Effect of a computer network-based feedback program on antibiotic prescription rates of primary care physicians: A cluster randomized crossover-controlled trial

Mailed feedback to primary care physicians on antibiotic prescribing for patients aged 65 years and older: pragmatic, factorial randomised controlled trial

OBJECTIVES

To evaluate whether providing family physicians with feedback on their antibiotic prescribing compared with that of their peers reduces antibiotic prescriptions. To also identify effects on antibiotic prescribing from case-mix adjusted feedback reports and messages emphasising antibiotic associated harms.

DESIGN

Pragmatic, factorial randomised controlled trial.

SETTING

Primary care physicians in Ontario, Canada PARTICIPANTS: All primary care physicians were randomly assigned a group if they were eligible and actively prescribing antibiotics to patients 65 years or older. Physicians were excluded if had already volunteered to receive antibiotic prescribing feedback from another agency, or had opted out of the trial.

INTERVENTION

A letter was mailed in January 2022 to physicians with peer comparison antibiotic prescribing feedback compared with the control group who did not receive a letter (4:1 allocation). The intervention group was further randomised in a 2x2 factorial trial to evaluate case-mix adjusted versus unadjusted comparators, and emphasis, or not, on harms of antibiotics.

MAIN OUTCOME MEASURES

Antibiotic prescribing rate per 1000 patient visits for patients 65 years or older six months after intervention. Analysis was in the modified intention-to-treat population using Poisson regression.

RESULTS

5046 physicians were included and analysed: 1005 in control group and 4041 in intervention group (1016 case-mix adjusted data and harms messaging, 1006 with case-mix adjusted data and no harms messaging, 1006 unadjusted data and harms messaging, and 1013 unadjusted data and no harms messaging). At six months, mean antibiotic prescribing rate was 59.4 (standard deviation 42.0) in the control group and 56.0 (39.2) in the intervention group (relative rate 0.95 (95% confidence interval 0.94 to 0.96). Unnecessary antibiotic prescribing (0.89 (0.86 to 0.92)), prolonged duration prescriptions defined as more than seven days (0.85 (0.83 to 0.87)), and broad spectrum prescribing (0.94 (0.92 to 0.95)) were also significantly lower in the intervention group compared with the control group. Results were consistent at 12 months post intervention. No significant effect was seen for including emphasis on harms messaging. A small increase in antibiotic prescribing with case-mix adjusted reports was noted (1.01 (1.00 to 1.03)).

CONCLUSIONS

Peer comparison audit and feedback letters significantly reduced overall antibiotic prescribing with no benefit of case-mix adjustment or harms messaging. Antibiotic prescribing audit and feedback is a scalable and effective intervention and should be a routine quality improvement initiative in primary care.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04594200.

Feedback Intervention for the Control of Glucocorticoid Prescription in Primary Care Institutions: A Cluster Randomized Cross-Over Controlled Trial in Southwest China

Purpose

The purpose of this study is to assess the effect of glucocorticoid prescription feedback intervention in complex primary care institutions for regulating its inappropriate use.

Design Setting and Interventions

A six-month cluster randomized cross-over controlled trial was conducted in primary care institutions. A total of 347 physicians from 69 participating institutions were randomly allocated to either group A or group B. Both groups were given feedback interventions or serve as control. The feedback intervention comprised two components: a real-time pop-up warning of inappropriate glucocorticoid prescriptions based on the Hospital Information System and a high-proportion prescription feedback intervention warning system.

Outcome Measures

The primary outcome measure was the 10-day inappropriate glucocorticoid prescription rate, while the 10-day glucocorticoid prescription rate served as secondary outcome measure.

Results

At baseline, the 10-day inappropriate glucocorticoid prescription rates were 66.63% and 66.57% in group A and group B, respectively, showing no significant difference (p = 0.140). Following the intervention, group A exhibited a significant reduction in 10-day inappropriate glucocorticoid prescription rate at the crossing point by 13.69% (p < 0.001). In contrast, group B, which served as the control group, experienced an increase of 5.93% (p = 0.037) at the same crossover point. After the crossover point, there was a decrease in 10-day inappropriate glucocorticoid prescription rate for both groups. Group B as the intervention group demonstrated a reduction of 28.22% compared to the crossing point (p < 0.001), whereas group A showed a decrease of 12.20% (p = 0.339). The characteristics of physicians did not significantly influence the inappropriate glucocorticoid prescription rate.

