1 Médecins Sans Frontières-France, P.O. Box 39719, Nairobi, Kenya
2 Ministry of Health, Division of Malaria Control, P.O. Box 20750, Nairobi, Kenya
3 KEMRI/Wellcome Trust Collaborative Programme, P.O. Box 43640, 00100 GPO, Nairobi, Kenya
4 Centre for Tropical Medicine, University of Oxford, John Radcliffe Hospital, Headington, Oxford OX3 9DU, UK
5 Malaria Branch, Division of Parasitic Diseases, National Center for Infectious Diseases, Centers for Disease Control and Prevention, Mailstop F22, 4770 Buford Highway, Atlanta, Georgia 30341, USA
6 Kenyatta National Hospital, P.O. Box 20723, Nairobi, Kenya
7 Center for Geographic Medicine, KEMRI, P.O. Box 230, Kilifi, Kenya
8 Department of Paediatrics, University of Oxford, John Radcliffe Hospital, Headington, Oxford OX3 9DU, UK
Correspondence: Dr Dejan Zurovac, KEMRI/Wellcome Trust Collaborative Programme, P.O. Box 43640, 00100 GPO, Nairobi, Kenya. E-mail: dzurovac{at}wtnairobi.mimcom.net
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Abstract |
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Methods We analysed data from a survey of government health facilities in four Kenyan districts in which HW consultations were observed, caretakers and HW were interviewed, and health facility assessments were performed. The analysis was limited to children 259 months old with uncomplicated malaria. Treatment was defined as recommended (antimalarial recommended by national guidelines), a minor error (effective, but non-recommended antimalarial), or inappropriate (no effective antimalarial).
Results We evaluated 1006 consultations performed by 135 HW at 81 facilities: 567 children received recommended treatment, 314 had minor errors, and 125 received inappropriate treatment (weighted percentages: 56.9%, 30.4%, and 12.7%). Multivariate logistic regression analysis revealed that programmatic interventions such as in-service malaria training, provision of guidelines and wall charts, and more frequent supervision were significantly associated with better treatment quality. However, neither in-service training nor possession of the guideline document showed an effect by itself. More qualified HW made more errors: both major and minor errors (but generally more minor errors) when second-line drugs were in stock, and more major errors when second-line drugs were not in stock. Child factors such as age and a main complaint of fever were also associated with treatment quality.
Conclusions Our results support the use of several programmatic strategies that can redress HW deficiencies in malaria treatment. Targeted cost-effectiveness trials would help refine these strategies and provide more precise guidance on affordable and effective ways to strengthen and maintain HW practices.
Accepted 19 April 2004
One strategy of the Roll Back Malaria Initiative to halve malaria mortality by 2010 is prompt access to effective antimalarial treatment, especially among children <5 years of age.1,2 Countries in East and Southern Africa have struggled in recent years to define affordable alternatives to the rapidly declining effectiveness of chloroquine. In 1998, the Kenyan Ministry of Health, through a difficult process of consensus building, changed the policy for the first-line treatment of uncomplicated malaria from chloroquine to sulfadoxine-pyrimethamine (SP).3 This new policy was stated in the Kenyan National Malaria Control Program's (NMCP) malaria guideline for health workers.4
Prescribers' adherence to treatment guidelines remains critical to the success of any new drug policy. However, results from health facility surveys have shown that health workers (HW) frequently do not comply with treatment guidelines.511 Different types of treatment error have been reported, each with different assumed clinical consequences.11 For example, compared with recommended treatment, treatment with an antimalarial drug that is effective but not recommended by a guideline has been considered a minor error as it does not increase the risk of a poor outcome; whereas treatment with an ineffective antimalarial (or no antimalarial) has been considered an inappropriate treatment or a major error. Several studies have analysed the reasons for inadequate paediatric clinical management,8,1215 but many had important methodological limitations (described in Rowe et al.5) and malaria treatment was rarely the focus of analysis.
