Community-Based Surveillance of Antimicrobial Use and ...

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8. Lessons learnt and recommendations8.3.1.4 Data management• In any surveillance programme, the data entry format has to be designed in consultationwith a statistician, in order to facilitate collection of all required data from all sites. Thedata entry formats used in the pilot sites differed in the features incorporated and thisaffected the ease of analysis.• Various types of errors were seen, including data entry errors and errors ininterpretation. Procedures need to be built in to minimize data entry errors.8.3.2 ABM use – Prescription dataABM use prescription data were collected by exit interviews at three sites in India and fromrecords maintained at the facilities at two sites in Africa. Feasibility, logistics and cost werethe prime considerations when developing these pilot projects. The objective was to evaluatethe feasibility of community‐based surveillance in resource‐poor settings. Although acomplex multistage cluster design was followed in each site, the model developed appears tobe feasible. However, several issues for improvement were identified.8.3.2.1 SamplingSampling involves the selection of a number of study ‘units’ from the study population. Atall sites ABMs could be obtained by the population through the private and public sectors.The main agencies prescribing or dispensing/selling ABMs for out‐patients were the publicsector primary health clinics, private general practices, the out‐patient clinics of the publicsector and private hospitals, and private pharmacies.• A multistage sampling was performed. In the first stage, clusters (facility typesprescribing or dispensing ABMs) were identified in the private and public sectors at eachsite. In the next step, the facilities to be included in each cluster were decided upon. Atthe third stage, the number of prescriptions containing ABM to be examined per monthper facility was determined. The decisions taken therefore, at each site, included thetypes of facilities to be sampled, the number of facilities per type and the number ofprescriptions to be examined per facility per month. There were no existing specificrecommendations on how this could be done, although the sites were referred to thestandard WHO/INRUD guidelines for assessing drug use in health facilities 53 . The facilitytypes were decided by the investigators based on local knowledge. The number offacilities to be included was decided on the basis of available lists of such facilitiesobtained from local bodies (such as the pharmacy association or medical association).The facilities were then selected either by random sampling or based on convenience.The latter method was more commonly applied. For determining the numbers ofprescriptions to be examined, a modification of the recommendations in the 1993 WHOguidelines was used 53 . The aim was to obtain 30 ABM‐containing prescriptions from eachfacility each month and to include at least 20 facilities. The plan was to include 10facilities from each facility type, but this was only achieved in some sites.• This approach of multistage sampling is practical, it appears to be satisfactory and isincluded in the current recommendations on assessing medicine use in communities 54 .Three of the five sites measured ABM use in various facility types in both the public andprivate sectors in order to better reflect the health‐care seeking behaviour of the localcommunities. However, the numbers and selection of facilities need to be reviewed and91
Community-based surveillance of antimicrobial useand resistance in resource-constrained settingsrefined. The clusters and the numbers per cluster need to reflect the health‐seekingbehaviour of the population in the area. For example, if 80% of the population seekshealth care in the public sector, 80% of the facilities need also to be in the public sector.However, establishing who uses what kind of facility in which sector is very complexand may be impossible to do in many resource‐poor settings. For example, while it maybe true that more than 80% of the South African population is uninsured, they may alsoresort to out‐of‐pocket purchase of health services and medicines, while being nominally“public sector dependent”. In India, the majority of people access health care in theprivate sector, despite the presence of public sector facilities.• Including multiple private and public sector facility types can improve the validity ofany inferences that may be drawn. Selecting appropriate facilities in developing countriescan be difficult for several reasons, including the non‐availability of accurate listings offacilities, lack of information and variability in the catchment population of facilities,overlap in the areas of service by facilities, and a lack of cooperation from randomlyselected facilities.• The number of prescriptions to be examined per month was decided upon based on thevariations expected. The minimum number of 30 antibiotic‐containing prescriptions perfacility per unit of time should be acceptable for cross‐sectional surveys, but a moreprecise sample number could be derived for time series analyses using the datagenerated in this study.8.3.2.2 Data collection• Data were collected by qualified pharmacists or specially trained individuals at mostsites. However, the data quality varied, especially in relation to the more detailed datarequired for calculating the number of DDDs per 100 patients. Where data on doses anddurations are not consistently recorded, such calculations will not be possible. These datawere more prone to error and showed much wider fluctuations than the data based onthe percentage of ABM‐containing prescriptions. Analysing data on additional ABM use,where patients had received more than one ABM, was difficult using the data setsprovided. Attention to training and supervision of data collectors is essential.• The required sample sizes, according to the agreed protocols, were often not obtained inmost sites. There were wide variations in the numbers of prescriptions noted betweenmonths and facility types in some sites. The reasons for these variations were myriad, butsuch variations could be minimized by continuous monitoring.• Monthly data did not show much variation. However, collecting data every month in asystematic manner is probably more sustainable than data collection at intervals of 3 to 6months.• Planning interventions is made easier if data are collected on the indications for ABMuse. Such data are, however, difficult to analyse because of the number of variables. Ifcommon out‐patient illnesses can be grouped (e.g., based on systems, symptoms), datauseful for developing interventions can be generated. One site attempted to determinethe degree of compliance with Standard Treatment Guidelines, and thus with theEssential Drugs List (EDL).92
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WHO/EMP/MAR/2009.2Community-Based S
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CONTENTSProject members ...........
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8.4 Lessons learnt concerning imple
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Community-based surveillance of ant
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How this report is organizedHow thi
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Executive summaryExecutive summaryI
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Executive summaryAlthough ABM use a
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1. Background, aims and general met
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