Conclusion

The real-time pop-up warning of inappropriate glucocorticoid prescriptions based on the Hospital Information System and high-proportion prescription feedback intervention warning system can effectively regulate the inappropriate glucocorticoid prescribing behavior of physicians.

Trial Registration

ISRCTN11747547.

Appropriate use of antibiotics for acute respiratory infections at primary healthcare facilities in China: a nationwide cross-sectional study from 2017 to 2019

Background

The appropriateness of antibiotic use for acute respiratory infections (ARIs) in Chinese primary healthcare facilities (PHFs) remained uncertain. We aimed to evaluate to what degree antibiotic prescribing for ARIs were aligned with guideline recommendations in primary settings across China.

Methods

We collected outpatient prescriptions from 262 Chinese PHFs in 27 cities of six provinces between 2017 and 2019. The appropriate antibiotic prescribing was defined as prescribing antibiotic classes that were recommended by Chinese clinical guidelines, if patients were prescribed antibiotics. We evaluated the magnitude of antibiotics prescribed for acute upper respiratory infections (AURIs), acute bronchitis, and community-acquired pneumonia (CAP) and their appropriateness.

Findings

Overall, 55.1% (87,684/159,150), 66.8% (30,836/46,153), and 68.5% (4615/6733) of outpatients with AURIs, acute bronchitis, and CAP treated at PHFs in China were prescribed with antibiotics. Of all antibiotic prescriptions, only 20.0% (17,542/87,684), 18.6% (5724/30,836) and 69.6% (3211/4615) used antibiotic classes that were recommended by the guidelines for AURIs, acute bronchitis, and CAP, respectively. Patients residing in the Chinese central region (17.0%, 15.4%, 69.3% for AURIs, acute bronchitis, and CAP, respectively) were less likely to be prescribed with antibiotics that were appropriately selected.

Interpretation

Unnecessary antibiotics were widely prescribed for patients with AURIs or acute bronchitis and most patients with ARIs did not receive guideline-recommended antibiotic classes in Chinese PHFs. Interventions to promote evidence-based treatment and the appropriate use of antibiotics are urgently needed at the primary level across China.

Funding

This work was supported by the National Natural Science Foundation of China [grant number 72074007, 81973294].

Trends and Patterns of Antibiotic Prescriptions in Primary Care Institutions in Southwest China, 2017-2022

Purpose

To explore the prescription patterns and usage trends of antibiotics within primary care institutions located in underdeveloped regions of China from 2017 to 2022.

Methods

A retrospective analysis of antibiotic prescriptions was conducted from 25 primary care institutions in Guizhou Province during the period of 2017-2022. Antibiotic prescriptions were categorized into appropriate and inappropriate use. Appropriate use is further categorized into preferred medication, and antibiotics can be used or substituted. Inappropriate use is further categorized into unnecessary use, incorrect spectrum of antibiotics and combined use of antibiotics. Factors associated with inappropriate use were investigated using generalized estimation equations. Holt-Winters and SARIMA models were employed to predict the number of inappropriate antibiotic prescriptions as the alternative model.

Results

A total of 941,924 prescriptions were included, revealing a decreasing trend in both the number and inappropriate rates of antibiotic prescriptions from 2017 to 2022. Diseases of the respiratory system (70.66%) was the most frequent target of antibiotic use, with acute upper respiratory infections of multiple and unspecified sites representing 52.04% of these cases. The most commonly used antibiotics were penicillins (64.44%). Among all prescriptions, inappropriate antibiotic prescriptions reached 66.19%. Physicians aged over 35, holding the title of associate chief physician and possessing more than 11 years of experience were more likely to prescribe antibiotics inappropriately. The phenomenon of inappropriate antibiotic use was commoner among children aged five or younger. By comparing model parameters, it was determined that the SARIMA model outperforms the Holt-Winters model in predicting the number of inappropriate antibiotic prescriptions among primary care institutions.

