Health care prioritization process for the elderly in rural Tanzania under decentralized system: Prospects and challenges.

INTRODUCTION: Beginning the early 1990s, many countries globally adopted the third-generation health sector reforms with a focus of strengthening the primary health care system through community participation. On the contrary, three decades later, primary health care systems in many Low- and Middle-Income countries (LMICs) including Tanzania have remained weak. Specifically, priority setting for the vulnerable groups including the elderly have been weak. We aimed to analyse the prospects and challenges of the priority setting process for the elderly health care services following the 1990s health sector reforms in Tanzania. METHODS: We conducted an exploratory case study on priority setting process for the elderly healthcare services in Igunga and Nzega Tanzania. We carried out 24 Key Informant Interviews (KIIs) with the positions of District medical officers, social welfare, Medical Officers in-charge (MOI), planning officers and health system information focal person. Additionally, we carried out two focus group discussions (FGDs), one from each district with six participants from each group. Participants for the FGDs were MOI, health secretary, representative members of Health Facility Governing Committee (HFGC) and Council Health Management Team (CHMT). Data were analyzed using the qualitative content analysis. RESULTS: Two categories emerged from the analysis of the transcripts. These were the prospects and challenges in priority setting for the elderly population under the decentralized health sector in rural Tanzania. The prospects included; the capacity of the LGAs on priority setting; existence of strategies used by LGAs; availability of teamwork spirit and the existence of guidelines for priority setting at LGAs. The challenges included difficulties of elderly identification, insufficient resources to implement the planned activities at the LGAs, unintegrated digitalized government health information tools or programs at the LGAs, interference of LGAs by the Central Government and low interest of stakeholders on elderly health care. CONCLUSION: This study highlights the prospects and challenges facing priority setting for elderly care at the centralized health system in rural Tanzania. From the results the process is well organized but faces some challenges which if not addressed jeopardized and has potential to continue affecting the priority setting. Addressing the challenges highlighted requires joint efforts from both the elderly population in the community, healthcare providers and decision makers across all levels of the health system. This study serves as an eye-opener and calls for a bigger study to get a comprehensive picture of priority setting of the elderly health care in Tanzania.

Health, wealth, and medical expenditures among the elderly in rural Tanzania: experiences from Nzega and Igunga districts.

BACKGROUND: The per capita health expenditure (HE) and share of gross domestic product (GDP) spending on elderly healthcare are expected to increase. The gap between health needs and available resources for elderly healthcare is widening in many developing countries, like Tanzania, leaving the elderly in poor health. These conditions lead to catastrophic HEs for the elderly. This study aimed to analyse the association between measures of health, wealth, and medical expenditure in rural residents aged 60 years and above in Tanzania. METHODS: The data of this study were collected through a cross-sectional household survey to residents aged 60 years and above living in Nzega and Igunga districts using a standardised World Health Organization (WHO) Study on Global Ageing and Adult Health (SAGE) and European Quality of Life Five Dimension (EQ-5D) questionnaires. The quality of life (QoL) was estimated using EQ-5D weights. The wealth index was generated from principal component analysis (PCA). The linear regression analyses (outpatient/inpatient) were performed to analyse the association between measures of health, wealth, medical expenditure, and socio-demographic variables. RESULTS: This study found a negative and statistically significant association between QoL and HE, whereby HE increases with the decrease of QoL. We could not find any significant relationship between HE and social gradients. In addition, age influences HE such that as age increases, the HE for both outpatient and inpatient care also increases. CONCLUSION: The health system in these districts allocate resources mainly according to needs, and social position is not important. We thus conclude that the elderly of lower socio-economic status (SES) was subjected to similar health expenditure as those of higher socio-economic status. Health, not wealth, determines the use of medical expenditures.

Does health insurance contribute to improved utilization of health care services for the elderly in rural Tanzania? A cross-sectional study.

