BMJ Open · acute upper respiratory infections in rural primary care settings in China, through changing doctors’ prescribing behaviors and educating parents/caregivers. Methods

For peer review only

A pragmatic cluster randomised controlled trial for reducing irrational antibiotic prescribing among children with upper

respiratory infections in rural China: a trial protocol

Journal: BMJ Open

Manuscript ID bmjopen-2015-010544

Article Type: Protocol

Date Submitted by the Author: 13-Nov-2015

Complete List of Authors: Zou, Guanyang; China Global Health Research and Development; Queen Margaret University, Institute for Global Health and Development Wei, X-L.; Dalla Lana School of Public Health; China Global Health

Research and Development Hicks, Joseph; University of Leeds, Nuffield Centre for International Health and Development, Leeds Institute of Health Sciences Hu, Yanhong; The Chinese University of Hong Kong Walley, John; University of Leeds, Nuffield Centre for International Health and Development, Leeds Institute of Health Sciences Zeng, Jun; Guangxi Autonomous Region Centre for Disease Control and Prevention Elsey, Helen; University of Leeds, Nuffield Centre for International Health and Development King, Rebecca; University of Leeds, Nuffield Institute For International Health and Development, Leeds Institute of Health Sciences

Yin, Jia; The Chinese University of Hong Kong Huang, Yuanyuan; China Global Health Research and Development Deng, Simin; China Global Health Research and Development, Zhang, Zhitong; China Global Health Research and Development Blacklock, Claire; University of Leeds, Nuffield Centre for International Health and Development, Leeds Institute of Health Sciences Sun, Qiang; Shandong University Lin, Mei; Guangxi Autonomous Region Centre for Disease Control and Prevention

<b>Primary Subject Heading</b>:

Public health

Secondary Subject Heading: Health policy, Public health, Health services research, Paediatrics, Respiratory medicine

Keywords: Antibiotics, Rational use, Clustered randomized control trial, PRIMARY CARE, China

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A pragmatic cluster randomised controlled trial for reducing irrational

antibiotic prescribing among children with upper respiratory infections in rural

China: a trial protocol

Guanyang Zou1,2+

, Xiaolin Wei3,1,4+

, Joseph P Hicks5, Yanhong Hu

4, John Walley

5,

Jun Zeng6, Helen Elsey

5, Rebecca King

5, Jia Yin

4, Yuanyuan Huang

1, Simin Deng

1,

Zhitong Zhang1, Claire Blacklock

5, Qiang Sun

7, Mei Lin

6*

* Corresponding author: Mei Lin Email: [email protected]

+ Equal contributors

1China Global Health Research and Development, Shenzhen, China

2 Institute for Global Health and Development, Queen Margaret University,

Edinburgh, UK

3 Dalla Lana School of Public Health, University of Toronto, Toronto, Canada

4School of Public Health and Primary Care, Chinese University of Hong Kong, Hong

Kong, China

5Nuffield Centre for International Health and Development, University of Leeds,

Leeds, UK

6 Guangxi Autonomous Region Centre for Disease Control and Prevention, Nanning,

China

7 Centre for Health Management and Policy, Shandong University, Jinan, China

Guanyang Zou and Xiaolin Wei contributed equally to this work.

Key words: antibiotics, rational use, upper respiratory infection, cluster randomized

controlled trial, primary care, China

Word count: 3994

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Abstract

Introduction

Irrational use of antibiotics is a serious issue within China and internationally. In 2012

the Chinese Ministry of Health issued a regulation for antibiotic prescriptions limiting

them to less than 20% of all prescriptions for outpatients, but no operational details

have been issued regarding policy implementation, especially at the primary care

level. This study aims to test the effectiveness of a multi-dimensional intervention

designed to reduce the use of antibiotics among children (aged 2-14 years old) with

acute upper respiratory infections in rural primary care settings in China, through

changing doctors’ prescribing behaviors and educating parents/caregivers.

Methods and analysis

This is a pragmatic, prospective, parallel-group, controlled, cluster-randomized

superiority trial, stratified by county, with blinded evaluation of outcomes and data

analysis, but un-blinded treatment. From two counties in Guangxi Province 12

township hospitals will be randomized to the intervention arm and 13 to the control

arm. In the control arm, the management of antibiotics prescriptions will continue

through usual care via clinical consultations. In the intervention arm, a provider and

client focused intervention will be embedded within routine primary care practice.

The provider intervention includes operational guidelines, systematic training, peer

review of antibiotic prescribing, and health education to patient caregivers. We will

also provide printed educational materials and educational videos to patient caregivers.

We aim to collect a minimum of 200 prescriptions per township hospital. The primary

outcome, collected over three months, is the proportion of all prescriptions for upper

respiratory infections in children aged 2-14 years old that include antibiotics.

Ethics and dissemination

The trial has received ethical approval from the Ethics Committee of Guangxi

Provincial Centre for Disease Control and Prevention, China. The results will be

disseminated through workshops, policy briefs, peer-reviewed publications, local and

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international conferences.

Trial registration: Current Controlled Trials: ISRCTN14340536

Strength and limitations

• We aim to test a comprehensive intervention targeting doctors and patients, an

approach shown to have the largest effect on reducing the irrational

prescribing on antibiotics in rural primary care settings.

• The study is adapted to the local context and fits into the current national

priority on antibiotics control.

• All the interventions are embedded within the routine primary care

management and practice, thus enhancing the replicability of the intervention.

• The effectiveness of the pragmatic trial will be limited by various contextual

factors, which will be explored by a qualitative process evaluation.

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INTRODUCTION

Irrational use of antibiotics is a serious issue within China and internationally.

Worldwide, around 50% of medicines are not appropriately prescribed, dispensed or

sold. 1-3 Irrational use of antibiotics not only brings high economic burdens to health

systems, but also increases the risk of antibiotic resistance.4 Acute upper respiratory

infections (URIs) are very common among children, but are usually viral and

self-limiting, with antibiotic treatment for URIs being unnecessary. For example, a

systematic review has shown that antibiotic use does not shorten the duration of

URIs.5 However, there is a high prevalence of antibiotics prescriptions for URIs in

primary care facilities.6 Antibiotic resistant bacteria are also frequently found in

children, especially infants, contributing to high childhood mortality in countries with

inadequate health infrastructure.7

China is one of the most notorious countries for antibiotic abuse. In 2012 the national

Ministry of Health reported that the average person consumed 138 grams of

antibiotics per year, ten times the rate in the Unites States.8 The situation is worse in

rural areas where health workers receive less education and continuous medical

training in practice.9 A recent study found frequent and inappropriate use of

antibiotics in primary health care settings in China with 78 % antibiotics prescribing

rate for colds and 93.5% for acute bronchitis.10 An earlier study in the primary care

settings of ten provinces in rural Western China showed that antibiotics accounted for

nearly half of all prescriptions, predominantly provided for URIs; while one fourth of

those receiving antibiotics were children under ten years old.11

Several national policies have been issued by the Ministry of Health, including the

most recent one limiting antibiotic prescriptions to less than 60% of all prescriptions

for inpatients and 20% for outpatients.12 However, no operational details were

provided on how to implement the policy, and no guidelines were provided on the

diagnosis and treatment of childhood URIs, or related clinician training especially for

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primary care doctors. In the 2009 health sector reform China launched the Essential

Medicines List policy, supported by the centralized procurement of essential

medicines and the Zero-Markup policy. However, after two years of implementation

there was no significant improvement in the rational use of medicines and cost

control.13

The majority of studies on reducing irrational antibiotic use have been conducted in

developed countries, which demonstrated that improving knowledge, attitudes and

behaviours of healthcare providers and consumers can effectively reduce irrational

antibiotic use.14 Commonly reported interventions for improving antibiotic use in URI

treatment included clinical decision support,15-18

point-of-care testing for C-reactive

protein,19-22

clinician communication skills training19-21

, education and feedbacks,23

discussion and monitoring workshops,24 governance structure change,

25 and

behavioral economics and social psychology.26 A Cochrane review demonstrated that

multi-faceted interventions targeting both physicians and patients significantly

reduced inappropriate antibiotic use in community settings;27 while single

interventions with parents have failed to impact on antibiotic prescribing.28-30

Studies of irrational antibiotic prescribing in the primary care are currently limited

settings in China and are mainly cross-sectional surveys.1110

The intervention studies

aimed at reducing the irrational prescribing of antibiotics at primary care were rarely

reported, although one study using public reporting method showed limited impact on

reducing antibiotics prescribing in primary care facilities.31 We aim to test the

effectiveness of multidimensional interventions aimed at changing doctor’s

prescribing behaviours and educating parents/caregivers to reduce the irrational use of

antibiotics among children with acute URIs in China’s rural primary care context.

METHODS AND ANALYSIS

Design of the study

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This is a prospective, parallel-group, cluster randomized controlled trial, designed as

a pragmatic evaluation of the superiority of a health behaviour change intervention

compared with routine practice (Figure 1). The study will be conducted in 25

township hospitals, with randomization of which stratified by county. Study

participants and doctors will not be blinded to the treatment, but measures will be

taken to ensure a blinded outcome evaluation by using the ‘PROBE’ design 32 and a

blinded analysis of the outcome data.

The study design broadly follows the Medical Research Council framework

Developing and evaluating complex interventions: new guidance.33 Prior to the

conduct of the trial we conducted a systematic review of interventions aimed at

reducing antibiotic use in children with URIs.34 We then developed our intervention

based on the results, which supported findings 27 that interventions targeting both

clinicians and patients had a greater effect on reducing irrational antibiotic use than

those targeting a single group. An internal pilot approach will be used to examine the

feasibility and acceptability of intervention and research procedures in a small number

of township hospitals. An independent trial steering committee has also been setup to

supervise the trial.

Setting

The trial will take place in two counties of Guangxi province, which is one of the

poorest provinces, and is located in the southwest mountainous terrain joining

Vietnam and Laos. Guangxi has a population of 48 million and contains 110 counties.

In the rural areas, primary care is provided by public township hospitals. Each

township hospital covers 20,000 to 100,000 people. Doctors in the township hospitals

are responsible for acute and preventive care. Although township hospitals have

inpatient treatment facilities, we only consider outpatients in this study because

inpatients are likely to have a range of co-morbidities, adding to the difficulty of

assessing the rationality of antibiotic prescriptions for URIs. Each township hospital

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has 5 to 20 doctors. Most patients visit township hospitals without prior booking or

referrals. We have not included village clinics, often equipped with an upgraded

community health worker, called a ‘village doctor’, who may be consulted. Rather,

our intervention focuses on professionally qualified clinicians who work as general

practitioners (‘doctors’) in township hospitals.

Eligibility

Eligibility criteria for clusters

All township hospitals from the two selected counties in Guangxi who agree to

participate in the study will be included. However, we will exclude the two township

hospitals located in the two county centres, as they have much better staff capacity

and equipment than their peers, and are close to the county general hospital. Both

counties have implemented the Essential Medicine List, its treatment guidelines and

the Zero-Markup Policy since 2012.

Eligibility criteria for participants

All outpatient prescriptions for children, aged between 2 and 14 years old, diagnosed

with URIs during the study period will be included for analysis. Children under 2

years old will be excluded because they are more vulnerable to secondary bacterial

infection, and exploratory work indicated that it was very difficult for doctor’s to

refuse antibiotics for younger children in this context. Prescriptions for children

diagnosed with pneumonia (where antibiotic prescription is appropriate) or severe

diseases such as cancer, tuberculosis, HIV/AIDS/immunodeficiency, chronic heart

diseases or others who need long term antibiotic treatment or as prophylaxis will be

excluded.

Intervention

No antibiotic should be used for common URIs as per national and international

guidelines. The multi-dimensional intervention aimed at changing doctor’s

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prescribing behaviours and educating parents/caregivers to reduce the irrational use of

antibiotics among children with acute URIs. It is designed to fit within the policy

requirements of antibiotics prescribing and routine supervision by the local health

authorities.

On the doctors’ side, the intervention include: 1) Operational guideline, which is

distributed to township hospital doctors. The guideline is based on Chinese antibiotics

use guidelines, Integrated Management of Childhood Illness (IMCI), and the National

Institute for Health and Care Excellence (NICE) guideline, focus on but not limit to

URIs. The guideline covers the work flow of URI management, methods of diagnosis

URI and other common diseases among children, communication skills between

doctors and patients. 2) Training workshops. All the doctors in the township doctors

are trained on rational use of antibiotics especially for childhood URI, using

participatory and interactive lectures, case discussion and questions and answers

sections. 3) Monthly peer review of rational use of antibiotics. Antibiotics

prescriptions are collected and reviewed by research team at the beginning of each

month. The research team calculates the APR and feed back to the township hospitals.

Peer review of antibiotics use are conducted based on the APR feedback in the

monthly hospital staff meeting. The project coordinator in the township hospitals

write a memo on the results of the peer review and send back to the research team. 4)

Health education to caregivers. Specific short messages are given to the caregivers

whose children have URIs during the clinical consultations. Examples of the short

messages are definition of antibiotic, rational antibiotic use for childhood URIs

On the caregivers’ side, the intervention includes: 1) Printed educational

material/leaflets (with simple words and pictures), which are distributed to the

caregivers whose children have URIs during the clinical consultation. They mainly

cover definition of antibiotic, impact of antibiotic resistance, rational use of

antibiotics for childhood URIs. 2) Educational videos, which are played on a loop in

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the waiting areas of township hospitals (5-8 minutes). The content mainly includes

definition of antibiotic, situation of irrational use antibiotics in China, impact of

antibiotics resistance (using local TV show).

Usual care

In the control arm doctors will be allowed to continue prescribing antibiotics

according to current national guidelines and existing practices. In these conventional

clinical consultations treatment is provided according to existing knowledge,

antibiotics are given at the individual clinician’s discretion, and no systematic health

education is provided to patients.

Outcomes

The primary outcome is the antibiotic prescription rate for childhood URIs, defined as

the proportion of prescriptions among all outpatient prescriptions for URIs that

include antibiotics (aged between 2 and 14 years old). This primary outcome is

selected because it should reflect the behavior change of both doctors and caregivers.

A reduction in the URIs will be a clinically beneficial outcome demonstrating

increased rational prescribing of antibiotics as most URIs are caused by viral infection

that do not require antibiotics. This measurement is reliable and feasible in the

primary care setting where prescriptions are well preserved either electronically or in

paper files.

The secondary outcomes are other commonly observed practices in routine primary

care. These include childhood URI prescription rate for multiple antibiotics,

broad-spectrum antibiotics and quinolones, defined as the proportion of prescriptions

among all outpatient prescriptions for URIs that include two or more antibiotics, a

broad-spectrum and quinolones respectively (aged between 2 and 14 years old).

