Malaria Journal BioMed Central
ssResearch Open Acce
Pattern of drug utilization for treatment of uncomplicated malaria 
in urban Ghana following national treatment policy change to 
artemisinin-combination therapy
Alexander NO Dodoo*1, Carole Fogg2,3, Alex Asiimwe3, Edmund T Nartey1, 
Augustina Kodua1, Ofori Tenkorang1 and David Ofori-Adjei1
Address: 1Centre for Tropical Clinical Pharmacology & Therapeutics, University of Ghana Medical School, P.O. Box KB 4236, Accra, Ghana, 2Drug 
Safety Research Unit, Bursledon Hall, Southampton, SO31 1AA, UK and 3University of Portsmouth, Portsmouth, UK
Email: Alexander NO Dodoo* - alexooo@yahoo.com; Carole Fogg - carole.fogg@dsru.org; Alex Asiimwe - alex.asiimwe@port.ac.uk; 
Edmund T Nartey - etnartey@chs.edu.gh; Augustina Kodua - appidanq@yahoo.com; Ofori Tenkorang - oheneofori@yahoo.com; David Ofori-
Adjei - dofori-Adjei@noguchi.mimcom.org
* Corresponding author    
Published: 5 January 2009 Received: 1 September 2008
Accepted: 5 January 2009
Malaria Journal 2009, 8:2 doi:10.1186/1475-2875-8-2
This article is available from: http://www.malariajournal.com/content/8/1/2
© 2009 Dodoo et al; licensee BioMed Central Ltd. 
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), 
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Background: Change of first-line treatment of uncomplicated malaria to artemisinin-combination therapy (ACT) is widespread
in Africa. To expand knowledge of safety profiles of ACT, pharmacovigilance activities are included in the implementation
process of therapy changes. Ghana implemented first-line therapy of artesunate-amodiaquine in 2005. Drug utilization data is an
important component of determining drug safety, and this paper describes how anti-malarials were prescribed within a
prospective pharmacovigilance study in Ghana following anti-malarial treatment policy change.
Methods: Patients with diagnosis of uncomplicated malaria were recruited from pharmacies of health facilities throughout
Accra in a cohort-event monitoring study. The main drug utilization outcomes were the relation of patient age, gender, type of
facility attended, mode of diagnosis and concomitant treatments to the anti-malarial regimen prescribed. Logistic regression was
used to predict prescription of nationally recommended first-line therapy and concomitant prescription of antibiotics.
Results: The cohort comprised 2,831 patients. Curative regimens containing an artemisinin derivative were given to 90.8% (n
= 2,574) of patients, although 33% (n = 936) of patients received an artemisinin-based monotherapy. Predictors of first-line
therapy were laboratory-confirmed diagnosis, age >5 years, and attending a government facility. Analgesics and antibiotics were
the most commonly prescribed concomitant medications, with a median of two co-prescriptions per patient (range 1–9).
Patients above 12 years were significantly less likely to have antibiotics co-prescribed than patients under five years; those
prescribed non-artemisinin monotherapies were more likely to receive antibiotics. A dihydroartemisinin-amodiaquine
combination was the most used therapy for children under five years of age (29.0%, n = 177).
Conclusion: This study shows that though first-line therapy recommendations may change, clinical practice may still be affected
by factors other than the decision or ability to diagnose malaria. Age, diagnostic confirmation and suspected concurrent
conditions lead to benefit:risk assessments for individual patients by clinicians as to which anti-malarial treatment to prescribe.
This has implications for adherence to policy changes aiming to implement effective use of ACT. These results should inform
education of health professionals and rational drug use policies to reduce poly-pharmacy, and also suggest a potential positive
impact of increased access to testing for malaria both within health facilities and in homes.Page 1 of 8
(page number not for citation purposes)
Malaria Journal 2009, 8:2 http://www.malariajournal.com/content/8/1/2Background adverse events experienced during treatment with the
Artemisinin combination therapy (ACT) is becoming anti-malarials reported in the cohort will be presented in
first-line treatment for uncomplicated Plasmodium falci- a forthcoming paper.
parum malaria episodes throughout Africa. The urgency
for ACT roll-out was spurred by alarming levels of drug Methods
resistance to previously used monotherapies such as chlo- Data presented in this article were collected during a pro-
roquine and sulphadoxine-pyrimethamine (SP) and ris- spective, longitudinal, non-interventional study to moni-
ing morbidity and mortality [1,2]. Kwa-Zulu Natal was tor adverse events (AEs) following administration of anti-
the first health ministry to switch to an ACT in 2001 [3], malarials for uncomplicated malaria in Accra, the capital
and ACT have now been adopted in 28 African countries, city of Ghana.