In Kenya, failure rates of nationally recommended antimalarial drugs (SP and amodiaquine) are increasing.16 As recommended by the World Health Organization (WHO), artemisinin-based combination treatments are now being considered to replace SP monotherapy. These drugs are considerably more expensive, have less well-documented safety profiles, and have complex dosing regimens.17 In recognition of the fact that new drug policies will need better implementation strategies in the health facility setting, and that better implementation strategies require an understanding of why treatment errors occur, we studied current prescription practices in Kenya to identify the factors that influence the quality of malaria treatment in government facilities.
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Methods |
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After the observed HW and caretaker (usually the child's mother) consented verbally, an observer recruited all sick children presenting to outpatient departments during working hours. If more than one HW was seeing sick children at a facility, all were observed and interviewed. The national ethical review board provided ethical clearance.
Surveys in each of the four districts were conducted with four teams. Surveyors were trained for 3 days. To assess surveyors' ability to accurately observe consultations (for observers) or record caretaker responses (for interviewers), we conducted role-plays of consultations and interviews in which a gold standard set of correct observations (or interview responses) was determined by the trainers (i.e. the investigators). For each role-play, we calculated a per cent agreement score for each surveyor, where per cent agreement = (number of survey items the surveyor recorded that matched the gold standard/total number of survey items for a particular role-play) x 100%. Training continued until the agreement scores were >90%. Data were collected using four methods. First, consultations were silently observed by a surveyor who recorded the performance of clinical tasks using a checklist. Second, caretakers were interviewed when they were ready to leave the facility. Interviewers collected information about the child's age, history of fever, and if the visit was an initial or follow-up consultation. Information was collected from patient-held records about diagnostic procedures requested and results reported (e.g. malaria blood smears), medications prescribed, and if the child was treated as an outpatient or referred for hospitalization. Third, interviews were conducted with observed HW to collect information on demographics, pre-service training, working experience, possession of the NMCP guideline document, and exposure to in-service training and supervision. Fourth, a health facility assessment was performed to record the availability of medical supplies and equipment related to malaria case management.
In this analysis, to identify predictors of treatment quality, we included the subset of children who: (1) had a completed interview with both the child's caretaker and the HW who performed the consultation, (2) were 259 months old, and (3) were brought to the facility for an initial consultation with uncomplicated malaria (Box 1).
Box 1 Definitions of uncomplicated malaria for children under 5 years old Definition according to the Kenya National Malaria Control Program guideline A) Parasitaemia and any of the clinical features of malaria (fever, myalgia, joint pains, chills, splenomegaly, mental confusion, abdominal pain and diarrhoea, nausea and vomiting, irritability and refusal to feed), especially fever, and no sign of severe or complicated malaria (prostration [cannot sit up if old enough or cannot feed in a younger child], impaired consciousness, respiratory distress [rapid deep breathing or chest indrawing], cerebral malaria with coma, convulsions, severe anaemia [hemoglobin <5 gm/dl], renal failure, hypoglycaemia [blood sugar <2.2 mmol/l], fluid and electrolyte imbalance, pulmonary oedema, hypovolaemic shock, hyperparasitaemia [which varies with immune status], malaria haemoglobinuria [coca cola coloured urine], and disseminated intravascular coagulopathy [spontaneous bleeding]). (Pages 12, 13, and 19 of reference 4) B) Note 1. In certain cases a slide may be negative even when the patient has malaria. Conversely, malaria parasitaemia may not be the cause of the presenting illness. (Page 16 of reference 4) C) Note 2. When [microscopic diagnosis] is not possible, treatment should be given on the basis of presumptive diagnosis of malaria. (Page 16 of reference 4) Definition used in the analysis History of fever during the present illness (according to the study interviewers), child treated as an Outpatient (according to the observed health worker), and the absence of a negative blood slide (according to the record in patient-held cards).
