eligible GPs will be invited to participate. Each practice will recruit up to 15 patients, aged 18 years or older. Questionnaires are based on a preliminary qualitative study and were pretested. Data will be analysed with descriptive statistics and regression modelling strategies adjusted for confounders and the GP-induced cluster structure.

ETHICS AND DISSEMINATION

Our study was approved by the Ethics Committee of the Medical Association of Hamburg and is conducted in accordance with the Declaration of Helsinki. Study participants give written informed consent before data collection and data is pseudonymised. Survey data and person identifiers are stored separately in locked cabinets and have restricted availability. The results of our study will be presented at conferences and published in peer-reviewed journals.

TRIAL REGISTRATION NUMBER

NCT02558322; Pre-results.

Examining regional variation in health care spending in British Columbia, Canada

Examining regional variation in health care spending may reveal opportunities for improved efficiency. Previous research has found that health care spending and service use vary substantially from place to place, and this is often not explained by differences in the health status of populations or by better outcomes in higher-spending regions, but rather by differences in intensity of service provision. Much of this research comes from the United States. Whether similar patterns are observed in other high-income countries is not clear. We use administrative data on health care use, covering the entire population of the Canadian province of British Columbia, to examine how and why health care spending varies among health regions. Pricing and insurance coverage are constant across the population, and we adjust for patient-level age, sex, and recorded diagnoses. Without adjusting for differences in population characteristics, per-capita spending is 50% higher in the highest-spending region than in the lowest. Adjusting for population characteristics as well as the very different environments for health service delivery that exist among metropolitan, non-metropolitan, and remote regions of the province, this falls to 20%. Despite modest variation in total spending, there are marked differences in mortality. In this context, it appears that policy reforms aimed at system-wide quality and efficiency improvement, rather than targeted at high-spending regions, will likely prove most promising.