with an additional 13 in the process of implementation
[4]. In Ghana, the Ministry of Health (MOH) policy Study design and sample size
changed, in 2004, in line with World Health Organization A cohort-event monitoring methodology was used, in
(WHO) recommendations to artesunate plus amodi- which all new patients prescribed anti-malarials for
aquine (ART-AQ) as first-line therapy for uncomplicated uncomplicated malaria, in the normal course of medical
malaria from 1st January 2005 [5]. Reports of adverse practice in the participating healthcare facilities in Accra
events with ART-AQ received by the then National Centre were eligible for recruitment; patients with severe/compli-
for Pharmacovigilance at the University of Ghana Medical cated malaria and pregnant women were excluded. An
School (UGMS) and increasing negative media coverage urban area was chosen to be able to recruit a large cohort
on the safety of ART-AQ led to withdrawal of specified in a short time period, and to reduce logistical constraints
brands of ART-AQ in December 2005 [6]. This was accom- of follow-up as many people were contactable by tele-
panied by a fall in the number of reports though there had phone and lived nearby to facilitate home visits. The vari-
been 131 reports of adverse events (AEs) to ART-AQ to the ety of health facilities and large numbers of health
UGMS by October 2007 [7]. professionals enabled assessment of a wide range of prac-
tices. The average prevalence of malaria in children in
Active post-marketing drug safety surveillance using pre- Accra is estimated at 14.8%, ranging from 6% to 22% by
scription-event monitoring methodology is practiced community [12]. The sample size calculation for the orig-
both in the UK [8] and New Zealand [9] by collecting inal study was based on the possibility of detecting a rare
event information for patients prescribed new drugs to adverse event at a frequency of 1 in 3,000 patients – that
detect previously unknown drug effects or to better char- is a sample size of 10,000 patients for each drug [13].
acterize known effects in 'real-life'. Within the context of Although the study was discontinued prematurely by the
post-marketing monitoring for adverse events, a knowl- sponsor, a substantial number of patients had already
edge of the patterns of drug utilization, both in terms of been included in the cohort.
prescriber characteristics and patient population, are
essential to characterize the potential risks that patients Recruitment
may experience. In March 2006, a non-interventional All public health facilities in Accra were approached to
pharmacovigilance study was initiated in Accra to comple- participate in the study and agreed to take part. Private
ment the spontaneous reporting system for newly intro- facilities with adequate staff availability and patient load
duced anti-malarials. The study was originally designed to were also invited to participate. The 24 health institutions
compare the 'real-life' safety profiles of ART-AQ and chlo- who participated are thought to be representative of prac-
rproguanil-dapsone (LapDap™) as they are used in real- tice across Accra; 15 government hospitals/clinics, two
life settings in Ghana. However, due to the limited use of quasi-government hospitals, one private clinic and six
LapDap™ following introduction of ACT [10] and the community pharmacies. Each facility was asked to sign a
progress of the development of chlorproguanil-dapsone- consent form to indicate acceptance for participation. All
artesunate [11], data on the existing available anti-malar- facilities operate a 'fee for service' system and fees are very
ial regimens was collected though the concerns above similar across facility types. Eligible patients were
caused the study to be formally terminated by the spon- recruited consecutively from the pharmacy at the time of
sor, WHO-TDR, in November 2006. dispensing the drug in order to reduce the number of
patients who might be prescribed anti-malarials but who
The objective of this paper is to describe the mode of diag- may be unable to obtain their supplies either due to avail-
nosis and pattern of drug management in outpatients ability of medicines or lack of patient funds. Patient
diagnosed with suspected uncomplicated malaria in recruitment rates varied based on staff time and the ability
health facilities in Accra, Ghana who were recruited into a of research team to post dedicated data collectors to the
prospective pharmacovigilance study. Safety analysis of sites.Page 2 of 8
(page number not for citation purposes)
Malaria Journal 2009, 8:2 http://www.malariajournal.com/content/8/1/2Data collection significance level for entry of the variable/category into
