Analyzing the equity of public primary care provision in Kenya: variation in facility characteristics by local poverty level

Poor quality for the poor? A study of inequalities in service readiness and provider knowledge in Indonesian primary health care facilities

BACKGROUND

For many low and middle-income countries poor quality health care is now responsible for a greater number of deaths than insufficient access to care. This has in turn raised concerns around the distribution of quality of care in LMICs: do the poor have access to lower quality health care compared to the rich? The aim of this study is to investigate the extent of inequalities in the availability of quality health services across the Indonesian health system with a particular focus on differences between care delivered in the public and private sectors.

METHODS

Using the Indonesian Family Life Survey (wave 5, 2015), 15,877 households in 312 communities were linked with a representative sample of both public and private health facilities available in the same communities. Quality of health facilities was assessed using both a facility service readiness score and a knowledge score constructed using clinical vignettes. Ordinary least squares regression models were used to investigate the determinants of quality in public and private health facilities.

RESULTS

In both sectors, inequalities in both quality scores existed between major islands. In public facilities, inequalities in readiness scores persisted between rural and urban areas, and to a lesser extent between rich and poor communities.

CONCLUSION

In order to reach the ambitious stated goal of reaching Universal Health Coverage in Indonesia, priority should be given to redressing current inequalities in the quality of care.

[Equity of access to immunization services in the Center-East health region in 2018, Burkina Faso]

INTRODUCTION

The Central East region of Burkina Faso has vaccine coverage which is among the lowest in the country with an epidemiological profile marked by the occurrence of measles or meningitis outbreaks. This study was conducted with the aim of carrying out an equity analysis of the organization of immunization services in this region in order to identify factors that cause potential inequities in vaccination offer.

MATERIALS AND METHOD

This descriptive cross-sectional study covered the seven districts in the Central East region. Data collection was done in two weeks combined with observation method, individual interviews and document review. Part of the data was collected using a self-administered questionnaire. The data analysis was performed with the Epi info 7 software using a plan designed for this purpose.

RESULTS

A total of 144 health centers in the region (93.0% coverage) were surveyed. The average distance between villages and health facilities was 5.2 km with 16.2% of villages that were located more than 10 km from a health facility. Health centers had an average of four health workers, however the urban health centers had more workers than those in rural areas. About 16% of the villages did not benefit from an on-site vaccination trip due to the unavailability of transport logistics. More than half of the health centers (53.9%) had experienced vaccine shortages in the last six months before the study. More than 5,000 safety boxes containing used syringes were stored in the districts of the region.

CONCLUSION

This study identified factors potentially responsible for an inequity in providing vaccination services in the Central East region. These factors include, but are not limited to, the geographical distribution of the health centers, the availability of transport logistics, and the shortage in vaccines and deficiencies in the waste disposal system. Concerted actions should be developed, involving all stakeholders in the health system in order to address these issues.

Socio-economic inequality and inequity in use of health care services in Kenya: evidence from the fourth Kenya household health expenditure and utilization survey

Background

Kenya is experiencing persistently high levels of inequity in health and access to care services. In 2018, decades of sustained policy efforts to promote equitable, affordable and quality health services have culminated in the launch of a universal health coverage scheme, initially piloted in four Kenyan counties and planned for national rollout by 2022. Our study aims to contribute to monitoring and evaluation efforts alongside policy implementation, by establishing a detailed, baseline assessment of socio-economic inequality and inequity in health care utilization in Kenya shortly before the policy launch.

Methods

We use concentration curves and corrected concentration indexes to measure socio-economic inequality in care use and the horizontal inequity index as a measure of inequity in care utilization for three types of care services: outpatient care, inpatient care and preventive and promotive care. Further insights into the individual and household level characteristics that determine observed inequality are derived through decomposition analysis.

Results

We find significant inequality and inequity in the use of all types of care services favouring richer population groups, with particularly pronounced levels for preventive and inpatient care services. These are driven primarily by differences in living standards and educational achievement, while the region of residence is a key driver for inequality in preventive care use only. Pro-rich inequalities are particularly pronounced for care provided in privately owned facilities, while public providers serve a much larger share of individuals from lower socio-economic groups.

Conclusions

Through its focus on increasing affordability of care for all Kenyans, the newly launched universal health coverage scheme represents a crucial step towards reducing disparities in health care utilization. However in order to achieve equity in health and access to care such efforts must be paralleled by multi-sectoral approaches to address all key drivers of inequity: persistent poverty, disparities in living standards and educational achievement, as well as regional differences in availability and accessibility of care.