Conclusion

The number and inappropriate rates of antibiotic prescriptions in southwest China exhibited a downward trend from 2017 to 2022, but inappropriate prescription remains a serious problem in primary care institutions. Therefore, future efforts should focus on strengthening physician education, training, and clinical practice. Additionally, physicians' awareness of common misconceptions about inappropriate antibiotic use must be improved, and the prescribing behavior of physicians who fulfill patients' expectations by prescribing antibiotics needs to be modified.

Effects of a feedback intervention on antibiotic prescription control in primary care institutions based on a Health Information System: a cluster randomized cross-over controlled trial

OBJECTIVES

Overuse and misuse of antibiotics are major factors in the development of antibiotic resistance in primary care institutions of rural China. In this study, the effectiveness of a Health Information System-based, automatic, and confidential antibiotic feedback intervention was evaluated.

METHODS

A randomized, cross-over, cluster-controlled trial was conducted in primary care institutions. All institutions were randomly divided into two groups and given either a three-month intervention followed by a three-month period without any intervention or vice versa. The intervention consisted of three feedback measures: a real-time pop-up warning message of inappropriate antibiotic prescriptions on the prescribing physician's computer screen, a 10-day antibiotic prescription summary, and distribution of educational manuals. The primary outcome was the 10-day inappropriate antibiotic prescription rate.

RESULTS

There were no significant differences in inappropriate antibiotic prescription rates (69.1% vs. 72.0%) between two groups at baseline (P = 0.072). After three months (cross-over point), inappropriate antibiotic prescription rates decreased significantly faster in group A (12.3%, P < 0.001) compared to group B (4.4%, P < 0.001). At the end point, the inappropriate antibiotic prescription rates decreased in group B (15.1%, P < 0.001) while the rates increased in group A (7.2%, P < 0.001). The characteristics of physicians did not significantly affect the rate of antibiotic or inappropriate antibiotic prescription rates.

CONCLUSION

A Health Information System-based, real-time pop-up warnings, a 10-day prescription summary, and the distribution of educational manuals, can effectively reduce the rates of antibiotic and inappropriate antibiotic prescriptions.

Association Between Antimicrobial Stewardship Programs and Antibiotic Use Globally: A Systematic Review and Meta-Analysis

IMPORTANCE

Antimicrobial resistance continues to spread rapidly at a global scale. Little evidence exists on the association of antimicrobial stewardship programs (ASPs) with the consumption of antibiotics across health care and income settings.

OBJECTIVE

To synthesize current evidence regarding the association between antimicrobial stewardship programs and the consumption of antibiotics globally.

DATA SOURCES

PubMed, Web of Science, and Scopus databases were searched from August 1, 2010, to Aug 1, 2020. Additional studies from the bibliography sections of previous systematic reviews were included.

STUDY SELECTION

Original studies of the association of ASPs with antimicrobial consumption across health care and income settings. Animal and environmental studies were excluded.

DATA EXTRACTION AND SYNTHESIS

Following the Preferred Reporting Items in Systematic Reviews and Meta-Analyses guideline, the pooled association of targeted ASPs with antimicrobial consumption was measured using multilevel random-effects models. The Effective Public Health Practice Project quality assessment tool was used to assess study quality.

MAIN OUTCOMES AND MEASURES

The main outcome measures were proportion of patients receiving an antibiotic prescription and defined daily doses per 100 patient-days.

RESULTS

Overall, 52 studies (with 1 794 889 participants) measured the association between ASPs and antimicrobial consumption and were included, with 40 studies conducted in high-income countries and 12 in low- and middle-income countries (LMICs). ASPs were associated with a 10% (95% CI, 4%-15%) reduction in antibiotic prescriptions and a 28% reduction in antibiotic consumption (rate ratio, 0.72; 95% CI, 0.56-0.92). ASPs were also associated with a 21% (95% CI, 5%-36%) reduction in antibiotic consumption in pediatric hospitals and a 28% reduction in World Health Organization watch groups antibiotics (rate ratio, 0.72; 95% CI, 0.56-0.92).