Data collected on the day of anti-malarial dispensing the model of p = 0.15. The performance of the model was
included demographics, contact details, method of diag- assessed on calibration and discrimination using Hosmer-
nosis (health professional presumptive diagnosis [by type Lemeshow goodness-of-fit test and area under the
of health professional] or slide-confirmed), anti-malarial Receiver Operating Characteristic (ROC) curve respec-
drugs prescribed and concomitant medications dispensed tively. 'Discrimination' refers to a variable's ability to dis-
on that day. All recruited patients were given a study card tinguish prescription of first line therapy/antibiotic use
which they could present at the Out-Patients Department from no prescription of first line therapy/no antibiotic
of the Korle-Bu Polyclinic (affiliated to the teaching hos- use. The AUC represents the probability that a patient
pital) in case their clinical condition did not improve and who had ART-AQ or used antibiotics had a higher pre-
they were unable or unwilling to visit a primary care facil- dicted probability than those who did not. An AUC of 0.5
ity or in case of adverse events for which the patient indicates that the variables do not predict better than
wished to seek hospital treatment. Collection of adverse chance. The discrimination of the variables is considered
event data by systematic follow-up contact by the research perfect if AUC = 1, good if AUC >0.8, moderate if AUC is
team and use of spontaneous report forms by patients will 0.6 to 0.8, and poor if AUC <0.6. 'Calibration' refers to the
be discussed in a subsequent paper. agreement between predicted probabilities and the 'true
probabilities', which can be approximated by taking the
Data management and analysis mean of the observed outcomes within predefined groups
Each enrolled patient was given a unique study number of patients. The Hosmer-Lemeshow test compares the
that was used in the storage and management of all data observed outcome in a group with the predicted outcome
relating to the patient. Data were double entered, data of that group [14]. The C goodness-of-fit statistic sorts
cleaned and managed using Microsoft Access (Microsoft observations according to their expected probability and
Corporation, Redmond, Washington) and analysed using partitions the observations into ten groups of equal size.
STATA version 9.2, (Stata Corporation, College Station, A high H relates to a small p value, implying significant
Texas). Anti-malarial treatment groups were defined as difference between observed and predicted outcome, and
follows: i) recommended first-line therapy (artesunate thus indicates a lack of fit of the variables.
plus amodiaquine – ART-AQ); ii) 'other ACT' group –
patients taking an artemisinin derivative in combination Ethical approval
with a non-artemisinin-containing anti-malarial; iii) Ethical approval for the project was obtained from the
monotherapy (artemisinin) group – patients taking only Ethical and Protocol Review Committee of the University
artemisinin-based compounds for treatment of malaria of Ghana Medical School. The original protocol was also
episode, including more than one type of artemisinin e.g. approved by WHO/TDR internal ethical procedures. Par-
artemether injection followed by oral artesunate; iv) mon- ticipation for patients was subject to a signed and wit-
otherapy (other) group – other monotherapy regimens nessed informed consent form by the patient or his/her
not containing artemisinin compounds. Data was carer or guardian for children (under 18 years).
expressed as means and standard deviations (SD) for con-
tinuous variables, and frequencies and percentages for cat- Results
egorical variables. Categories of the variable 'facility type' Recruitment was carried out between April 2006 and
were regrouped into government facilities vs. non-govern- November 2006. Of patients who were diagnosed with
ment facilities (quasi-government, private clinic, commu- malaria and attended pharmacies to collect medication,
nity pharmacy) due to small numbers and common more than 95% consented to participate. The most com-
characteristics within the non-government group. Catego- mon reason for non-participation was time constraints for
ries of the variable 'mode of diagnosis' were regrouped the patient. The final number of patients recruited was
into laboratory confirmed diagnosis vs. presumptive diag- 2,835, although four of these were excluded from analysis
nosis (including doctor, pharmacist, other health profes- due to ambiguity of anti-malarial prescribed. The majority
sional and self) categories. Chi-square and Fishers' Exact of patients were recruited from government facilities
Test were used for categorical variables and students T-test (95.9%, n = 2,716).