Irrational prescribing causes great concern for the potential drug-resistance; while

misuse of quinolones may result in the increasing identification of extensively

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drug-resistant tuberculosis.35 Additionally, we will measure the mean cost of

childhood URI prescriptions, based on all prescriptions for URIs among outpatients

aged between 2 and 14 years old.

Sample size

We expect our intervention to lead to at least a 25% reduction in the antibiotic

prescription rate within township hospitals, based on a conservative estimate from our

systematic review.34 Based on our exploratory study the current average antibiotic

prescription rate is approximately 50%, which is therefore assumed for the usual care

arm. Consequently, our sample size calculation 36 is based on being able to detect a

25% or greater reduction in the antibiotic prescription rate in the intervention arm

compared to the usual care arm (i.e. an absolute reduction to 37.5% or less). Based on

exploratory work and an outcome data collection period of three-months, we assume a

cluster size of 200, using the harmonic mean to account for variation in cluster size,

and we assume a moderate between cluster coefficients of 0.15. Consequently, to

achieve 90% power using two-sided testing at the 5% significance level it is estimated

that 9 township hospitals per arm will be required. Allowing for stratified

randomization and a 10% loss of data due to lost and illegible prescriptions requires a

total of 24 township hospitals. As there are 25 eligible township hospitals within the

two counties it was decided to include all 25.

Randomization

In total, 25 township hospitals were eligible for the trial, with 14 in Rong county and

11 in Liujiang county. Randomization was stratified by county, and blocking was

used to ensure control over the allocation ratio within each county, with the block size

equal to the size of the stratum. Randomization was conducted by the study

statistician (JPH) using a computer program written in R (version 3.2.0), 36 37

and

township hospitals were randomized for the main trial and the internal pilot in the

same process. Initially, township hospitals within Rong county were randomized in a

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1:1 allocation ratio, whilst within Liujiang county township hospitals were

randomized in a 5:6 allocation ratio (treatment:control). Subsequently, within Rong

county six hospitals, three from each treatment arm, were randomly selected to

become the internal pilot clusters. The remaining 19 township hospitals (8 in Rong

county and 11 in Liujiang county) will therefore participate in the main trial along

with the six hospitals involved in the internal pilot. Overall the 25 hospitals were

allocated in a12:13 (treatment:control) allocation ratio.

Internal pilot process

The internal pilot study aims to assess recruitment rates and the extent to which the

intervention is delivered within township hospitals, as well as contributing outcome

data to the main trial. The six township hospitals in the pilot study will be recruited

and followed-up for three months, and the decision as to whether to continue with the

full trial will then be taken based on two key criteria: 1) sufficient levels of

recruitment (number of prescriptions sufficient to achieve minimum sample size

required); 2) feasibility of implementing the intervention (at least 50% of clinicians

trained and 50% using the guidelines at the end of the three months after the

intervention). If these criteria are met, the internal pilot hospitals and their outcome

data will then become part of the main trial, and will be followed-up for a further

three months. The remaining 19 hospitals will have been recruited, and if the trial is

proven to be feasible via the pilot they will be enrolled into the study and followed-up

for six months (meaning that data collection in the pilot and main trial hospitals will

finish at different times).

Data collection and management

To evaluate the primary and secondary outcomes, a minimum of two hundred

prescriptions for childhood URIs will be randomly selected in each township hospital

during the three months before (to provide baseline data) and the last three months

after the implementation of the intervention. Prescription data will be obtained from

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electronic records where available, or alternatively photographic copies will be taken

of patients’ paper prescriptions. Data collected from electronic or photographic

records will then be entered into a password-protected SPSS version 20.0 (IBM Corp.

Armonk, NY.) database. Information includes the township hospital, the date of the

prescription, the patient’s age, symptoms, diagnosis, related treatment, related

laboratory tests, treatment payment and insurance status. Personally identifying

information (e.g, names) will not be entered into the database, and each prescription

will be assigned a unique study identification number. Physical study data materials

will be stored securely in a locked cabinet, separate from the data of other studies. The

photographed prescriptions will be managed as audio files that will be deleted as soon

as possible following information extraction.

Data analysis

Analysis of outcomes

There are no interim analyses planned. Therefore, the outcomes will be analysed once

all data has been collected from all eligible prescriptions. The intention-to-treat (ITT)

population is defined as all patient-prescriptions issued for URIs in children (aged

2-14 years old) collected from each township hospital, regardless of the compliance of

township hospitals to the intervention. Statistical analyses of primary and secondary

outcomes will initially be by ITT, but per-protocol analyses will also be considered if

there are any protocol violators (i.e. if any township hospitals randomized to the

intervention arm do not implement the intervention). Inference will be based on

hypothesis testing with statistical significance assessed at the 5% level.

The crude-effect of the intervention on outcomes will be analysed using methods

appropriate for cRCTs where there are less than 20 clusters per arm.36 For the primary

outcome and those secondary outcomes involving proportions an overall risk ratio

will be estimated from a weighted average of the within-stratum risk ratios, with

weights inversely proportional to the stratum-specific variances. Stratum-specific risk

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ratios will be calculated from the unweighted stratum-specific means of

township-hospital-level outcomes. If the within-arm distribution of risk ratios is found

to be strongly skewed for an outcome, a logarithmic transformation will first be

applied. Formal hypothesis testing will be conducted using stratified t-tests, and 95%

confidence intervals will be adjusted for between-cluster variance and stratification.

The average cost of childhood URI prescriptions will be analysed using the same

methods, but with stratum-specific differences between the mean outcomes in each

arm used in place of stratum-specific risk ratios.

To adjust for important covariates, including individual and contextual factors, a

two-stage process will be carried out.36 For proportion outcomes a logistic regression

model will be fitted to the individual-level data including stratum and the covariates

of interest as fixed effects, but ignoring the treatment effect. Covariate-adjusted ratio

residuals will then be calculated from the ratios of cluster-specific observed and

expected values. The covariate-adjusted ratios will then be used in place of

cluster-specific proportions to conduct stratified t-tests and calculate 95% confidence

intervals using the above methods. To analyse the average cost of childhood URI

prescriptions using this two-stage method a normal regression model will be used; and

cluster-specific difference residuals, calculated from the differences between

cluster-specific observed and expected values, used in place of stratum-specific

differences in means.

Due to the likely causes of missing data described previously all missing data will be

assumed to be missing completely at random, and complete case analyses will be

conducted. All data will be analysed using STATA version 12.1 (SE) (STATA

Corporation, College Station, Texas).

Sub-group analyses

Planned sub-group analyses will be conducted on all outcomes to determine whether

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there is any significant heterogeneity in treatment effects occurring in township

hospitals of different size, and in patients of different ages and genders. For each

outcome the cluster-level residuals described above will be regressed on stratum,

treatment group, the subgroup variable and all their possible two-way interactions.

F-tests will be used to determine whether there are any significant interactions

between treatment group and subgroups.

Process evaluation

A qualitative process evaluation will be conducted at six months into the intervention

in selected clusters from the intervention and control arms (in the control arm to

understand the implementation process of existing guidelines by clinicians, i.e. usual

practice). The process evaluation aims to describe the health system and service

delivery context in which the intervention was delivered; explore whether or not the

intervention is delivered as intended, both at the cluster level (training) and the

individual level (provider delivery); and understand mechanisms of impact both at the

provider level and caregiver level. Methods will include document review (e.g.

meeting minutes), observation of training sessions and consultations, and qualitative

interviews.

In each county we will select one control cluster. After three months of

implementation we will review prescription rates in intervention clusters. If all

intervention clusters are performing in a similar way (i.e. very good, medium, poor),

then we will select one intervention cluster from each county. However, if

intervention clusters are performing very differently, then we will need to select two

intervention clusters from each county (high and low performers) to understand

cluster level factors. In each township hospital selected, we will interview doctors, the

hospital director and the pharmacist. We will conduct a focus group discussion with

caregivers. A sampling frame will be developed and participants will be purposively

selected for inclusion from the selected sites.

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Qualitative data will be recorded if the participants agree to use audio-recording. The

audio files will be transcribed as soon as possible, and any audio files recorded by

mobile recording devices will be immediately deleted once they have been

transcribed. Only the researchers conducting the study will know the names of

participants, and have access to the responses from individual participants.

Analysis of process evaluation

Qualitative data will be analysed as soon as possible after it has been collected. The

analysis should feed into subsequent interviews, and if interesting issues emerge they

can be followed up in subsequent interviews. Data will be audio recorded and

transcribed. Nvivo version 10 (QSR International Pty Ltd) will be used to manage the

data. The data will be analysed using a simple thematic approach.38

Discussion

Our study is one of the first addressing irrational antibiotic prescribing in the primary

care context of a developing country. The study is of great significance given

antibiotic-resistant infections have contributed to high mortality among children,

particularly in developing contexts.7 Our study will contribute to the currently limited

number of studies addressing irrational antibiotic prescribing in the primary care

context of rural of China. In China most studies have focused on either clinicians or

patients. We therefore aim to test a comprehensive intervention targeting both

clinicians and patients, an approach shown to have the largest effect 27 in rural

primary care settings.

The evidence-based and user-friendly guideline on rational antibiotic prescribing is

developed to address the current lack of operational guidelines for primary care

practices. However, simple dissemination of guidelines alone has had limited effects

on health worker performance39 40

, including in ambulatory care settings27.

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Considering the insufficient medical training received by rural primary care doctors

compared to their urban peers in China 9, we aim to improve their knowledge through

continued professional training in rational antibiotic prescribing. Peer review of

antibiotics prescribing is also planned at monthly hospital staff meetings to monitor

fidelity to the intervention, and enhance the knowledge of doctors. Antibiotics are

culturally accepted in rural China as the first response to URIs. Thus, educating the

caregivers through primary care doctors is challenging but essential.41 We have

designed an iterative and participatory training process, with an emphasis on

improving the communication and educational skills of primary care doctors

interacting with elders. Our study will be conducted in poor rural areas where many

young parents have migrated to cities, leaving grandparents to act as caregivers for

children. We have thus tailored the educational materials to be more easily understood

by people with less education. By improving caregivers’ knowledge, the intervention

is expected to reduce patient demand for antibiotic prescribing in URIs.

The study fits into the current national priority on antibiotics control in China.

However, major control efforts have currently focused on referral hospitals rather than

the primary care level, especially in rural areas. The study will thus help to shape the

policies and regulations regarding antibiotic use, especially in primary care.12 Multiple

interventions have proved effective on improving the rational use of antibiotics.

However, some interventions, such as point-of-care tests, are not feasible in primary

care settings in the poorer rural areas of China. In this trial, all the interventions are

embedded within the routine primary care management and practice. Thus, additional

work and costs that would otherwise have been added to primary care will be reduced,

enhancing the replicability of the intervention.

Through this trial we aim to understand the barriers and facilitators which are

embedded within the context, the implementation and mechanisms of impact, and

which affect the behaviour change outcome;42 and we aim to understand how to

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overcome implementation challenges and scale-up the intervention. For instance, the

uncertain effect of the zero-price mark-up policy on reducing medicine use may

suggest influences beyond providers and patients, such as those of pharmaceutical

companies. It is hoped that our intervention may be able to influence this and other

negative factors, and achieve desirable behavior change outcomes. Outputs will

include an operational guideline on the rational use of antibiotics for URIs among

children, and training modules and other materials that may be scaled-up in Guangxi

and other western provinces. These materials also have the potential to be adapted to

other low and middle income countries. We therefore believe this trial will greatly

contribute to improving the prescribing behavior of doctors in the rural primary care

context of Guangxi, China.




disseminated through policy briefs, workshops, peer-reviewed publications and local

and international conferences.

Contributors

All authors made substantive contributions to the trial development and provided final

approval for this manuscript. XW, GZ, JW, HE ,RK and YH designed the trial and

related studies. GZ and XW drafted the manuscript. ML, JZ, YH, YH, ZZ, SD, RK,

HE contributed to designing the trial and participated in the pilot study. JPH

contributed to the statistical issues in the study design and wrote the statistical

analysis plan. RK contributed to the design of the process evaluation and qualitative

methods. HE contributed to trial and process evaluation design and critically reviewed

the manuscript. CB, JW, JPH and QS contributed to ethics development and critically

reviewed the manuscript. JW, JPH and QS critically reviewed the manuscript.

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Funding

The trial is supported by the Department for International Development of the UK

Government (DFID) via the Communicable Disease - Health Service Delivery

(COMDIS-HSD) Research Programme Consortium.

Competing interests

The authors declare that they have no competing interests.

.

References:

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24. Ruvinsky S, Monaco A, Perez G, et al. Effectiveness of a program to improve antibiotic

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26. Persell SD, Friedberg MW, Meeker D, et al. Use of behavioral economics and social

psychology to improve treatment of acute respiratory infections (BEARI): rationale

and design of a cluster randomized controlled trial [1RC4AG039115-01]--study

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2013;13:290.

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df?v=1&t=ifphjtif&s=aaa533bb3d45fdf3ed3d83bfa608884a95301f66.

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results of a cluster-randomized, multicommunity intervention. Pediatrics

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29. Taylor JA, Kwan-Gett TS, McMahon EM, Jr. Effectiveness of a parental educational

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41. Yu M, Zhao G, Stalsby Lundborg C, et al. Knowledge, attitudes, and practices of parents in

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a. Eligible subjects include all outpatient prescriptions for children, aged between 2 and 14 years old, diagnosed with URIs

b. Intervention package includes: operational guidelines, training, peer review, consultation(providers); education leaflets, video(patients);

c. Usual care refers to health care following routine works at the discretion of individual doctors.

