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Efficacy of a patient-based health education intervention in reducing
antibiotic use for acute upper respiratory tract infections in the
private sector primary care setting in Singapore
Magdalene Hui Min Lee1, Darius Shaw Teng Pan1, Joyce Huixin Huang1, Mark I-
Cheng Chen, MBBS, MMed(Public Health), PhD2,3* , Ee Hui Goh, BSc(Hons),
MPH2, Lili Jiang, MD, MPH, MSc2, Yee Sin Leo, MBBS, MMed(Internal Med),
MRCP, FAMS, FRCP, MPH,1,2,3,5, Tau Hong Lee, MBBS, MRCP3, Chia Siong
Wong, MBBS, MMed(Public Health)3, Victor Weng Keong Loh, MBBS,
MMed(Family Med)4, Fong Seng Lim4, Adrian Zhongxian Poh6, Tat Yean Tham,
MBBS, MCFP(S), GDFM, GradDip FPDerm, GradDip OccMed1,4,6, Wei Mon
Wong, MBBS, GradDip FRDerm, GradDip FAMS4,7,8, Yue Yu1
*Corresponding Author
1 Yong Loo Lin School of Medicine, National University of Singapore, Singapore
2 Saw Swee Hock School of Public Health, National University of Singapore,
Singapore
3 Institute of Infectious Diseases & Epidemiology, Communicable Disease
Centre, Tan Tock Seng Hospital, Singapore
4 Division of Family Medicine, Department of Medicine, University Medicine
Cluster, National University Hospital System, Singapore
5 Lee Kong Chian School of Medicine, Nan Yang Technological University,
Singapore
6 Frontier Healthcare Group, Singapore
7 Division of Primary Care, Raffles Medical Group, Singapore
8 Duke NUS Graduate Medical School, National University of Singapore,
Singapore
Corresponding Author:
Dr Mark I-Cheng Chen
mark.chen.ic@gmail.com
Phone: (+65) 65165781
2 Saw Swee Hock School of Public Health, National University of Singapore, 16
Medical Drive, Kent Ridge, 117597, Singapore
3 Institute of Infectious Diseases & Epidemiology, Communicable Disease
Centre, Tan Tock Seng Hospital, Singapore
Keywords: Upper respiratory tract infection, intervention, antibiotics
Abbreviations:
URTI: Upper tract respiratory infection
GP: General practitioner
Source of support: Saw Swee Hock School of Public Health
Prior Presentation: Poster presentation at Singapore Health & Biomedical
Congress, October 2015
Word Count: 2700
Number of tables: 2
Number of Figures: 3
Conflict of interest statement: None of the authors has conflict of interest.
Abstract
Purpose: We investigated the effectiveness of patient-targeted education in reducing antibiotic
prescriptions for upper respiratory tract infections (URTIs) amongst adults in the private primary
care setting in Singapore.
Methods: Our randomized controlled trial enrolled patients aged 21 years and above presenting
at GP (general practitioner) clinics with URTI symptoms for 7 days or less. Intervention arm
patients were verbally educated via pamphlets about the etiology of URTIs and role of
antibiotics in treating URTIs. Control arm patients were educated on influenza vaccinations.
Both arms were compared on proportions prescribed antibiotics and patients’ post-consultation
perceptions.
Results: 914 patients consulting 35 doctors from 24 clinics completed the study (457 in each
arm). Demographics in both arms were similar. 19.1% were prescribed an antibiotic, but this
varied from 0% to 70% for individual GPs. The intervention did not significantly reduce antibiotic
prescriptions (odds ratio [OR] 1.20, 95% confidence intervals [CI] 0.84–1.72) except in patients
of Indian ethnicity (OR 0.32, 95% CI 0.14–0.75). Intervention arm patients were more likely to
agree that the education improved their understanding of URTI causes (Spearman’s rho
0.13, p<0.001). However positive effects on the view that antibiotics were not needed most of
the time for URTIs (Spearman’s rho 0.20, p=0.047) and being worried about the side effects of
antibiotics (Spearman’s rho 0.24,p=0.018) were restricted to the Indian subgroup.
Conclusions: Our educational intervention was effective only in the Indian ethnic subgroup.
Follow-up studies to investigate differences in responses to educational programs between
ethnicities, and to assess GP-targeted interventions, are recommended.