for continuous variables for univariate analysis to predict
prescription of: i) first-line therapy (ART-AQ); ii) antibiot- Cohort characteristics and malaria diagnosis
ics. Results were considered statistically significant at a 60.6% of the cohort was in the 13–59 year age band
level of p < 0.05. (Table 1). Although overall females comprised 59.9% of
the cohort, the proportion of females increased with
A stepwise multivariate logistic regression method was increasing age, from 48.4% of under 5's to 69.4% of the
used to assess the effect of variables on the outcomes of over 60's (Chi square trend for those with known age =
prescription of first line therapy and antibiotics using a 63.6, p < 0.001). The major mode of diagnosis of malariaPage 3 of 8
(page number not for citation purposes)
Malaria Journal 2009, 8:2 http://www.malariajournal.com/content/8/1/2Table 1: Characteristics according to age group
Age group Total
<5 5–12 13–59 ≥60 NK
n = 610 n = 317 n = 1,716 n = 157 n = 31 N = 2,831
(21.6%) (11.2%) (60.6%) (5.5%) (1.1%)
n (%) n (%) n (%) n (%) n (%) n (%)
Gender
Male 315 (51.6) 151 (47.6) 606 (35.3) 48 (30.6) 16 (51.6) 1,136 (40.1)
Female 295 (48.4) 166 (52.4) 1,110 (64.7) 109 (69.4) 15 (48.4) 1,695 (59.9)
Facility type
Community pharmacy 4 (0.7) 1 (0.3) 18 (1.1) 3 (1.9) 0 (0) 26 (0.9)
Government 599 (98.2) 312 (98.4) 1,621 (94.5) 153 (97.5) 31 (100) 2,716 (95.9)
Private clinic 4 (0.7) 1 (0.3) 27 (1.6) 0 (0) 0 (0) 32 (1.1)
Quasi-government 3 (0.5) 3 (1.0) 50 (2.9) 1 (0.6) 0 (0) 57 (2.0)
Mode of diagnosis
Doctor 501 (82.1) 242 (76.4) 1,383 (80.6) 125 (79.6) 18 (58.1) 2,269 (80.2)
Laboratory Confirmation 20 (3.3) 19 (6.0) 48 (2.8) 3 (1.9) 1 (3.2) 91 (3.2)
Other health professional 18 (3.0) 22 (6.9) 127 (7.4) 8 (5.1) 5 (16.1) 180 (6.4)
Pharmacist 0 (0) 0 (0) 10 (0.6) 1 (0.6) 0 (0) 11 (0.4)
Self 0 (0) 2 (0.6) 6 (0.4) 0 (0) 0(0) 8 (0.3)
Unknown 71 (11.6) 32 (10.1) 142 (8.3) 20 (12.7) 7 (22.6) 272 (9.6)
Anti-malarial treatment prescribed
Combination therapy 161 (26.4) 181 (57.1) 790 (46.0) 76 (48.4) 9 (29.0) 1,217 (43.0)
(ART-AQ)
Combination therapy 240 (39.3) 40 (12.6) 124 (7.2) 5 (3.2) 9 (29.0) 418 (14.8)
(Other ACT)
Monotherapy 111 (18.2) 55 (17.4) 700 (40.8) 61 (38.9) 9 (29.0) 936 (33.1)
(Artemisinin based)
Monotherapy 98 (16.1) 41 (12.9) 102 (5.9) 15 (9.6) 4 (12.9) 260 (9.2)
(Non-artemisinin)
NK = not known
was presumptive diagnosis by a physician (Table 1). Only sion model had a Hosmer-Lemeshow chi square value=
3.2% (n = 91) of diagnoses were parasitologically con- 0.07, (2 degrees of freedom), p-value = 0.97. The area
firmed, with the highest proportion of laboratory con- under the ROC curve was 0.63 indicating a moderate fit of
firmed diagnoses in the 5–12 years age group (6.0%, n = the model.
19).
Co-prescribed medications
Anti-malarial treatment prescribed Co-prescribed medications were given to 89.5% of the
There were 23 different anti-malarial regimens recorded cohort (n = 2,533), with a median number of two per
(Table 2). The majority of patients (90.8%) received an patient (range 1–9). The most commonly prescribed con-
artemisinin-based compound in their treatment regimen. comitant medications were analgesics, given to 76.3% (n
However, only 43.0% received the recommended first line = 2,162) of patients, followed by antibiotics (30.8%, n =
therapy of ART-AQ, although this was the most common 872), and vitamins (25.8%, n = 729). The proportion of
regimen reported. Dihydroartemisinin (DHA) was used patients according to characteristic who were prescribed
next most frequently, either alone (20.4%) or combined antibiotics and logistic regression results are in Tables 3
with another anti-malarial (9.4%). The proportion of and 4 respectively. Patients aged over 12 years were signif-
patients according to characteristic who were prescribed icantly less likely to have an antibiotic co-prescription
ART-AQ as opposed to the other regimens is shown in than patients under 5 years, while patients prescribed
Table 3, with logistic regression results in Table 4. It is of non-artemisinin monotherapies were significantly more
note that of the 91 microscopically confirmed diagnoses, likely to have anti-biotic co-prescription. The Hosmer-
86.8% (n = 79) were prescribed ART-AQ (adjusted OR 9.7 Lemeshow goodness of fit test had a chi-square of 4.85,
[5.2–18.2]). Other factors related to ART-AQ prescription (df = 3), p-value = 0.18, indicating good fit. However, the
were patients aged five years or above and attendance of a area under the ROC curve was poor with an AUC = 0.58.