Role of Socioeconomic Status in Hypertension among Chinese Middle-Aged and Elderly Individuals

Hypertension is an important global health concern. The relationship between hypertension and socioeconomic status (SES) has been extensively studied. However, the role of SES in hypertension is still controversial, and this kind of study is sorely lacking among Chinese middle-aged and elderly individuals. The data of this study come from the China Health and Retirement Longitudinal Survey (CHARLS) released in May 2017. A total of 21,126 people from all around China, with ages older than 45 years, were enrolled in the questionnaire survey. Hypertension was determined according to the entry in CHARLS (“Do you have doctor-diagnosed hypertension?”), and 17,676 people responded to this entry. The basic demographic and SES information were collected. Multivariate logistic regression was used to evaluate the risk factors of hypertension. Concentration index was used to measure inequality of hypertension incidence. Among the investigated middle-aged and elderly individuals, 5,177/17,676 (29.3%) had doctor-diagnosed hypertension. Multivariate logistic regression implied that individuals older than 55 years (OR 1.436, 95% CI 1.085–1.900 for age interval of 55–64 years; OR 2.032, 95% CI 1.455–2.839 for age interval of 65–74 years; OR 1.672, 95% CI 1.031–2.714 for age interval of older than 75 years), male (OR 0.038, 95% CI 0.595–0.986), overweight (OR 2.47, 95% CI 1.462–4.183), and diabetes (OR 3.159, 95% CI 2.129–4.687) were associated with hypertension. For society support, individuals in the lowest quintile were more likely to suffer hypertension. Concentration index results suggested that different income groups did not show inequality on hypertension incidence. Elder age, male, overweight, diabetes, and poor society support were suggested to be associated with hypertension incidence among middle-aged and elderly individuals in China. Our study provides implications for controlling and managing hypertension.

Current realities versus theoretical optima: quantifying efficiency and sociospatial equity of travel time to hospitals in low-income and middle-income countries

Background

Having hospitals located in urban areas where people, resources and wealth concentrate is efficient, but leaves long travel times for the rural and often poorer population and goes against the equity objective. We aimed to assess the current efficiency (mean travel time in the whole population) and equity (difference in travel time between the poorest and least poor deciles) of hospital care provision in four sub-Saharan African countries, and to compare them against their theoretical optima.

Methods

We overlaid the locations of 480, 115, 3787 and 256 hospitals in Kenya, Malawi, Nigeria and Tanzania, respectively, with high-resolution maps of travel time, population and wealth to estimate current efficiency and equity. To identify the potential optima, we simulated 7500 sets of hospitals locations based on various population and wealth weightings and percentage reallocations for each country.

Results

The average travel time ranged from 38 to 79 min across countries, and the respective optima were mildly shorter (<15%). The observed equity gaps were wider than their optima. Compared with the best case scenarios, differences in the equity gaps varied from 7% in Tanzania to 77% in Nigeria. In Kenya, Malawi and Tanzania, narrower equity gaps without increasing average travel time were seen from simulations that held 75%–90% of hospitals at their current locations.

Interpretations

Current hospital distribution in the four sub-Saharan African countries could be considered efficient. Simultaneous gains in efficiency and equity do not necessarily require a fundamental redesign of the healthcare system. Our analytical approach is readily extendible to aid decision support in adding and upgrading existing hospitals.

Malaria, medicines and miles: A novel approach to measuring access to treatment from a household perspective

Nearly a decade after the adoption of confirmed diagnosis and artemisinin combination therapy (ACT) for the treatment of uncomplicated falciparum malaria, a large treatment gap persists. We describe a novel approach of combining data from households and the universe of treatment sources in their vicinities to produce nationally representative indicators of physical and financial access to malaria care from the household's perspective in Benin, Nigeria, Uganda and Zambia. We compare differences in access across urban and rural areas, countries, and over time. In 2009, more urban households had a provider stocking ACT within 5 km than rural households. By 2012, this physical ACT access gap had largely been closed in Uganda, and progress had been made in Benin and Nigeria; but the gap persisted in Zambia. The private sector helped to fill this gap in rural areas. Improvements in Nigeria and Uganda were driven largely by increased ACT availability in licensed drug stores, and in Benin by increased availability in unregulated open-air market stalls. Free or subsidised ACT from public and non-profit facilities continued to be available to many households by 2012, but much less so in rural areas. Where private sector expansion increased physical access to ACT, these additional options were on average more expensive. Also by 2012, the majority of urban households in all four countries had access to a provider nearby offering malaria diagnostic services; however, this access remained low for rural households in Benin, Nigeria and Zambia. The methods developed in this study could improve how access to healthcare is measured in low- and middle-income country settings, particularly where private for-profit providers are an important source of care, and for conditions that may be treated by informal providers. The method could also lead to better explanations of the performance of complex interventions aiming to improve healthcare access.

