According to the World Health Organization (WHO) (2014), antibiotic resistance is a worldwide public issue. Resistant bacteria are linked to increased incidences of disability, death, and socioeconomic costs (WHO, 2014). Moreover, most of the acute Respiratory infections (ARIs) are caused by overuse of antibiotics, but still, antibiotic prescriptions for the disease are on the increase (Barnett & Linder, 2014). Studies have indicated that inappropriate prescriptions of antibiotics are likely to cause severe drug impacts, high costs of treatment, and the increase and transmission of resistant organisms (Centres for Disease Control and Prevention (CDCP) (2013). CDCP (2013) found out that inappropriate use of antibiotics is the primary cause of drug resistance. The increase in antimicrobial resistance has become a global public health concern (WHO, 2014). There are fears that the resistance in the future may increase to unprecedented levels which may interrupt important medical procedures (Davies, Fowler, Watson, Livermore, & Walker, 2013).
Non-adherence to clinical procedures by healthcare experts has been found in multiple settings. More specifically, the non-compliance to outlined guidelines has always been evidenced in primary care (McDermott et al., 2014). Non-compliance to procedures in primary care can result in multiple complications in addition to the deterioration of the medical condition of the patient or the increase in the risk factors that influence the disorder. As a result, several invention mechanisms have been proposed to foster compliance with guidelines. Some of these are educational programmes and materials, and automated delivered systems (McDermott et al., 2014). The objective of this paper is to ascertain the effectiveness of Community and Primary Care Education Interventions at Reducing Rates of Antibiotic Prescriptions by critically examining relevant literature.
Relevant articles to the study topic were searched for using specific keywords such as intervention, upper respiratory tract infection, acute respiratory infection, antibiotics, prescriptions of antibiotics, and primary care. These keywords were keyed into specific search engines namely Google Scholar, NCBI, and PubMed. Only articles published in English and not older than five years were included in the search. Furthermore, the articles had to be peer-reviewed and randomized control trials (RCTs). The research was conducted between September and December 2018, and published journals were retrieved from the databases after identification, evaluation and quality check. The articles were critiqued using the CASP checklist for cohort studies.
The study by Lee et al. (2017) examined the effectiveness of patient-focused education in lowering antibiotic prescriptions for upper respiratory tract infection (URTIs) among grown persons in Singapore and receiving primary care. The subjects under study had to be diagnosed with URTI symptoms for a week or less. Therefore, the study addressed the research question. The RCT was a most appropriate design for the study because it enables the researcher to compare the efficacy of intervention with another to ascertain superiority. The sample is relatively representative of the defined population because of its high rate of the outcome. Charan and Biswas (2013) observe that the rates of outcome in cohort studies help to determine sample size. For instance, data on antibiotic prescription were unavailable, and thus the authors had to work with estimates of 10% to 30%. The patients were randomly assigned to either the experimental or control arm by the use of sequential envelopes with automatically generated tasks founded on essential block randomization. This ensured that that selection bias was minimal (Sterne et al., 2016).
Furthermore, the confounding effect of variations in the prescription practices of the general practitioner was addressed by using randomization level instead of cluster level. A similar procedure was used to classify all the participants into the study groups thus avoiding any potential risk of bias (Lee et al., 2017). The study was approved by an ethical approval board, and informed consent was obtained from the general practitioners’ clinics before the study. Thus, the study met ethical considerations. Using the FORM technique of grading evidence, the study by Lee et al. (2017) has scored grade B, implying that the body of evidence can be relied upon but with caution because of the missing data on antibiotic prescriptions, and is likely to affect the outcomes.
Elouafkaoui et al. (2016) conducted a cluster RCT to determine the efficiency of an audit and feedback intervention in minimizing the prescription of antibiotics in general dental practices. The study population consisted of all antibiotic prescribing NHS general dental practices in Scotland. The risk factors for antibiotic prescriptions are also considered. This is an indication that the study clearly addressed the research question (CASP, n.d.). The study used the RAPiD cluster randomized controlled trial. This technique was the most appropriate for the study because it ensured that the recruitment of trial subjects were not in contact with each other, no self-report measures, and prohibited the researchers from influencing the rates of antibiotic prescriptions in the feedback (McCambridge, Kypri, & Elbourne, 2014). All these strengths of the design minimized the potential for any sources of bias linked to the entire process of research. Thus, the RAPiD RCT was best suited for the study.
The sample size of the study was a representation of the target population because it achieved 80% power (Im & Halberda, 2013). Furthermore, the study assessed all antibiotic prescribing NHS general dental practices in Scotland, hence the reason for the high power of the sample size.
