Toward a needs based mechanism for capitation purposes in Italy: the role of socioeconomic level in explaining differences in the use of health services

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.

High-resolution age-specific mapping of the two-week illness prevalence rate based on the National Health Services Survey and geostatistical analysis: a case study in Guangdong province, China

BACKGROUND

The two-week illness prevalence rate is an important and comparable indicator of health service needs. High-spatial-resolution, age-specific risk mapping of this indicator can provide valuable information for health resource allocation. The age-prevalence relationships may be different among areas of the study region, but previous geostatistical models usually ignored the spatial-age interaction.

METHODS

We took Guangdong province, the province with the largest population and economy in China, as a study case. We collected two-week illness data and other potential influencing predictors from the fifth National Health Services Survey in 2013 and other open-access databases. Bayesian geostatistical binary regression models were developed with spatial-age structured random effect, based on which, high-resolution, age-specific two-week illness prevalence rates, as well as number of people reporting two-week illness, were estimated. The equality of health resource distribution was further evaluated based on the two-week illness mapping results and the health supply data.

RESULTS

The map across all age groups revealed that the highest risk was concentrated in the central (i.e., Pearl River Delta) and northern regions of the province. These areas had a two-week illness prevalence > 25.0%, compared with 10.0-20.0% in other areas. Age-specific maps revealed significant differences in prevalence between age groups, and the age-prevalence relationships also differed across locations. In most areas, the prevalence rates decrease from age 0 to age 20, and then increase gradually. Overall, the estimated age- and population-adjusted prevalence was 16.5% [95% Bayesian credible interval (BCI): 14.5-18.6%], and the estimated total number of people reporting illness within the two-week period was 17.5 million (95% BCI: 15.5-19.8 million) in Guangdong Province. The Lorenz curve and the Gini coefficient (resulted in 0.3526) showed a moderate level of inequality in health resource distribution.

CONCLUSIONS

We developed a Bayesian geostatistical modeling framework with spatial-age structured effect to produce age-specific, high-resolution maps of the two-week illness prevalence rate and the numbers of people reporting two-week illness in Guangdong province. The methodology developed in this study can be generalized to other global regions with available relevant survey data. The mapping results will support plans for health resource allocation.

Health care utilization by immigrants in Italy

Healthcare utilization studies show how well documented disparities between migrants and non-migrants. Reducing such disparities is a major goal in European countries. However, healthcare utilization among Italian immigrants is under-studied. The objective of this study is to explore differences in healthcare use between immigrant and native Italians. Cross-sectional study using the latest available (2004/2005) Italian Health Conditions Survey. We estimated separate hurdle binomial negative regression models for GP, specialist, and telephone consultations and a logit model for emergency room (ER) use. We used logistic regression and zero-truncated negative binomial regression to model the zero (contact decision) and count processes (frequency decisions) respectively. Adjusting for risk factors, immigrants are significantly less likely to use healthcare services with 2.4 and 2.7 % lower utilization probability for specialist and telephone consultations, respectively. First- and second-generation immigrants' probability for specialist and telephone contact is significantly lower than natives'. Immigrants, ceteris paribus, have a much higher probability of using ERs than natives (0.7 %). First-generation immigrants show a higher probability of visiting ERs (1 %). GP visits show no significant difference. In conclusion Italian immigrants are much less likely to use specialist healthcare and medical telephone consultations than natives but more likely to use ERs. Hence, we report an over-use of ERs and under-utilization of preventive care among immigrants. We recommend improved health policies for immigrants: promotion of better information dissemination among them, simplification of organizational procedures, better communications between providers and immigrants, and an increased supply of health services for the most disadvantaged populations.

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

Background

Widespread literature on inequity in healthcare access and utilization has been published, but research on socioeconomic differences in waiting times is sparse and the evidence is fragmentary and controversial. The objective of the present study is the analysis of the relationship between individual socioeconomic level and waiting times for in-hospital elective surgery.

Methods

We retrospectively studied the waiting times experienced by patients registered on hospital waiting lists for 6 important surgical procedures by using the Hospital Discharge Database (HDD) of the Piedmont Region (4,000,000 inhabitants in the North West of Italy) from 2006 to 2008. The surgical procedures analyzed were: coronary artery by-pass (CABG), angioplasty, coronarography, endarterectomy, hip replacement and cholecystectomy. Cox regression models were estimated to study the relationship between waiting times and educational level taking into account the confounding effect of the following factors: sex, age, comorbidity, registration period, and Local Health Authorities (LHA) as a proxy of supply.

Results

Median waiting times for low educational level were higher than for high educational level for all the selected procedures. Differences were particularly high for endarterectomy and hip replacement. For all considered procedures, except CABG, an inverse gradient between waiting times and educational level was observed: the conditional probabilities of undergoing surgery were lower among individuals with a low to middle level education than for individuals with a higher level of education after adjustment for sex, age, comorbidities, registration period, and LHAs. For most procedures the effect decreases over the follow up period.

Conclusions

The results of the study show evidence of inequalities in access to elective surgery in Italy. Implementation of policies aimed to promote national information initiatives that guarantee wider access to those with low socio-economic status is strongly recommended.