Figure 1 Trial flow chart

Process

evaluation

Outcome

evaluation

Total clusters in two counties (n=27)

Eligible clusters for randomization (n=25)

Exclude 2

ineligible

clusters

Intervention arm (n=12) Control arm (n=13)

Internal pilot

� Intervention(n=3), 3 months

� Baseline data collection in

pilot clusters

Internal pilot

� Usual care(n=3), 3 months


pilot clusters

Main trial

� Intervention:

3 pilot clusters, 3 months;

9 remaining clusters, 6

months


remaining clusters

Main trial

� Usual care:

3 pilot clusters, 3 months;

10 remaining clusters, 6

months


remaining clusters

Outcome data collection Outcome data collection

Analyse prescriptions

(Intention-to-treat)

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Reducing irrational antibiotic prescribing among children with upper respiratory

infections: statistical analysis plan of a clustered randomized controlled trial in rural

China

Version 1.0

1. Introduction

1.1. Background

Irrational use of antibiotics is a serious international issue that is particularly acute in low-

and middle-income countries, and it is estimated that globally over half of all medicines are

inappropriately prescribed or sold, whilst over half all patients fail to take their medicine

appropriately.[1-3] Irrational use of antibiotics not only brings high economic burdens to

health systems, but also increases the risk of antibiotic resistance.[2] Acute upper respiratory

infections (URIs) are very common among children, but are usually viral and self-limiting,

with antibiotic treatment being unnecessary.[4] However, irrational use of antibiotics for

URIs in children is very prevalent in primary care settings internationally.[5]

A cross-sectional study in ten provinces in rural Western China showed that antibiotics

accounted for over half of all prescriptions, predominantly provided for URIs, and with

approximately one quarter of those receiving antibiotics being children under ten years

old.[6] Irrational antibiotic use amongst children is known to contribute to higher childhood

mortality in countries with inadequate health infrastructure.[7] Several national policies have

been issued by the Ministry of Health, including the most recent one limiting antibiotic

prescriptions to less than 60% of all prescriptions for inpatients and 20% for outpatients.[8]

However, no operational details were provided on how to implement the policy, and no

guidelines were provided for the diagnosis and treatment of URIs in children, or related

clinician training. Potentially because of this situation, despite attempts at health sector

reform there has been no significant improvement in the rational use of antibiotics or cost

control in China.[9]

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Commonly reported interventions for improving antibiotic use in URI treatment included

clinical decision support,[10-13] point-of-care testing for C-reactive protein,[14-17] clinician

communication skills training,[14-16] education and feedback,[18] public reporting of

antibiotic prescribing rates,[19] discussion and monitoring workshops,[20] governance

structure change,[21] and interventions based on behavioural economics and social

psychology.[22] However, a Cochrane review demonstrated that while multi-faceted

interventions targeting both physicians and patients significantly reduced inappropriate

antibiotic use in community settings,[23] single interventions with parents failed to impact on

antibiotic prescribing.[24-26]

Therefore, we developed a multidimensional intervention targeting doctors and patient

caregivers which aimed to reduce the irrational use of antibiotics for URIs in children within

China’s rural primary care context (specifically within township hospitals). The intervention

was developed through exploratory work, and its feasibility, acceptance and the adequate

adherence of doctors to the intervention has been confirmed via an internal pilot.

1.2. Aims and objectives

This study aims to evaluate the clinical effectiveness of the intervention in realistic primary

care settings in rural China, to guide decisions on the implementation of programmes to

reducing irrational antibiotic use across China. Therefore, the study’s objective is to

determine whether the intervention reduces the amount of antibiotics prescribed for URIs in

child outpatients within township hospitals, compared to existing practice.

1.3. Study design and randomisation process

The trial has been designed as a pragmatic, parallel-group, multi-centre, cluster randomised,

controlled trial. The trial will evaluate the superiority of the intervention within township

hospitals, which are the unit of randomisation. The trial will be undertaken within two

counties, across which a total of 25 township hospitals (14 in Rong county and 11 in Liujiang

county) will be recruited and allocated between treatment arms (including 6 hospitals used in

the internal pilot). Randomization was conducted by the study statistician (JPH) using a

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computer program written in R (version 3.2.0). To control the allocation ratio block

randomisation was conducted, stratified by county, with the block size equal to the size of the

stratum. For the main trial hospitals within Rong county were randomised in a 1:1 allocation

ratio, and hospitals within Liujiang county were randomised in a 5:6 (treatment:control)

allocation ratio to reduce financial and logistical costs. Within Rong county 6 hospitals were

then randomly selected from the allocation list, three from each arm, to become the internal

pilot clusters. Therefore, 19 hospitals remained for the main trial (8 in Rong county and 11 in

Liujiang county), with an overall 12:13 (treatment:control) allocation ratio for all 25

hospitals.

Outcome data will be collected from at least 5000 prescriptions (approximately 200 per

hospital) issued for URIs in outpatients aged between 2 and 14 years old during the last three

months following the implementation of the intervention in treatment-arm hospitals, and

during the equivalent period in control-arm hospitals. Baseline outcome data will also be

gathered from at least 5000 child-outpatient URI prescriptions issued during the three months

prior to the implementation of the intervention in each arm.

Within intervention hospitals all family doctors will receive training to increase their

knowledge on the rational use of antibiotics, and to improve the effectiveness of their

communication skills when interacting with caregivers of children with URIs, facilitating the

education of caregivers on the rational use of antibiotics. Monthly peer review meetings will

also assess doctors’ antibiotic prescribing practices, and reinforce desired behaviours. Printed

and video-based educational materials will also be provided for caregivers in intervention

hospital waiting rooms to improve understanding about the rational use of antibiotics. In

control hospitals none of the intervention components will be implemented, and the only

apparent impact will be via the collection of prescription data.

Blinding is clearly not possible for doctors or caregivers, but there will be blinded evaluation

of all outcomes. Similarly, a cluster design was chosen due to the difficulty of preventing

contamination of both doctors and caregivers, and the need for hospital-wide participation of

doctors in the peer review meetings, which are felt to be a key component of the intervention.

1.4. Sample size (if applicable) and expected accrual

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The intervention is expected to lead to at least a 25% reduction in the antibiotic prescription

rate (the primary outcome) within township hospitals, based on a conservative estimate from

similar interventions.[27] This change would be clinically highly significant. Based on

exploratory work the current average antibiotic prescription rate is estimated to be

approximately 50%, which is assumed for the usual care arm. The resulting sample size

calculation [28] is based on being able to detect a 25% or greater reduction in the antibiotic

prescription rate in the intervention arm compared to the usual care arm (i.e. an absolute

reduction from 50% to 37.5% or less). Based on exploratory work we assume a mean of 200

eligible prescriptions will be collected per township hospital over the three-month outcome

collection period, and a moderate between-cluster coefficient of variation of 0.15.

Consequently, to achieve 90% power using two-sided testing at the 5% significance level it is

estimated that 9 township hospitals per arm will be required. Allowing for stratified

randomization and a 10% loss of data due to expected hospital-losses and illegible

prescriptions 24 township hospitals are required. As there are 25 eligible township hospitals

in total it was decided to include all 25 on ethical grounds.

1.5. Planned analyses

No interim analyses are planned. All outcomes will be analysed after the data collection

period ends.

2. Outcomes

All outcome data will be collected from prescriptions (both paper and, where available,

electronic records) over a three month period prior to the implementation of the intervention

(baseline outcome data), and over the last three month period following the implementation

of the intervention (with data collection in control hospitals occurring over the same period).

2.1. Primary outcome

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The antibiotic prescription rate for childhood URIs. Defined at the township-hospital level as

the proportion of prescriptions for URIs among outpatients aged between 2 and 14 years old

that include at least one antibiotic. The antibiotic prescription rate is the primary outcome

because it should reflect the behaviour change of both doctors and caregivers. Most URIs are

caused by viral infection that are self-limiting and do not require antibiotics, and a reduction

in this rate will be a clinically beneficial outcome demonstrating increased rational

prescribing of antibiotics for childhood URIs. This measurement is also reliable and feasible

in the primary care setting because prescriptions are well preserved either electronically or in

paper files.

2.2. Secondary outcome

• The childhood URI multiple antibiotic prescription rate: the proportion of

prescriptions for URIs among outpatients aged between 2 and 14 years old that

include two or more antibiotics;

• The childhood URI broad-spectrum antibiotic prescription rate: the proportion of

prescriptions for URIs among outpatients aged between 2 and 14 years old that

include a broad-spectrum antibiotic;

• The childhood URI quinolones prescription rate: the proportion of prescriptions for

URIs among outpatients aged between 2 and 14 years old that include a quinolone

antibiotic;

• Additionally, to understand the medical costs associated with antibiotics prescribing

we will measure the mean cost (Yuan) of childhood URI prescriptions, based on all

prescriptions for URIs among outpatients aged between 2 and 14 years old.

Secondary outcomes were chosen to assess the extent to which the intervention will reduce

other commonly observed practices in routine primary care relating to antibiotic prescribing

practices for URIs that are particularly likely to increase drug-resistance, and the

intervention’s cost effectiveness.

2.3. Missing data

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Due to the assumed plausible reasons for missing data (lost paper and electronic prescriptions

records, and unreadable paper prescription records) all missing data will be assumed to be

missing completely at random, and only complete case analyses will be conducted.

3. Populations

3.1. Township hospital eligibility criteria

All township hospitals from the two selected counties in Guangxi who agree to participate in

the study will be included. However, we will exclude the two township hospitals located in

the two county centres. Compared to all other township hospitals they have much higher staff

capacity and equipment levels, and their proximity to the county general hospital is likely to

result in patient populations with substantially different characteristics.

3.2. Patient prescription eligibility criteria

All outpatient prescriptions for children aged between 2 and 14 years old who are diagnosed

with URIs during the study period will be included for analysis. Children under 2 years old

will be excluded because they are more vulnerable to secondary bacterial infection, and

exploratory work indicated that it was very difficult for doctor’s to refuse antibiotics for

younger children in China’s context. Prescriptions for children diagnosed with pneumonia

(where antibiotic prescription is appropriate) or other severe diseases requiring long-term

antibiotic treatment (or as prophylaxis) will also be excluded. Prescriptions for inpatients will

not be collected.

3.3. Populations

The intention-to-treat (ITT) population is defined as all outpatient-prescriptions issued for

URIs in children aged 2-14 years old collected from township hospitals, regardless of the

compliance of township hospitals to the intervention. Statistical analyses of primary and

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secondary outcomes will initially be by ITT, but per-protocol analyses will also be considered

if there are any protocol violators (i.e. if any township hospitals randomized to the

intervention arm do not implement the intervention).

4. Data handling

4.1. Data monitoring

All personally identifying details will be removed from the study database. Data will be

checked weekly for quality and completeness by the study data manager (ZZ), and any

missing data will be followed-up with township hospitals until received (if electronically

available), confirmed as set aside for later collection by researchers (if paper-based) or

confirmed as not available. Recruitment rates will be monitored on a monthly basis. There is

no Data Monitoring and Ethics Committee or equivalent associated with the study.

4.2. Data validation

Prior to analysis the final database will be validated using a STATA program to identify any

anomalous, inconsistent and missing data. This program will check/identify:

• Eligibility criteria of prescriptions

• Consistency of prescription issue dates relative to the baseline and outcome data

collection periods

• Outlying and anomalous (e.g. incorrect format, impossible value) data

• Missing data

All anomalous, inconsistent or unexpectedly missing data will be checked against original

paper or photographic prescription records where feasible. Any anomalous or inconsistent

data that can be unambiguously corrected will be, but where any ambiguity cannot be

resolved values will be recorded as missing data.

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5. Data analysis

5.1. General calculations

Percentage calculations will exclude any missing prescriptions from the denominators.

Summary statistics such as percentages and means will be rounded to 1 decimal place, or 1

significant figure for numbers less than 1, but standard deviations will be rounded to 2

decimal places, or 2 significant figures for numbers less than 1. Parameter estimates,

including standard errors SEs and 95% confidence intervals (CIs), will be rounded to 2

decimal places, or 2 significant figures for numbers less than 1. All hypothesis testing will be

2-sided and at the 5% significance level. All analyses will be carried out using STATA

Version 12.1 (SE) software, but other packages will be employed if necessary. The primary

and the secondary outcome analyses will be based on the intention-to-treat (ITT) population.

All analyses will be conducted by the study statistician (JPH).

5.2. Analysis

5.2.1. Baseline characteristics

The baseline characteristics of the ITT population will be summarised using frequencies and

means (with SDs) as appropriate for each treatment group.

5.2.2. Primary and secondary outcome analyses

The crude and covariate adjusted effect of the intervention on outcomes will be analysed

using methods appropriate for cRCTs where there are less than 20 clusters per arm.[28] For

the primary outcome and those secondary outcomes involving proportions an overall risk

ratio will be estimated from a weighted average of the within-stratum risk ratios, with

weights inversely proportional to the stratum-specific variances. Stratum-specific risk ratios

will be calculated from the unweighted stratum-specific means of township-hospital-level

outcomes. If the within-arm distribution of risk ratios is found to be strongly skewed for an

outcome, a logarithmic transformation will first be applied to the outcome proportions.

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Formal hypothesis testing will be conducted using stratified t-tests, and 95% confidence

intervals will be adjusted for between-cluster variance and stratification. The average cost of

childhood URI prescriptions will be analysed using the same methods, but with stratum-

specific differences between the mean outcomes in each arm used in place of stratum-specific

risk ratios.

To adjust for important covariates, including individual and township-hospital level factors, a

two-stage process will also be followed. For proportion outcomes a logistic regression model

will be fitted to the individual-level data including stratum and the covariates of interest as

fixed effects, but ignoring the treatment effect. Covariate-adjusted ratio residuals will then be

calculated from the ratios of cluster-specific observed and expected values. The covariate-

adjusted ratios will then be used in place of cluster-specific proportions to conduct stratified

t-tests and calculate 95% confidence intervals using the above methods. To analyse the

average cost of childhood URI prescriptions using this two-stage method a normal regression

model will be used, and cluster-specific difference residuals, calculated from the differences

between cluster-specific observed and expected values, used in place of stratum-specific

differences in means. As per CONSORT both unadjusted and adjusted results will be

presented.

For all outcomes, within each treatment arm and strata estimates of the between-cluster

coefficient of variation and the intraclass correlation coefficient will also be calculated and

made available to facilitate future trial planning and systematic reviews.

5.2.3. Subgroup analyses

Planned sub-group analyses will be conducted for all outcomes to determine whether there is

any significant heterogeneity in treatment effects due to variation in the size of township

hospitals, patient age or patient gender. In a normal regression model for each outcome the

unadjusted and adjusted cluster-level residuals described above will be regressed on county,

treatment group, a subgroup dummy variable and all their possible two-way interactions. Any

significant interactions (based on t-tests) between treatment group and subgroups will be

taken as evidence for differences in treatment effects between subgroups.

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6. References


Promoting rational use of medicines: Core components. 2002



1990 and 2006. 2009


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4. Alves Galvão Márcia G, Rocha Crispino Santos Marilene A, Alves da Cunha Antonio JL.

Antibiotics for preventing suppurative complications from undifferentiated acute

respiratory infections in children under five years of age. Cochrane Database of

Systematic Reviews 2014; (2).


http://onlinelibrary.wiley.com/store/10.1002/14651858.CD007880.pub2/asset/CD007880.pdf

?v=1&t=ifqozjug&s=ffa4fb20e6eb6cab84110af79bf87112e990651c.


antibiotic use for acute respiratory tract infections in children: a systematic review and

meta-analysis. PLoS One 2012;7(1):e30334 doi:

10.1371/journal.pone.0030334[published Online First: Epub Date]|.


provinces of Western China. J Antimicrob Chemother 2008;62(2):410-5 doi:

10.1093/jac/dkn153[published Online First: Epub Date]|.