Introduction
Antibiotic resistance is an increasingly prevalent public health problem worldwide1, largely due
to the overuse of antibiotics.2-5 Antibiotic-resistant bacterial infections increase morbidity and
mortality6 and generate socioeconomic costs.1, 5 The declining rate of development of new
antimicrobial agents exacerbates the problems faced with resistance.7, 8
Current evidence-based guidelines do not support antibiotic use in most cases of upper
respiratory tract infections (URTIs).9, 10 This is because URTIs are frequently of viral etiology,11-13
are often self-limiting,14, 15 and seldom lead to serious complications.16 Using antibiotics for
URTIs promotes the selection of antibiotic-resistant bacteria,17 increases the risk of adverse
drug reactions18 and increases costs.1, 5 However, antibiotic prescriptions for URTIs in primary
care remain high worldwide.2, 19, 20 While there is no data on antibiotic use for URTIs in
Singapore, it has been noted that antibiotics are frequently prescribed for URTIs,21 the most
common condition seen in primary care.22 Causes of inappropriate antibiotic prescribing for
URTIs are multifactorial and include patients having inadequate knowledge on appropriate
antibiotic use for URTIs,21, 23-25 and direct or indirect pressure from patients on physicians to
prescribe antibiotics.14, 21, 26-30
There is evidence that reducing antibiotic prescriptions decreases the prevalence of antibiotic-
resistant bacteria.31, 32 Interventions to reduce antibiotic prescriptions for URTIs have been
attempted, mostly in the USA and Europe, with varying results.33, 34 While there are no published
studies on such interventions in Singapore, one local study showed that patients had several
misconceptions regarding the use of antibiotics in URTI, and that those who knew that URTIs
are self-resolving had more appropriate health-seeking behaviours.21 We hypothesized that
correcting such misconceptions through patient education might reduce antibiotic prescriptions.
We hence designed a patient-targeted educational intervention in the form of verbal counseling
and educational pamphlets on the causes of URTIs and the role of antibiotics in treating URTIs.
We performed a randomized controlled trial to investigate its efficacy in the private general
practitioner (GP) setting, which accounts for 87% of URTI consults in Singapore,22 and
assessed if our intervention was effective in reducing antibiotic prescriptions and changing
patients’ views about the use of these medications for URTIs.
Methods
Study design and setting
We conducted a two-arm, parallel group randomized controlled trial over eight working days in
February 2015. GPs from the academic medicine network affiliated with the National University
of Singapore (NUS) and three major GP clinic chains were approached via email. We then
visited the GPs who responded to assess their clinics’ suitability for inclusion into the study,
explain the study objectives and execution, address their concerns, and obtain their consent. In
all, 35 GPs were recruited from 24 clinics of various sizes, including solo and group practices in
both residential and commercial areas across Singapore.
38 fourth-year medical students from NUS Yong Loo Lin School of Medicine (YLLSoM) were
deployed in pairs as field researchers to participating clinics during operating hours. These
students had undergone a carefully planned full day training program that included video
demonstrations, simulations and role-play, which aimed to familiarize all researchers with the
study protocol and standardize the questionnaire and education process.
The inclusion criteria were patients aged 21 years and above, presenting with at least one of
four URTI symptoms (runny nose, blocked nose, cough or sore throat) for seven days or less at
participating clinics. Patients were excluded if they had sought medical consultation for the
same symptoms in the preceding 30 days, were on long-term immunosuppressive or oral
corticosteroid medications, had chronic kidney disease, had a history of advanced stage or
metastatic cancer, were immunocompromised (e.g. human immunodeficiency virus infection), or
were not conversant in English or Mandarin. Eligible patients who provided written consent were
enrolled into the study.
Following patient enrolment, the first researcher administered an interviewer-assisted pre-
consultation questionnaire on the patient’s demographic characteristics and details of the
presenting illness. Each patient was then randomly allocated to either the control or intervention
arm using sequential envelopes containing pre-generated assignments based on simple
randomization. Patients in the intervention arm were educated on causes of URTIs and when
antibiotics are appropriate to treat URTIs. Patients in the control arm were educated on
influenza vaccinations, a topic relevant to the patients’ presenting complaints but not expected
to directly influence antibiotic prescription. The first researcher then verbally educated patients
for three minutes via educational pamphlets using standardized scripts in English or Mandarin.
After the patient’s consultation with the GP, the second researcher, who was not involved in the
pre-consultation questionnaire or education, administered an interviewer-assisted post-
consultation questionnaire on the patient’s views about URTI causes and antibiotic use on a 4-
point scale, and collected information on all medications prescribed.
Health education materials
The intervention pamphlets and counseling scripts were designed based on information from
patient information pamphlets and booklets from the Health Promotion Board (HPB),
Singapore35-37 and the Centers for Disease Control and Prevention (CDC), USA.38 Several
primary care and infectious disease physicians and public health experts were also consulted.