government facility. The goodness of fit test for the regres-Page 4 of 8
(page number not for citation purposes)
Malaria Journal 2009, 8:2 http://www.malariajournal.com/content/8/1/2Table 2: Anti-malarial treatment prescribed health facilities. However, 33.1% of patients received an
artemisinin monotherapy, a regimen which has not been
Drug group/treatment N %
recommended by WHO since January 2006 due to the
1st line therapy (ART-AQ) 1,217 43.0 potential for drug resistance in this class of drugs due to its
Combination therapy – other ACT 418 14.8 short half-life. The reasons for this may include lack of
DHA+AQ 240 8.5 availability of ACTs or safety concerns of the prescriber
Artemether+AQ 77 2.7 following the media coverage of side effects of amodi-
Artemether+lumefantrine 58 2.1 aquine. The need to educate health care workers to stop
DHA+pyrimethamine-sulphametopirazine 13 0.5 recommending artemisinin monotherapy is obvious and
Artesunate+SP 12 0.4 urgent. This situation could be expected to be different in
DHA+SP 6 0.2
DHA+chloroquine 5 0.2 rural areas, where there is less choice of drugs and where
Artesunate+chloroquine 3 0.1 subsidized ART-AQ is available in health centres. The
Artemether+pyrimethamine-sulphametopirazine 1 0.04 diversity of regimens used has implications for post-mar-
Artemether+quinine 1 0.04 keting safety monitoring, where correct ascertainment of
Artesunate+ quinine 1 0.04 exposure is necessary for attribution of potential adverse
DHA+artemether+lumefantrine 1 0.04 effects to a specific suspect drug.
Monotherapy – artemisinin based 936 33.1
DHA 577 20.4
Artesunate 293 10.4 This study illustrated some practical realities of the day-to-
Artemether 55 1.9 day diagnosis and treatment of uncomplicated malaria.
Artesunate/artemether 10 0.4 Firstly, the high level of presumptive diagnosis of malaria,
Artemether/DHA 1 0.04 based on country-specific guidelines [5], seems to be a
Monotherapy – non-artemisinin 260 9.2 limiting factor for prescribing the new first-line therapy. A
Amodiaquine 133 4.7 patient with a parasitologically confirmed diagnosis was 9
SP 78 2.8
Pyrimethamine-sulphametopirazine 32 1.1 times more likely than a patient with presumptive diagno-
Chloroquine 14 0.5 sis to be prescribed the first-line therapy, suggesting that
Quinine 3 0.1 the confidence of health professionals in adhering to new
Total 2,831 guidelines is enhanced by having access to confirmatory
tests. Similar findings in Zambia where the first-line ther-
DHA = dihydroartemisinine; AQ = amodiaquine; SP = sulphadoxine- apy artemether-lumefantrine was prescribed more fre-
pyrimethamine quently to patients with positive blood smears or rapid
Children under five years diagnostic tests (RDTs) relative to those with a negative
There were 610 patients aged under five years in the test would support this [15]. Overall, only 3.2% of the
cohort and this age group was more likely to be prescribed cohort had a positive test result, indicating very low rates
a DHA-AQ combination (29%, n = 177), rather than ART- of use of malaria diagnostics. This would support calls to
AQ (26.4%, n = 161). Amodiaquine and DHA were used roll-out newer diagnostic technologies such as rapid diag-
as monotherapies in a further 15.7% (n = 96) and 13.8% nostic tests (RDTs) for malaria in conjunction with
(n = 84) respectively. Only two children under five years changes to ACT first line therapy to limit over-use of ACTs
received a non-artemisinin monotherapy (chloroquine). [16].
