Antibiotic resistance is an urgent global health threat that is accelerating due to inadequate infection prevention and control practices, and sub-optimal prescribing of antibiotics (National Institute for Health and Care Excellence (NICE), 2015; World Health Organization (WHO), 2020). The effectiveness of antibiotics to treat bacterial infections is diminishing and, currently, there is little evidence to suggest new antibiotics will be effective or available (WHO, 2020). Infections are becoming harder to treat, with a consequent increase in medical costs, length of hospital stays and mortality rates (WHO, 2020).
Reducing the incidence of antibiotic resistance requires ‘antimicrobial stewardship’, defined as ‘an organisational or healthcare system-wide approach to promoting and monitoring judicious use of antimicrobials to preserve their future’ (NICE, 2015). This requires prescribers to be aware of the public health implications of antibiotic use and follow appropriate prescribing behaviours (Ness et al, 2016).
Prescribing decisions are complex, and are influenced by a range of factors including guideline adherence, time pressure and experience (Courtenay et al, 2019; Rose et al, 2019), as well as cultural, contextual and behavioural determinants; for example, emulating the incorrect prescribing behaviours of senior colleagues (Charani et al, 2011). While factors influencing the prescribing decisions of medical professionals have been widely researched, particularly in relation to doctors in acute settings or of GPs in primary care settings (Courtenay et al, 2019; Rose et al, 2019), less is known about factors influencing independent nurse prescribers' (INPs') prescribing decisions (Cope et al, 2016). Understanding these factors is important for ensuring optimal prescribing behaviours and antimicrobial stewardship.
The objective of this study was to identify some of the factors that influence different groups of INPs' prescribing decisions.
Aim
To establish the factors that influence INPs' antibiotic prescribing decisions, and to compare the responses between practice settings with factors that influence medical prescribers' antibiotic prescribing decisions.
Method
Members of three Facebook groups: Royal College of Nursing (RCN) General Practice Nurses (approximately 6000 members); RCN Advanced Nurse Practitioners (approximately 1700 members); and General Practice Nurse UK (approximately 6400 members), were invited to complete an online questionnaire between January and March 2021. These groups were chosen for their large membership and propensity to include INP members, which increased the size of the potential study sample. A post was added to each group page seeking the views of INPs with information about the research aims and the questionnaire. A consent form was included when the link was followed.
The opening question asked whether the responder was an INP. If not, the survey closed and there was only one attempt allowed per respondent. To improve response rates, the hyperlink was accessible from computers and smartphones, and the Facebook post was resubmitted on different days of the week to ensure people accessing social media on different days were able to see the post.
Data collection
Demographic data collected was age, area of work (GP, primary, secondary, other) and whether the respondent had an advanced nurse practitioner (ANP) qualification, how long they had been qualified and how long they had been prescribing (Figure 1a–b).
Data were collected using an adapted version of the knowledge and attitudes regarding antibiotics and resistance (KAAR-11) questionnaire (López-Vázquez et al, 2016), developed and validated for use with primary care physicians. The wording was changed to cover the demographics of nurses rather than doctors. The original question about buying antibiotics over the counter was excluded as this was not applicable in the UK.
Questions were rephrased for clarity as they had been translated from Spanish. This limited the effect on validity and reliability, as minor changes are less likely to have a significant impact (Boynton and Greenhalgh, 2004). According to López-Vázquez et al (2016), including two negative, two positive and a neutral rating can reduce leading bias by offering balanced response options. The author used Likert for easier use and data analysis than the original visual analogue scale. The adapted questionnaire was uploaded online using an online survey tool that enables users to build and distribute surveys, and analyse responses. The questionnaire was piloted on a convenience sample of eight INPs working in the researcher's primary care network. Detailed feedback was obtained from colleagues, establishing how long it took to complete, whether the instructions were comprehensive and the understanding of the statements. Using a questionnaire with a limited number of statements and graded scale response may not establish all the factors influencing INPs' prescribing decisions; however, time and cost constraints meant this was a practical and rapid method of including a wide range of respondents and gaining an awareness of some of these factors. Previous research has also used questionnaires to reveal prescribing influences, advocating it is an appropriate approach (Silverman, 2011).
Data analysis
Descriptive and inferential statistics were used to present the data. The data was displayed in graphs, allowing the different groups and their responses to be compared. The respondents were also compared to the demographics of the reported nursing UK population to ensure it was representative (Bloomberg and Volpe, 2019).