7. Ilic K, Jakovljevic E, Skodric-Trifunovic V. Social-economic factors and irrational

antibiotic use as reasons for antibiotic resistance of bacteria causing common

childhood infections in primary healthcare. Eur J Pediatr 2012;171(5):767-77 doi:

10.1007/s00431-011-1592-5[published Online First: Epub Date]|.

8. Xiao Y, Li L. Legislation of clinical antibiotic use in China. Lancet Infectious Diseases

2013;13(3):189-91 doi: 10.1016/s1473-3099(13)70011-2[published Online First:

Epub Date]|.

9. Mao W, Vu H, Xie Z, et al. Systematic Review on Irrational Use of Medicines in China

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and Vietnam. PloS one 2015;10(3):e0117710

10. Gonzales R, Anderer T, McCulloch CE, et al. A cluster randomized trial of decision

support strategies for reducing antibiotic use in acute bronchitis. JAMA Intern Med

2013;173(4):267-73 doi: 10.1001/jamainternmed.2013.1589[published Online First:

Epub Date]|.

11. Litvin CB, Ornstein SM, Wessell AM, et al. Adoption of a clinical decision support

system to promote judicious use of antibiotics for acute respiratory infections in

primary care. Int J Med Inform 2012;81(8):521-6 doi:

10.1016/j.ijmedinf.2012.03.002[published Online First: Epub Date]|.


decision support tool to improve antibiotic prescribing for acute respiratory infections:

the ABX-TRIP study. J Gen Intern Med 2013;28(6):810-6 doi: 10.1007/s11606-012-

2267-2[published Online First: Epub Date]|.

13. Mainous AG, 3rd, Lambourne CA, Nietert PJ. Impact of a clinical decision support

system on antibiotic prescribing for acute respiratory infections in primary care:

quasi-experimental trial. J Am Med Inform Assoc 2013;20(2):317-24 doi:

10.1136/amiajnl-2011-000701[published Online First: Epub Date]|.


respiratory tract infections in German primary care--the cluster-randomized controlled

CHANGE-2 trial. BMC Fam Pract 2012;13:124 doi: 10.1186/1471-2296-13-

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cluster randomized trial. Ann Fam Med 2013;11(2):157-64 doi:

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randomised, factorial, controlled trial. Lancet 2013;382(9899):1175-82 doi:

10.1016/s0140-6736(13)60994-0[published Online First: Epub Date]|.


patient knowledge and attitudes about appropriate antibiotic use for acute respiratory

tract infections. Patient Educ Couns 2011;85(3):493-8 doi:

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2011;66(11):2659-66 doi: 10.1093/jac/dkr312[published Online First: Epub Date]|.


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Argent Pediatr 2014;112(2):124-31 doi: 10.1590/s0325-

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21. Liang X, Xia T, Zhang X, et al. Governance structure reform and antibiotics prescription

in community health centres in Shenzhen, China. Fam Pract 2014;31(3):311-8 doi:

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?v=1&t=ifphjtif&s=aaa533bb3d45fdf3ed3d83bfa608884a95301f66.



2007;119(4):698-706 doi: 10.1542/peds.2006-2600[published Online First: Epub

Date]|.



Pediatr Infect Dis J 2005;24(6):489-93


parent attitudes toward pediatric antibiotic use. Pediatrics 2001;108(3):591-6


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infections COMDIS Health Service Delivery Research Consortium, China

Programme 2015.


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A protocol for a pragmatic cluster randomized controlled trial for reducing irrational antibiotic prescribing among

children with upper respiratory infections in rural China

Journal: BMJ Open

Manuscript ID bmjopen-2015-010544.R1

Article Type: Protocol

Date Submitted by the Author: 08-Apr-2016

Complete List of Authors: Zou, Guanyang; China Global Health Research and Development Wei, xiaolin; University of Toronto, DL School of Public Health; China Global Health Research and Development

Hicks, Joseph; University of Leeds, Nuffield Centre for International Health and Development, Leeds Institute of Health Sciences Hu, Yanhong; The Chinese University of Hong Kong Walley, John; University of Leeds, Nuffield Centre for International Health and Development, Leeds Institute of Health Sciences Zeng, Jun; Guangxi Autonomous Region Centre for Disease Control and Prevention Elsey, Helen; University of Leeds, Nuffield Centre for International Health and Development King, Rebecca; University of Leeds, Nuffield Institute For International Health and Development, Leeds Institute of Health Sciences Zhang, Zhitong; China Global Health Research and Development

Deng, Simin; China Global Health Research and Development, Huang, Yuanyuan; China Global Health Research and Development Blacklock, Claire; University of Leeds, Nuffield Centre for International Health and Development, Leeds Institute of Health Sciences Yin, Jia; The Chinese University of Hong Kong Sun, Qiang; Shandong University Lin, Mei; Guangxi Autonomous Region Centre for Disease Control and Prevention

<b>Primary Subject Heading</b>:

Public health

Secondary Subject Heading: Health policy, Public health, Health services research, Paediatrics,

Respiratory medicine

Keywords: Antibiotics, Rational use, Clustered randomized control trial, PRIMARY CARE, China

Note: The following files were submitted by the author for peer review, but cannot be converted to PDF. You must view these files (e.g. movies) online.

Figure_1_Trial_flow_chart.tif


BMJ Open on M

arch 21, 2020 by guest. Protected by copyright.

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A protocol for a pragmatic cluster randomized controlled trial for reducing

irrational antibiotic prescribing among children with upper respiratory

infections in rural China

Guanyang Zou1+, Xiaolin Wei

2,1+*, Joseph P Hicks

3, Yanhong Hu

4, John Walley

3, Jun

Zeng5, Helen Elsey

3, Rebecca King

3, Zhitong Zhang

1, Simin Deng

1, Yuanyuan

Huang1, Claire Blacklock

3, Jia Yin

4, Qiang Sun

6, Mei Lin

5*

* Corresponding authors: Mei Lin Email: [email protected]

Xiaolin Wei: [email protected]

+ Equal contributors

1 China Global Health Research and Development, Shenzhen, China

2 Dalla Lana School of Public Health, University of Toronto, Toronto, Canada

3 Nuffield Centre for International Health and Development, University of Leeds,

Leeds, UK

4 School of Public Health and Primary Care, Chinese University of Hong Kong, Hong

Kong, China

5 Guangxi Autonomous Region Centre for Disease Control and Prevention, Nanning,

China

6 Centre for Health Management and Policy, Shandong University, Jinan, China

Guanyang Zou and Xiaolin Wei contributed equally to this work.

Key words: antibiotics, rational use, upper respiratory infection, cluster randomized

controlled trial, primary care, China

Word count: 4878

Document version number and date: 02 (30th March 2016).

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Abstract

Introduction

Irrational use of antibiotics is a serious issue within China and internationally. In 2012

the Chinese Ministry of Health issued a regulation for antibiotic prescriptions limiting

them to less than 20% of all prescriptions for outpatients, but no operational details

have been issued regarding policy implementation. This study aims to test the

effectiveness of a multi-dimensional intervention designed to reduce the use of

antibiotics among children (aged 2-14 years old) with acute upper respiratory

infections in rural primary care settings in China, through changing doctors’

prescribing behaviors and educating parents/caregivers.

Methods and analysis

This is a pragmatic, parallel-group, controlled, cluster-randomized superiority trial,

with blinded evaluation of outcomes and data analysis, but un-blinded treatment.

From two counties in Guangxi Province 12 township hospitals will be randomized to

the intervention arm and 13 to the control arm. In the control arm, the management of

antibiotics prescriptions will continue through usual care via clinical consultations. In

the intervention arm, a provider and patient/caregiver focused intervention will be

embedded within routine primary care practice. The provider intervention includes

operational guidelines, systematic training, peer review of antibiotic prescribing, and

provision of health education to patient caregivers. We will also provide printed

educational materials and educational videos to patients’ caregivers. The primary

outcome is the proportion of all prescriptions issued by providers for upper respiratory

infections in children, aged 2-14 years old, which include at least one antibiotic.




disseminated through workshops, policy briefs, peer-reviewed publications, local and

international conferences.

Trial registration: Current Controlled Trials: ISRCTN14340536

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Strength and limitations

• We aim to test a comprehensive intervention targeting doctors and patients/

caregivers, an approach shown to have the largest effect on reducing the

irrational prescribing of antibiotics in rural primary care settings.

• The study is adapted to the local context and fits into the current Chinese

national priority on antibiotics control.

• All the interventions are embedded within routine primary care management

and practice, thus enhancing the potential scale-up of the intervention.

• The effectiveness of the pragmatic trial may be limited by various contextual

factors, which will be explored by a qualitative process evaluation.

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INTRODUCTION

Irrational use of antibiotics is a serious issue within China and internationally.

Worldwide, around 50% of medicines are not appropriately prescribed, dispensed or

sold. 1-3 Irrational use of antibiotics not only brings high economic burdens to health

systems, but also increases the risk of antibiotic resistance.4 Acute upper respiratory

infections (URIs) are very common among children, however most are usually viral

and self-limiting, with antibiotic treatment for URIs being unnecessary. For example,

a systematic review has shown that antibiotic use does not shorten the duration of

URIs.5 Despite this, there is a high prevalence of antibiotics prescriptions for URIs in

primary care facilities.6 Antibiotic resistant bacteria are also frequently found in

children, especially infants, particularly in countries with less stringent prescribing

regulations in healthcare and agriculture.7

China is notorious for antibiotic misuse in healthcare. In 2012 the national Ministry of

Health reported that the average person consumed 138 grams of antibiotics per year,

ten times the rate in the Unites States.8 The situation is worst in rural areas where

health workers receive less education and continuous medical training in practice.9

Knowledge and awareness about antibiotic misuse and resistance is also poorer in

rural communities compared to amongst urban residents.10 Another recent study

found frequent and inappropriate use of antibiotics in primary health care settings in

China, that a 78% antibiotics were prescribed for colds and 93.5% for acute

bronchitis.11 An earlier study in the primary care settings of ten provinces in rural

Western China showed that antibiotics accounted for nearly half of all prescriptions,

predominantly provided for URIs, while one fourth of those receiving antibiotics were

children under ten years old.12

Several national policies have been issued by the Ministry of Health, including the

most recent limiting antibiotic prescriptions to less than 60% of all prescriptions for

inpatients and 20% for outpatients.13 However, no operational details were provided

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on how to implement the policy, and no guidelines were provided on the diagnosis

and treatment of childhood URIs, or related clinician training especially for primary

care doctors. In the 2009 health sector reform China launched the Essential Medicines

List policy, supported by the centralized procurement of essential medicines and the

Zero-Markup policy. However, after two years of implementation there was no

significant improvement in the rational use of medicines and cost control.14

The majority of studies on reducing irrational antibiotic use have been conducted in

developed countries, which have demonstrated that improving knowledge, attitudes

and behaviors of healthcare providers and consumers can effectively reduce irrational

antibiotic use.15 Commonly reported interventions for improving antibiotic use in URI

treatment included clinical decision support,16-20

point-of-care testing for C-reactive

protein,21-24

clinician communication skills training21-23

, education and feedbacks,25

discussion and monitoring workshops,26 governance structure change,

27 and

behavioral economics and social psychology.28 A Cochrane review demonstrated that

multi-faceted interventions targeting both physicians and patients significantly

reduced inappropriate antibiotic use in community settings;29 whereas single

interventions with parents failed to impact on antibiotic prescribing.30-32

Studies of irrational antibiotic prescribing in primary care settings in China are

currently limited, and mainly cross-sectional surveys.11 12

Studies involving

interventions aimed at reducing the irrational prescribing of antibiotics in primary are

rare, except one study showing limited impact of a public reporting intervention on

reducing antibiotics prescribing in primary care facilities.33 Therefore, we aim to test

the effectiveness of a multidimensional intervention targeting doctors’ prescribing

behaviors and the education of parents/caregivers, which we hypothesize will reduce

the irrational use of antibiotics among children with acute URIs in China’s rural

primary care context.

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METHODS AND ANALYSIS

Design of the study

This is a parallel-group, cluster randomized controlled trial, designed as a pragmatic

evaluation of the superiority of a health behaviour change intervention compared with

routine practice (Figure 1 Trial Flow Chart). The study will be conducted in 25

township hospitals, with randomization stratified by county. Randomization is at the

level of township hospitals because it would not be practically or logistically feasible

to randomize individual doctors or patients/caregivers in this multidimensional

intervention that involves both provider and patient/caregivers components. Study

participants and doctors will not be blinded to the treatment, but measures will be

taken to ensure a blinded outcome evaluation by using the ‘PROBE’ design.34

The study design broadly follows the Medical Research Council framework

Developing and evaluating complex interventions: new guidance.35 Prior to the

conduct of the trial we conducted a systematic review of interventions aimed at

reducing antibiotic use in children with URIs.36 We then developed our intervention

based on the results, which supported findings29 that interventions targeting both

clinicians and patients had a greater effect on reducing irrational antibiotic use than

those targeting a single group. An internal pilot approach will be used to examine the

feasibility and acceptability of intervention and research procedures in six township

hospitals. An independent trial steering committee, where lead investigators will be

steering committee members, has also been setup to supervise the trial, review

progress, and if necessary decide on any changes to the protocol. A data monitoring

committee will not be set up given the lack of any interim analyses and very low risk

to participants, but the statistician will provide any data advice to the trial steering

committee as necessary.

Setting

The trial will take place in two counties of Guangxi province, which is one of the

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poorest provinces in China, and is located in the southwest mountainous terrain

joining Vietnam and Laos. Guangxi has a population of 48 million and contains 110

counties. In the rural areas, primary care is provided by public township hospitals, and

this trial will be conducted in 25 such hospitals. Each township hospital covers 20,000

to 100,000 people, and doctors in the township hospitals are responsible for acute and

preventive care. Although township hospitals have inpatient treatment facilities, we

only consider outpatients in this study because inpatients are likely to have a range of

co-morbidities, leading to difficulty in assessing rational prescribing for URIs. Each

township hospital has 5 to 20 doctors. No booking system is operated in rural

township hospitals. We have not included village clinics, often equipped with an

upgraded community health worker, called a ‘village doctor’, because both public and

private clinics co-exist which may confound the interventions. Rather, our

intervention focuses on professionally qualified public clinicians who work as general

practitioners (‘doctors’) in township hospitals.

Eligibility

Eligibility criteria for clusters

All doctors working in township hospitals from the two selected counties in Guangxi

who agreed to participate in the study are included. We excluded the two township

hospitals located in the two county centers, as they have much better staff capacity

and equipment than their peers, and are close to the county general hospital. Both

counties have implemented the Essential Medicine List, its treatment guidelines and

the Zero-Markup Policy since 2012.