The material specifically addressed key misconceptions identified in the previous study of URTI
patients at local primary care clinics21. It was first tested on layperson volunteers, then field-
tested during a pilot study in December 2014. It was then refined based on feedback from
participating GPs and patients.
Blinding
Attempts were made to blind the GPs and researchers assessing the study outcomes. The first
and second researchers were kept in separate partitioned areas to minimize communication
between them, with the second researcher unaware of which study arm the patient was
assigned to. In addition, patients were asked to keep the pamphlets within sealed envelopes we
provided to prevent the GP and the second researcher from seeing the pamphlets. GPs were
not told each patient’s allocation, and were informed not to attempt to find out what topic each
patient was counseled on. However, GPs were not blinded to the study aims, and we
emphasized that they should educate their patients about antibiotics where appropriate. We
assessed the adequacy of blinding for the GPs through intra-consult questionnaires for each
patient and found that in 99% of instances, GPs were unaware of which arm the patient was in.
Outcome measures
The primary outcome was the proportion of patients in each arm prescribed antibiotics. The
secondary outcomes were patients’ agreement on a 4-point scale to the following three
statements: that the education had improved their understanding about causes of URTI, that
they were worried about the side effects of antibiotics, and that antibiotics are not needed most
of the time for URTI.
Sample size calculations, data management and data analysis
We estimated that, with equal numbers in the intervention and control arms, and assuming that
10% of patients would receive antibiotics in the absence of any intervention, we would need 900
patients to complete the study to have 80% power to detect the effect of an intervention that
halved the prescription rate at a p-value of less than 0.05.
Data collected at each GP clinic was entered twice into a shared database. We present the
effect of the intervention on antibiotic prescription using odds ratios (ORs) and 95% confidence
intervals (CIs), with robust standard errors to account for potential clustering of results at the GP
level. Patients’ post-consultation views about URTIs and antibiotics were analyzed as ordinal
outcomes using Spearman’s rho to assess the strength of the correlation with the study arm.
Stratified analyses were performed to investigate the effect of age, gender, education level and
ethnicity on the efficacy of the intervention, and to identify patterns in the variation of the effect
by GP.
All data was analysed using Stata for Windows, version 11 (Stata Corporation, College Station,
Texas, USA). P-values of less than 0.05 were considered statistically significant.
Ethics approval
The institutional review board of NUS approved the study (reference B-14-259).
Results
Of the 48 GPs approached, 35 agreed to participate (Figure 1). 1258 of their patients were
approached; 80 declined and 262 were ineligible. The remaining 916 patients were randomized
into control and intervention arms. 2 patients dropped out, with 457 patients from each arm
completing the study.
The median age of participating patients was 35 (interquartile range [IQR] 28–45, see Table 1).
48.8% were male, 68.9% were Chinese, and 74.4% had post-secondary qualifications or higher.
Distributions for age, gender, ethnicity and educational qualifications were similar between both
arms.
Overall, the intervention did not significantly affect antibiotic prescriptions (Table 2), with 94
(20.6%) intervention and 81 (17.7%) control arm patients prescribed antibiotics (p=0.313).
However, in the Indian ethnic subgroup, intervention arm patients received significantly fewer
antibiotic prescriptions (OR 0.32, 95% CI 0.14–0.75, p=0.008), whereas there was no significant
difference amongst those of non-Indian ethnicity (OR 1.40, 95% CI 0.93–2.13, p=0.110).
Stratification by age, gender and educational qualifications did not reveal significant differences
in prescription between intervention and control arms in any other subgroups (data not shown).
Figure 2 compares patients’ post-consultation views of URTIs and antibiotic use by study arm.
Overall (Figure 2A), there was a significant positive association between the intervention and
agreement with the statement that the education improved the patient’s understanding of URTI
causes (Spearman’s rho 0.13, p<0.001). However, significant positive effects on views about
antibiotics were restricted to those of Indian ethnicity (Figure 2C), both on agreement that
antibiotics are not needed most of the time for URTIs (Spearman’s rho 0.20, p=0.047) and on
being worried about the side effects of antibiotics (Spearman’s rho 0.24, p=0.018). In contrast,
there were no significant associations between the responses to these two statements and
study arm for those of non-Indian ethnicity (Figure 2B).
Amongst GPs who contributed more than 10 patients, the proportion prescribed antibiotics by
each GP varied widely from 0 to 70% (Figure 3). 10 GPs were more likely to prescribe
antibiotics for control than intervention arm patients, the converse was true for 13 GPs, and the
difference was statistically significant for only one GP each way. There was no apparent pattern
in the efficacy of the intervention by participating GP.