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Definitions
Our definitions reflected national recommendations for malaria diagnosis and treatment in place at the time of the survey (Box 1). The definition of uncomplicated malaria was modified because the NMCP guideline lacked precision and because we did not collect all the information needed for establishing the diagnosis according to the NMCP guideline. As we did not perform an independent clinical re-examination of the sick children to establish a gold standard diagnosis, we used the HW decision to manage the child as an outpatient as a proxy measure of uncomplicated malaria. We acknowledge that some children treated as outpatients may have had severe malaria, and thus were misclassified in the analysis. However, given that severe disease is relatively uncommon among febrile children in outpatient setting,1820 the potential bias this misclassification introduced was considered minor. Furthermore, if a child who truly had severe malaria was treated as an outpatient because the HW thought the child had uncomplicated malaria, an evaluation of the child's treatment still provides useful information because the prescribed drugs reflect HW performance in managing uncomplicated malaria.
For uncomplicated malaria, the NMCP guideline recommends oral SP as the first-line treatment and oral amodiaquine or quinine as the second-line treatment. Guidelines do not specify if HW should prescribe second-line drugs if the child had received treatment at home with SP. Therefore, we defined recommended treatment as prescription of oral SP monotherapy. In addition, to prevent HW practices from being judged as incorrect due to the unclear guideline recommendation, if the caretaker reported during the consultation that the child's illness had been treated with SP, the prescription of either SP, amodiaquine, or quinine (prescribed as an oral medication and as a monotherapy) was considered recommended treatment. A minor error was defined as the prescription of all non-recommended but still effective antimalarial treatments. Inappropriate treatment (or a major error) was defined as either chloroquine or no antimalarial treatment.
A potential limitation of this definition was that it did not include drug dosage. Dosage was not considered because: (1) we did not weigh children, and using only age to determine correct dosage might have misclassified treatment quality; and (2) HW commonly prescribed SP syrups and drops without clearly documenting the dosage.
Data entry and statistical analysis
Data were entered and validated with Access 2000 (Microsoft Inc, Redmond, Washington) through customized data-entry screens with range and consistency checks. Questionnaires were entered twice by independent data entry clerks, and data files were compared for errors. The analysis was performed using STATA, version 6 (StataCorp, College Station, Texas). Results from all four districts were combined. To account for unequal probabilities of selection of health facilities, all results were weighted (weight = 1/probability of selection).
To identify predictors of three categories of treatment quality (recommended, minor errors, and inappropriate), we used multiple binomial logistic regression modeling.11 With this technique, a series of binomial logistic regression models are created (one model for each category of treatment quality), and the results are interpreted together. We first performed a univariate analysis in which the logistic regression models were fitted with the STATA xtgee procedure using an exchangeable working correlation matrix. This procedure uses generalized estimating equations to account for the potential correlation of treatment quality among children seen by the same HW.21 The exchangeable correlation structure assumes the correlation of the treatment quality between any pair of children is approximately constant.
In the univariate analysis, we estimated the odds ratio (OR), P-value, and 95% CI for the association of each category of treatment quality with the following factors: duration of the consultation; starting time of the consultation (before 1:00 p.m. versus 1:00 p.m. or later); caseload during 2 days of the survey visit, both as a continuous variable and a dichotomous variable (30 versus <30 child consultations); child's age; caretakers' report during the consultation on previous use of SP; main complaint of fever; case complexity as a three-level variable (main complaint of fever with cough or diarrhoea versus main complaint of fever alone versus fever not mentioned as a main complaint); HW age, work experience (years working as a health worker), and pre-service training (clinical officers with a 3-year diploma in clinical medicine, nurses whose training included primary health care and nursing aides, informally trained with skills comparable to community HW); and all variables listed in Table 1. For in-service malaria training, we examined whether the HW attended the training, duration of the training, and whether the training included clinical practice. For supervision, we focused on the previous 6 months. We examined the quality (three levels: no supervision, supervision with observation of a consultation and feedback, and supervision without observation and feedback) and quantity (three levels: no supervision, 13 visits, and 410 visits). Availability of SP could not be studied because SP was in stock in nearly all (97.7%) facilities. We evaluated statistical interactions between in-service malaria training and HW pre-service training, supervision and in-service training, in-service training and availability of malaria treatment wall charts, pre-service training and availability of second-line drugs, and availability of guidelines and in-service training.