Descriptive statistics were used to organise the data so they were easily understood, allowing the research to display the average responses and ages by calculating the mean (Holcomb and Cox, 2017). Emerging patterns in responses were considered by using inferential statistics to draw conclusions inductively and to compare these conclusions with research of medical prescribers' prescribing decisions. T-test calculations were use on the demographic data to establish statistical significance. Fisher's exact test calculations were used to compare the responses with a P-value of <0.5 set at the significance level. This works better with a small sample group.
Ethical considerations
Ethical approval was granted from the university Health and Life Sciences Faculty Research Ethics Committee. A comprehensive, university ethics committee approved consent form was included, explaining the results would be part of a published university MSc in Advanced Nursing Practice, and may then be available online. It explained data would be securely digitally stored through the university Google Drive, guaranteeing anonymity as no identifying information would be used.
Results
There were 144 responses to the questionnaire, of which 24 were incomplete and another five were completed by non-prescribers; therefore, these 29 questionnaires were not included in analysis. The eight responses from the pilot were included as no change was made to the questionnaire following the pilot.
This gave a total of 115 completed questionnaires. Just over half of respondents worked in primary care, with 22% in general practice and 20% in secondary care; but there was enough representation of respondents from other practice settings to allow for comparison of results (Figure 2)
Discussion
The discussion reflected themes identified in previous qualitative research by Rose et al (2019) to analyse 17 qualitative studies from several countries focusing on GPs' views of antibiotic prescribing in primary care.
Patient factors
In response to the statement, ‘Antibiotics are often prescribed due to patients' demands', 47% (54) of respondents agreed and 39% (45) disagreed (Figure 2). This shows a polarised range of responses. When further analysed by practice area, there was a stronger opinion from respondents in secondary care, with 22% (25) totally disagreeing (Figure 3a).
Although respondents were not asked specifically if they prescribed antibiotics in response to a patient's request, the results suggest there may be a perception among respondents of patient demand. Furthermore, their responses may not reflect their own prescribing behaviour, but rather their perceptions or their observation of others' behaviours. This requires further exploration. Courtenay et al (2016), who examined whether patients' expectations for antibiotics affected the likelihood of receiving them, found INPs were not unduly influenced by patients' expectations, which is reflected in this study, but reported lower satisfaction levels among patients who expected but did not receive an antibiotic. In relation to medical prescribing, one literature review found GPs identified maintaining a good relationship with the patient as a key factor in their prescribing behaviour and antibiotics were prescribed for some patients despite normal clinical findings (Rose et al, 2019).
A study by O'Connor et al (2019) of patients in an out-of-hours facility diagnosed with an upper respiratory tract infection found only 34% requested antibiotics. The most expressed expectations were for further examination (53%), reassurance (51%) and information (49%). Other influencing factors related to GP prescribing in response to patient demand for antibiotics have included insufficient time and diagnostic uncertainty, making it more difficult to resist patient pressure (Coenen et al, 2013). This research reflects these findings.
Diagnostic uncertainty and the consequences of incorrect decisions or treatments
In response to the statement, ‘When unsure of the diagnosis I will prescribe an antibiotic as a precaution’, 87% (100) of respondents disagreed (Figure 2). When responses were compared between primary and secondary care settings, 15% (17) of respondents in primary care settings agreed or were neutral while only 9% (10) of those in secondary care were neutral (Figure 3b).
This was not a large enough group from which to draw conclusions, but the response is noteworthy as prescribing as a precaution could be more of an influencing factor in primary care and could be linked to fewer opportunities for follow-up or workload time pressures compared to secondary care. Diagnostic testing has become an important feature of advanced practice by speeding up an accurate diagnosis and, therefore, appropriate treatment (Kassirer, 2014). Diagnostic uncertainty has been associated with an increased likelihood of antibiotic prescribing to protect the patient from potential deterioration (Public Health England and Department of Health, 2015). Similarly, 7% (8) of respondents agreed with statement 9 – ‘I will prescribe an antibiotic when in doubt as to whether the patient has a bacterial disease’ – which further emphasises the challenges associated with being unable to quickly perform confirmation diagnostic tests and consequent unnecessary prescribing of antibiotics (Cooke et al, 2015) (Figure 2).
Horwood et al (2016) investigated antibiotic prescribing decisions among 22 GPs and six nurses in primary care settings, and found that differentiating between viral and bacterial infection was not always possible, with participants tending to favour prescribing due to this uncertainty.
Challenges to following up patients
In response to the statement, ‘I often prescribe antibiotics when it is difficult to conduct a follow-up of the patient’, 31% (27) of respondents did not disagree (Figure 2). However, the term ‘follow-up’ is open to interpretation. There was little difference between primary and secondary care responses when the data were analysed (Figure 3c). Although a conclusion cannot be drawn from this small sample, it is notable that, for some INPs, their decision to prescribe antibiotics is influenced by their inability to follow up patients.