Prescription practices were randomly ordered in a simultaneous manner and the identity of the practices blinded from the researcher. Moreover, the allocation schedule was electronically generated and randomization stratified. The blinding of the researcher and simultaneous randomization reduced the potential for selection bias ( Probst et al., 2016). Additionally, the similarity of the measurement methods across the groups minimized any potential risk for performance bias (Mansournia, Higgins, Sterne, & Hernán, 2017). Stratified randomization as used in the research is an indication of that the study accounted for confounding factors (Braga, Farrokhyar, & Bhandari, 2012). The research by Elouafkaoui et al. (2016) obtained ethical approval from the relevant ethics committee. Furthermore, the protocol was submitted to the NHS and approved. There was no need for informed consent since the data used for analysis did not have any information on the personal profile.
The study can be awarded grade A (excellent) based on the FORM approach because there is consistency in the study and high generalizability since the target population is also the sample size. Thus, the body of evidence can be relied on for implementation (Hillier et al., 2011).
Persell et al. (2016) carried out a randomized pilot trial on social interventions to minimize wrong antibiotic prescription. A total of 3,276 visits were assessed in the year of pre-intervention and 3,099 in the intervention year. This included all practicing nurses and doctors that attended The North-western Medical Faculty Foundation. Based on the objective of the study it is clear that the research endeavored to find out the harmful effect of inappropriate antibiotic prescription. Furthermore, the outcomes of the study are considered and discussed as primary and secondary outcomes. Therefore, the study indeed addressed the issue under focus. The randomized pilot trial study design was the most appropriate because it is the most powerful empirical evidence of a treatment’s efficacy. Additionally, randomization ensures that allocation and selection bias is at a minimum (Bench, Day, & Metcalfe, 2013).
The study population consisted of all practicing nurses and doctors that attended The North-western Medical Faculty Foundation. The participants were randomized into three-factorial experiments with three interventions. The randomization of the clinicians was done simultaneously into blocks by some qualifying visits to ensure equality in allocation (Persell et al., 2016). Randomization ensured that allocation bias was minimized (Bench, et al,. 2013). The subjects were not blinded to their study group tasks once the intervention was commenced. Blinding of the researcher minimizes performance bias and any other potential threat to validity (Probst et al., 2016). Moreover, the participants were assigned to their groups using a random number generator carried out by a researcher who was blinded of the identities of the clinicians until after the completion of randomization. This increased performance bias and is likely to affect the outcomes (Probst et al., 2016).
The pre-intervention sample was 3,276 visits whereas during the intervention year only 3,099 visits were realized. This represented a prescription decline from 24.7% to 5.2%. This significant decline can be attributed to lack of blinding of the subjects thus increasing the chances of performance bias and other potential threats to validity (Probst et al., 2016). Using the FORM technique of grading evidence, the study by Persell et al. (2016) scores grade D (poor), because the study had a high risk of performance bias, the evidence in the pre-intervention and intervention is inconsistent. The study obtained the informed consent of the participants in writing in addition to an ethical approval from the appropriate committee.
A pragmatic RCT was undertaken by Hallsworth et al. (2016) with the aim of minimizing inappropriate prescriptions of antibiotics by the GP in England. The risk factors of unnecessary antibiotic prescriptions such as antimicrobial resistance were assessed in the study. Furthermore, the outcomes of the research were considered in light of the objective. According to the CASP (n.d.) tool of critiquing cohort studies, these descriptions are evidence that the study indeed addressed the focused issue (Hallsworth et al., 2016). The pragmatic RCT was inappropriate for the study because it involved only one intervention group thus making it difficult to separate the impacts of the different intervention elements. This also implies that it wasn’t possible to measure the effect of the intervention on health outcomes and thus impossible to determine the harms and benefits, which is the principal objective of RCT (Hallsworth et al., 2016). The sample population consisted of only GP practices in England. This sample was not representative because it was made up of the highest prescribers’ only, thus increasing selection bias (Mansournia et al. 2017). As a result, the generalizability of the study to the rest of the population is compromised (Smith, 2018).