Discussion
Patients who received our educational intervention in the form of verbal counseling and
educational pamphlets on the causes of URTIs and the role of antibiotics reported that it
improved their understanding of URTI causes. This however did not reduce antibiotic
prescription rates except in patients of Indian ethnicity, amongst whom the intervention also had
a demonstrable effect on increasing awareness of the potential side effects of antibiotics and
that antibiotics are not indicated most of the time for URTIs. Across GPs, the proportion of
patients prescribed antibiotics and the intervention effect varied widely.
Previous patient-targeted educational interventions have reported both positive25, 39, 40 and
negative41, 42 findings. There are several possible explanations for this. Firstly, it has been
postulated that patients undergo a complex process of behavioral change as exemplified by the
transtheoretical model,43 with time needed for the effects of an educational intervention to
produce results. If so, studies like ours focusing on prescriptions in the same visit may be more
likely to have negative findings. Outcome measures such as prescriptions at subsequent
consultations may hence be more suitable in assessing the efficacy of such interventions. Also,
one randomized controlled trial in the pediatric population found that an educational intervention
for parents modified parental attitudes about the use of antibiotics but did not significantly
reduce antibiotic prescriptions for their children.;42 There is some suggestion of such a trend
amongst our non-Indian patients, amongst whom the intervention resulted in more patients
agreeing that their understanding of URTI causes had improved but did not affect antibiotic
prescriptions. This could be due to the presence of multiple links in the causal chain between
patient perceptions and eventual antibiotic prescription, including GP factors such as clinical
judgment, prescribing habits44, 45 and healthcare system factors.46 It might hence be useful to
investigate whether patients use antibiotics after receiving them.39
Our study may also have failed to detect an overall intervention effect more modest than the
50% relative reduction in prescriptions that the sample size was adequately powered for.
However, we did detect a significant effect in the subset of patients of Indian ethnicity which
suggests heterogeneity in Singapore’s patient population’s response to educational
interventions. In addition to being less likely to receive antibiotics, Indian patients in the
intervention arm were also more likely than those in the control arm to have appropriate post-
intervention views about antibiotics. This was not seen amongst non-Indian patients. Possible
reasons are differing receptiveness to health education and degrees to which patients
understood our health education. In Singapore, there are three major ethnic groups: Chinese,
Malays and Indians. One local study found that Malays and Indians are more willing to
participate in health education programs than the Chinese,47 and another demonstrated that
these ethnic differences in receptivity extended to patients’ willingness to being interviewed and
examined by medical students in clinics.48 Moreover, our pamphlets were designed only in
English, and verbal counseling was provided only in English and Mandarin. Although we only
selected patients conversant in English or Mandarin, local census data shows that only 21.2%
of Malays who are literate in English speak English at home, compared to 49.8% of Indians and
45.2% of Chinese.49 Therefore ethnic differences in the degree of understanding of the
education provided may have arisen. Ethnic and cultural factors have been noted to affect
health education outcomes elsewhere50 and should be investigated further, perhaps through
qualitative research methods, and accounted for in future health education interventions in
Singapore.
Another explanation for the negative findings in our study is the wide variation in GPs’ antibiotic
prescription practices. The proportion prescribed antibiotics ranged from 0 to 70% for each GP.
Although there was little to imply that the intervention was effective in any particular subset of
GPs, this large variation suggests that factors other than clinical indications and patient
expectations may drive prescription decisions. GP level factors identified by others that could
lead to inappropriate antibiotic prescriptions include fear of medico-legal repercussions,51 saving
time51 and financial incentives.52 Our intervention, in targeting only the patient’s desire for
antibiotics, did not address these factors, and would thus be effective only in GPs who were
primarily influenced by patients’ expectations when prescribing medications. Although not the
primary objective of our study, it is worth noting that the high prescription levels by some GPs of
up to 70%, and the high overall prescriptions of 19.1% as compared to other Asian countries
with similar healthcare standards like Taiwan (6%)53 and Hong Kong (5%)54, suggests room for
optimizing antibiotic prescription practices in Singapore. More research is needed to study
factors influencing antibiotic prescription and to explore the role of GP-targeted interventions.