CONCLUSIONS AND RELEVANCE

In this systematic review and meta-analysis, ASPs appeared to be effective in reducing antibiotic consumption in both hospital and nonhospital settings. Impact assessment of ASPs in resource-limited settings remains scarce; further research is needed on how to best achieve reductions in antibiotic use in LMICs.

Nudge interventions to reduce unnecessary antibiotic prescribing in primary care: a systematic review

OBJECTIVES

Antibiotic prescribing in primary care contributes significantly to antibiotic overuse. Nudge interventions alter the decision-making environment to achieve behaviour change without restricting options. Our objectives were to conduct a systematic review to describe the types of nudge interventions used to reduce unnecessary antibiotic prescribing in primary care, their key features, and their effects on antibiotic prescribing overall.

METHODS

Medline, Embase and grey literature were searched for randomised trials or regression discontinuity studies in April 2021. Risk of bias was assessed independently by two researchers using the Cochrane Effective Practice and Organisation of Care group's tool. Results were synthesised to report the percentage of studies demonstrating a reduction in overall antibiotic prescribing for different types of nudges. Effects of social norm nudges were examined for features that may enhance effectiveness.

RESULTS

Nineteen studies were included, testing 23 nudge interventions. Four studies were rated as having a high risk of bias, nine as moderate risk of bias and six as at low risk. Overall, 78.3% (n=18, 95% CI 58.1 to 90.3) of the nudges evaluated resulted in a reduction in overall antibiotic prescribing. Social norm feedback was the most frequently applied nudge (n=17), with 76.5% (n=13; 95% CI 52.7 to 90.4) of these studies reporting a reduction. Other nudges applied were changing option consequences (n=3; with 2 reporting a reduction), providing reminders (n=2; 2 reporting a reduction) and facilitating commitment (n=1; reporting a reduction). Successful social norm nudges typically either included an injunctive norm, compared prescribing to physicians with the lowest prescribers or targeted high prescribers.

CONCLUSIONS

Nudge interventions are effective for improving antibiotic prescribing in primary care. Expanding the use of nudge interventions beyond social norm nudges could reap further improvements in antibiotic prescribing practices. Policy-makers and managers need to be mindful of how social norm nudges are implemented to enhance intervention effects.

The Effectiveness of Interactive Dashboards to Optimise Antibiotic Prescribing in Primary Care: A Systematic Review

Governments and healthcare organisations collect data on antibiotic prescribing (AP) for surveillance. This data can support tools for visualisations and feedback to GPs using dashboards that may prompt a change in prescribing behaviour. The objective of this systematic review was to assess the effectiveness of interactive dashboards to optimise AP in primary care. Six electronic databases were searched for relevant studies up to August 2022. A narrative synthesis of findings was conducted to evaluate the intervention processes and results. Two independent reviewers assessed the relevance, risk of bias and quality of the evidence. A total of ten studies were included (eight RCTs and two non-RCTs). Overall, seven studies showed a slight reduction in AP. However, this reduction in AP when offering a dashboard may not in itself result in reductions but only when combined with educational components, public commitment or behavioural strategies. Only one study recorded dashboard engagement and showed a difference of 10% (95% CI 5% to 15%) between intervention and control. None of the studies reported on the development, pilot or implementation of dashboards or the involvement of stakeholders in design and testing. Interactive dashboards may reduce AP in primary care but most likely only when combined with other educational or behavioural intervention strategies.

