August Kuwawenaruwa

Background: Tanzania has made considerable gains in children’s nutrition between 1991/92 and 2022. The country’s stunting rate has decreased from 50% in 1992 to 30% in 2022. However, stunting varies greatly among regions. The purpose of this study was to examine regional trends in stunting rates and associated characteristics related to the risk of being stunted among children under the age of five in Tanzania. Methods: Descriptive statistics were used to summarize the data on stunting, from the Tanzania Demographic and Health Survey (TDHS) data. A total of 42,408 under-five children from repeated TDHS cross-sectional studies conducted in 1991–1992 (n = 6,585), 1996 (n = 5,438), 1999 (n = 2,555), 2004–2005 (n = 7,230), 2009–2010 (n = 6,792), 2015–2016 (n = 9,001), and 2022 (n = 4,807) were analysed to examine trends in stunting and its associated characteristics in the country. Frequencies and percentages were calculated and presented in tables and graphs as cross-sectional data points. A multivariable logistic regression model was estimated to identify factors associated with stunting in 2022. All analyses have been weighted using the weighting generated by the TDHS. STATA version 15 was used for data management and analysis. Results: Over the previous three decades, stunting rates in boys under five have consistently been 4-7 percentage points (ppt) higher than those in girls of the same age. The prevalence of stunted children was greater in households with the lowest socioeconomic status (SES) (38.6%) compared to those with the highest SES (12.6%). Similar to the trend analysis, a multivariable regression analysis found that residency in the Southern Highlands (AOR = 2.368; 95% CI: 1.746-3.212, p < 0.001), male children (AOR = 1.583 [95% CI: 1.349 - 1.858], p < 0.001), low birth weight (AOR = 3.639 [95% CI: 2.279 - 5.810], p < 0.001), maternal exposure to alcohol (AOR = 1.440 [95% CI: 1.057 – 1.963], p < 0.05), and unimproved sanitation facilities (AOR = 1.345 [95% CI: 1.055 – 1.714], p < 0.05) were significantly associated with a higher risk of stunting. In contrast, a birth interval of 24 to 47 months (AOR = 0.762 [95% CI: 0.598 - 0.969], p < 0.001), a high level of maternal education (AOR = 0.715 [95% CI: 0.530 – 0.963], p < 0.05), and high socioeconomic status (AOR = 0.268 [95% CI: 0.178 – 0.403], p < 0.001) were significantly associated with a lower risk of stunting. Conclusion: Although child stunting has decreased in the country, it remains a major challenge in Tanzania, driven by factors such as residing in the Southern Highlands, child and maternal issues, and household economic and environmental factors. To combat stunting and eliminate structural obstacles, including the empowerment of marginalised groups, a multisectoral strategy is required. Furthermore, current regulations and standards place more emphasis on educating mothers about diet and health than on empowering them economically.

Background: Many countries’ health systems are implementing reforms to improve the functioning and performance of the Health Management Information System (HMIS) to facilitate evidence-based decisions for delivery of accessible and quality health services. However, in some countries such efforts and initiatives have led to a complex HMIS ecosystem characterized by multiple and fragmented sub-systems. We undertook an in-depth analysis of the HMIS ecosystem in Tanzania to inform the ongoing initiatives, by understanding the relationship and power differences among stakeholders, as well as drivers and barriers to HMIS investment and strengthening. Methodology: This was a qualitative research method incorporating data collection through document review and key informant interviews guided by political economy analytical framework. A total of 17 key informant interviews were conducted between April and May 2022. A thematic content analysis was used during data analysis. Results: Good relationship between the government and stakeholders dealing/supporting HMIS ecosystem was noted as there are technical working groups which brings stakeholders together to discuss and harmonize HMIS activities. The ‘need for the data’ has been the driving force toward investment in the HMIS ecosystem. The analysis showed that the government is the main stakeholder within the HMIS ecosystem and responsible for identifying the needs for improvement and has the power to approve or reject systems which are not in line with the government priority as stipulated with the HMIS investment roadmap/strategy. Moreover, partners with long relationship are powerful in influencing HMIS investment decision-making compared to those who are recently coming to support. It was further noted shortage of staff with technical competence, inadequate financial resources, and the development of fact that some of the existing systems have not been developed to their full capacity and have hindered the whole systems’ integration and interoperability exercise of ensuring integration and interoperability of the systems. Conclusion: A need-based assessment of staff capacity at the sub-national level is equally important to identify available capabilities and the knowledge gap to strengthen the HMIS ecosystem. Strong coordination of the ideas and resources intended to strengthen the HMIS ecosystem would help to reduce fragmentation. In addition, there is a need to mobilize resources within and outside the country to facilitate the integration and interoperability process smoothly.

