In 2005, Nigeria changed its antimalarial drug policy to Artemisinin-based Combination Therapies (ACTs) for the treatment of malaria infection, and it is imperative for prescribers to strictly comply with this guideline to harmonize malaria management practices within the country. This study aims to evaluate prescribers’ adherence with the National Antimalarial Treatment Guideline (NATG) in the treatment of malaria infections and to describe the determinants of antimalarial drugs coprescription with antibiotics at a tertiary hospital in Nigeria. A cross-sectional, retrospective study of antimalarial drug prescriptions of one-year period of 2013 was conducted. A simple method for assessing the quality of drug prescribing (DU90%) was adopted. Logistic regression was used to predict antimalarial drugs coprescription with antibiotics. Overall, 95.8% of the total prescriptions contained ACTs, out of which 80.8% were Artemether/Lumefantrine. However, adherence to NATG was 88.2% with an adjusted value of 100.0%. Age was the only predictor for antimalarial drugs coprescription with antibiotics. This study showed high concordance with NATG at the studied hospital. Age less than 5 years is a significant risk factor for antimalarial drugs coprescription with antibiotics.
Malaria remains the most common public health problem in Nigeria where it accounts for more cases and deaths than any other country in the world. Malaria is a risk for majority of Nigeria’s population with an estimated 100 million malaria cases with over 300,000 deaths per year in Nigeria [
Following a period of continuous increase in resistance of
To meet the goal of universal access to right interventions for all populations at risk of malaria, it is required that the proper clinical investigation is conducted prior to treatment with effective antimalarial drugs [
Appropriate treatment of malaria and the correct use of antimalarial drugs are needed in order to achieve Nigerian’s goal of preelimination and reducing malaria related death to zero by 2020 [
In Nigeria today, there is paucity of data on the implementation of this new antimalarial policy in the NHIS. An NHIS antimalarial prescription audit has been done in the South Western part of the country [
This was a descriptive, cross-sectional, retrospective study of prescriptions purposively carried out among NHIS outpatients at the University of Nigeria Teaching Hospital (UNTH), Enugu. NHIS outpatients are seen by medical doctors from various specialties. These patients access their NHIS approved drugs with a 10% copayment only from the NHIS outpatients’ pharmacy unit. UNTH is a tertiary health care facility of about 500-bed capacity with staff made up of professionals and nonprofessionals. It serves as the teaching hospital for the faculty of medicine of the University of Nigeria and is a participating Health Care Provider (HCP) on the insurance scheme.
This comprised all NHIS outpatients’ prescriptions that contained at least one antimalarial drug filled from January to December 2013. Prescriptions from antenatal clinic were excluded due to the use of SP for Intermittent Preventive Therapy (IPT) in pregnancy.
Large sample size which exceeded the minimum of 100 suggested by WHO was employed in order to enhance the reliability of the results since only one health facility was used for the study [
The modified World Health Organization (WHO) prescribing indicator form was used to extract the following data: age; sex; month of prescription; the names of antimalarial drugs prescribed; number of drugs prescribed; number of drugs dispensed; number of drugs prescribed from Essential Drug List (EDL) [
Abstracted information was later keyed into Statistical Package for Social Sciences (SPSS, version 21, Chicago, USA) coded for data analysis. Raw data were double-checked with soft data for consistency. The WHO drug use indicators investigated in this study were the average number of drugs per encounter, percentage encounter with an antibiotic, percentage encounter with an injection, number of drugs prescribed by generic name, and the number of drugs prescribed from NHIS EDL described elsewhere [
Permission to conduct the study was sought from the hospital management and ethical clearance was obtained from the Research and Ethics Committee of the UNTH.
Demographic information of the study patients is presented in Table
Demographic characteristics of patients prescribed antimalarial drugs
Variable | |
---|---|
| |
Female | 231 (69.4) |
Male | 104 (30.6) |
| |
<5 | 21 (6.3) |
5–11 | 24 (7.2) |
12–18 | 11 (3.3) |
>18 | 179 (53.8) |
Not indicated | 98 (29.4) |
| |
First quarter | 80 (24.0) |
Second quarter | 125 (37.5) |
Third quarter | 118 (35.4) |
Fourth quarter | 10 (3.0) |
A quarter refers to one-fourth of a year (a period of 3 months).
Table
Prescription pattern of antimalarial drugs
Antimalarial drug regimens prescribed | |
---|---|
| |
Proguanil | 5 (1.5) |
Sulphadoxine-Pyrimethamine | 2 (0.6) |
Amodiaquine | 1 (0.3) |
| |
Artesunate | 2 (0.6) |
Arteether | 2 (0.6) |
Artemether | 1 (0.3) |
Dihydroartemisinin | 1 (0.3) |
| |
Artemether/Lumefantrine | 269 (80.8) |
Artesunate/Mefloquine | 20 (6.0) |
Dihydroartemisinin/Piperaquine | 16 (4.8) |
Artesunate/Amodiaquine | 8 (2.4) |
Artesunate/Piperaquine | 4 (1.2) |
Artemether/Lumefantrine + Sulphadoxine-Pyrimethamine | 1 (0.3) |
Artesunate/Sulphadoxine-Pyrimethamine + Proguanil | 1 (0.3) |
Figure
Table
Drug prescribing indicators.