Effects of social norm feedback on antibiotic prescribing and its characteristics in behaviour change techniques: a mixed-methods systematic review

Low-cost and low-barrier antibiotic stewardship strategies are urgently needed to deal with the widespread problem of antibiotic resistance. Social norm feedback could be a promising strategy. In this mixed-methods systematic review (PROSPERO: CRD42022361039), we aimed to identify the key behaviour change techniques used in social norm feedback for antibiotic stewardship and assess their effectiveness in reducing antibiotic prescribing. We searched PubMed, Embase, Web of Science, and Scopus for peer-reviewed studies published between Jan 1, 2000, and Jan 20, 2022. 3547 studies were screened, of which 23 studies reporting the effects of social norm feedback interventions on antibiotic prescribing met the inclusion criteria. 19 behaviour change techniques were tested in the included studies. The meta-analyses showed that social norm feedback is an effective strategy for reducing antibiotic prescribing, with an overall rate difference of 4% (p<0·0001). The behaviour change technique with the highest effective ratio (ER=13) was information about health consequences, followed by instruction on how to perform the behaviour (ER=9) and adding objects to the environment (ER=9). Social norm feedback is a promising strategy to reduce antibiotic prescribing, and can be incorporated into the clinical decision-making support system.

Effectiveness of clinical dashboards as audit and feedback or clinical decision support tools on medication use and test ordering: a systematic review of randomized controlled trials

BACKGROUND

Clinical dashboards used as audit and feedback (A&F) or clinical decision support systems (CDSS) are increasingly adopted in healthcare. However, their effectiveness in changing the behavior of clinicians or patients is still unclear. This systematic review aims to investigate the effectiveness of clinical dashboards used as CDSS or A&F tools (as a standalone intervention or part of a multifaceted intervention) in primary care or hospital settings on medication prescription/adherence and test ordering.

METHODS

Seven major databases were searched for relevant studies, from inception to August 2021. Two authors independently extracted data, assessed the risk of bias using the Cochrane RoB II scale, and evaluated the certainty of evidence using GRADE. Data on trial characteristics and intervention effect sizes were extracted. A narrative synthesis was performed to summarize the findings of the included trials.

RESULTS

Eleven randomized trials were included. Eight trials evaluated clinical dashboards as standalone interventions and provided conflicting evidence on changes in antibiotic prescribing and no effects on statin prescribing compared to usual care. Dashboards increased medication adherence in patients with inflammatory arthritis but not in kidney transplant recipients. Three trials investigated dashboards as part of multicomponent interventions revealing decreased use of opioids for low back pain, increased proportion of patients receiving cardiovascular risk screening, and reduced antibiotic prescribing for upper respiratory tract infections.

CONCLUSION

There is limited evidence that dashboards integrated into electronic medical record systems and used as feedback or decision support tools may be associated with improvements in medication use and test ordering.

Changing antibiotic prescribing practices in outpatient primary care settings in China: Study protocol for a health information system-based cluster-randomised crossover controlled trial

Background

The overuse and abuse of antibiotics is a major risk factor for antibiotic resistance in primary care settings of China. In this study, the effectiveness of an automatically-presented, privacy-protecting, computer information technology (IT)-based antibiotic feedback intervention will be evaluated to determine whether it can reduce antibiotic prescribing rates and unreasonable prescribing behaviours.

Methods

We will pilot and develop a cluster-randomised, open controlled, crossover, superiority trial. A total of 320 outpatient physicians in 6 counties of Guizhou province who met the standard will be randomly divided into intervention group and control group with a primary care hospital being the unit of cluster allocation. In the intervention group, the three components of the feedback intervention included: 1. Artificial intelligence (AI)-based real-time warnings of improper antibiotic use; 2. Pop-up windows of antibiotic prescription rate ranking; 3. Distribution of educational manuals. In the control group, no form of intervention will be provided. The trial will last for 6 months and will be divided into two phases of three months each. The two groups will crossover after 3 months. The primary outcome is the 10-day antibiotic prescription rate of physicians. The secondary outcome is the rational use of antibiotic prescriptions. The acceptability and feasibility of this feedback intervention study will be evaluated using both qualitative and quantitative assessment methods.

Discussion

This study will overcome limitations of our previous study, which only focused on reducing antibiotic prescription rates. AI techniques and an educational intervention will be used in this study to effectively reduce antibiotic prescription rates and antibiotic irregularities. This study will also provide new ideas and approaches for further research in this area.

Trial registration

ISRCTN, ID: ISRCTN13817256. Registered on 11 January 2020.