Dataset Information

Has Tanzania embraced the green leaf? Results from outlet and household surveys before and after implementation of the Affordable Medicines Facility-malaria.

ABSTRACT:

Background

The Affordable Medicines Facility-malaria (AMFm) is primarily an artemisinin combination therapy (ACT) subsidy, aimed at increasing availability, affordability, market share and use of quality-assured ACTs (QAACTs). Mainland Tanzania was one of eight national scale programmes where AMFm was introduced in 2010. Here we present findings from outlet and household surveys before and after AMFm implementation to evaluate its impact from both the supply and demand side.

Methods

Outlet surveys were conducted in 49 randomly selected wards throughout mainland Tanzania in 2010 and 2011, and data on outlet characteristics and stocking patterns were collected from outlets stocking antimalarials. Household surveys were conducted in 240 randomly selected enumeration areas in three regions in 2010 and 2012. Questions about treatment seeking for fever and drugs obtained were asked of individuals reporting fever in the previous two weeks.

Results

The availability of QAACTs increased from 25.5% to 69.5% among all outlet types, with the greatest increase among pharmacies and drug stores, together termed specialised drug sellers (SDSs), where the median QAACT price fell from $5.63 to $0.94. The market share of QAACTs increased from 26.2% to 42.2%, again with the greatest increase in SDSs. Household survey results showed a shift in treatment seeking away from the public sector towards SDSs. Overall, there was no change in the proportion of people with fever obtaining an antimalarial or ACT from baseline to endline. However, when broken down by treatment source, ACT use increased significantly among clients visiting SDSs.

Discussion

Unchanged ACT use overall, despite increases in QAACT availability, affordability and market share in the private sector, reflected a shift in treatment seeking towards private providers. The reasons for this shift are unclear, but likely reflect both persistent stockouts in public facilities, and the increased availability of subsidised ACTs in the private sector.

SUBMITTER: Thomson R

PROVIDER: S-EPMC4015933 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Calls have been made for improved measurement of coverage for maternal, newborn and child health interventions. Recently, methods linking household and health facility surveys have been used to improve estimation of intervention coverage. However, linking methods rely the availability of household and health facility surveys which are temporally matched. Because nationally representative health facility assessments are not yet routinely conducted in many low and middle income countries, estimates of intervention coverage based on linking methods can be produced for only a subset of countries. Estimates of intervention coverage are a critical input for modelling the health impact of intervention scale-up in the Lives Saved Tool (LiST). The purpose of this study was to develop a data-driven approach to estimate coverage for a subset of antenatal care interventions modeled in LiST.Using a five-step process, estimates of population level coverage for syphilis detection and treatment, case management of diabetes, malaria infection, hypertensive disorders, and pre-eclampsia, were computed by linking household and health facility surveys. Based on data characterizing antenatal care and estimates of coverage derived from the linking approach, predictive models for intervention coverage were developed. Updated estimates of coverage based on the predictive models were compared, first with current default proxies, then with estimates based on the linking approach. Model fit and accuracy were assessed using three measures: the coefficient of determination, Pearson's correlation coefficient, and the root mean square error (RMSE).The ability to predict intervention coverage was fairly accurate across all interventions considered. Predictive models accounted for 20-63% of the variance in intervention coverages, and correlation coefficients ranged from 0.5 to 0.83. The predictive model used to estimate coverage of management of pre-eclampsia performed relatively better (RMSE = 0.11) than the model estimating coverage of diabetes case management (RMSE = 0.19).The new approach to estimate coverage represents an improvement over current default proxies in LiST. As the availability of reliable coverage data improves, impact estimates generated by LiST will improve. This study underscores the need for continued efforts to improve coverage measurement, while bringing to the fore the importance of health facility assessments as complementary data sources.

Project description:BackgroundLinking facility and household surveys through geographic methods is a popular technique to draw conclusions about the relationship between health services and population health outcomes at local levels. These methods are useful tools for measuring effective coverage and tracking progress towards Universal Health Coverage, but are understudied. This paper compares the appropriateness of several geospatial methods used for linking individuals (within displaced survey cluster locations) to their source of family planning (at undisplaced health facilities) at a national level.MethodsIn Malawi, geographic methods linked a population health survey, rural clusters from the Woman's Questionnaire of the 2015 Malawi Demographic and Health Survey (MDHS 2015), to Malawi's national health facility census to understand the service environment where women receive family planning services. Individuals from MDHS 2015 clusters were linked to health facilities through four geographic methods: (i) closest facility, (ii) buffer (5 km), (iii) administrative boundary, and (iv) a newly described theoretical catchment area method. Results were compared across metrics to assess the number of unlinked clusters (data lost), the number of linkages per cluster (precision of linkage), and the number of women linked to their last source of modern contraceptive (appropriateness of linkage).ResultsThe closest facility and administrative boundary methods linked every cluster to at least one facility, while the 5-km buffer method left 288 clusters (35.3%) unlinked. The theoretical catchment area method linked all but one cluster to at least one facility (99.9% linked). Closest facility, 5-km buffer, administrative boundary, and catchment methods linked clusters to 1.0, 1.4, 21.1, and 3.3 facilities on average, respectively. Overall, the closest facility, 5-km buffer, administrative boundary, and catchment methods appropriately linked 64.8%, 51.9%, 97.5%, and 88.9% of women to their last source of modern contraceptive, respectively.ConclusionsOf the methods studied, the theoretical catchment area linking method loses a marginal amount of population data, links clusters to a relatively low number of facilities, and maintains a high level of appropriate linkages. This linking method is demonstrated at scale and can be used to link individuals to qualities of their service environments and better understand the pathways through which interventions impact health.