In Horwood et al's 2016 study, some of the GP and nurse participants reported that if they were concerned they could not follow up with a patient, they would be more likely to prescribe an antibiotic. This was also reflected in the results of a seminal study undertaken in Germany that sought to establish the prescribing habits of primary care doctors over the course of a week (Kuehlein et al, 2010). The researchers reported that there was a 23% increase in antibiotic prescribing on Fridays and attributed this to doctors' uncertainty about the availability of treatment over the weekend.
Remote prescribing challenges
A total of 37(32%) respondents agreed with the statement, ‘I am more likely to prescribe an antibiotic during a remote/telephone/video consultation’, which may reflect the inability to perform diagnostic tests as well as risk avoidance (Figure 2).
Not all respondents may have experienced remote consultations, so this result may not reflect inappropriate prescribing behaviours in this context; but this is important to consider given the move towards remote consultation in all areas of healthcare (Murphy et al, 2021).
Time pressures
It is notable that statement 11 reveals 17% (20) make prescribing decisions influenced by time pressures (Figure 2). When analysed further by practice setting, 20% (23) of respondents in primary care, and only 4% (5) of those in secondary care, agreed with this statement (Figure 3d). This is statistically significant according to Fisher's exact calculation and may be related to the increasing number of patients in general practices alongside the decline in GP numbers, resulting in higher workload (British Medical Association, 2021).
Research of GPs' antibiotic prescribing patterns undertaken in Norway reported higher prescribing rates in GPs with higher consultation rates but did not establish causality (Gjelstad et al, 2011).
Limitations
The study could be limited by selection bias as it was an opportunistic sample group; however, as the respondents' profile was representative of the INP population in the UK, any potential selection bias was likely to be minimal. Additionally, the small study sample may limit generalisability of the results, but the representative population should provide confidence in the results. As the study used a self-report data collection tool there was a risk of social desirability bias, where people ‘know’ the appropriate answer and give it regardless of their real view (Rossi et al, 2013); however, the anonymity of respondents minimised this risk. No incentives were provided other than the desire to improve clinical practice and patient care, so the answers were more likely to be authentic.
Implications for practice and future research
This research has indicated there is a need to improve education and training for INPs to ensure they have a comprehensive understanding of antimicrobial resistance, the future of antibiotic development and antimicrobial stewardship in order to improve antibiotic prescribing. A greater understanding of the external pressures to prescribe and how these can be addressed is also needed, moving the focus back to clinical decisions.
In practice settings, greater availability of near-patient testing, timely laboratory processing and/or validated diagnostic tools may support optimal prescribing behaviours. There is a need for further exploration of the factors that influence INPs' prescribing decisions. This could be achieved through a repeat of this study using a larger sample of INPs. It would also be useful to conduct observational studies and audit of INPs' prescribing behaviours in practice, including during remote consultations. Follow-up research could consider patient education and look at the information prescribers can use to help educate patients about self-care and antibiotic resistance.
Conclusion
There is seldom an immediate or tangible repercussion to prescribing an antibiotic as a caution, but there is if we fail to prescribe. Antibiotic prescribing behaviours are complex and influenced by various factors, and there is a lack of research of this topic among INPs. This study has identified some of these factors in INPs working in primary and secondary care settings. The results suggest that a lack of access to diagnostic testing, time pressures and patient expectations can influence INPs' decisions in terms of prescribing antibiotics; however, they do not appear to be influenced by the need to maintain positive relationships with patients; a factor that has been found to influence doctors' prescribing decisions. INP respondents in this study also appear to believe patients bear some responsibility in terms of perceived requests for antibiotics. Increasing awareness and understanding of these factors among nurses and policy makers could improve prescribing practices and inform interventions to increase antimicrobial stewardship.
Key Points
- Many factors other than diagnosis infiuence the prescribing of antibiotics
- Education and training tailored to the specific needs independent nurse prescribers (INPs) and the settings in which they practice may enhance antimicrobial stewardship
- Greater availability of near-patient testing and timely laboratory processing in practice may support optimal prescribing behaviours
- There is a need for further exploration of the factors that infiuence INPs' prescribing decisions
- Observational studies and/or audit of INPs' prescribing behaviours in practice, including during remote consultations, would be useful
- Further research should consider the use of patient education tools
CPD reflective questions
- Do I prescribe an antibiotic as a precaution?
- Do I worry about the consequences of over prescribing?
- Do I worry about the consequences of withholding an antibiotic?
- Do I feel pressure to prescribe an antibiotic?
- What do I feel would help my antibiotic prescribing decisions?