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Although meeting the entrance criteria for the multivariate analysis, variables for health facility type and caseload 30 were excluded because they were strongly correlated with HW pre-service training: clinical officers were much more likely than nurses and nursing aides to have high caseloads and to have never worked in dispensaries. The malaria diagnosis variable was excluded because it was believed to be in the causal pathway between other independent variables and treatment quality. The three multivariate models were forced to contain the same variables: any variable meeting the entrance criteria for one model was automatically entered into the other two models. This approach ensured that the three OR (one from each model) for a given factor would be adjusted for the same covariates. Hypothesis testing and CI estimation were done with an alpha level of 0.05. The term borderline statistical significance was used to indicate associations with a P-value between 0.05 and 0.10.
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Results |
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Most HW were nurses (76.8%) or clinical officers (15.7%) (Table 1). No HW received Integrated Management of Childhood Illness training (a training course developed by WHO and the United Nations Children's Fund (UNICEF) that includes instruction on managing malaria), and 44.9% received malaria in-service training. About one-third of HW who received malaria in-service training were trained in 19981999, and about two-thirds were trained in 20002001. The duration of malaria training was 1 day for 32 (50.1%) health workers, 23 days for 18 (33.3%), and 57 days for 9 (16.6%). The malaria training course of 25 (43.8%) HW included clinical practice. Sixty (67.6%) HW had 13 supervisory visits in the last 6 months, 30 (28.1%) had 46 visits, and 4 (4.4%) had 710 visits. SP was in stock on the day of survey in 80 of 81 surveyed facilities, while either amodiaquine or quinine was available in only 53.1% of facilities.
For the predictors analysis, 1006 sick children met our definition of uncomplicated malaria: 567 (56.9%) received recommended treatment, 314 (30.4%) had a minor error, and 125 (12.7%) were given an inappropriate treatment. Only 20 caretakers reported that their child had been treated with SP before coming to the health facility. The distribution of antimalarial treatments within each category of treatment quality is presented in Table 2.
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Generally, nursing aides adhered much more closely to guidelines than nurses and clinical officers, and the effect of HW pre-service training on treatment quality depended on the availability of second-line drugs at the facility. When second-line drugs were not in stock, children were significantly more likely to receive inappropriate treatment if treated by a clinical officer (ORmaj = 25.45) or nurse (ORmaj = 7.11) compared with a nursing aide (Table 4). When second-line drugs were in stock, children treated by clinical officers were significantly less likely to receive recommended treatment and more likely to have minor errors (ORrec = 0.07 and ORmin = 13.06), and children treated by nurses were significantly less likely to receive recommended treatment and more likely to have major errors (ORrec = 0.09 and ORmaj = 3.27). The effect of in-service malaria training depended whether a HW possessed a copy of the NMCP guideline. When HW did not have the guideline, there was no significant association between in-service training and the quality of treatment. However, when HW had the guideline, children seen by trained health workers were significantly more likely to receive recommended treatment (ORrec = 2.98) and significantly less likely to receive inappropriate treatment (ORmaj = 0.25).
Among factors excluded from the multivariate analysis, we found several interesting univariate results. For example, treatment quality was significantly better for children whose malaria was diagnosed by the HW, for children treated in dispensaries, and for children treated by health workers who had a 2-day caseload <30 consultations (Table 5). However, as described in the Methods, the influence of health facility type and high caseload cannot be separated from HW pre-service training.
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Discussion |
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Our first main finding was that several commonly used interventions for improving HW practices were significantly associated with prescribing recommended treatment: in-service training, possession of the NMCP guideline, treatment wall charts, and supervision. Regarding in-service training, other studies with a similar design have reported a variety of results, ranging from an association with better HW performance24 to an association with more minor errors25 to no association with performance.5,11 Our study has found something new: specific subgroups of HW for whom training seemed beneficial (HW possessing the guideline) or inconsequential (those without the guideline). The association with possessing the guideline, however, must be interpreted with caution because we do not know whether the factor was causally related to HW practices or simply a marker for another characteristic not measured in our study that was causally related (e.g. motivation). Perhaps motivated HW were more likely both to possess the guideline and benefit from training.