Under-fives were the most likely to receive an antibiotic
(42.6%, n = 260), and the least likely to receive an analge- Secondly, there was a high level of co-prescription of anti-
sic (60.8%, n = 371) or a vitamin (15.4%, n = 94). biotics (30.8% of patients receiving at least one antibiotic
prescription), which is promoted under febrile illness
Discussion strategies [17]. The widespread concomitant use of antibi-
This evaluation, including predominantly government otics has implications for patient safety in increasing the
facilities in an urban setting, showed that nearly two years potential for drug-drug interactions, and also for pharma-
following the change in national anti-malarial policy, the covigilance, as antibiotics have a high incidence of com-
first-line therapy was adhered to in less than 50% of cases. mon adverse events such as rashes and pruritis, which
It is possible that the initial safety concerns associated may be ascribed to the new anti-malarials by patients/
with ART-AQ and availability of a wide variety of alterna- health care providers. The fact that non-artemisinin mon-
tives in addition to the fact that patients pay at the point otherapy was significantly more likely to be prescribed
of service delivery could have contributed to this. Artem- with an antibiotic would suggest that these are patients for
isinins, either as monotherapy or combination therapy, whom the prescriber is less confident of a true diagnosis
were used to treat more than 90% of cases of uncompli- of malaria and is prescribing anti-malarials as a 'cover' for
cated malaria, indicating widespread acceptance of artem- potential infection or to prevent subclinical infection
isinin therapies and their extensive absorption into urban becoming manifest. This correlates with findings in Tan-Page 5 of 8
(page number not for citation purposes)
Malaria Journal 2009, 8:2 http://www.malariajournal.com/content/8/1/2Table 3: Characteristics of patients prescribed first-line therapy (ART-AQ) or a co-prescription of antibiotics
Anti-malarial prescribed Antibiotic co-prescription
ART-AQ Other anti-malarial regimen Antibiotic co-prescription No antibiotic
N = 1,217 N = 1,614 N = 872 N = 1,959
n, %1 n, % n, % n, %
Gender
Male 464 40.9 672 59.2 376 33.1 760 66.9
Female 753 44.4 942 55.6 496 29.3 1,199 70.7
Age group
<5 161 26.4 449 73.6 260 42.6 350 57.4
5–12 181 56.9 136 43.1 119 37.4 198 62.5
13–59 790 46.0 926 54.0 445 25.9 1, 271 74.1
≥60 76 48.4 81 51.6 40 25.5 117 74.5
Not known 9 29.0 22 71.0 8 25.8 23 74.2
Facility type
Non-government 15 13.0 100 87.0 28 24.4 87 75.7
Government 1,202 44.3 1,514 55.7 844 31.1 1,872 68.9
Mode of diagnosis
Presumptive 1,041 42.2 1,427 57.8 758 30.7 1,710 69.3
Laboratory confirmed 79 86.8 12 13.2 21 23.1 70 76.9
Not known 97 35.7 175 64.3 93 34.2 179 65.8
Anti-malarial treatment prescribed
Combination therapy (ART-AQ) - - 349 28.7 868 71.3
Combination therapy (Other ACT) - - 140 33.5 278 66.5
Monotherapy (Artemisinin based) - - 277 29.6 659 70.4
Monotherapy (Non-artemisinin) - - 106 40.8 154 59.2
1 % are row percentages within supercolumns
zania for patients with a history of cough within the pre- severe morbidity, the types of paediatric formulations
vious 48 hours and a negative blood slide being predictive available or the promotional activities of pharmaceutical
of no anti-malarial treatment given (as opposed to pre- companies operating in Accra. A qualitative study would
scribing anti-malarials even with a negative result) [18]. be useful to explore this.
The benefit:risk decision of the clinician whether or not to
co-prescribe could also depend on factors such as pres- There were several potential limitations to this study.
ence of measurable fever, ability of the patient to afford Recruitment was potentially biased towards facilities with
the multiple medications, likelihood of the patient being a high patient load, which were mainly government facil-
able to return if the condition worsens and previous treat- ities. However, this usage of facilities reflects the health-
ments the patient received. seeking behaviour of patients, and is therefore likely to be
a representative sample of the population with suspected
Although the under-5 age group were the least likely malaria in Accra. Utilization of government health facili-
group to receive the recommended ART-AQ regimen ties far outstrips that of private facilities, most of which are
(29.0%), this age group seemed to be managed the least small. Other background data on presentation was not
conservatively overall, with only 2 patients receiving chlo- collected and this information could have been useful in
roquine and no sulphonamides prescribed, and a signifi- understanding the treatment regimen prescribed, for
cantly higher proportion of antibiotic prescriptions. example presence of fever on examination, suspected con-
Similar findings have been shown in Zambia and Kenya, comitant infections and previous intake of anti-malarials.