Our study had several limitations. Firstly, the pre-consultation questionnaires may have caused
control arm patients to recognize the importance of appropriate antibiotic use, thus reducing
differences between the study arms. Secondly, selection bias was present in the recruitment of
GPs. The sample population of GPs was relatively small and disproportionate numbers of
patients from 6 to 60 were recruited per GP. This was due to variations in the number of eligible
patients visiting each clinic during the study period. Thirdly, because some of the participating
GPs were from an academic medicine network, they would be more likely to value good
prescription habits. For more accurate representation, an alternative GP recruitment strategy
would have been to approach GPs randomly sampled from a national register. However our
previous study employing this strategy resulted in a dismal response rate.55 Also, physicians in
public primary care clinics were not included in this study. Finally, a follow-up questionnaire after
several weeks would have been helpful in evaluating if patients’ views of URTIs and antibiotic
use remained similar, while a longitudinal follow up on patients would be helpful in assessing for
changes in antibiotic prescriptions at subsequent consultations.
Conclusion
Our study found that an intervention to reduce antibiotic prescriptions in Singapore’s primary
healthcare setting was partially effective. Patients in the intervention arm reported improved
understanding of URTI causes, but the intervention was associated with reduced antibiotic
prescriptions and more appropriate views on antibiotics only in the Indian ethnic subgroup.
Follow-up studies to investigate differences in responses to educational programs between
ethnic groups would facilitate the design of more targeted patient level interventions. The wide
variation in antibiotic prescriptions across GPs also suggests a role for GP-targeted
interventions.
References
1. World Health Organization. Antimicrobial resistance: global report on surveillance.
France: World Health Organization; 2014.
2. Goossens H, Ferech M, Vander Stichele R, Elseviers M. Outpatient antibiotic use in
Europe and association with resistance: a cross-national database study. Lancet.
2005;365(9459):579-87.
3. Soothill G, Hu Y, Coates A. Can We Prevent Antimicrobial Resistance by Using
Antimicrobials Better? Pathogens. 2013;2(2):422-35.
4. Costelloe C, Metcalfe C, Lovering A, Mant D, Hay AD. Effect of antibiotic prescribing in
primary care on antimicrobial resistance in individual patients: systematic review and meta-
analysis. Br Med J. 2010;340:c2096.
5. Thabit AK, Crandon JL, Nicolau DP. Antimicrobial resistance: impact on clinical and
economic outcomes and the need for new antimicrobials. Expert Opin Pharmacother.
2015;16(2):159-77.
6. Butler CC, Hillier S, Roberts Z, Dunstan F, Howard A, Palmer S. Antibiotic-resistant
infections in primary care are symptomatic for longer and increase workload: outcomes for
patients with E.coli UTIs. Br J Gen Pract. 2006;56(530):686-92.
7. Projan S, Shlaes D. Antibacterial drug discovery: is it all downhill from here? Clin
Microbiol Infect. 2004;10(s4):18-22.
8. Gwynn MN, Portnoy A, Rittenhouse SF, Payne DJ. Challenges of antibacterial discovery
revisited. Ann N Y Acad Sci. 2010;1213(1):5-19.
9. Zoorob R, Sidani MA, Fremont RD, Kihlberg C. Antibiotic use in acute upper respiratory
tract infections. Am Fam Physician. 2012;86(9):817-22.
10. National Institute for Health and Care Excellence. Clinical Guideline 69. Respiratory tract
infections – antibiotic prescribing: Prescribing of antibiotics for self-limiting respiratory tract
infections in adults. London: National Institute for Health and Care Excellence, 2008.
11. Hong C-Y, Lin RT, Tan ES, Chong P-N, Tan YS, Lew Y-J, et al. Acute respiratory
symptoms in adults in general practice. Fam Pract. 2004;21(3):317-23.
12. van Gageldonk-Lafeber AB, Heijnen M-LA, Bartelds AI, Peters MF, van der Plas SM,
Wilbrink B. A case-control study of acute respiratory tract infection in general practice patients in
The Netherlands. Clin Infect Dis. 2005;41(4):490-7.
13. Poole PM, Tobin J. Viral and epidemiological findings in MRC/PHLS surveys of
respiratory disease in hospital and general practice. Postgrad Med J. 1973;49(577):778-87.
14. Gonzales R, Bartlett JG, Besser RE, Cooper RJ, Hickner JM, Hoffman JR, et al.
Principles of appropriate antibiotic use for treatment of acute respiratory tract infections in
adults: Background, specific aims, and methods. Ann Emerg Med. 2001;37(6):690-7.
15. Meropol SB, Localio AR, Metlay JP. Risks and benefits associated with antibiotic use for
acute respiratory infections: a cohort study. Ann Fam Med. 2013;11(2):165-72.
16. Petersen I, Johnson A, Islam A, Duckworth G, Livermore D, Hayward A. Protective effect
of antibiotics against serious complications of common respiratory tract infections: retrospective
cohort study with the UK General Practice Research Database. Br Med J. 2007;335(7627):982.
