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Record W1548673617 · doi:10.5451/unibas-006281233

Health system governance in Tanzania : impact on service delivery in the public sector

2014· dissertation· en· W1548673617 on OpenAlexfundno aff
Inez Mikkelsen-Lopez

Bibliographic record

Venueedoc (University of Basel) · 2014
Typedissertation
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsnot available
FundersMedicines for Malaria VentureInternational Development Research CentreUniversität BaselSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science Foundation
KeywordsTanzaniaCorporate governanceProcurementAccountabilityBusinessService delivery frameworkEssential medicinesHealth carePublic economicsEconomic growthService (business)Political scienceEconomicsEnvironmental planningMarketingFinanceGeography

Abstract

fetched live from OpenAlex

Governance in the health system has perhaps been the least explored building block of the health system, receiving less attention due to its vague definition and complex nature. When discussed at the country level it often focuses on single elements such as corruption or accountability and doesn’t consider wider interactions of relevance to how policies are formed. How well governed a health system is can often mean the difference between the efficient use of resources and inefficient waste, which is even more important in a resource constrained environment. 
\nThe United Republic of Tanzania has been a major recipient of donor aid over the past few decades. Tanzania’s health sector in particular has been the subject of much donor interest, especially regarding medicines. One of the first donors to support medicines was Danida who funded the essential medicines kit, and since then numerous donors have been involved in either funding medicines, designing policies around medicines selection, procurement and distribution, or direct medicines donations. Although Tanzania has largely benefited from this increase in donor support, not all of it has been designed and implemented adequately to suit the situation and needs of Tanzania. In other words, health systems governance may sometimes have been weakened by donor-interest, resulting in reduced quality of health care. 
\nThe aim of this research was to contribute to a better understanding of health system governance and apply this knowledge to the Tanzanian health system. The insights gained should aid policy makers and other stakeholders to design interventions that are appropriate for the local context to ensure a stronger health system which is able to attain its goals of improving the level and distribution of health, while responding to the population’s needs and protecting them from large, often catastrophic financial expenditures. 
\nThe research was carried out as part of the Governance of Health Systems project, a collaborative endeavour between the Swiss Tropical and Public Health Institute and the Basel Institute of Governance. Quantitative and qualitative methods were applied to data collected in two areas of the local Health and Demographic Surveillance System (HDSS), Ulanga District and Rufiji District. We used both primary data collection and secondary data, covering the period from 1999 – 2011. 
\nThe overall findings are that despite the interest over the past decade to develop frameworks to assess governance in the health system, few have been empirically applied. The first part of this thesis focuses on developing a framework to assess governance in the health system; the second part applies this framework to a selected governance issue in Tanzania, namely the delivery of essential medicines to public health centres in Tanzania. At the national level, this investigation found that the medicines ordering system was based on a complex paper-based system which had not been designed with local capacity in mind, nor did it improve the accountability of medicines. Lack of accountability was also found at the health facility level, where over half of respondents interviewed who sought care in the public sector for fever, subsequently experienced the consequences of one form or another of non-compliant health-worker behaviour (overcharging for treatment and medicines, stocking out of the first line antimalarial, dispensing an inappropriate monotherapy). This resulted in an additional cost to the patient, on average, of USD1.62 per treatment episode, representing 125% of the national per capita daily income, or 164% of the rural per capita daily income. 
\nStockouts of essential medicines are an immediate indicator of governance failure and in the case of fully funded donor medicines, stockouts represent a health system failure. This research identified that in a 15 month period from October 2011 until the end of 2012, an estimated 29% of health facilities were stocked out of the first line antimalarial at any one time. These stockouts were due to failures at the national and international level where excessive bureaucratic procedures resulted in fragmented and dysfunctional procedures for procurement of the first line antimalarial. 
\nThe findings in this thesis suggest that Tanzania should redesign the medicines ordering system, with greater participation from health workers, in order to better understand the challenges they face. We recommend various interventions across the health system to strengthen it and improve the availability of medicines. The most important recommendation would be to increase accountability and transparency of the medicines delivery system and force reconciliation between data sources thereby creating information on medicines consumed. 
\nThe findings of this thesis contribute to a more comprehensive understanding of governance in health systems and how overlooking governance can cause major catastrophic stockouts of essential medicines, in addition to a reduced level of service delivery and greater economic hardship for households. 
\n

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.453
Threshold uncertainty score0.963

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.237
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2014
Admission routes1
Has abstractyes

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