Objective This study aimed to model the long-term cost associated with expanding public health insurance coverage in Tanzania. Design, setting and participants We analysed the 2016 claims of 2 923 524 beneficiaries of the National Health Insurance Fund in Tanzania. The analysis focused on determining the average cost per beneficiary across 5-year age groups separated by gender, and grouped by broad health condition categories. We then modelled three different insurance coverage scenarios from 2020 to 2050 and we estimated the associated costs. Outcome measures Average cost per beneficiary and the projected financing requirements, projected from 2020 to 2050. Results The analysis revealed that the average per beneficiary cost for insurance claims was $38.58. Among males over 75 years, the average insurance claims costs were highest, amounting to $125. The total estimated annual cost of claims in 2020 was $151 million. Under the status quo coverage scenario, total claims were projected to increase to $415 million by 2050. Increasing coverage from 7% to 50% would result in an additional financing requirement of $2.27 billion. If coverage would increase by 10% annually, reaching 56% of the population by 2050, the additional financing need would amount to $2.84 billion. Conclusion This study highlights the critical importance of assessing the long-term financial viability of health insurance schemes aimed to cover large segments of the population in low-income countries. The findings demonstrate that even without expansion of coverage, financing requirements for insurance will more than triple by 2050. Furthermore, increasing coverage is likely to substantially escalate the cost of claims, potentially requiring significant government or external contributions to finance these additional costs. Policymakers and stakeholders should carefully evaluate the sustainability of insurance schemes to ensure adequate financial support for expanding coverage and improving healthcare access in low-income settings.

Background The resources for critical care are limited in many settings, exacerbating the significant morbidity and mortality associated with critical illness. Budget constraints can lead to choices between investing in advanced critical care (e.g. mechanical ventilators in intensive care units) or more basic critical care such as Essential Emergency and Critical Care (EECC; e.g. vital signs monitoring, oxygen therapy, and intravenous fluids). Methods We investigated the cost effectiveness of providing EECC and advanced critical care in Tanzania in comparison with providing ‘no critical care’ or ‘district hospital-level critical care’ using coronavirus disease 2019 (COVID-19) as a tracer condition. We developed an open-source Markov model (https://github.com/EECCnetwork/POETIC_CEA) to estimate costs and disability-adjusted life-years (DALYs) averted, using a provider perspective, a 28-day time horizon, patient outcomes obtained from an elicitation method involving a seven-member expert group, a normative costing study, and published literature. We performed a univariate and probabilistic sensitivity analysis to assess the robustness of our results., Results EECC is cost effective 94% and 99% of the time when compared with no critical care (incremental cost-effectiveness ratio [ICER] $37 [−$9 to $790] per DALY averted) and district hospital-level critical care (ICER $14 [−$200 to $263] per DALY averted), respectively, relative to the lowest identified estimate of the willingness-to-pay threshold for Tanzania ($101 per DALY averted). Advanced critical care is cost effective 27% and 40% of the time, when compared with the no critical care or district hospital-level critical care scenarios, respectively. Conclusion For settings where there is limited or no critical care delivery, implementation of EECC could be a highly cost-effective investment. It could reduce mortality and morbidity for critically ill COVID-19 patients, and its cost effectiveness falls within the range considered ‘highly cost effective’. Further research is needed to explore the potential of EECC to generate even greater benefits and value for money when patients with diagnoses other than COVID-19 are accounted for.