Eligibility criteria for participants

All outpatient prescriptions for children aged between 2 and 14 years old and

diagnosed with URIs during the baseline and intervention data collection period

(Figure 1) will be included for analysis. Children under 2 years old will be excluded

because they are more vulnerable to secondary bacterial infection, and exploratory

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work indicated that it was very difficult for doctor’s to refuse antibiotics for younger

children in this context. Prescriptions for children diagnosed with pneumonia (where

antibiotic prescription is appropriate) or severe diseases such as cancer, tuberculosis,

HIV/AIDS/immunodeficiency, chronic heart diseases or others who need long-term

antibiotic treatment or as prophylaxis will be excluded.

Intervention

No antibiotic should be used for self-limiting viral URIs, as per national and

international guidelines. The multi-dimensional intervention is aimed at changing

doctors’ prescribing behaviors and educating parents/caregivers to reduce the

irrational use of antibiotics among children with acute URIs. It is designed to fit

within the policy requirements of antibiotics prescribing and routine supervision by

the local health authorities.

The intervention design is informed by the Theoretical Domains Framework (TDF),

an emerging method developed from a wide range of theories relevant to behavior

change. The TDF, which consists of 14 theoretical domains (groups of constructs

from theories of behavior change) has been widely used for exploring influencing

factors and designing interventions37-39

in implementation research. Based on our

exploratory study and systematic review, several theoretical domains from the TDF

were identified as important in antibiotic prescribing, to which relevant behaviour

change techniques, and content of interventions were targeted (Table 1). 40

On the doctors’ side the intervention includes: 1) Operational guidelines. These will

be distributed to township hospital doctors. The guidelines are based on Chinese

antibiotics use guidelines, Integrated Management of Childhood Illness (IMCI)

guidelines, and the National Institute for Health and Care Excellence UK (NICE)

guidelines, which focus on but are not limited to URIs. The operational guidelines

cover the workflow of URI management, methods of diagnosis of URIs and other

common diseases among children, and communication skills between doctors and

patients; 2) Training workshops. All the doctors in the township hospitals are trained

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on the rational use of antibiotics, especially for childhood URIs, using participatory

and interactive lectures, case discussion and question and answer sessions. These two

components address the theoretical domains of knowledge, skills, and beliefs about

capabilities of rational prescribing, using the technique of information provision; 3)

Monthly peer review of rational use of antibiotics. Antibiotics prescriptions are

collected and reviewed by research team at the beginning of each month. The research

team calculates the antibiotic prescription rate (APR) for childhood URIs and feeds it

back to the township hospitals. Peer review of antibiotics use are then conducted

based on the APR feedback in the monthly hospital staff meeting. The project

coordinator in the township hospitals will communicate the results of the peer review

back to the research team. This component addresses the theoretical domain of

behavior regulation among doctors, using the techniques of monitoring and feedback;

and 4) Health education to caregivers. Concise messages are given by doctors to the

caregivers whose children have URIs during the clinical consultations, along with

simple printed educational materials. Examples of the messages are explanations

about antibiotics and rational use of antibiotics for childhood URIs. This component

addresses the theoretical domains of beliefs about consequences (specifically of not

being given antibiotics), knowledge and social influence of antibiotics use among

caregivers/parents, and uses techniques of information giving and persuasive

communication.

On the caregivers’ side, the intervention includes: 1) Health education messages from

doctor and printed educational materials/leaflets (with simple words and pictures),

which are distributed to the caregivers whose children have URIs during the clinical

consultation. They mainly cover explanations about antibiotics, the impacts of

antibiotic resistance, and rational use of antibiotics for childhood URIs; and 2)

Educational videos, which are played on a loop in the waiting areas of township

hospitals (5-8 minutes). The content mainly includes explanations about antibiotics,

the situation of irrational use of antibiotics in China, and the impacts of antibiotic

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resistance (using a local TV show). This component also addresses the theoretical

domains of beliefs about consequences (specifically of not giving antibiotics),

knowledge and social influence of antibiotics use among caregivers/parents, and uses

the technique of information giving.

Usual care

In the control arm doctors will be allowed to continue prescribing antibiotics

according to current national guidelines and existing practices. In these conventional

clinical consultations treatment is provided according to existing knowledge,

antibiotics are given at the individual clinician’s discretion, and no systematic health

education is provided to patients. This is therefore a pragmatic comparator reflecting

typical routine practice, which allows the intervention to be usefully compared to the

existing situation.

Outcomes

The primary outcome is the APR for childhood URIs, and will be measured for each

township hospital based on all prescriptions for URIs in outpatients aged between 2

and 14 years old issued between the start of the intervention’s implementation and

six-month follow-up. Based on these prescriptions the APR is defined as the

proportion of outpatients aged between 2 and 14 years old who have been diagnosed

with a URI and, from that consultation, prescribed at least one antibiotic as a result of

their diagnosis. This primary outcome is selected because it should reflect the

integrated effect of the behavior change of both doctors and patients/caregivers. A

reduction in the APR will be a clinically beneficial outcome demonstrating increased

rational prescribing of antibiotics, as most self-limiting URIs are caused by viral

infection that do not require antibiotics. This measurement is reliable and feasible in

the primary care setting where prescriptions are well preserved either electronically or

in paper files.

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The secondary outcomes are all based on data extracted from the same prescriptions

as described for the primary outcome:

1. The multiple antibiotic prescription rate: the proportion of prescriptions for

childhood URIs that include two or more antibiotics.

2. The broad-spectrum antibiotic prescription rate: the proportion of

prescriptions for childhood URIs that include at least one broad-spectrum

antibiotic.

3. The quinolones prescription rate: the proportion of prescriptions for

childhood URIs that include at least one quinolone.

4. The mean cost of childhood URI prescriptions.

These secondary outcomes relate to other commonly observed practices in routine

primary care that cause great concern for their potential to promote drug-resistance,

while misuse of quinolones may also contribute to the increasing identification of

extensively drug-resistant tuberculosis.41

Sample size

Based on our exploratory study the current APR is approximately 50%, which is

therefore assumed for the usual care arm. We expect our intervention to lead to at

least a 25% relative reduction in the antibiotic prescription rate within township

hospitals, based on a conservative estimate from our systematic review.36

Consequently, to detect a 25% or greater reduction in the APR (i.e. an absolute

reduction to 37.5% APR or less) with 90% power, using two-sided testing at the 5%

significant level, assuming a harmonic mean cluster size of 200 and a between cluster

coefficient of variation of 0.15 (based on exploratory and pilot work), we estimate

that we require 9 township hospitals per arm.42 Allowing for stratified randomization

and a 10% loss of data, due to lost and illegible prescriptions, requires a total of 24

township hospitals. As there are 25 eligible township hospitals within the two

counties it was decided to include all 25.

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Randomization

A total of 25 township hospitals were eligible for the trial, with 14 in Rong County

and 11 in Liujiang County. Randomization was stratified by county to avoid any

imbalances in allocation between counties, given potentially important variation in

outcomes between counties. Within each county randomization was further restricted

to two subsets of all possible allocation ratios. In Rong County randomization was

restricted to those allocations resulting in equal numbers of township hospitals in

each arm, whilst in Liujiang County randomization was restricted to those allocations

resulting in township hospital treatment: control arm allocation ratio of 5:6. This was

chosen to ensure as equal an allocation ratio as possible, whilst minimizing the

logistical cost from treatment arm hospitals. After all 25 hospitals were randomized,

within Rong County 6 hospitals, 3 from each arm, were further randomly selected to

become the internal pilot clusters. The remaining 19 township hospitals (8 in Rong

County and 11 in Liujiang County) will therefore participate in the main trial, along

with the 6 hospitals involved in the internal pilot. Therefore, overall the 25 hospitals

were allocated in a 12:13 treatment: control allocation ratio. Randomization was

conducted by the study statistician (JPH) using a computer program written in R

(version 3.2.0).42 43

Internal pilot process

The internal pilot study aims to assess recruitment rates and the extent to which the

intervention is delivered within township hospitals, as well as contributing outcome

data to the main trial. The six township hospitals in the pilot study will be recruited

and followed-up for three months, and the decision as to whether to continue with the

full trial will then be taken based on two key criteria: 1) sufficient levels of

recruitment (number of prescriptions sufficient to achieve minimum sample size

required); 2) feasibility of implementing the intervention (at least 50% of clinicians

trained and 50% using the guidelines at the end of the three months after the

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intervention). If these criteria are met, the internal pilot hospitals and their outcome

data will then become part of the main trial, and will be followed-up for a further

three months. The remaining 19 hospitals will have been recruited, and if the trial is

proven to be feasible via the pilot they will be enrolled into the study and followed-up

for six months (meaning that data collection in the pilot and main trial hospitals will

finish at different times).

Data collection and management

To evaluate the primary and secondary outcomes two hundred prescriptions for

childhood URIs will be randomly selected in each township hospital during the three

months before the implementation of the intervention to provide baseline data, and

during the 4th to the 6

th months after randomization. Prescription data will be obtained

from electronic records where available, or alternatively photographic copies will be

taken of patients’ paper prescriptions. Data collected from electronic or photographic

records will then be entered into a password-protected SPSS database (version 20.0,

IBM Corp. Armonk, NY.). Information collected will include the township hospital,

the date of the prescription, the patient’s age, symptoms, diagnosis, prescribed

medicines, related treatment, related laboratory tests, treatment payment and

insurance status.

Data analysis

Analysis of outcomes

The statistical analyses are described in full detail in the accompanying statistical

analysis plan (SUPP INFO 1), and are therefore only outlined in brief here. No

interim analyses are planned, and all outcomes will be analysed following data

collection. All analyses will be on the intention-to-treat (ITT) population, defined as

all outpatient-prescriptions issued in township hospitals for URIs in children aged

2-14 years old, regardless of the compliance of township hospitals, doctors and

parents/caregivers to the intervention. Descriptive statistics will be calculated and

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presented, and formal inference will be based on hypothesis testing with statistical

significance assessed at the 5% level.

The crude-effect of the intervention on outcomes will be analysed using methods

appropriate for cRCTs where there are small numbers of clusters per arm.42 For the

primary and secondary outcomes involving proportions, data at the township hospital

level will be used to calculate weighted risk ratios and their 95% confidence intervals

(accounting for between-hospital variance and stratification), and formal hypothesis

testing with stratified t-tests will be conducted. If the data are strongly skewed a

logarithmic transformation will first be applied. The same methods will be used to

analyse the data on the average cost of childhood URI prescriptions, but based on the

weighted mean difference in the outcome between treatment arms.

To adjust for important covariates, including individual and contextual factors, a

two-stage process will be carried out.42 This will involve fitting either logistic or

normal regression models (for the proportion or average cost of prescription outcomes

respectively) to individual-level outcome data with all covariates of interest (including

stratum) included apart from the treatment effect. Township-hospital specific

covariate-adjusted ratio or difference residuals will then be calculated for proportion

or average cost of prescription outcomes respectively. Using the methods described

above the hospital-specific residuals will then be used in place of raw hospital-level

outcome data to calculate covariate-adjusted weighted risk ratios/the weighted mean

difference (as appropriate) and their 95% confidence intervals, and to conduct

stratified t-tests. All data will be analysed using STATA version 12.1 (SE) (STATA

Corporation, College Station, Texas).

Sub-group analyses

Planned sub-group analyses will be conducted on outcomes to determine whether

there is any significant heterogeneity in treatment effects occurring between important

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groups, such as across patients of different genders and ages, and between hospitals of

different sizes. For each outcome the cluster-level residuals described above will be

regressed on stratum, treatment group, the subgroup variable and all their possible

two-way interactions. F-tests will be used to determine whether there are any

significant interactions between treatment group and subgroups.

Process evaluation

A qualitative process evaluation44 will be conducted at six months into the

intervention, in selected clusters from the intervention and control arms (in the control

arm to understand the implementation process of existing guidelines by clinicians, i.e.

usual practice). The process evaluation aims to describe the health system and service

delivery context in which the intervention was delivered; explore whether or not the

intervention is delivered as intended, both at the cluster level (training) and the

individual level (provider delivery); and understand mechanisms of impact both at the

provider level and caregiver level. The methods, which will also be informed by the

TDF,37-39

will include document review (e.g. meeting minutes), observation of

training sessions and consultations, and qualitative interviews.

In each county we will select one control cluster. After three months of

implementation we will review prescription rates in intervention clusters. If all

intervention clusters are performing in a similar way (i.e. very good, medium, poor),

then we will select one intervention cluster from each county. However, if

intervention clusters are performing very differently, then we will need to select two

intervention clusters from each county (high and low performers) to understand

cluster level factors. In each township hospital selected we will interview doctors, the

hospital director and the pharmacist. We will also conduct a focus group discussion

with caregivers. A sampling frame will be developed and participants will be

purposively selected for inclusion from the selected sites.

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Qualitative data will be recorded if the participants agree to use audio-recording. The

audio files will be transcribed as soon as possible, and any audio files recorded by

mobile recording devices will be immediately deleted once they have been

transcribed.

Analysis of process evaluation

Qualitative data will be analysed as soon as possible after it has been collected. The

analysis will feed into subsequent interviews, and if new issues emerge they can be

followed up in subsequent interviews. Data will be audio recorded and transcribed.

Nvivo version 10 (QSR International Pty Ltd) will be used to manage the data. The

data will be analysed using a simple thematic approach.45 Quality of reporting the

qualitative study will be ensured by adhering to the Consolidated criteria for reporting

qualitative studies (COREQ) .46

Discussion

Our study is one of the first trials to address irrational antibiotic prescribing in the

primary care context in China. The study is of great significance given

antibiotic-resistant infections have contributed to high levels of resistance among

children, particularly in countries with less stringent antibiotic prescribing

regulations.7 Our study will contribute to the currently limited number of studies

addressing irrational antibiotic prescribing in the primary care context of rural of

China, and should be more widely applicable to similar contexts. In China most

studies have focused on either clinicians or patients. We therefore aim to test a

comprehensive intervention targeting both clinicians and patients, an approach shown

to have the largest effect29 in rural primary care settings.

The evidence-based and user-friendly guideline on rational antibiotic prescribing is

developed to address the current lack of operational guidelines for primary care

practices. However, simple dissemination of guidelines alone has had limited effects

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on health worker performance,47 48

including in ambulatory care settings.29

Considering the insufficient medical training received by rural primary care doctors

compared to their urban peers in China, 9 we aim to improve their knowledge through

continued professional training in rational antibiotic prescribing. Peer review of

antibiotics prescribing is also planned at monthly hospital staff meetings to monitor

fidelity to the intervention, and enhance the knowledge of doctors. Antibiotics are

culturally accepted in rural China as the first response to self-limiting viral URIs.

Thus, educating the caregivers through primary care doctors is challenging but

essential.49 We have designed an iterative and participatory training process, with an

emphasis on improving the communication and educational skills of primary care

doctors interacting with elders. Our study will be conducted in poor rural areas where

many caregivers are grandparents because many of the young generation have

temporally migrated to cities for employment. We have thus tailored the educational

materials to be more easily understood by people with less education. By improving

caregivers’ knowledge, the intervention is expected to reduce patient demand for

antibiotic prescribing in URIs.