17. Chung A, Perera R, Brueggemann AB, Elamin AE, Harnden A, Mayon-White R, et al.
Effect of antibiotic prescribing on antibiotic resistance in individual children in primary care:
prospective cohort study. Br Med J. 2007;335(7617):429.
18. Lode H. Safety and tolerability of commonly prescribed oral antibiotics for the treatment
of respiratory tract infections. Am J Med. 2010;123(4):S26-S38.
19. McCaig LF, Hughes JM. Trends in antimicrobial drug prescribing among office-based
physicians in the United States. J Am Med Assoc. 1995;273(3):214-9.
20. Trap B, Hansen E. Treatment of upper respiratory tract infections–a comparative study
of dispensing and non‐dispensing doctors. J Clin Pharm Ther. 2002;27(4):289-98.
21. Tan Y, Hong C, Chong P, Tan E, Lew Y, Lin R. Knowledge that upper respiratory tract
infection resolves on its own is associated with more appropriate health-seeking behaviour and
antibiotic cognition. Singapore Med J. 2006;47(6):518-24.
22. Sng QS. Primary Care Survey 2010: Profile of Primary Care Patients. Singapore:
Ministry of Health Singapore, 2011.
23. Belongia EA, Naimi TS, Gale CM, Besser RE. Antibiotic Use and Upper Respiratory
Infections: A Survey of Knowledge, Attitudes, and Experience in Wisconsin and Minnesota. Prev
Med. 2002;34(3):346-52.
24. Cals JW, Boumans D, Lardinois RJ, Gonzales R, Hopstaken RM, Butler CC, et al. Public
beliefs on antibiotics and respiratory tract infections: an internet-based questionnaire study. Br J
Gen Pract. 2007;57(545):942-7.
25. Mainous AG, Zoorob RJ, Oler MJ, Haynes DM. Patient knowledge of upper respiratory
infections: implications for antibiotic expectations and unnecessary utilization. J Fam Pract.
1997;45(1):75-83.
26. Sanchez G, V, Roberts RM, Albert AP, Johnson D, D, Hicks L, A. Effects of Knowledge,
Attitudes, and Practices of Primary Care Providers on Antibiotic Selection, United States. Emerg
Infect Dis. 2014;20(12):2041.
27. Scott JG, Cohen D, DiCicco-Bloom B, Orzano AJ, Jaen CR, Crabtree BF. Antibiotic use
in acute respiratory infections and the ways patients pressure physicians for a prescription. J
Fam Pract. 2001;50(10):853-8.
28. Butler CC, Rollnick S, Pill R, Maggs-Rapport F, Stott N. Understanding the culture of
prescribing: qualitative study of general practitioners' and patients' perceptions of antibiotics for
sore throats. Br Med J. 1998;317(7159):637-42.
29. Coenen S, Francis N, Kelly M, Hood K, Nuttall J, Little P, et al. Are Patient Views about
Antibiotics Related to Clinician Perceptions, Management and Outcome? A Multi-Country Study
in Outpatients with Acute Cough. PLoS One. 2013;8(10):e76691.
30. Currie J, Lin W, Zhang W. Patient knowledge and antibiotic abuse: Evidence from an
audit study in China. J Health Econ. 2011;30(5):933-49.
31. Seppälä H, Klaukka T, Vuopio-Varkila J, Muotiala A, Helenius H, Lager K, et al. The
Effect of Changes in the Consumption of Macrolide Antibiotics on Erythromycin Resistance in
Group A Streptococci in Finland. N Engl J Med. 1997;337(7):441-6.
32. Fujita K, Murono K, Yoshikawa M, Murai T. Decline of erythromycin resistance of group
A streptococci in Japan. Pediatr Infect Dis J. 1994;13(12):1075-8.
33. Arnold SR, Straus SE. Interventions to improve antibiotic prescribing practices in
ambulatory care. Cochrane Database Syst Rev. 2005(4):Cd003539.
34. Wensing M, van der Weijden T, Grol R. Implementing guidelines and innovations in
general practice: which interventions are effective? Br J Gen Pract. 1998;48(427):991-7.
35. Health Promotion Board. Fight Flu: Because Sharing Isn't Caring. Singapore. 2012.
36. Health Promotion Board. Use of Antibiotics in Adults. Singapore: GAP Advertising &
Design; 2007.
37. Health Promotion Board. Antibiotics: To Take or Not To Take? Singapore: Paper
Innovation Pte Ltd; 2000.