Objectives Critical care is essential in saving lives of critically ill patients, however, provision of critical care across lower resource settings can be costly, fragmented and heterogenous. Despite the urgent need to scale up the provision of critical care, little is known about its availability and cost. Here, we aim to systematically review and identify reported resource use, availability and costs for the provision of critical care and the nature of critical care provision in Tanzania. Design This is a systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Data sources Medline, Embase and Global Health databases were searched covering the period 2010 to 17 November 2020. Eligibility criteria We included studies that reported on forms of critical care offered, critical care services offered and/or costs and resources used in the provision of care in Tanzania published from 2010. Data extraction and synthesis Quality assessment of the articles and data extraction was done by two independent researchers. The Reference Case for Estimating the Costs of Global Health Services and Interventions was used to assess quality of included studies. A narrative synthesis of extracted data was conducted. Costs were adjusted and reported in 2019 US$ and TZS using the World Bank GDP deflators. Results A total 31 studies were found to fulfil the inclusion and exclusion criteria. Critical care identified in Tanzania was categorised into: intensive care unit (ICU) delivered critical care and non-ICU critical care. The availability of ICU delivered critical care was limited to urban settings whereas non-ICU critical care was found in rural and urban settings. Paediatric critical care equipment was more scarce than equipment for adults. 15 studies reported on the costs of services related to critical care yet no study reported an average or unit cost of critical care. Costs of medication, equipment (eg, oxygen, personal protective equipment), services and human resources were identified as inputs to specific critical care services in Tanzania. Conclusion There is limited evidence on the resource use, availability and costs of critical care in Tanzania. There is a strong need for further empirical research on critical care resources availability, utilisation and costs across specialties and hospitals of different level in low/middle-income countries like Tanzania to inform planning, priority setting and budgeting for critical care services. PROSPERO registration number CRD42020221923.

Many low‐income countries are in the process of scaling up health insurance with the goal of achieving universal coverage. However, little is known about the usage and financial sustainability of mandatory health insurance. This study analyzes 26 million claims submitted to the Tanzanian National Health Insurance Fund (NHIF), which covers two million public servants for whom public insurance is mandatory, to understand insurance usage patterns, cost drivers, and financial sustainability. We find that in 2016, half of policyholders used a health service within a single year, with an average annual cost of 33 US$ per policyholder. About 10% of the population was responsible for 80% of the health costs, and women, middle‐age and middle‐income groups had the highest costs. Out of 7390 health centers, only five health centers are responsible for 30% of total costs. Estimating the expected health expenditures for the entire population based on the NHIF cost structure, we find that for a sustainable national scale‐up, policy makers will have to decide between reducing the health benefit package or increasing revenues. We also show that the cost structure of a mandatory insurance scheme in a low‐income country differs substantially from high‐income settings. Replication studies for other countries are warranted.

Background: Strategic health purchasing in low- and middle-income countries has received substantial attention as countries aim to achieve universal health coverage (UHC), by ensuring equitable access to quality health services without the risk of financial hardship. There is little evidence published from Tanzania on purchasing arrangements and what is required for strategic purchasing. This study analyses three purchasing arrangements in Tanzania and gives recommendations to strengthen strategic purchasing in Tanzania. Methods: We used the multi-case qualitative study drawing on the National Health Insurance Fund (NHIF), Social Health Insurance Benefit (SHIB), and improved Community Health Fund (iCHF) to explore the three purchasing arrangements with a purchaser-provider split. Data were drawn from document reviews and results were validated with nine key informant (KI) interviews with a range of actors involved in strategic purchasing. A deductive and inductive approach was used to develop the themes and framework analysis to summarize the data. Results: The findings show that benefit selection for all three schemes was based on the standard treatment guidelines issued by the Ministry of Health. Selection-contracting of the private healthcare providers are based on the location of the provider, the range of services available as stipulated in the scheme guideline, and the willingness of the provider to be contracted. NHF uses fee-for-service to reimburse providers. While SHIB and iCHF use capitation. NHIF has an electronic system to monitor registration, verification, claims processing, and referrals. While SHIB monitoring is done through routine supportive supervision and for the iCHF provider performance is monitored through utilization rates. Conclusion: Enforcing compliance with the contractual agreement between providers-purchasers is crucial for the provision of quality services in an efficient manner. Investment in a routine monitoring system, such as the use of the district health information system which allows effective tracking of healthcare service delivery, and broader population healthcare outcomes.

