Author: Lourenco Camnahas
Camnahas, Lourenco, 2020 Identification of factors impacting on pharmaceutical supply, and alternative approaches to human resource capacity, inventory management, quantification, and forecasting of pharmaceuticals in Timor-Leste (A mixed-methods study), Flinders University, College of Nursing and Health Sciences
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Timor-Leste gained independence in 2002 and faces similar challenges to other fragile states. Among the challenges is the continuous pharmaceutical stock-out in health facilities in the country. This has been the case since independence.
There are three theoretical frameworks deployed to understand the pharmaceutical stock-out phenomenon in Timor-Leste. The first is the Privett and Gonsalvez (2014) dependency model which is used to identify pharmaceutical supply chain management within the country. The second is the post-colonial and hybrid state theorem. The last is Andersen’s (Andersen 1995a) behavioural model which has been used to forecast and quantify pharmaceuticals. These frameworks have guided the study, the data collection, and the analysis of the findings.
Privett and Gonsalvez’s dependency model (2014) has been used to identify how the pharmaceutical supply chain process functions within the health sector in Timor-Leste. The Privett and Gonsalvez model is fundamental to uncovering the most important problems in the global pharmaceutical supply chain. It is, by itself, a theoretical framework used to collect data and present the findings logically according to well-defined levels of pharmaceutical supply chain management. The top 10 global pharmaceutical issues identified by Privett and Gonsalvez guided the development of the interviews and the document reviews during data collection and in the presentation of the findings.
The findings from the Privett and Gonsalvez model (2014) were then combined with the findings from 10 previous studies specifically conducted in the country that examined the problems with pharmaceutical stock-out in Timor-Leste. These reports identified major issues such as lack of leadership, policies and guidelines, poor human resource management, infrastructure, inventory management, and quantification; and faulty procurement strategies in the government sector. A lack of data to inform quantification and forecasting was also found to be the case in two of the development partner organisations providing healthcare in the country.
As a post-conflict country and fragile state, Timor-Leste requires slow but steady development of its systems, infrastructure, and human resource development. An innovative approach to pharmaceutical planning needs to be introduced. Andersen’s behavioural model for healthcare utilisation was applied in the study specifically to the quantification and forecasting of pharmaceuticals. This was seen as a suitable approach because the model has extensive predictors that can be applied to quantifying and forecasting of pharmaceutical needs. Andersen’s model is appropriate for this purpose because it deploys extensive predictor variables that enable accurate decisions on pharmaceutical quantification. The predictors applied to the quantification approach are population predictors, socio-economic factors, the health system, education, literacy and employment rates, attitudes towards health services, and health outcomes. The outcome variables are made up of pharmaceutical consumption and expenditures during 2016. Andersen’s behavioural model of healthcare utilisation guided the cross-sectional data collection, statistical testing, and analysis of the results of the forecasting and quantification model generated for the government and development partner organisations.
The results of the statistical analysis of the quantification and forecasting provided a conclusion to the thesis by testing which forecasting model was more suitable for Timor-Leste. The recommended forecasting model would be based on the acceptance of any of the hypotheses being tested. Whether the forecasting should be based on total primary healthcare need/expenditure per health facility, per-capita, or per out-patient department visits is to be determined later. The analysis encompassed univariate analysis, T-test and multivariate analysis, and the Shapiro-Wilk’s test for dichotomic variables.
Optimal statistical modelling for prediction was performed using a stepwise regression analysis to identify the significant predictors, followed by a nested stepwise regression analysis to test the changes in coefficient values and the percentage of variability of the explanatory variables to the predicted variables. Statistical tests on both linear-linear and log-linear models were determined by the best fit of the model. Overall, eight prediction models were produced. The explanatory power of the models ranged from 55% to 94%. A final prediction model with 89% explanatory power is proposed for future pharmaceutical planning.
Keywords: inventory management, pharmaceutical forecasting, and quantification, pharmaceutical stock-out, pharmaceutical supply chain management, Timor-Leste
Subject: Health Service Management thesis
Thesis type: Doctor of Philosophy
Completed: 2020
School: College of Nursing and Health Sciences
Supervisor: Professor Eileen Willis