Background: Health care systems in developing countries such as Tanzania depend heavily on out-of-pocket payments. This mechanism contributes to inefficiency, inequity and cost, and is a barrier to patients seeking access to care. There are efforts to expand health insurance coverage to vulnerable groups, including older adults, in Sub-Saharan African countries. Objective: To analyse the association between health insurance and health service use in rural residents aged 60 and above in Tanzania. Methods: Data were obtained from a household survey conducted in the Nzega and Igunga districts. A standardised survey instrument from the World Health Organization Study on global AGEing and adult health was used. This comprised of questions regarding demographic and socio-economic characteristics, health and insurance status, health seeking behaviours, sickness history (three months and one year prior to the survey), and the receipt of health care. A multistage sampling method was used to select wards, villages and respondents in each district. Local ward and hamlet officers guided the researchers in identifying households with older people. Crude and adjusted logistic regression methods were used to explore associations between health insurance and outpatient and inpatient health care use. Results: The study sample comprised 1,899 people aged 60 and above of whom 44% reported having health insurance. A positive statistically significant association between health insurance and the utilisation of outpatient and inpatient care was observed in all models. The odds of using outpatient (adjusted OR = 2.20; 95% CI: 1.54, 3.14) and inpatient services (adjusted OR = 3.20; 95% CI: 2.46, 4.15) were higher among the insured. Conclusion: Health insurance is a predictor of outpatient and inpatient health services in people aged 60 and above in rural Tanzania. Further research is needed to understand the perceptions of both the insured and uninsured regarding the quality of care received.

Responsiveness of health care services towards the elderly in Tanzania: does health insurance make a difference? A cross-sectional study.

BACKGROUND: Responsiveness has become an important health system performance indicator in evaluating the ability of health care systems to meet patients' expectations. However, its measurement in sub-Saharan Africa remains scarce. This study aimed to assess the responsiveness of the health care services among the insured and non-insured elderly in Tanzania and to explore the association of health insurance (HI) with responsiveness in this population. METHODS: A community-based cross-sectional study was conducted in 2017 where a pre-tested household survey, administered to the elderly (60 + years) living in Igunga and Nzega districts, was applied. Participants with and without health insurance who attended outpatient and inpatient health care services in the past three and 12 months were selected. Responsiveness was measured based on the short version of the World Health Organization (WHO) multi-country responsiveness survey study, which included the dimensions of quality of basic amenities, choice, confidentiality, autonomy, communication and prompt attention. Quantile regression was used to assess the specific association of the responsiveness index with health insurance adjusted for sociodemographic factors. RESULTS: A total of 1453 and 744 elderly, of whom 50.1 and 63% had health insurance, used outpatient and inpatient health services, respectively. All domains were rated relatively highly but the uninsured elderly reported better responsiveness in all domains of outpatient and inpatient care. Waiting time was the dimension that performed worst. Possession of health insurance was negatively associated with responsiveness in outpatient (- 1; 95% CI: - 1.45, - 0.45) and inpatient (- 2; 95% CI: - 2.69, - 1.30) care. CONCLUSION: The uninsured elderly reported better responsiveness than the insured elderly in both outpatient and inpatient care. Special attention should be paid to those dimensions, like waiting time, which ranked poorly. Further research is necessary to reveal the reasons for the lower responsiveness noted among insured elderly. A continuous monitoring of health care system responsiveness is recommended.

Can survey data facilitate local priority setting? Experience from the Igunga and Nzega districts in Tanzania.

PURPOSE: This study aimed to investigate whether a local survey applying EQ-5D and SAGE could provide data valuable in setting priorities. METHODOLOGY: A cross-sectional household survey was used to collect information from a total of 1,899 elderly individuals aged 60 years and over living in the Nzega and Igunga districts using the WHO-SAGE and EQ-5D questionnaires. QALY weights were generated using the average of an EQ-5D index. A multivariable regression model was performed to analyse the effect of socioeconomic factors and self-rated health status on the EQ-5D index, using a linear regression model. RESULTS: The confidence interval estimates indicate higher HRQoL among men, married, urban dwellers, and elderly rated with good health than in women, unmarried, rural dwellers, and elderly rated with bad/moderate health, and it decreases with age. Income and education level have a positive relationship with HRQoL. The regression analysis; Model 1 (not adjusted with SAGE variables): age in all groups (p = 0.01, 0.00 and 0.02) and marital status (p = 0.01) have an influence on HRQoL. Model 2 (adjusted with SAGE variables): self-rated health (p < 0.00), the age for the 80-89 group (p = 0.01), marital status (not married), and high income have an influence on HRQoL. Sex, education, and residence were not statistically significant (in either model) to affect the HRQoL of the elderly. CONCLUSION: Local surveys, applying a combination of EQ-5D and SAGE, generate relevant and valuable information for policy makers when setting priorities at the district level. Therefore, this paper provides an empirical analysis for decision makers to consider the importance of combining EQ-5D, SAGE, and socioeconomic factors when setting priorities to improve HRQoL among the elderly.