where 11% and 26% of children were prescribed the rec- Drug availability in facilities was not monitored, but
ommended ACT shortly after implementation [19,20]. stock-outs highly unlikely due to the multiplicity of prod-
The preference for the DHA-AQ over ART-AQ may reflect ucts available for purchase by all facilities, both public
clinician expectation of drug efficacy and/or safety in this and private. This study was purely non-interventional and
population more likely to have higher parasitaemias and did not assess whether prescription was appropriate forPage 6 of 8
(page number not for citation purposes)
Malaria Journal 2009, 8:2 http://www.malariajournal.com/content/8/1/2Table 4: Predictors of first-line therapy prescription and co-prescription of concomitant antibiotics1,2
Prescription of first-line therapy (ART-AQ) Antibiotic use
Adjusted odds ratio p-value Adjusted odds ratio p-value
[95% CI] [95% CI]
Age group
<5 1.0 1.0
5–12 3.6 [2.6–4.9] <0.001 - -
13–59 2.5 [2.0–3.1] <0.001 0.53 [0.44–0.64] <0.001
≥60 2.6 [1.8–3.9] <0.001 0.55 [0.37–0.83] 0.004
Facility type
Non-government 1.0 - -
Government 6.3 [3.6–11.1] <0.001 - -
Mode of diagnosis
Presumptive 1.0 1.0
Laboratory confirmed 9.7 [5.2–18.2] <0.001 0.68 [0.41–1.1] 0.13
Anti-malarial treatment prescribed
Combination therapy (ART-AQ) - - 1.0
Combination therapy (Other ACT) - - - -
Monotherapy (Artemisinin based) - - 1.2 [0.97–1.4] 0.11
Monotherapy (Non-artemisinin) - - 1.4 [1.1–1.9] 0.02
1 Gender was not significant in either of the final models
2 N = 2,535 for both models. Patients with unknown age (n = 31) and/or unknown mode of diagnosis (n = 272) were excluded.
age and weight. There was also no information collected therapy in an environment in which a wide variety of cur-
on the availability of diagnostics, which may have ative regimens are used. The challenge of pharmacovigi-
explained the low utilization, although this is more likely lance in environments with limited routine data
to be due to high patient load and lack of time to wait for collection facilities should not be underestimated and
the result. Finally, the level of training of staff or familiar- requires significant innovation.
ity with guidelines was not assessed as a potential factor
contributing to the variance in prescribing, but as the Competing interests
majority of facilities were government facilities in the cap- The authors declare that they have no competing interests.
ital city, these staff would have had the highest likelihood
of access to training and related resources. Authors' contributions
AD and DO-A were the co-investigators for this study and
In summary, this study further adds support to the state- designed the project proposal and oversaw the project. ET
ment that global eradication of malaria, as called for by was responsible for database design, data entry and pre-
Bill and Melinda Gates in October 2007 and supported by analysis management. AK and OT were the research asso-
WHO, the US President's Malaria Initiative and all major ciates implementing the study, managing the data collec-
players [21], is unlikely unless there is proper diagnosis tors and visiting the various project sites. CF and AA
and management of malaria in all health facilities, includ- performed statistical analysis. CF and AD drafted the man-
ing those in resource-constrained environments. This uscript, and all authors read and approved the final man-
study suggests an important role for confirmatory diag- uscript.
nostics in rational prescribing, which would add support
for increased access to diagnostic tools to positively Acknowledgements
impact on patient management. Continued education of The study team would like to express their appreciation to all doctors, 
government and private providers on the new national pharmacists, nurses and health workers in the Greater Accra Region of 
anti-malarial guidelines is also recommended. Knowledge Ghana for their support and/or involvement in this work. Special acknowl-
of drug utilization patterns is key in understanding edgement is due to Dr David Nortey of the Korle-Bu Polyclinic for con-
senting to the use of the Polyclinic for patients who reported with ADRs. 
patient management and consequent drug safety issues, We are grateful to Dr Lynda Wilton for comments on the manuscript. The 
and this paper demonstrates the potential difficulties of data used for this article was collected as part of a study supported by 
pharmacovigilance activities for a recommended first-line WHO/TDR grant A40741.Page 7 of 8
(page number not for citation purposes)
Malaria Journal 2009, 8:2 http://www.malariajournal.com/content/8/1/2References
1. Marsh K: Malaria disaster in Africa.  Lancet 1998, 352:924.
2. White NJ, Nosten F, Looareesuwan S, Watkins WM, Marsh K, Snow
RW, Kokwaro G, Ouma J, Hien TT, Molyneux ME, Taylor TE, New-
bold CI, Ruebush TK 2nd, Danis M, Greenwood BM, Anderson RM,
Olliaro P: Averting a malaria disaster.  Lancet 1999, 353:1965-7.