Introduction Economic analysis of supply chain management interventions to improve the availability of healthcare commodities at healthcare facilities is important in generating evidence for decision-makers. The current study assesses the cost and cost drivers for setting-up a public-private partnership programme in Tanzania in which all public healthcare facility orders for complementary medicines are pooled at the district level, and then purchased from one contracted supplier, the prime vendor (referred to as ‘Jazia Prime Vendor System’ (Jazia PVS)). Methods Financial and economic costs of Jazia PVS were collected retrospectively and using the ingredients approach. The financial costs were spread over the implementation period of January 2014–July 2019. In addition, we estimated the financial rollout costs of Jazia PVS to the other 23 regions in the country over 2 years (2018–2019). A multivariate sensitivity analysis was conducted on the estimates. Results Jazia PVS start-up and recurrent financial costs amounted to US$2 170 989.74 and US$709 302.32, respectively. The main cost drivers were costs for short-term experts, training of staff and healthcare workers and the Jazia PVS technical and board management activities. The start-up financial cost per facility was US$2819.47 and cost per capita was US$0.37. Conclusion In conclusion, the study provides useful information on the cost and cost drivers for setting-up a complementary pharmaceutical supply system to complement an existing system in low-income settings. Despite the substantial costs incurred in the initial investment and operations of the Jazia PVS, the new framework is effective in achieving the desired purpose of improving availability of healthcare commodities.

Background: Pharmaceutical supply chain management in low- and middle-income countries has received substantial attention to address the shortage of medicines at peripheral facilities. The focus has been on health system interventions, including the establishment of public-private partnerships (PPPs). In 2014, the United Republic of Tanzania began implementing the Jazia prime vendor system (Jazia PVS) with a contracted private wholesale supplier to complement the national medicines supply chain in public facilities. Few studies have investigated the acceptability of such a prime vendor system. This study analyses factors that contributed to the acceptability of Jazia PVS introduced in Tanzania. We used qualitative analytical methods to study experiences of Jazia PVS implementers in 4 districts in mid-2018. Methods: Data were drawn from 14 focus group discussions (FGDs), 7 group discussions (GDs) and 30 in-depth interviews (IDIs) with a range of actors involved in Jazia PVS. The study analysed 7 acceptability dimensions as defined in the acceptability framework by Sekhon et al. Framework analysis was adopted to summarise the results using a deductive and an inductive approach. Results: The findings show that participants’ acceptability of Jazia PVS was influenced by the increased availability of essential medicines at the facilities, higher order fulfilment rates, and timely delivery of the consignment. Furthermore, acceptability was also influenced by the good reputation of the prime vendor, close collaboration with district managers, and participants’ understanding that the prime vendor was meant to complement the existing supply chain. Intervention coherence, experienced opportunity cost and intervention burden, affective attitude and self-efficacy were also important in explaining the acceptability of the Jazia PVS. Conclusion: In conclusion, the most critical factor contributing to the acceptability of the Jazia PVS was the perceived effectiveness of the system in achieving its intended purpose. Districts purchasing directly from the prime vendor have a policy based on the possibility to increase availability of essential medicines at peripheral facilities in a low income setting; however, it is crucial to select a reputable and competent vendor, as well as to abide by the contractual agreements.