Project description:IntroductionPrivate sector drug shops are an important source of medicines in Tanzania. In 2003, the government introduced the accredited drug dispensing outlet (ADDO) program to improve access to good-quality medicines in rural and peri-urban areas that have frequent drug shortages in public health facilities and few or no registered pharmacies. However, increasing access may also contribute to antimicrobial resistance (AMR) due to the potential overuse and misuse of drugs.MethodsWe conducted a cross-sectional household survey in four regions in mainland Tanzaniato characterize consumer care-seeking habits and medicines use and to determine the extent to which members of the community are knowledgeable about antimicrobials and AMR. Within the regions, we applied a multistage cluster sampling design, cascading from districts, wards, and villages to households. Multivariate logistic analysis was done to determine variables influencing knowledge of antimicrobials and AMR, while controlling for confounding factors. Variables included age, occupation, level of education, membership in an insurance scheme, and wealth status.Results and discussionWe revealed that communities in four Tanzanian regions have low levels of knowledge of the concepts of antimicrobials and their use and AMR. Level of public understanding rose with wealth status and education. Only one-third of 1,200 respondents (33.6%) had ever heard of a medicine called an antimicrobial, and 5-15% could name at least one antimicrobial spontaneously. Some thought other medicines, such as paracetamol were antimicrobial (7.5%). People were equally likely to agree that pneumonia should be treated with an antimicrobial (21.4%) as well as common cold (28.4%). Understanding of AMR risks was better, particularly related to HIV and AIDS (32.2%) and malaria (38.6%)-most likely due to information campaigns focused on those two diseases. The level of knowledge decreased the further away respondents lived from an ADDO (p = 0.0001) and where ADDO density was lower (p = 0.001), which supports the use of ADDO dispensers as sources of community information and change agents for more appropriate medicine use.ConclusionLack of knowledge about antimicrobials and AMR in Tanzanian communities needs to be addressed through multi-pronged strategies that focus on prescribers and the public-especially those who are poorer and less educated.

Project description:The 2011 United Nations (UN) General Assembly Political Declaration on Prevention and Control of Non-Communicable Diseases (NCDs) brought NCDs to the global health agenda. Essential medicines are central to treating chronic diseases such as hypertension and diabetes. Our study aimed to quantify access to essential medicines for people with chronic conditions in five low- and middle-income countries and to evaluate how household socioeconomic status and perceptions about medicines availability and affordability influence access. We analysed data for 1867 individuals with chronic diseases from national surveys (Ghana, Jordan, Kenya, Philippines and Uganda) conducted in 2007-10 using a standard World Health Organization (WHO) methodology to measure medicines access and use. We defined individuals as having access to medicines if they reported regularly taking medicine for a diagnosed chronic disease and data collectors found a medicine indicated for that disease in their homes. We used logistic regression models accounting for the clustered survey design to investigate determinants of keeping medicines at home and predictors of access to medicines for chronic diseases. Less than half of individuals previously diagnosed with a chronic disease had access to medicines for their condition in every country, from 16% in Uganda to 49% in Jordan. Other than reporting a chronic disease, higher household socioeconomic level was the most significant predictor of having any medicines available at home. The likelihood of having access to medicines for chronic diseases was higher for those with medicines insurance coverage [highest adjusted odds ratio (OR) 3.12 (95% confidence intervals (CI): 1.38, 7.07)] and lower for those with past history of borrowing money to pay for medicines [lowest adjusted OR 0.56 (95% CI: 0.34, 0.92)]. Our study documents poor access to essential medicines for chronic conditions in five resource-constrained settings. It highlights the importance of financial risk protection and consumer education about generic medicines in global efforts towards improving treatment of chronic diseases.

Project description:IntroductionImproving the impact of nutrition interventions requires adequate measurement of both reach and quality of interventions, but limited evidence exists on advancing coverage measurement. We adjusted contact-based coverage estimates, taking into consideration the inputs required to deliver quality nutrition services, to calculate input-adjusted coverage of nutrition interventions across the continuum of care from pregnancy through early childhood in Bangladesh.MethodsWe used data from the 2014 Bangladesh Demographic and Health Surveys to assess use of maternal and child health services and the 2014 Service Provision Assessment to determine facility readiness to deliver nutrition interventions. Service readiness captured availability of nutrition-specific inputs (including human resources and training, equipment, diagnostics and medicines). Contact coverage was combined with service readiness to create a measure of input-adjusted coverage at the national and regional levels, across place of residence, and by maternal education and household socioeconomic quintiles.ResultsContact coverage varied from 28% for attending at least four ANC visits to 38% for institutional delivery, 35% for child growth monitoring and 81% for sick child care. Facilities demonstrated incomplete readiness for nutrition interventions, ranging from 48% to 51% across services. Nutrition input-adjusted coverage was suboptimal (18% for ANC, 23% for institutional delivery, 20% for child growth monitoring and 52% for sick child care) and varied between regions within the country. Inequalities in input-adjusted coverage were large during ANC and institutional delivery (14-17 percentage points (pp) between urban and rural areas, 15 pp between low and high education, and 28-34 pp between highest and lowest wealth quintiles) and less variable for sick child care (<2 pp).ConclusionNutrition input-adjusted coverage was suboptimal and varied subnationally and across the continuum of care in Bangladesh. Special efforts are needed to improve the reach as well as the quality of health and nutrition services to achieve the Sustainable Development Goals.