Evidence map›Paper›PMID 26290329›Full record

Observational studyBMC health services research2015

Predictors of primary health care pharmaceutical expenditure by districts in Uganda and implications for budget setting and allocation.

Paschal N Mujasi, Jaume Puig-Junoy

Abstract readObservational Study
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Observational study in BMC health services research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

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0cells of the map it votes in
7citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Paschal N MujasiDepartment of Economics and Business, Universitat Pompeu Fabra, Barcelona School of Management, Balmes 132, 08001, Barcelona, Spain. Pmujasi@yahoo.co.uk.
Jaume Puig-JunoyDepartment of Economics and Business and Centre for Research in Health and Economics (CRES), Universitat Pompeu Fabra, Ramón Trias Fargas 25-27, 08005, Barcelona, Spain. jaume.puig@upf.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere is need for the Uganda Ministry of Health to understand predictors of primary health care pharmaceutical expenditure among districts in order to guide budget setting and to improve efficiency in allocation of the set budget among districts.

methodsCross sectional, retrospective observational study using secondary data. The value of pharmaceuticals procured by primary health care facilities in 87 randomly selected districts for the Financial Year 2011/2012 was collected. Various specifications of the dependent variable (pharmaceutical expenditure) were used: total pharmaceutical expenditure, Per capita district pharmaceutical expenditure, pharmaceutical expenditure per district health facility and pharmaceutical expenditure per outpatient department visit. Andersen's behaviour model of health services utilisation was used as conceptual framework to identify independent variables likely to influence health care utilisation and hence pharmaceutical expenditure. Econometric analysis was conducted to estimate parameters of various regression models.

resultsAll models were significant overall (P < 0.01), with explanatory power ranging from 51 to 82%. The log linear model for total pharmaceutical expenditure explained about 80% of the observed variation in total pharmaceutical expenditure (Adjusted R(2) = 0.797) and contained the following variables: Immunisation coverage, Total outpatient department attendance, Urbanisation, Total number of government health facilities and total number of Health Centre IIs. The model based on Per capita Pharmaceutical expenditure explained about 50% of the observed variation in per capita pharmaceutical expenditure (Adjusted R(2) = 0.513) and was more balanced with the following variables: Outpatient per capita attendance, percentage of rural population below poverty line 2005, Male Literacy rate, Whether a district is characterised by MOH as difficult to reach or not and the Human poverty index.

conclusionsThe log-linear model based on total pharmaceutical expenditure works acceptably well and can be considered useful for predicting future total pharmaceutical expenditure following observed trends. It can be used as a simple tool for rough estimation of the potential overall national primary health pharmaceutical expenditure to guide budget setting. The model based on pharmaceutical expenditure per capita is a more balanced model containing both need and enabling factor variables. These variables would be useful in allocating any set budget to districts.

Indexed as

BudgetsHealth ExpendituresPrimary Health CareResource AllocationAdolescentAdultAgedCross-Sectional StudiesFemaleHealth Services Needs and DemandHumansMaleMiddle AgedPovertyPrescription DrugsRetrospective StudiesPrescription Drugs

Identifiers

PMID26290329
PMCPMC4545968

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.