Assessment of Inequalities in Coverage of Essential Reproductive, Maternal, Newborn, Child, and Adolescent Health Interventions in Kenya

IMPORTANCE

Previous work has underscored subnational inequalities that could impede additional health gains in Kenya.

OBJECTIVE

To provide a comprehensive assessment of the burden, distribution, and change in inequalities in reproductive, maternal, newborn, child, and adolescent health (RMNCAH) interventions in Kenya from 2003 to 2014.

DESIGN, SETTING, AND PARTICIPANTS

This population-based cross-sectional study used data from the 2003, 2008, and 2014 Kenya Demographic and Health Surveys. The study included women of reproductive age (ages 15-49 years) and children younger than years, with national, regional, county, and subcounty level representation. Data analysis was conducted from April 2018 to November 2018.

EXPOSURES

Socioeconomic position that was derived from asset indices and presented as wealth quintiles. Urban and rural residence and regions of Kenya were also considered.

MAIN OUTCOMES AND MEASURES

Absolute and relative measures of inequality in coverage of RMNCAH interventions.

RESULTS

For this analysis, representative samples of 31 380 women of reproductive age and 29 743 children younger than 5 years from across Kenya were included. The RMNCAH interventions examined demonstrated pro-rich and bottom inequality patterns. The most inequitable interventions were skilled birth attendance, family planning needs satisfied, and 4 or more antenatal care visits, whereby the absolute difference in coverage between the wealthiest (quintile 5) and poorest quintiles (quintile 1) was 61.6% (95% CI, 60.1%-63.1%), 33.4% (95% CI, 31.9%-34.9%), and 31.0% (95% CI, 30.5%-31.6%), respectively. The most equitable intervention was early initiation of breastfeeding, with an absolute difference (quintile 5 minus quintile 1) of -7.9% (95% CI, -11.1% to -4.8%), although antenatal care (1 visit) and diphtheria-tetanus-pertussis immunization (3 doses) demonstrated the best combination of high coverage and low inequalities. Our geospatial analysis revealed significant socioeconomic disparities in the northern and eastern regions of Kenya that have translated to suboptimal intervention coverage. A significant gap remains for rural, disadvantaged populations.

CONCLUSIONS AND RELEVANCE

Coverage of RMNCAH interventions has improved over time, but wealth and geospatial inequalities in Kenya are persistent. Policy and programming efforts should place more emphasis on improving the accessibility of health facility-based interventions, which generally demonstrate poor coverage and high inequalities, and focus on integrated approaches to maternal health service delivery at the community level when access is poor. Scaling up of health services for the urban and, in particular, rural poor areas and those residing in Kenya's former north eastern province will contribute toward achievement of universal health coverage.

An assessment of equity in the distribution of non-financial health care inputs across public primary health care facilities in Tanzania

BACKGROUND

There is limited evidence on how health care inputs are distributed from the sub-national level down to health facilities and their potential influence on promoting health equity. To address this gap, this paper assesses equity in the distribution of health care inputs across public primary health facilities at the district level in Tanzania.

METHODS

This is a quantitative assessment of equity in the distribution of health care inputs (staff, drugs, medical supplies and equipment) from district to facility level. The study was carried out in three districts (Kinondoni, Singida Rural and Manyoni district) in Tanzania. These districts were selected because they were implementing primary care reforms. We administered 729 exit surveys with patients seeking out-patient care; and health facility surveys at 69 facilities in early 2014. A total of seventeen indices of input availability were constructed with the collected data. The distribution of inputs was considered in relation to (i) the wealth of patients accessing the facilities, which was taken as a proxy for the wealth of the population in the catchment area; and (ii) facility distance from the district headquarters. We assessed equity in the distribution of inputs through the use of equity ratios, concentration indices and curves.

RESULTS

We found a significant pro-rich distribution of clinical staff and nurses per 1000 population. Facilities with the poorest patients (most remote facilities) have fewer staff per 1000 population than those with the least poor patients (least remote facilities): 0.6 staff per 1000 among the poorest, compared to 0.9 among the least poor; 0.7 staff per 1000 among the most remote facilities compared to 0.9 among the least remote. The negative concentration index for support staff suggests a pro-poor distribution of this cadre but the 45 degree dominated the concentration curve. The distribution of vaccines, antibiotics, anti-diarrhoeal, anti-malarials and medical supplies was approximately proportional (non dominance), whereas the distribution of oxytocics, anti-retroviral therapy (ART) and anti-hypertensive drugs was pro-rich, with the 45 degree line dominating the concentration curve for ART.