38. Centers of Disease Control and Prevention. Get Smart: Know When Antibiotics Work.
Atlanta, GA, USA. 2015.
39. Macfarlane J, van Weel C, Holmes W, Gard P, Thornhill D, Macfarlane R, et al.
Reducing antibiotic use for acute bronchitis in primary care: blinded, randomised controlled trial
of patient information leaflet. Br Med J. 2002;324(7329):91-4.
40. Francis NA, Phillips R, Wood F, Hood K, Simpson S, Butler CC. Parents’ and clinicians’
views of an interactive booklet about respiratory tract infections in children: a qualitative process
evaluation of the EQUIP randomised controlled trial. BMC Fam Pract. 2013;14:182.
41. Flottorp S, Oxman AD, Håvelsrud K, Treweek S, Herrin J. Cluster randomised controlled
trial of tailored interventions to improve the management of urinary tract infections in women
and sore throat. Br Med J. 2002;325(7360):367.
42. Taylor JA, Kwan-Gett TSC, McMahon Jr EM. Effectiveness of a parental educational
intervention in reducing antibiotic use in children: a randomized controlled trial. Pediatr Infect
Dis J. 2005;24(6):489-93.
43. Finch R, Metlay J, Davey P, Baker L. Educational interventions to improve antibiotic use
in the community: report from the International Forum on Antibiotic Resistance (IFAR)
colloquium 2002. Lancet Infect Dis. 2004;4(1):44-53.
44. Cadieux G, Tamblyn R, Dauphinee D, Libman M. Predictors of inappropriate antibiotic
prescribing among primary care physicians. Can Med Assoc J. 2007;177(8):877-83.
45. Senok AC, Ismaeel AY, Al-Qashar FA, Agab WA. Pattern of Upper Respiratory Tract
Infections and Physicians’ Antibiotic Prescribing Practices in Bahrain. Med Princ Pract.
2009;18(3):170-4.
46. Juncosa S, Porta M. Effects of primary health care reform on the prescription of
antibiotics A longitudinal study in a Spanish county. Eur J Public Health. 1997;7(1):54-60.
47. Ng CWL, Heng BH, Molina JA, Wong LY, George PP, Cheah J. Demographic and
lifestyle characteristics associated with non-willingness to participate in health promotion
programmes among adults of a lower socioeconomic status in Singapore. Glob Health Promot.
2012;19(4):9-19.
48. Koh GC, Wong TY, Cheong SK, Lim EC, Seet RC, Tang WE, et al. Acceptability of
medical students by patients from private and public family practices and specialist outpatient
clinics. Ann Acad Med Singapore. 2010;39(7):555.
49. Singapore Department of Statistics. Census of Population 2010 Statistical Release 1:
Demographic Characteristics, Education, Language and Religion. Singapore. 2011.
50. Pasick RJ, D'Onofrio CN, Otero-Sabogal R. Similarities and differences across cultures:
Questions to inform a third generation for health promotion research. Health Educ Q.
1996:S142-S61.
51. Lam T, Lam K. What are the non-biomedical reasons which make family doctors over-
prescribe antibiotics for upper respiratory tract infection in a mixed private/public Asian setting?
J Clin Pharm Ther. 2003;28(3):197-201.
52. Kim NS, Jang SN, Jang SM. Factors Influencing Antibiotics Prescribing of Primary
Health Physicians in Acute Upper Respiratory Infections. J Prev Med Public Health.
2005;38(1):1-8.
53. Hou S-W, Lee Y-K, Hsu C-Y, Lee C-C, Su Y-C. Antibiotic Prescriptions for Upper
Respiratory Infection in the Emergency Department: A Population-Based Study. ISRN
Emergency Medicine. 2014;2014:5.
54. Kung K, Wong CK, Wong SY, Lam A, Chan CK, Griffiths S, et al. Patient presentation
and physician management of upper respiratory tract infections: a retrospective review of over 5
million primary clinic consultations in Hong Kong. BMC Fam Pract. 2014;15:95.
55. Ong JBS, Chen MIC, Cook AR, Lee HC, Lee VJ, Lin RTP, et al. Real-Time Epidemic
Monitoring and Forecasting of H1N1-2009 Using Influenza-Like Illness from General Practice
and Family Doctor Clinics in Singapore. PLoS One. 2010;5(4):e10036.
Acknowledgements
We would like to thank all participating GPs for offering their clinics for patient recruitment. We
also acknowledge other members of the Yong Loo Lin School of Medicine 2014/2015
Community Health Project Team 1 for their contributions to study design and conduct of field
work, and Dr Gerald Koh and Ms Moira Soh, for providing academic and administrative support
during the project. Finally, we acknowledge the Saw Swee Hock School of Public Health for
funding the study.