The study fits into the current national priority on antibiotics control in China.

However, major control efforts have currently focused on referral hospitals rather than

the primary care level, especially in rural areas. The study will thus help to shape the

policies and regulations regarding antibiotic use, especially under primary care

settings.13 Multiple interventions have proved effective on improving the rational use

of antibiotics. However, some interventions, such as point-of-care tests, are not

feasible in primary care settings in poor rural areas of China. In this trial, all the

interventions are embedded within the routine primary care management and practice.

Thus, additional work and costs that would otherwise have been added to primary

care will be reduced, enhancing the replicability of the intervention.

Normaliszation Process Theory (NPT)50 51

provides a useful lens for understanding

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the processes that affect the implementation, embedding, and integration of rational

antibiotic prescribing into healthcare systems. However, our main aim for the process

evaluation 44 is to understand the barriers and facilitators which are embedded within

the context, the implementation and mechanisms of impact, and which mechanisms

affect behaviour change outcomes. We also aim to understand how to overcome

implementation challenges and scale-up the intervention. For instance, the uncertain

effect of the zero-price mark-up policy on reducing medicine use may suggest

influences beyond providers and patients, such as those of pharmaceutical companies.

In this study we use the APR as the outcome, rather than other clinical and laboratory

measures such as the positive rate of the extended-spectrum beta-lactamases, because

we want to focus on provider behavior, whereas more complex patient outcomes will

be difficult to interpret in the face of many confounding factors. Trials of reducing

antibiotic prescriptions for acute respiratory infections are not uncommon in

high-income countries.18 21 25 28

Given few relevant interventions exist in

low-to-middle income countries, and different studies have focused on different

populations, comparisons with other studies needs to be cautious. Misdiagnosis (either

over- or under-diagnosis) of URIs may happen, which would bias the APR and could

even have a negative impact on treatment. However, this bias will be minimized as

diagnosis and treatment in both arms is based on Chinese antibiotics use guidelines

and IMCI guidelines.

Outputs will include an operational guideline on the rational use of antibiotics for

URIs among children, and training modules and other materials that may be scaled-up

in Guangxi and other western provinces. These materials also have the potential to be

adapted to other low- and middle-income country contexts. We therefore believe this

trial will greatly contribute to improving the prescribing behavior of doctors in the

rural primary care context in China, and other developing countries.

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The trial has received ethical approval from the Ethics Committees of the University

of Leeds and Guangxi Provincial Centre for Disease Control and Prevention, China.

The results will be disseminated through policy briefs, workshops, peer-reviewed

publications and local and international conferences.

There have been no modifications to the protocol which may impact on the conduct of

the study, potential benefit and safety of the patients, including changes of the

objectives, design, population, sample sizes, procedures, or significant administrative

aspects of the study. Any amendment in the future will seek prior approval from the

Ethics Committees.

No consent form will be provided for prescription review. Guangxi CDC will seek

agreement from each hospital under study. They will explain to them that we will use

the patients’ information only for research purposes and ensure the confidentiality of

the patients. Personal identifying information such as names and national ID would be

deleted before data is input into our research files. For the provider interviews, to

allow for the rural China context, we will allow verbal consent to be given by

providers if requested for interviews, to protect people working in bureaucratic health

systems, and to obtain as much objective information as much. Regarding the

patient/caregiver focus groups, written informed consent will be obtained from each

participant (verbal consent from the illiterate parents/caregivers). Information sheets

will be provided and/or explained for both providers (SUPP INFO 2) and caregivers

(SUPP INFO 3).

For the prescription data, personally identifying information will be deleted before

data is entered into the database, and each prescription will be assigned a unique study

identification number. Physical hard copies of study data materials will be stored

securely in a locked cabinet, separate from the data of other studies. The

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photographed prescriptions will be deleted as soon as possible following information

extraction. For the qualitative data, only the researchers conducting the study will

know the names of participants, and have access to the responses from individual

participants.

Only the principal investigators (XW and ML) will be given access to the cleaned

data sets. Project data sets will be stored electronically by the China Global Health

Research and Development, and all data sets will be password protected.

We will disseminate the main findings to provincial and national CDC and authorities,

our Communicable Disease – Health Service Delivery (COMDIS-HSD) Research

Programme Consortium country partners in South Asia and Africa, and relevant

international stakeholders. We will publish in national and international journals, and

present at national and international conferences.

The protocol adheres to the recommendations provided by the SPIRIT 2013.52 All

items from the World Health Organization Trial Registration Data Set are available in

SUPP INFO 4.

Contributors

All authors made substantive contributions to the trial development and provided final

approval for this manuscript. XW, GZ, JW, HE, RK and YH designed the trial and

related studies. GZ and XW drafted the manuscript. JW, ML, JZ, YH, YH, ZZ, SD,

RK, HE, QS contributed to designing the trial and participated in the pilot study. JPH

contributed to the statistical issues in the study design and wrote the statistical

analysis plan. RK contributed to the design of the process evaluation and qualitative

methods. HE contributed to trial and process evaluation design and critically reviewed

the manuscript. CB, SD and GZ contributed to ethics development. CB, JW and JPH

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critically reviewed the manuscript. XW and ML are co-principal investigators of the

trial.

The trial sponsor is China Global Health Research and Development (Contact name:

Dr. Xiaolin Wei, Address: Room 403 No.1032 Dongmen Bei Road, Shenzhen, China

Tel: (86)755 22250390, Email: [email protected])

Funding

The trial is supported by the Department for International Development of the UK

Government (DFID) via the COMDIS-HSD Research Programme Consortium. This

funding source had no role in the design of this study and will not have any role

during its execution, analyses, interpretation of the data, or decision to submit results.

Competing interests

The authors declare that they have no competing interests.

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Table 1: Multi-dimensional interventions designed to reduce the use of antibiotics among children

Targeted group Theoretical domains Behavior change techniques, modes and content of delivery

Provider side

(doctors)

1. Knowledge

2. Skills

3. Beliefs about capabilities

Techniques: information provision.

Mode 1: operational guidelines.

Content: URI management work flow, methods of diagnosis URI and other

common diseases among children, communication skills between clinicians and

patients.

Mode 2: facilitated training/workshop.

Content: rational antibiotics use especially for childhood URI (using lectures,

case discussion and Q&A (participatory and interactive).

Behavior regulation Techniques: monitoring and feedback

Mode: antibiotics prescribing appraisal

Contents/procedures:

1) Monthly antibiotic prescriptions collected by research team at the

beginning of every month; 2) Feedback sent back to township hospital

after calculating the APR by research team; 3) Antibiotics use appraisal

according to APR feedback in monthly hospital staff meeting; 4) Meeting

memo written down by the township coordinator; 5) Township

coordinator sends the memo to trial manager.

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1. Beliefs about consequences

(care givers)

2. Knowledge (caregivers)

3. Social influence (caregivers)

Techniques: information provision and persuasive communication.

Mode: health education to patient caregivers during clinical consultations.

Content: specific short messages, e.g., definition of antibiotic, rational antibiotic

use for childhood URIs, accompanied by simple printed educational materials.

Consumer side

(parents/caregivers)

1. Beliefs about consequences

(care givers)

2. Knowledge (caregivers)

3. Social influence (caregivers)

Techniques: information provision.

Mode 1: Educational messages from doctors, and educational material/leaflets.

Content: explanation about antibiotics, the impacts of antibiotic resistance and

rational antibiotics use for childhood URIs (using leaflets with simple words and

pictures).

Mode 2: educational videos played at township hospitals (5-8 minutes).

Content: explanation about antibiotics, the situation of irrational use of antibiotics

in China and the impact of antibiotic resistance (using a local TV show)

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a. Eligible subjects include all outpatient prescriptions for children, aged between 2 and 14 years

old, diagnosed with URIs.

b. Intervention package for doctors includes: operational guidelines, training, peer review

meetings, consultation (with educational leaflets); and for parents/caregivers includes:

messages from doctors, educational leaflets and videos.

c. Usual care refers to health care following routine practice at discretion of individual doctors.

d. Baseline data: three months before intervention; outcome data: the last three months of the

intervention.

Figure 1 Trial Flow Chart

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An analysis plan for a pragmatic cluster randomized controlled trial for reducing

irrational antibiotic prescribing among children with upper respiratory infections in

rural China

Introduction

Irrational use of antibiotics, defined by the World Health Organization as antibiotic

prescriptions exceeding 30% of all prescriptions,1 is a serious issue both within China and

internationally. Worldwide, around 50% of medicines are not appropriately prescribed,

dispensed or sold.1 Irrational use of antibiotics not only brings high economic burdens to

health systems, but also increases the risk of antibiotic resistance.1 Acute upper respiratory

infections (URIs) are very common among children, but are usually viral and self-limiting,

with antibiotic treatment being unnecessary.2 However, irrational use of antibiotics for URIs

in children is very prevalent in primary care settings internationally.3

A cross-sectional study in ten provinces in rural Western China showed that antibiotics

accounted for over half of all prescriptions, predominantly provided for URIs, and with

approximately one quarter of those receiving antibiotics being children under ten years old.4

Irrational antibiotic use amongst children is known to contribute to higher childhood

mortality in countries with inadequate health infrastructure.5 Several national policies have

been issued by the Ministry of Health, including the most recent one limiting antibiotic

prescriptions to less than 60% of all prescriptions for inpatients and 20% for outpatients.6

However, no operational details were provided on how to implement the policy, and no

guidelines were provided for the diagnosis and treatment of URIs in children, or related

clinician training. Potentially because of this situation, despite attempts at health sector

reform there has been no significant improvement in the rational use of antibiotics or cost

control in China.7

Commonly reported interventions for improving antibiotic use in URI treatment include

clinical decision support,8-11

clinician communication skills training,12-14

education and

feedback,15

public reporting of antibiotic prescribing rates,16

discussion and monitoring

workshops,17

governance structure change,18

and interventions based on behavioural

economics and social psychology.19

However, a Cochrane review demonstrated that while

multi-faceted interventions targeting both physicians and patients significantly reduced

inappropriate antibiotic use in community settings,20

single interventions with parents failed

to impact on antibiotic prescribing.21-23

Therefore, we developed a multidimensional intervention targeting doctors and patient

caregivers that aimed to reduce the irrational use of antibiotics for treating URIs in children

within China’s rural primary care context (specifically within township hospitals). The

intervention was developed through exploratory work, and its feasibility, acceptance and the

adequate adherence of doctors to the intervention has been confirmed via an internal pilot.

Aims and objectives

This study aims to evaluate the clinical effectiveness of the intervention in realistic primary

care settings in rural China, by determining whether the intervention reduces the amount of

antibiotics prescribed for URIs in child outpatients within township hospitals, compared to

existing prescribing practice.

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Study design

The trial has been designed as a pragmatic, parallel-group, cluster randomised, controlled

trial. The trial will evaluate the superiority of the intervention within township hospitals,

which are therefore the unit of randomization.

Randomization process

In total 25 township hospitals were eligible for the trial, with 14 in Rong County and 11 in

Liujiang County. Randomization was stratified by county to avoid imbalances in allocation

between counties, because of the potential for important variation in outcomes between the

counties. Randomization was further restricted within each county to a subset of all possible

allocation ratios. Within Rong County randomization was restricted to only that subset of

allocations that resulted in equal numbers of township hospitals in each arm, and in Liujiang

County randomization was restricted to only that subset of allocations that resulted in the

allocation of township hospitals to the treatment and control arms in a 5:6 allocation ratio.

This allocation ratio was chosen to ensure that the allocation ratio was as equal as possible

with an odd number of township hospitals, whilst minimizing the logistical costs of the

treatment arm by having the additional hospital allocated to the control arm. After all 25

hospitals were randomized, within Rong County 6 hospitals, 3 from each arm, were further

randomly selected to become the internal pilot clusters. The remaining 19 township hospitals

(8 in Rong County and 11 in Liujiang County) will therefore participate in the main trial,

along with the 6 hospitals involved in the internal pilot. Therefore, overall the 25 hospitals

were allocated to treatment and control arms in a 12:13 allocation ratio. Randomization was

conducted by the study statistician (JPH) using a computer program written in R (version

3.2.0).24 25

Outcome data will be collected from at least 5000 prescriptions (approximately 200 per

hospital) issued for URIs in outpatients aged between 2 and 14 years old during the three

months before the implementation of the intervention to provide baseline data, and during the

4th

to the 6th

month following randomization of hospitals.

Within intervention hospitals all family doctors will receive training to increase their

knowledge on the rational use of antibiotics, and to improve the effectiveness of their

communication skills when interacting with caregivers of children with URIs, facilitating the

education of caregivers on the rational use of antibiotics. Monthly peer review meetings will

also assess doctors’ antibiotic prescribing practices, and reinforce desired behaviours. Printed

and video-based educational materials will also be provided for caregivers in intervention

hospital waiting rooms to improve understanding about the rational use of antibiotics. In

control hospitals none of the intervention components will be implemented, and the only

apparent impact will be via the collection of prescription data.

Blinding is clearly not possible for doctors or caregivers, but there will be blinded evaluation

of all outcomes. A cluster design was chosen due to the difficulty of preventing

contamination of both doctors and caregivers, and the need for hospital-wide participation of

doctors in the peer review meetings, which are a key component of the intervention.

Sample size

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Based on our exploratory study the current APR is approximately 50%, which is therefore

assumed for the usual care arm. We expect our intervention to lead to at least a 25% relative

reduction in the antibiotic prescription rate within township hospitals, based on a

conservative estimate from our systematic review.26

Consequently, to detect a 25% or greater

reduction in the APR (i.e. an absolute reduction to 37.5% APR or less) with 90% power,

using two-sided testing at the 5% significant level, assuming a harmonic mean cluster size of

200 and a between cluster coefficient of variation of 0.15 (based on exploratory and pilot

work), we estimate that we require 9 township hospitals per arm.24

Allowing for stratified

randomization and a 10% loss of data, due to lost and illegible prescriptions, requires a total

of 24 township hospitals. As there are 25 eligible township hospitals within the two counties

it was decided to include all 25.

Outcomes and data

All outcome data will be obtained from the prescriptions collected at baseline and during

follow-up, either in the form of electronic or photographic records of paper copies of

prescriptions. Information collected will include the township hospital, the date of the

prescription, the patient’s age, symptoms, diagnosis, prescribed medicines, related treatment,

related laboratory tests, treatment payment and insurance status.