Similarly, caution is needed when interpreting the association of treatment wall charts. Wall charts could be causally associated with better treatment, but also could be a marker for motivated HW who are more likely to follow guidelines. The relationship may be more complex, however, given that one study found that wall charts were associated with treatment errors.5
As with in-service training and wall charts, supervision has had different reported effects in different studies. Our findings essentially agree with the results from Benin,11 Philippines,15 and Zimbabwe,26 while results from the Central African Republic and Malawi did not show an association with treatment quality.5,25 Unfortunately, most studies (including ours) had only limited details of the supervision, and thus it is difficult to make conclusions about the effectiveness of this common intervention.
However, given the discordant results for all these interventions, should we even be asking the question of whether an intervention is effective or not? Perhaps better questions are: what are the characteristics of successful training and supervision programmes?, and what are the most cost-effective combinations of interventions?
Our second main finding was that clinical officers and nurses were much less likely than nursing aides to adhere to guidelines. The results even suggested that clinical officers were less adherent than nurses, who were less adherent than nursing aides. This finding was remarkably similar to results from Benin for the treatment of fever11 and diarrhoea.12 Furthermore, in our study, the effect of pre-service training depended on the availability of second-line drugs. Several reasons may explain these results. First, nursing aides may not know how to prescribe second-line drugs and therefore avoid using them. Second, nursing aides may be better at following clinical algorithms because they have less of a medical vocabulary of alternative diagnoses and treatments that might interfere with the simple fever = malaria concept upon which the guideline is based. Third, clinical officers and, to a lesser extent, nurses, may have been taught (or socialized) that their clinical judgement can overrule guidelines. Indeed, they may view guidelines as suggestions, rather than rules that should be followed systematically. Fourth, clinical officers and nurses may have lost confidence in SP. Fifth, clinical officers and nurses may be more susceptible to pressures to prescribe second-line drugs inappropriately, such as profit motives or caretaker demands. Finally, it is possible that the causal factor is not HW pre-service training, but rather another closely related factor such as health facility type or caseload, the effects of which could not be separated from pre-service training.
The third main finding was that child and consultation factors were significantly associated with treatment quality. First, caretakers' report of fever as the chief complaint was associated with better treatment quality. A possible explanation is that HW consider a fever less important if a caretaker does not mention it voluntarily. The result supports interventions that teach caretakers to actively report their child's fever. Similarly, it may be helpful to instruct HW during training courses and supervision visits to check for fever and always pay attention to the fevers they identify because if the caretaker does not mention it, the malaria may be missed.
The second child-level factor was the child's age. Infants were less likely than older children to have minor errors. Perhaps this reveals HW concerns that second-line drugs such as amodiaquine or quinine are less safe for younger children. If this hypothesis is true and if failure rates with SP continue to rise, then appropriate use of second-line drugs should be emphasized for infants. A third factor, which was a consultation characteristic, only had borderline significance; however, our results suggested that children seen after 1 p.m. received better treatment. A possible explanation is that HW are less rushed in the afternoon, as most patients arrive at facilities in the morning. If confirmed, the results support interventions to space out consultations more evenly throughout the day or adding extra staff only for the mornings.
The last main finding was that we identified two statistical interactions. Although interactions complicate the interpretation of results, they act as a high-resolution lens for examining the influences of HW performance. Intuitively, interactions which allow the effect of a factor to be conditional on other factors seem to be an appropriate element of models that explain a phenomenon as complex as HW performance.
Limitations
Our study had several important limitations. First, the presence of the study observer may have caused HW to perform better than usual (i.e. the Hawthorn effect, as suggested by results from Benin27) or worse than usual, if observers made HW nervous. Second, as mentioned in Methods, there was no clinical re-examination to provide a gold standard diagnosis, and our definitions of treatment quality did not include drug dosage. Third, not all potential factors were studied, such as the child's temperature and the complexity of the guideline. Fourth, we had only limited details on key programmatic interventions such as supervision and training. Finally, we have performed multiple comparisons and some of the results may have been significant by chance.
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Conclusions and future directions |
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KEY MESSAGES
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Acknowledgments |
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References |
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