Overview of Tables and Figures
Figure 1: Participating GPs and patients
Table 1: Demographics and visit characteristics of patients in control and intervention arms
Table 2: Effect of intervention on antibiotic prescription in all patients and stratified by
ethnicity
Figure 2: Effect of intervention on patients’ perceptions about URTI and antibiotic use
Figure 3: Proportion prescribed antibiotics in intervention and control arms, stratified by
participating GP
Figure 1:
Recruitment of participating GPs and patients
GP: general practitioner
48 GPs approached
35 GPs recruited
1258 patients approached
1178 patients assessed for
eligibility
916 patients recruited
458 control arm patients
457 completed study
1 patient dropped out
458 intervention arm
patients
457 completed
study
1 patient dropped out
262 patients ineligible
80 patients declined
13 GPs declined
Table 1:
Patients’ demographic characteristics (age, gender, ethnicity and highest
qualification) in control and intervention arms
Characteristic
Total
(N = 914)
Control
(N = 457,
50.0%)
Intervention
(N = 457,
50.0%)
Age
Median (IQR) 35 (28 – 45) 35 (28 – 45) 36 (28 – 44)
Gender (%)
Male
454 (48.8%)
218 (47.0%)
236 (50.5%)
Ethnicity (%)
Chinese
630 (68.9%)
310 (67.8%)
320 (70.0%)
Malay
116 (12.7%)
62 (13.6%)
54 (11.8%)
Indian
99 (10.8%)
46 (10.1%)
53 (11.6%)
Others
69 (7.6%)
39 (8.5%)
30 (6.6%)
Highest qualification attained (%)
1 missing
1 missing
Secondary and below
234 (25.6%)
118 (25.8%)
116 (25.4%)
Post-secondary and above
679 (74.4%)
339 (74.5%)
340 (74.4%)
IQR: Interquartile range
Table 2:
Overall intervention effect on prescription and subgroup analysis in different ethnic
groups
Group /
Subgroup
Control arm
Intervention arm
OR
(95% CI)†
p-
value
Total
patients
Number (%)
received
antibiotics
Total
patients
Number
(%)
received
antibiotics
All patients
457
81 (17.7)
457
94 (20.6)
1.20 (0.84 – 1.72)
0.313
Ethnicity
- Chinese 310 52 (16.8) 320 72 (22.5) 1.44 (0.90 – 2.31) 0.130
- Malay 62 11 (17.7) 54 9 (16.7) 0.93 (0.32 – 2.72) 0.891
- Indians
46
13 (28.3)
53
6 (11.3)
0.32 (0.14 – 0.75)
0.008
- Others
39
5 (12.8)
30
7 (23.3)
2.07 (0.47 – 9.20)
0.339
†With control arm as reference category
CI: confidence interval, OR: odds ratio
Figure 2:
Effect of intervention on patients’ views about URTI and antibiotic use. A) In all patients, B)
In patients of non-Indian ethnicity and C) In patients of Indian ethnicity. Dark blue, green, light blue and orange
bars represent strongly disagree, disagree, agree and strongly agree respectively.
URTI: upper respiratory tract infection
Figure 3:
Proportion of patients prescribed antibiotics in intervention and control arms,
stratified by participating GP. Green bars and blue bars represent percentage of patients prescribed
antibiotics in control and intervention arms respectively. Horizontal orange line is the difference in proportion of
antibiotic prescription between the two arms (two of the GPs are highlighted in different colours because the
difference was statistically significant; green in the case where more antibiotics was prescribed in the intervention
arm and red in the case where more antibiotics was prescribed for the control arm). Error bars denote 95%
confidence intervals.
GP: General practitioner
457
8
17
19
18
12
18
14
8
7
12
9
6
31
35
13
28
14
25
9
15
10
36
28
17
20
-100%
-80%
-60%
-40%
-20%
0%
20%
40%
60%
80%
100%
-100%
-80%
-60%
-40%
-20%
0%
20%
40%
60%
80%
100%
457
11
21
17
17
11
14
9
7
10
26
7
9
27
21
18
31
29
29
14
16
10
21
32
7
19
Difference in proportion pre scribed
antibiot ic (Cont rol -Inte rvention)
Control
Inte rvention
Difference in % prescribed
n =
n =
% of CONTROL
patients prescribed
antibiot ic
No dif-
ference
Control > Intervention Intervention > Control
% of INTERVENTION
patients prescribed
antibiot ic
All
patients
Unstratified Stratified by participating GPs with > 10 patie nts