Primary outcome

The antibiotic prescription rate for childhood URIs. Measured at the township hospital level,

and defined as the proportion of prescriptions for URIs among outpatients aged between 2

and 14 years old that include at least one antibiotic. The antibiotic prescription rate is the

primary outcome because it should reflect the behaviour change of both doctors and

caregivers. Most URIs are caused by viral infection that are self-limiting and do not require

antibiotics, and a reduction in this rate will be a clinically beneficial outcome demonstrating

increased rational prescribing of antibiotics for childhood URIs. This measurement is also

reliable and feasible in the primary care setting because prescriptions are well preserved

either electronically or in paper files.

Secondary outcomes

The childhood URI multiple antibiotic prescription rate: measured at the township

hospital level and defined as the proportion of prescriptions for URIs among

outpatients aged between 2 and 14 years old that include two or more antibiotics;

The childhood URI broad-spectrum antibiotic prescription rate: measured at the

township hospital level and defined as the proportion of prescriptions for URIs among

outpatients aged between 2 and 14 years old that include a broad-spectrum antibiotic;

The childhood URI quinolones prescription rate: measured at the township hospital

level and defined as the proportion of prescriptions for URIs among outpatients aged

between 2 and 14 years old that include a quinolone antibiotic;

Additionally, to understand the medical costs associated with antibiotics prescribing

we will measure the mean cost (in Yuan) at the township hospital level of childhood

URI prescriptions, based on all prescriptions for URIs among outpatients aged

between 2 and 14 years old.

Secondary outcomes were chosen to assess the extent to which the intervention will reduce

other commonly observed practices in routine primary care relating to antibiotic prescribing

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practices for URIs that are particularly likely to increase drug-resistance, and the

intervention’s cost effectiveness.

Missing data

An exploration of the patterns of missingness will be conducted, but it is expected that due to

the most likely and plausible reasons for missing data (lost paper and electronic prescriptions

records, and unreadable paper prescription records), missing data will be missing completely

at random. Therefore, only complete case analyses will be conducted unless there is an

indication that data may be missing at random, in which appropriate methods to deal with

missingness will be employed as sensitivity analyses in addition to the complete case

analyses.

Populations

Township hospital eligibility criteria

All township hospitals from the two selected counties in Guangxi who agree to participate in

the study will be included. However, we will exclude the two township hospitals located in

the two county centres. Compared to all other township hospitals they have much higher staff

capacity and equipment levels, and their proximity to the county general hospital is likely to

result in patient populations with substantially different characteristics.

Patient prescription eligibility criteria

All outpatient prescriptions for children aged between 2 and 14 years old who are diagnosed

with URIs during the study period will be included for analysis. Children under 2 years old

will be excluded because they are more vulnerable to secondary bacterial infection, and

exploratory work indicated that it was very difficult for doctor’s to refuse antibiotics for

younger children in China’s context. Prescriptions for children diagnosed with pneumonia

(where antibiotic prescription is appropriate) or other severe diseases requiring long-term

antibiotic treatment (or as prophylaxis) will also be excluded. Prescriptions for inpatients will

not be collected.

Populations

The intention-to-treat (ITT) population is defined as all outpatient-prescriptions issued for

URIs in children aged 2-14 years old collected from township hospitals, regardless of the

compliance of township hospital doctors and/or caregivers to the intervention. All statistical

analyses of primary and secondary outcomes will be by ITT.

Data handling

Data monitoring

All personally identifying details will be removed from the study database. Data will be

checked weekly for quality and completeness by the study data manager, and any missing

data will be followed-up with township hospitals until received (if electronically available),

confirmed as set aside for later collection by researchers (if paper-based) or confirmed as not

available. Recruitment rates will be monitored on a monthly basis. There is no Data

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Monitoring and Ethics Committee or equivalent associated with the study. Data collected

from electronic or photographic records of prescriptions will be entered into a password-

protected SPSS database (version 20.0, IBM Corp. Armonk, NY.).

Data validation

Prior to analysis the final database will be validated using a STATA program to identify any

anomalous, inconsistent and missing data. This program will check/identify:

Eligibility criteria of prescriptions

Consistency of prescription issue dates relative to the baseline and outcome data

collection periods

Outlying and anomalous (e.g. incorrect format, impossible value) data

Missing data

All anomalous, inconsistent or unexpectedly missing data will be checked against original

paper or photographic prescription records where feasible. Any anomalous or inconsistent

data that can be unambiguously corrected will be, but where any ambiguity cannot be

resolved values will be recorded as missing data.

Data analysis

General calculations

Percentage calculations will exclude any missing prescriptions from the denominators.

Summary statistics such as percentages and means will be rounded to 1 decimal place, or 1

significant figure for numbers less than 1, but standard deviations will be rounded to 2

decimal places, or 2 significant figures for numbers less than 1. Parameter estimates,

including standard errors SEs and 95% confidence intervals (CIs), will be rounded to 2

decimal places, or 2 significant figures for numbers less than 1. All hypothesis testing will be

2-sided and at the 5% significance level. All analyses will be carried out using STATA

Version 12.1 (SE) software, but other packages will be employed if necessary. The primary

and the secondary outcome analyses will be based on the intention-to-treat (ITT) population.

All analyses will be conducted by the study statistician (JPH).

Planned analyses

No interim analyses are planned. Therefore, all outcomes will be analysed after data

collection is completed.

Baseline characteristics

The baseline characteristics of the ITT population (including gender, age, insurance type,

total prescription fee, total number of medicines prescribed; whether or not they were

prescribed an antibiotic, a broad spectrum antibiotic, multiple antibiotics, and which category

of antibiotic(s) they were prescribed; whether the antibiotic was delivered via injection or

orally; and type of diagnosis) and township hospitals (within township hospitals catchment

areas the number of residents, average annual income, number of village clinics and the

number of doctors who can prescribe medicines) will be summarised using frequencies (plus

sample sizes) and means (plus SDs) as appropriate for each treatment group.

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Primary and secondary outcome analyses

The crude and covariate adjusted average effect of the intervention on outcomes will be

analysed using methods appropriate for cRCTs with small numbers of clusters per arm.24

For

the primary outcome an estimate of the overall risk ratio between the intervention and control

arms will be estimated from the weighted average of the stratum-specific risk ratios, with

weights that are inversely proportional to the stratum-specific variances. Stratum-specific risk

ratios will be calculated from the unweighted stratum-specific risks (mean township-hospital-

level outcomes) in each arm. If the within-arm distribution of risk ratios is found to be

strongly skewed for an outcome, a logarithmic transformation will first be applied to the

outcome proportions. Formal testing of the null hypothesis that the overall risk ratios are

equal to 1 will be conducted using stratified t-tests, and 95% confidence intervals will be

adjusted for between-cluster variance and stratification.

Secondary outcomes involving proportions will be analysed using the same methods as the

primary outcome, whilst the average cost of childhood URI prescriptions outcome will be

analysed using similar methods, but with stratum-specific differences between the mean

township-hospital-level outcomes in each arm used in place of stratum-specific risk ratios.

To adjust for potentially important covariates, including baseline values of outcomes, sex,

age and additional important individual and township-hospital level factors two-stage

adjusted analyses will also be conducted. For the primary outcome a logistic regression

model will be fitted to the individual-level data including stratum and the covariates of

interest as fixed effects, but without adjusting for the treatment effect. Covariate-adjusted

ratio residuals will then be calculated from the ratios of cluster-specific observed and

expected values. The covariate-adjusted ratio residuals will then be used in place of cluster-

specific proportions to conduct stratified t-tests and calculate 95% confidence intervals using

the above methods. To analyse the secondary outcomes involving proportions the same

methods will be used as for the primary outcome. To analyse the average cost of childhood

URI prescriptions outcome the same two-stage method will be employed, but using a normal

regression model instead, and with cluster-specific difference residuals, calculated from the

differences between cluster-specific observed and expected values, used in place of stratum-

specific differences in means. Following CONSORT guidelines both unadjusted and adjusted

results will be presented.

For all outcomes within each treatment arm and strata estimates of the between-cluster

coefficient of variation and the intraclass correlation coefficient will also be calculated and

made available to facilitate future trial planning and systematic reviews.

Subgroup analyses

Planned sub-group analyses will be conducted on outcomes to determine whether there is any

significant heterogeneity (or effect modification) in treatment effects occurring between

important groups, such as across patients of different genders and ages, and between hospitals

of different sizes. Cluster-level subgroup analyses will be based on cluster-level covariates

with two groups only, given the limited number of clusters. The methods for unadjusted

cluster-level analyses described above will be used for the cluster-level subgroup analyses,

but applied separately to the two groups of clusters, as determined by the relevant cluster-

level covariate, to obtain estimates of the treatment effect, its 95% confidence interval and

statistical significance within each subgroup. However, if the number of clusters per stratum

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are too few for either of the subgroups then a non-stratified version of these methods will be

used. To estimate the statistical significance of any differences in treatment effect between

subgroups analysis of variance will be used on the cluster-level summary outcome data, with

terms for treatment arm, the relevant subgroup and the interaction between them.24

Individual-level subgroup analyses will be based on computing the difference in outcome

(logged when the outcome effect wanted is a ratio) between subgroups within each cluster,

and then comparing the mean difference in the treatment and control arms. To estimate the

size (and associated 95% confidence intervals) and significance of any interaction between

the treatment effect and subgroups (i.e. effect modification) an unpaired t-test will be

conducted on the cluster-level differences between subgroups.24

References

1. El Mahalli A. WHO/INRUD drug prescribing indicators at primary health care centres in

Eastern province, Saudi Arabia. EMHJ;18(11).

2. Alves Galvão Márcia G, Rocha Crispino Santos Marilene A, Alves da Cunha Antonio JL.

Antibiotics for preventing suppurative complications from undifferentiated acute

respiratory infections in children under five years of age. Cochrane Database of

Systematic Reviews 2014; (2).



?v=1&t=ifqozjug&s=ffa4fb20e6eb6cab84110af79bf87112e990651c.


antibiotic use for acute respiratory tract infections in children: a systematic review and

meta-analysis. PLoS One 2012;7(1):e30334.



5. Ilic K, Jakovljevic E, Skodric-Trifunovic V. Social-economic factors and irrational

antibiotic use as reasons for antibiotic resistance of bacteria causing common

childhood infections in primary healthcare. Eur J Pediatr 2012;171(5):767-77.

6. Xiao Y, Li L. Legislation of clinical antibiotic use in China. Lancet Infectious Diseases

2013;13(3):189-91.

7. Mao W, Vu H, Xie Z, et al. Systematic Review on Irrational Use of Medicines in China

and Vietnam. PloS one 2015;10(3):e0117710.

8. Gonzales R, Anderer T, McCulloch CE, et al. A cluster randomized trial of decision

support strategies for reducing antibiotic use in acute bronchitis. JAMA Intern Med

2013;173(4):267-73.


to promote judicious use of antibiotics for acute respiratory infections in primary care.

Int J Med Inform 2012;81(8):521-6.


decision support tool to improve antibiotic prescribing for acute respiratory infections:

the ABX-TRIP study. J Gen Intern Med 2013;28(6):810-6.

11. Mainous AG, 3rd, Lambourne CA, Nietert PJ. Impact of a clinical decision support

system on antibiotic prescribing for acute respiratory infections in primary care:


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respiratory tract infections in German primary care--the cluster-randomized controlled

CHANGE-2 trial. BMC Fam Pract 2012;13:124.










2011;66(11):2659-66.


respiratory tract infections in primary care: a matched-pair cluster-randomized trial in

China. Health Res Policy Syst 2014;12:61.



Argent Pediatr 2014;112(2):124-31.

18. Liang X, Xia T, Zhang X, et al. Governance structure reform and antibiotics prescription

in community health centres in Shenzhen, China. Fam Pract 2014;31(3):311-8.





2013;13:290.





?v=1&t=ifphjtif&s=aaa533bb3d45fdf3ed3d83bfa608884a95301f66.



2007;119(4):698-706.







25. Team. RDC. R: A Language and Environment for Statistical Computing. . Available

online at http://www.R-project.org/: Vienna, Austria : the R Foundation for Statistical

Computing., 2011.



infections COMDIS Health Service Delivery Research Consortium, China

Programme 2015.

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Reducing irrational antibiotic use among children with upper respiratory

infections (URIs) in Guangxi

Participant Information Sheet (PIS) for township hospital directors/clinical

doctors - In-depth interview

Background to the research study

Overuse of antibiotics is an issue in rural China. Inappropriate use of antibiotics increases the

risk of bacterial resistance, and can lead to difficulty treating patient with serious bacterial

infections.

An intervention was designed to reduce inappropriate antibiotic use in rural Guangxi (for

example, for minor childhood upper respiratory viral infections). The intervention aims to

reduce inappropriate prescribing of antibiotics by doctors, and increase the health knowledge

of parents and caregivers in regards to minor self-limiting childhood viral illnesses. It does

this through the provision of up-to-date guidelines on antibiotics prescribing for doctors,

training, and clinical support activities. In addition, parents and caregivers of children are

given information leaflets, and videos about antibiotics and minor illnesses in childhood are

available to watch in waiting areas.

Who is conducting the research?

The research is led by Global Health Research and Development (GHRD), China. Technical

support is provided by Leeds University, UK.

Why have I been invited to take part in an interview?

The township hospital in which you work has been involved in this intervention study. We

would like to find out your views and experiences.

What am I being asked to do?

You are invited to participate in a short interview with a researcher. Your views are important

to us, and will help our future efforts to improve the current intervention. The interview will

last about 30-40 minutes, and will be audio-recorded. The decision to participate is yours.

Before starting the interview, a researcher will ask for your signed consent/ agreement. If you

change your mind during the interview, we will respect your wish and end the interview.

Your participation is entirely voluntary; you will not receive payment for the interview.

What will happen to the information I give?

All information collected during the interview will be used for research purposes. We will not

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share any information that could identify you outside the research team. All identifying

information will be kept securely locked away by the research team, and a number will be

used instead of your name where required. Any quotes from interviews which are used in

research reports will not contain information that could identify you.

Who has approved the research?

The study has been approved by the Guangxi Centre for Disease Control Ethical Review

Board and the University of Leeds School of Medicine Research Ethics Committee.

Who has funded the research?

This project has been funded by Department for International Development (DFID), as part

of the COMDIS-HSD consortium of the University of Leeds, UK.

What should I do if I have more questions?

Please talk to the researcher who gave you this form if you have any questions. If you have

any further questions about this study, please contact Prof. Wei Xiaolin, the principal

investigator of the project, by phone 0755-22250390 or by Email at [email protected].

Or contact Guangxi CDC Dr. Mei Lin by phone 0771-5300561.

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Consent Form for township hospital directors/clinical doctors – In-depth

interview

The purpose of the interview has been explained to me.

I consent to take part in an interview about my views and experiences as outlined in the

information sheet.

I also consent for the interview to be audio-recorded.

My participation is completely voluntary. I understand that I am free to stop the interview

at any time.

