Healthy Firms: Constraints to Growth among Private Health Sector Facilities in Ghana and Kenya

Background: Health outcomes in developing countries continue to lag the developed world, and many countries are not on target to meet the Millennium Development Goals. The private health sector provides much of the care in many developing countries (e.g., approximately 50 percent in Sub-Saharan Africa), but private providers are often poorly integrated into the health system. Efforts to improve health systems performance will need to include the private sector and increase its contributions to national health goals. However, the literature on constraints private health care providers face is limited. Methodology/Principal Findings: We analyze data from a survey of private health facilities in Kenya and Ghana to evaluate growth constraints facing private providers. A significant portion of facilities (Ghana: 62 percent; Kenya: 40 percent) report limited access to finance as the most significant barrier they face; only a small minority of facilities report using formal credit institutions to finance day to day operations (Ghana: 6 percent; Kenya: 11 percent). Other important barriers include corruption, crime, limited demand for goods and services, and poor public infrastructure. Most facilities have paper-based rather than electronic systems for patient records (Ghana: 30 percent; Kenya: 22 percent), accounting (Ghana: 45 percent; Kenya: 27 percent), and inventory control (Ghana: 41 percent; Kenya: 24 percent). A majority of clinics in both countries report undertaking activities to improve provider skills and to monitor the level and quality of care they provide. However, only a minority of pharmacies report undertaking such activities

Impact of home-based management of malaria on health outcomes in Africa: a systematic review of the evidence

BACKGROUND: Home-based management of malaria (HMM) is promoted as a major strategy to improve prompt delivery of effective malaria treatment in Africa. HMM involves presumptively treating febrile children with pre-packaged antimalarial drugs distributed by members of the community. HMM has been implemented in several African countries, and artemisinin-based combination therapies (ACTs) will likely be introduced into these programmes on a wide scale. CASE PRESENTATIONS: The published literature was searched for studies that evaluated the health impact of community- and home-based treatment for malaria in Africa. Criteria for inclusion were: 1) the intervention consisted of antimalarial treatment administered presumptively for febrile illness; 2) the treatment was administered by local community members who had no formal education in health care; 3) measured outcomes included specific health indicators such as malaria morbidity (incidence, severity, parasite rates) and/or mortality; and 4) the study was conducted in Africa. Of 1,069 potentially relevant publications identified, only six studies, carried out over 18 years, were identified as meeting inclusion criteria. Heterogeneity of the evaluations, including variability in study design, precluded meta-analysis. DISCUSSION AND EVALUATION: All trials evaluated presumptive treatment with chloroquine and were conducted in rural areas, and most were done in settings with seasonal malaria transmission. Conclusions regarding the impact of HMM on morbidity and mortality endpoints were mixed. Two studies showed no health impact, while another showed a decrease in malaria prevalence and incidence, but no impact on mortality. One study in Burkina Faso suggested that HMM decreased the proportion of severe malaria cases, while another study from the same country showed a decrease in the risk of progression to severe malaria. Of the four studies with mortality endpoints only one from Ethiopia showed a positive impact, with a reduction in the under-5 mortality rate of 40.6% (95% CI 29.2 - 50.6). CONCLUSION: Currently the evidence base for HMM in Africa, particularly regarding use of ACTs, is narrow and priorities for further research are discussed. To optimize treatment and maximize health benefits, drug regimens and delivery strategies in HMM programmes may need to be tailored to local conditions. Additional research could help guide programme development, policy decision-making, and implementation

Using a community-based definition of poverty for targeting poor households for premium subsidies in the context of a community health insurance in Burkina Faso

Background: One of the biggest challenges in subsidizing premiums of poor households for community health insurance is the identification and selection of these households. Generally, poverty assessments in developing countries are based on monetary terms. The household is regarded as poor if its income or consumption is lower than a predefined poverty cut-off. These measures fail to recognize the multi-dimensional character of poverty, ignoring community members? perception and understanding of poverty, leaving them voiceless and powerless in the identification process. Realizing this, the steering committee of Nouna's health insurance devised a method to involve community members to better define `perceived? poverty, using this as a key element for the poor selection. The community-identified poor were then used to effectively target premium subsidies for the insurance scheme. Methods: The study was conducted in the Nouna's Health District located in northwest Burkina Faso. Participants in each village were selected to take part in focus-group discussions (FGD) organized in 41 villages and 7 sectors of Nouna's town to discuss criteria and perceptions of poverty. The discussions were audio recorded, transcribed and analyzed in French using the software NVivo 9. Results: From the FGD on poverty and the subjective definitions and perceptions of the community members, we found that poverty was mainly seen as scarcity of basic needs, vulnerability, deprivation of capacities, powerlessness, voicelessness, indecent living conditions, and absence of social capital and community networks for support in times of need. Criteria and poverty groups as described by community members can be used to identify poor who can then be targeted for subsidies. Conclusion: Policies targeting the poorest require the establishment of effective selection strategies. These policies are well-conditioned by proper identification of the poor people. Community perceptions and criteria of poverty are grounded in reality, to better appreciate the issue. It is crucial to take these perceptions into account in undertaking community development actions which target the poor. For most community-based health insurance schemes with limited financial resources, using a community-based definition of poverty in the targeting of the poorest might be a less costly alternative

Clostridium difficile infection.

Infection of the colon with the Gram-positive bacterium Clostridium difficile is potentially life threatening, especially in elderly people and in patients who have dysbiosis of the gut microbiota following antimicrobial drug exposure. C. difficile is the leading cause of health-care-associated infective diarrhoea. The life cycle of C. difficile is influenced by antimicrobial agents, the host immune system, and the host microbiota and its associated metabolites. The primary mediators of inflammation in C. difficile infection (CDI) are large clostridial toxins, toxin A (TcdA) and toxin B (TcdB), and, in some bacterial strains, the binary toxin CDT. The toxins trigger a complex cascade of host cellular responses to cause diarrhoea, inflammation and tissue necrosis - the major symptoms of CDI. The factors responsible for the epidemic of some C. difficile strains are poorly understood. Recurrent infections are common and can be debilitating. Toxin detection for diagnosis is important for accurate epidemiological study, and for optimal management and prevention strategies. Infections are commonly treated with specific antimicrobial agents, but faecal microbiota transplants have shown promise for recurrent infections. Future biotherapies for C. difficile infections are likely to involve defined combinations of key gut microbiota