Variable | Value |
---|---|
Average number of drugs prescribed per encounter (mean ± SD) | 4.8 ± 1.8 |
Percentage encounter with an antibiotic (%) | 37.2 |
Percentage encounter with an injection (%) | 1.5 |
Percentage of drugs prescribed by generic name (%) | 49.3 |
Percentage of drugs prescribed from EDL (%) | 63.0 |
Percentage drugs dispensed (%) | 91.8 |
Table
Predictor variables for antimalarial drug coprescription with antibiotics.
Variable | Adjusted odds ratio | 95% CI | |
---|---|---|---|
| |||
<5 years | Reference | ||
5–11 years | 0.16 | 0.04–0.61 | 0.007 |
12–18 years | 0.20 | 0.04–1.03 | 0.055 |
>18 years | 0.29 | 0.11–0.75 | 0.011 |
| |||
Female | Reference | ||
Male | 0.86 | 0.52–1.42 | 0.551 |
| |||
First quarter | Reference | ||
Second quarter | 0.87 | 0.48–1.58 | 0.650 |
Third quarter | 0.94 | 0.51–1.72 | 0.837 |
Fourth quarter | 1.72 | 0.44–6.76 | 0.441 |
This study revealed high prevalence of use of ACTs especially AL for the treatment of malaria infections among insured patients. AL is the antimalarial drug of choice for the treatment of uncomplicated malaria in Nigeria due to its demonstrated efficacy. The results of the drug efficacy trials carried out in the all the geopolitical regions of the country in 2004 found AL to be highly efficacious and thus suitable for use in the treatment of uncomplicated
Analysis of drug prescribing indicators revealed high average number of drugs prescribed per encounter which indicates occurrence of polypharmacy. This result is comparable with the values of 3.4, 3.8, and 4.1 got from earlier NHIS studies in tertiary hospitals in South Western, North Eastern, and North Western Nigeria [
However, evaluation of encounters with antibiotics revealed a higher value of 37.2% as against the WHO reference range of 20.0%–26.8% [
The low number of drugs prescribed from the EDL was due to nonrevision of NHIS EDL 2005 edition for almost a decade. Implementation of this EDL after 8 years constrained the prescribers in the scheme, thereby forcing them to prescribe some drugs not listed in the NHIS EDL that were considered effective based on clinical judgment to meet the desired health outcomes for the patients. The concept of essential drugs incorporates the need to regularly delete obsolete medicines and add newer more effective ones to reflect new treatment options and changing therapeutic needs among others [
The low use of injections and high amount of medicine dispensed were commendable. Use of injections is associated with adverse events and increased cost. On the other hand, high number of medicines dispensed reported by this study shows that the hospital procured some medicines outside the NHIS EDL to decrease patients out-of-pocket expenses on medicines due to the restriction imposed by the outdated NHIS EDL.
Furthermore, this study assessed the factors associated with antimalarial drugs coprescription with antibiotics. Predictor found to be associated with the risk of being coprescribed antimalarial drugs with antibiotics was age. Children under five years of age were much more likely to be coprescribed antimalarial drugs and antibiotics than those aged 5 years and more. Similar findings were reported in South Eastern and South Western Nigeria [
The limitations of this study include the retrospective collection of prescription data. This made it impossible for parasitological and patient clinical results to be collected. Therefore, use of drug could not be linked with the clinical decisions that informed the prescriptions. However, only prescription data was used to describe quality indicator index of drug prescribing: DU90%. Due to time lag between data collection and publishing of findings, the study findings may not reflect the current antimalarial drug prescribing practice of the setting studied. Lastly, the use of only one centre for the study restricts the generalization of the findings.
This study showed a higher use of artemisinin-based combination therapy and high concordance with National Antimalarial Treatment Guideline for the treatment of malaria infection. Based on this result, policy makers can consider addressing Universal Health Coverage (UHC) as health priority for Nigerian citizens as part of national malaria elimination strategy. Age less than 5 years is a significant risk factor for antimalarial drugs coprescription with antibiotics We recommend that prescribers at the study setting should conduct appropriate test to confirm bacterial infections before prescribing antibiotics especially for this vulnerable age group.
The authors declare that they have no conflicts of interest to disclose regarding the publication of this paper.
Additional file (xls) containing antimalarial drug information and drug prescribing indicators data.