The GP practices were assigned to placebo or experimental groups by the researcher on a random basis and stratified by the NHS local area groups. According to Sedgwick (2015) stratification in RCT can be an indication of confounding. The allocation was done with the help of numbers that were electronically generated, thus reducing the risk of allocation bias (Mansournia et al. 2017). The study subjects were cognizant of their intervention groups but not aware of whether they were included in the trial. Thus there was no blinding of the research team to group assignment. The exclusion of blinding or concealment in an RCT increases performance bias and therefore, significantly compromises the validity and reliability of the study (Probst et al., 2016). The NHS research ethics committee approved the study in addition to waiving the need for informed consent. This study can be graded as D (poor) because of the inappropriate selection of the study design (RCT) in which there is only one intervention, and the participants are not blinded. Moreover, the study has issues with generalizability because of the unrepresentative sample.
McDermott et al. (2014) carried out a process assessment for a cluster randomized trial of an electronically administered point of care intervention to lower the prescription rate of antibiotics in primary care. The target population consisted of 103 GPs and four implementation staff. The risk factors in the study were antibiotic prescriptions of RTI patients. Thus, the above facts are proof that the study answers the research question according to the CSAP checklist (CSAP, n.d.). The use of a mixed approach was appropriate for the study because it is useful in developing a suitable research instrument that generates precise measures. Furthermore, the design allows the involvement of community-based stakeholders such as patients and physicians (Tariq & Woodman., 2013).
Data was collected using a telephone interview and semi-structured questionnaires which were designed using the Linnan and Steckler criteria (Moore et al., 2015). Lai (2013) observes that the development of research instruments by validated instruments increases the possibility of collecting correct data. The interviewer did not participate in the trial management thus minimizing the risk of selection bias (Mansournia et al. 2017). The sample size is likely to be unrepresentative because the participants joined the study on a voluntary basis. More specifically, the GPs with interest in the study topic was likely to volunteer as participants, thus making it difficult to generalize the findings since the sample for analysis only represents GPs aware of the research. This further compromises the validity and reliability of the results (Heale & Twycross, 2015). Ethical approval was obtained from the research committee in addition to informed consent. This implies that the study minimized any risk of harm, and therefore the participants would give appropriate information (Newson & Lipworth., 2016). Based on the grading by FORM, this study scores C because the body of evidence can be implemented but cautiously due to lack of generalizability.
Educational intervention gives more insight into the cause of upper respiratory tract infections (URTI), but the education must first create awareness on the side effects of antibiotics and that it’s not always the case that they should be diagnosed in cases of URTIs. However, the effectiveness of the education intervention is also dependent on a factor such as the willingness to receive education on antibiotics and existing ethnic and cultural factors (Lee et al., 2017). Pan et al. (2016) found out that patients who had desired to be given antibiotics indeed received them. Personalized audit and feedback interventions have also been found to be effective in reducing the number of prescriptions per 100NHS treatment assertions — the pictorial presentation of a line graph that showed a practitioners monthly prescriptions alongside a drafter behavior change positively influenced general practitioners (Elouafkaoui et al., 2016).
Furthermore, feedback interventions are the most preferred than other alternatives because they are economically viable, can be achieved on a large scale, and minimal hindrances when undertaking feedback interventions. The implementation of the principles of social psychology and behavioral economics in designing community and education interventions to reduce the rate of antibiotic prescriptions. The study by Elouafkaoui et al. (2016) was of the highest quality because there is consistency in the study and high generalizability since the target population is also the sample size. Thus, the body of evidence can be relied on for implementation. However, the study findings can be implemented in policy and practice because they are all RCTs that are based on actual experiences and conducted across different countries and settings. This implies that common findings across the studies can be implemented in policy and practice as is practically possible. However, there is a need for further research on how the efficacy of antibiotic prescription feedback can be optimized. The major limitation of this study is that it was impossible to ascertain whether the decline in the prescription of antibiotics occurred only for infections for which they were ineffective or not.
Conclusion:
The constant use of antibiotics has led to increased incidences of morbidity and mortality worldwide. Moreover, the overuse of antibiotics is the main cause of drug resistance. Inappropriate prescriptions of antibiotics by general practitioners is due to non-adherence to clinical guidelines especially on primary care. This critical review has a significant impact on antibiotic prescriptions both to patients and general practitioners. Community and education in primary care are most effective in reducing antibiotic prescriptions. An education approach that objectively focuses on meeting the needs of the patient is one of the most effective intervention. Furthermore, education on antibiotic prescription is likely to increase the patients’ comprehension of the causes of URTI and reduction in the rate of antibiotic prescriptions. Furthermore, an audit and feedback intervention can lead to significant reduction in the rate of antibiotic prescriptions by general practitioners. However, several factors can hinder the success of such interventions such as the desire to be trained, and existing ethnic and cultural factors.
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