3. Malaria Research Programme of the Medical Research
Council SA   [http://www.malaria.org.za/Malaria_Risk/Update/
update2005.html]
4. World Health Organization. Global AMP Database – AFRO
[http://www.who.int/malaria/amdp/amdp_afro.htm]
5. Ghana Health Service: Ghana National Antimalarial Policy. Accra 2004.
6. Yeboah EK: Stop sale: Ministry orders withdrawal of two
brands of new malarial drugs.  Daily Graphic .
7. Dodoo ANO, Bart-Plange C, Allotey NK, Segbeya S, Appiah-Danquah
A, Nyarko J: Benefits of spontaneous reporting ADR systems
to public health programmes in Sub-Saharan Africa.  Drug
Safety 2007, 30:931-932.
8. Mann RD: Prescription-event monitoring – recent progress
and future horizons.  Br J Clin Pharmacol 1998, 46:195-201.
9. Coulter DM: Signal generation in the New Zealand Intensive
Medicines Monitoring Programme: a combined clinical and
statistical approach.  Drug Safety 2002, 25:433-9.
10. World Health Organization: Facts on ACTs (Artemisinin-based combina-
tion therapies). Geneva 2006.
11. World Health Organization: Review of the safety of chlorproguanil-dap-
sone in the treatment of uncomplicated falciparum malaria in Africa: Report
of a Technical Consultation convened by the World Health Organization.
Geneva 2005.
12. Klinkenberg E, McCall PJ, Wilson MD, Akoto AO, Amerasinghe FP,
Bates I, Verhoeff FH, Barnish G, Donnelly MJ: Urban malaria and
anaemia in children: a cross-sectional survey in two cities of
Ghana.  Trop Med Int Health 2006, 11:578-88.
13. Strom B: Sample size considerations for pharmacoepidemiol-
ogy studies.  In Pharmacoepidemiology 4th edition. Edited by: Strom
B. Chichester, UK: John Wiley & Sons; 2005:29-36. 
14. Hosmer D, Lemeshow S: Applied Logistic Regression 2nd edition. NY:
Wiley & Sons; 2000. 
15. Hamer DH, Ndhlovu M, Zurovac D, Fox M, Yeboah-Antwi K, Chanda
P, Sipilinyambe N, Simon JL, Snow RW: Improved diagnostic test-
ing and malaria treatment practices in Zambia.  JAMA 2007,
297:2227-31.
16. Wongsrichanalai C, Barcus MJ, Muth S, Sutamihardja A, Wernsdorfer
WH: A review of malaria diagnostic tools: microscopy and
rapid diagnostic test (RDT).  Am J Trop Med Hyg 2007, 77(6
Suppl):119-127.
17. World Health Organization, UNICEF: Improving child health IMCI
1999.
18. Reyburn H, Ruanda J, Mwerinde O, Drakeley C: The contribution
of microscopy to targeting antimalarial treatment in a low
transmission area of Tanzania.  Malar J 2006, 5:4.
19. Zurovac D, Ndhlovu M, Rowe AK, Hamer DH, Thea DM, Snow RW:
Treatment of paediatric malaria during a period of drug
transition to artemether-lumefantrine in Zambia: cross sec-
tional study.  BMJ 2005, 331:734.
20. Zurovac D, Njogu J, Akhwale W, Hamer DH, Snow RW: Transla-
tion of artemether-lumefantrine treatment policy into pae-
diatric clinical practice 2008: an early experience from
Kenya.  Trop Med Int Health 2008, 13:99-107.
21. Bill and Melinda Gates Foundation   [http://www.gatesfounda
tion.org/speeches-commentary/Pages/bill-gates-malaria-forum.aspx] Publish with BioMed Central   and e very 
scientist can read your work free of charge
"BioMed Central will be the most significant development for 
disseminating the results of biomedical research in our lifetime."
Sir Paul Nurse, Cancer Research UK
Your research papers will be:
available free of charge to the entire biomedical community
peer reviewed and published immediately upon acceptance
cited in PubMed and archived on PubMed Central 
yours — you keep the copyright
Submit your manuscript here: BioMedcentral
http://www.biomedcentral.com/info/publishing_adv.aspPage 8 of 8
(page number not for citation purposes)