None of my experiences or thoughts will be shared anyone outside of this study unless all

identifying information is removed first.

Participant’s name: ________________ Date ________________

Participant's signature(no need to sign if oral consent is used): ____________

Researcher's name: ________________ Date ________________

Researcher's signature: ____________

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Reducing irrational antibiotic use among children with upper

respiratory infections (URIs) in Guangxi

1

Participant Information Sheet (PIS) for parents/caregivers – Focus

group

Background to the research study

Antibiotics are sometimes used when they are not needed, in rural areas of China. This

causes bacteria to become more resistant to antibiotics, and serious infections are more

difficult for doctors to treat effectively. One way to reduce resistance is to stop using

unnecessary antibiotics for minor illnesses (such as self-limiting viral infections in

children).

An intervention has been designed to reduce unnecessary antibiotic use in rural Guangxi

(for example, for minor childhood upper respiratory viral infections). The intervention

aims to reduce unnecessary antibiotics given by doctors, and educate parents and

caregivers on minor self-limiting childhood viral illnesses. The intervention gives doctors

up-to-date guidelines on antibiotics, training, and support. Parents and caregivers of

children are given information leaflets, and videos about antibiotics and minor illnesses in

childhood are available to watch in waiting areas.

Who is conducting the research?

The research is led by Global Health Research and Development (GHRD), China.

Technical support is provided by Leeds University, UK.

Why have I been invited to take part in an interview?

A researcher has invited you to be part of a focus group discussion because your child was

treated for an upper respiratory infection in the township hospital recently.

What am I being asked to do?

We would like you to join a discussion about patient and caregiver experiences of their

child’s recent hospital visit. The discussion will be in a small group with other parents and

caregivers, and a researcher. Your views are important to us, and will help our efforts to

reduce unnecessary prescribing of antibiotics. The focus group discussion will last about

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2

30-40 minutes, and will be audio-recorded. The decision to participate is yours, and will

not affect the care your child receives in any way. Before starting the focus group, a

researcher will ask for your signed consent/ agreement to participate. If you change your

mind during the focus group, your decision will be respected. Your contribution up to that

point will remain (since it is a part of the audio-recording), but the researcher will

facilitate your exit from the group and from any further discussions. Your participation is

entirely voluntary; you will not receive payment for the being in the focus group.

What will happen to the information I give?

All information collected during the focus group will be used for research purposes, to

improve efforts to stop antibiotic resistance. We will not share any information that could

identify you outside the research team: all identifying information will be kept securely

locked away by the research team, and any quotes from the focus group which are used in

research reports will not contain information that could identify you.

Who has approved the research?

The study has been approved by the Guangxi Centre for Disease Control Ethical Review

Board and the University of Leeds School of Medicine Research Ethics Committee.

Who has paid for the research?

This project has been funded by Department for International Development (DFID), as

part of the COMDIS-HSD consortium of the University of Leeds, UK.

What should I do if I have more questions?

Please talk to the researcher who gave you this form if you have any questions. If you

have any further questions about this study, please contact Prof. Wei Xiaolin, the principal

investigator of the project, by phone 0755-22250390 or by Email at

[email protected]. Or contact Guangxi CDC Dr. Mei Lin by phone 0771-5300561.

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3

Consent Form for parent/ caregiver – Focus group

The purpose of the focus group has been explained to me.

I consent to take part in a focus group about my child’s recent hospital visit.

I consent for the focus group to be audio-recorded.

My participation is completely voluntary. I understand that I am free to leave the

focus group at any time, however my contribution up to that point would remain as

part of the group’s audio-recording.

None of my experiences or thoughts will be shared anyone outside of this study unless

all identifying information is removed first.

Participant’s name: ________________ Date ________________

Participant's signature: ____________

Researcher's name: ________________ Date ________________

Researcher's signature: ____________

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Category Information

Primary registry and

trial identifying number

ISRCTN14340536

Date of registration in

primary registry

23 June, 2015

Secondary identifying

numbers

N/A

Source(s) of monetary

or material support

Department for International Development of the UK Government

Primary sponsor China Global Health Research and Development

Secondary sponsor(s) N/A

Contact for public

queries

Dr. Xiaolin Wei, MD, MPH,PHD [[email protected]]

Contact for scientific

queries

Dr. Xiaolin Wei, MD, MPH,PHD [[email protected]]

China Global Health Research and Development, Shenzhen, China

Public title Reducing irrational antibiotic prescribing among children with upper respiratory infections in rural China

Scientific title A pragmatic cluster randomized controlled trial for reducing irrational antibiotic prescribing among children

with upper respiratory infections in rural China

Countries of recruitment China

Health condition(s) or

problem(s) studied

Antibiotic treatment, Upper respiratory infections

Intervention(s) Operational guidelines

Systematic training

Peer review of antibiotic prescribing

Health education to patient caregivers with printed educational materials and educational videos provided

Key inclusion and

exclusion criteria

Ages eligible for study: 2-14 years

Sexes eligible for study: both

Accepts healthy volunteers: no

Inclusion criteria: All outpatient prescriptions for children aged between 2 and 14 years old, diagnosed with

URIs during the baseline and intervention data collection period will be included for analysis.

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Category Information

Exclusion criteria: Prescriptions for children diagnosed with pneumonia or severe diseases such as cancer,

tuberculosis, HIV/AIDS/immunodeficiency, chronic heart diseases or others who need long term antibiotic

treatment or as prophylaxis

Study type Interventional

Allocation: randomized intervention model. Parallel assignment masking: blinded outcome evaluation, but

un-blinded treatment.

Primary purpose: prevention

Date of first enrolment June 2015

Target sample size 5000

Recruitment status Completed

Primary outcome(s) Antibiotic prescription rate for childhood URIs

Key secondary

outcomes

Childhood URI prescription rate for multiple antibiotics, broad-spectrum antibiotics and quinolones; mean

cost of childhood URI prescriptions

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SPIRIT 2013 Checklist: Recommended items to address in a clinical trial protocol and related documents*

Section/item Item No

Description Addressed on page number

Administrative information

Title 1 Descriptive title identifying the study design, population, interventions, and, if applicable, trial

acronym

Page 1

Trial registration 2a Trial identifier and registry name. If not yet registered, name of intended registry Page 2

2b All items from the World Health Organization Trial Registration Data Set SUPP INFO 4____________

Protocol version 3 Date and version identifier Page 1____________

Funding 4 Sources and types of financial, material, and other support Page 21_____________

Roles and

responsibilities

5a Names, affiliations, and roles of protocol contributors Page 1 & 20____________

5b Name and contact information for the trial sponsor Page 21____________

5c Role of study sponsor and funders, if any, in study design; collection, management, analysis,

and interpretation of data; writing of the report; and the decision to submit the report for

publication, including whether they will have ultimate authority over any of these activities

Page 21_____________

5d Composition, roles, and responsibilities of the coordinating centre, steering committee,

endpoint adjudication committee, data management team, and other individuals or groups

overseeing the trial, if applicable (see Item 21a for data monitoring committee)

Page 6_____________

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Introduction

Background and

rationale

6a Description of research question and justification for undertaking the trial, including summary

of relevant studies (published and unpublished) examining benefits and harms for each

intervention

Page 4-6_____________

6b Explanation for choice of comparators Page 10

Objectives 7 Specific objectives or hypotheses Page 5_____________

Trial design 8 Description of trial design including type of trial (eg, parallel group, crossover, factorial, single

group), allocation ratio, and framework (eg, superiority, equivalence, noninferiority,

exploratory)

Page 6_____________

Methods: Participants, interventions, and outcomes

Study setting 9 Description of study settings (eg, community clinic, academic hospital) and list of countries

where data will be collected. Reference to where list of study sites can be obtained

Page 6-7____________

Eligibility criteria 10 Inclusion and exclusion criteria for participants. If applicable, eligibility criteria for study centres

and individuals who will perform the interventions (eg, surgeons, psychotherapists). How are

patients recruited, or self-selected?

Page 7____________

Interventions 11a Interventions for each group with sufficient detail to allow replication, including how and when

they will be administered

Page 8-10____________

11b Criteria for discontinuing or modifying allocated interventions for a given trial participant (eg,

drug dose change in response to harms, participant request, or improving/worsening disease)

N/A

11c Strategies to improve adherence to intervention protocols, and any procedures for monitoring

adherence (eg, drug tablet return, laboratory tests)

Page 8-10____________

11d Relevant concomitant care and interventions that are permitted or prohibited during the trial N/A

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Outcomes 12 Primary, secondary, and other outcomes, including the specific measurement variable (eg,

systolic blood pressure), analysis metric (eg, change from baseline, final value, time to event),

method of aggregation (eg, median, proportion), and time point for each outcome. Explanation

of the clinical relevance of chosen efficacy and harm outcomes is strongly recommended

Page 10-11____________

Participant timeline 13 Time schedule of enrolment, interventions (including any run-ins and washouts), assessments,

and visits for participants. A schematic diagram is highly recommended (see Figure)

Fig 1____________

Sample size 14 Estimated number of participants needed to achieve study objectives and how it was

determined, including clinical and statistical assumptions supporting any sample size

calculations

Page 11_____________

Recruitment 15 Strategies for achieving adequate participant enrolment to reach target sample size N/A as data come from prescriptions, so no

enrolment._____________

Methods: Assignment of interventions (for controlled trials)

Allocation:

Sequence

generation

16a Method of generating the allocation sequence (eg, computer-generated random numbers), and

list of any factors for stratification. To reduce predictability of a random sequence, details of

any planned restriction (eg, blocking) should be provided in a separate document that is

unavailable to those who enrol participants or assign interventions

Page 11-12_____________

Allocation

concealment

mechanism

16b Mechanism of implementing the allocation sequence (eg, central telephone; sequentially

numbered, opaque, sealed envelopes), describing any steps to conceal the sequence until

interventions are assigned

N/A

Implementation 16c Who will generate the allocation sequence, who will enrol participants, and who will assign

participants to interventions

Page 12 (but note as a cRCT there is no

enrolment/participant assignment).

Blinding (masking) 17a Who will be blinded after assignment to interventions (eg, trial participants, care providers,

outcome assessors, data analysts), and how

Page 6_____________

17b If blinded, circumstances under which unblinding is permissible, and procedure for revealing a

participant’s allocated intervention during the trial

N/A

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Methods: Data collection, management, and analysis

Data collection

methods

18a Plans for assessment and collection of outcome, baseline, and other trial data, including any

related processes to promote data quality (eg, duplicate measurements, training of assessors)

and a description of study instruments (eg, questionnaires, laboratory tests) along with their

reliability and validity, if known. Reference to where data collection forms can be found, if not

in the protocol

Page 12-16_____________

18b Plans to promote participant retention and complete follow-up, including list of any outcome

data to be collected for participants who discontinue or deviate from intervention protocols

NA_____________

Data management 19 Plans for data entry, coding, security, and storage, including any related processes to promote

data quality (eg, double data entry; range checks for data values). Reference to where details

of data management procedures can be found, if not in the protocol

Page 12-13_____________

Statistical methods 20a Statistical methods for analysing primary and secondary outcomes. Reference to where other

details of the statistical analysis plan can be found, if not in the protocol

Page 13-14 & accompanying statistical

analysis plan( SUPP INFO 1)________

20b Methods for any additional analyses (eg, subgroup and adjusted analyses) Page 13-14 & accompanying statistical

analysis plan( SUPP INFO 1)________

20c Definition of analysis population relating to protocol non-adherence (eg, as randomised

analysis), and any statistical methods to handle missing data (eg, multiple imputation)

Page 13-14 & accompanying statistical

analysis plan( SUPP INFO

1)____________

Methods: Monitoring

Data monitoring 21a Composition of data monitoring committee (DMC); summary of its role and reporting structure;

statement of whether it is independent from the sponsor and competing interests; and

reference to where further details about its charter can be found, if not in the protocol.

Alternatively, an explanation of why a DMC is not needed

Page 6

21b Description of any interim analyses and stopping guidelines, including who will have access to

these interim results and make the final decision to terminate the trial

No interim analyses._____________

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Harms 22 Plans for collecting, assessing, reporting, and managing solicited and spontaneously reported

adverse events and other unintended effects of trial interventions or trial conduct

N/A

Auditing 23 Frequency and procedures for auditing trial conduct, if any, and whether the process will be

independent from investigators and the sponsor

N/A, but see p12 for details of internal pilot

process involving thresholds for start of

main trial_____________


Research ethics

approval

24 Plans for seeking research ethics committee/institutional review board (REC/IRB) approval Page 20

Protocol

amendments

25 Plans for communicating important protocol modifications (eg, changes to eligibility criteria,

outcomes, analyses) to relevant parties (eg, investigators, REC/IRBs, trial participants, trial

registries, journals, regulators)

Page 19-20

Consent or assent 26a Who will obtain informed consent or assent from potential trial participants or authorised

surrogates, and how (see Item 32)

Page 19-20

26b Additional consent provisions for collection and use of participant data and biological

specimens in ancillary studies, if applicable

N/A

Confidentiality 27 How personal information about potential and enrolled participants will be collected, shared,

and maintained in order to protect confidentiality before, during, and after the trial

Page 19-20____________

Declaration of

interests

28 Financial and other competing interests for principal investigators for the overall trial and each

study site

Page 21_____________

Access to data 29 Statement of who will have access to the final trial dataset, and disclosure of contractual

agreements that limit such access for investigators

Page 20___________

Ancillary and post-

trial care

30 Provisions, if any, for ancillary and post-trial care, and for compensation to those who suffer

harm from trial participation

N/A

Dissemination policy 31a Plans for investigators and sponsor to communicate trial results to participants, healthcare

professionals, the public, and other relevant groups (eg, via publication, reporting in results

databases, or other data sharing arrangements), including any publication restrictions

Page 20_____________

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31b Authorship eligibility guidelines and any intended use of professional writers N/A____________

31c Plans, if any, for granting public access to the full protocol, participant-level dataset, and

statistical code

N/A

Appendices

Informed consent

materials

32 Model consent form and other related documentation given to participants and authorised

surrogates

SUPP INFO 2 AND 3

Biological

specimens

33 Plans for collection, laboratory evaluation, and storage of biological specimens for genetic or

molecular analysis in the current trial and for future use in ancillary studies, if applicable

N/A

*It is strongly recommended that this checklist be read in conjunction with the SPIRIT 2013 Explanation & Elaboration for important clarification on the items.

Amendments to the protocol should be tracked and dated. The SPIRIT checklist is copyrighted by the SPIRIT Group under the Creative Commons

“Attribution-NonCommercial-NoDerivs 3.0 Unported” license.

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Documents

BMJ Open · acute upper respiratory infections in rural primary care settings in China, through changing doctors’ prescribing behaviors and educating parents/caregivers. Methods