CONCLUSION

This study has shown there are inequities in the distribution of health care inputs across public primary care facilities. This highlights the need to ensure a better coordinated and equitable distribution of inputs through regular monitoring of the availability of health care inputs and strengthening of reporting systems.

Place of Residence Moderates the Risk of Infant Death in Kenya: Evidence from the Most Recent Census 2009

Background

Substantial progress has been made in reducing childhood mortality worldwide from 1990–2015 (Millennium Development Goal, target 4). Achieving target goals on this however remains a challenge in Sub-Saharan Africa. Kenya’s infant mortality rates are higher than the global average and are more pronounced in urban areas as compared to rural areas. Only limited knowledge exists about the differences in individual level risk factors for infant death among rural, non-slum urban, and slum areas in Kenya. Therefore, this paper aims at 1) assess individual and socio-ecological risk factors for infant death in Kenya, and at 2) identify whether living in rural, non-slum urban, or slum areas moderated individual or socio-ecological risk factors for infant death in Kenya.

Methodology

We used a cross-sectional study design based on the most recent Kenya Population and Housing Census of 2009 and extracted the records of all females who had their last child born in 12 months preceding the survey (N = 1,120,960). Multivariable regression analyses were used to identify risk factors that accounted for the risk of dying before the age of one at the individual level in Kenya. Place of residence (rural, non-slum urban, slum) was used as an interaction term to account for moderating effects in individual and socio-ecological risk factors.

Results

Individual characteristics of mothers and children (older age, less previously born children that died, better education, girl infants) and household contexts (better structural quality of housing, improved water and sanitation, married household head) were associated with lower risk for infant death in Kenya. Living in non-slum urban areas was associated with significantly lower infant death as compared to living in rural or slum areas, when all predictors were held at their reference levels. Moreover, place of residence was significantly moderating individual level predictors: As compared to rural areas, living in urban areas was a protective factor for mothers who had previous born children who died, and who were better educated. However, living in urban areas also reduced the health promoting effects of better structural quality of housing (i.e. poor or good versus non-durable). Furthermore, durable housing quality in urban areas turned out to be a risk factor for infant death as compared to rural areas. Living in slum areas was also a protective factor for mothers with previous child death, however it also reduced the promoting effects of older ages in mothers.

Conclusions

While urbanization and slum development continues in Kenya, public health interventions should invest in healthy environments that ideally would include improvements to access to safe water and sanitation, better structural quality of housing, and to access to education, health care, and family planning services, especially in urban slums and rural areas. In non-slum urban areas however, health education programs that target healthy diets and promote physical exercise may be an important adjunct to these structural interventions.

Implementation of patient charges at primary care facilities in Kenya: implications of low adherence to user fee policy for users and facility revenue

With user fees now seen as a major hindrance to universal health coverage, many countries have introduced fee reduction or elimination policies, but there is growing evidence that adherence to reduced fees is often highly imperfect. In 2004, Kenya adopted a reduced and uniform user fee policy providing fee exemptions to many groups. We present data on user fee implementation, revenue and expenditure from a nationally representative survey of Kenyan primary health facilities. Data were collected from 248 randomly selected public health centres and dispensaries in 2010, comprising an interview with the health worker in charge, exit interviews with curative outpatients, and a financial record review. Adherence to user fee policy was assessed for eight tracer conditions based on health worker reports, and patients were asked about actual amounts paid. No facilities adhered fully to the user fee policy across all eight tracers, with adherence ranging from 62.2% for an adult with tuberculosis to 4.2% for an adult with malaria. Three quarters of exit interviewees had paid some fees, with a median payment of US dollars (USD) 0.39, and a quarter of interviewees were required to purchase additional medical supplies at a later stage from a private drug retailer. No consistent pattern of association was identified between facility characteristics and policy adherence. User fee revenues accounted for almost all facility cash income, with average revenue of USD 683 per facility per year. Fee revenue was mainly used to cover support staff, non-drug supplies and travel allowances. Adherence to user fee policy was very low, leading to concerns about the impact on access and the financial burden on households. However, the potential to ensure adherence was constrained by the facilities' need for revenue to cover basic operating costs, highlighting the need for alternative funding strategies for peripheral health facilities.