Behavioral Nudges to Improve Audit and Feedback Report Opening among Antibiotic Prescribers: A Randomized Controlled Trial

Derivation of a risk-adjusted model to predict antibiotic prescribing among hospitalists in an academic healthcare network

Background

Among inpatients, peer-comparison of prescribing metrics is challenging due to variation in patient-mix and prescribing by multiple providers daily. We established risk-adjusted provider-specific antibiotic prescribing metrics to allow peer-comparisons among hospitalists.

Methods

Using clinical and billing data from inpatient encounters discharged from the Hospital Medicine Service between January 2020 through June 2021 at four acute care hospitals, we calculated bimonthly (every two months) days of therapy (DOT) for antibiotics attributed to specific providers based on patient billing dates. Ten patient-mix characteristics, including demographics, infectious disease diagnoses, and noninfectious comorbidities were considered as potential predictors of antibiotic prescribing. Using linear mixed models, we identified risk-adjusted models predicting the prescribing of three antibiotic groups: broad spectrum hospital-onset (BSHO), broad-spectrum community-acquired (BSCA), and anti-methicillin-resistant Staphylococcus aureus (Anti-MRSA) antibiotics. Provider-specific observed-to-expected ratios (OERs) were calculated to describe provider-level antibiotic prescribing trends over time.

Results

Predictors of antibiotic prescribing varied for the three antibiotic groups across the four hospitals, commonly selected predictors included sepsis, COVID-19, pneumonia, urinary tract infection, malignancy, and age >65 years. OERs varied within each hospital, with medians of approximately 1 and a 75th percentile of approximately 1.25. The median OER demonstrated a downward trend for the Anti-MRSA group at two hospitals but remained relatively stable elsewhere. Instances of heightened antibiotic prescribing (OER >1.25) were identified in approximately 25% of the observed time-points across all four hospitals.

Conclusion

Our findings indicate provider-specific benchmarking among inpatient providers is achievable and has potential utility as a valuable tool for inpatient stewardship efforts.

Self-management behavior strategy based on behavioral economics in patients with hypertension: a scoping review

Hypertensive patients often do not make the most favorable choices and behaviors for managing disease. Behavioral economics strategies offer new ideas for guiding patients toward health behavior. The scoping review aimed to summarize behavioral economics strategies designed to improve hypertension self-management behaviors. A literature search was conducted in September 2022 using the following electronic databases: Embase, Medline, CINAHL, PsycINFO, Web of Science, Cochrane Library, CNKI, Wan Fang Database for Chinese Periodicals, and CBM-SinoMed. We screened the literature for experimental studies written in Chinese or English reporting on BE strategies designed to improve self-management behavior in hypertension. We searched 17 820 records and included 18 articles in the final scoping review. We performed qualitative synthesis by the categories of choice architecture. The most common BE strategies were those targeting decision information and decision assistance, such as changing the presentation of information, making information visible, and providing reminders for actions. Most strategies targeted BP, diet, medication adherence, and physical activity behavior. Ten out of 18 studies reported statistically significant improvement in self-management behavior. Further research on BE strategies should focus on addressing the challenges, including changing the decision structure, encompassing a more comprehensive range of target behaviors, and examining the long-term effects of BE strategies.

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.

Evaluation of an automated feedback intervention to improve antibiotic prescribing among primary care physicians (OPEN Stewardship): a multinational controlled interrupted time-series study

Tools to advance antimicrobial stewardship in the primary health care setting, where most antimicrobials are prescribed, are urgently needed. The aim of this study was to evaluate OPEN Stewarship (Online Platform for Expanding aNtibiotic Stewardship), an automated feedback intervention, among a cohort of primary care physicians. We performed a controlled, interrupted time-series study of 32 intervention and 725 control participants, consisting of primary care physicians from Ontario, Canada and Southern Israel, from October 2020 to December 2021. Intervention participants received three personalized feedback reports targeting several aspects of antibiotic prescribing. Study outcomes (overall prescribing rate, prescribing rate for viral respiratory conditions, prescribing rate for acute sinusitis, and mean duration of therapy) were evaluated using multilevel regression models. We observed a decrease in the mean duration of antibiotic therapy (IRR = 0.94; 95% CI: 0.90, 0.99) in intervention participants during the intervention period. We did not observe a significant decline in overall antibiotic prescribing (OR = 1.01; 95% CI: 0.94, 1.07), prescribing for viral respiratory conditions (OR = 0.87; 95% CI: 0.73, 1.03), or prescribing for acute sinusitis (OR = 0.85; 95% CI: 0.67, 1.07). In this antimicrobial stewardship intervention among primary care physicians, we observed shorter durations of therapy per antibiotic prescription during the intervention period. The COVID-19 pandemic may have hampered recruitment; a dramatic reduction in antibiotic prescribing rates in the months before our intervention may have made physicians less amenable to further reductions in prescribing, limiting the generalizability of the estimates obtained.IMPORTANCEAntibiotic overprescribing contributes to antibiotic resistance, a major threat to our ability to treat infections. We developed the OPEN Stewardship (Online Platform for Expanding aNtibiotic Stewardship) platform to provide automated feedback on antibiotic prescribing in primary care, where most antibiotics for human use are prescribed but where the resources to improve antibiotic prescribing are limited. We evaluated the platform among a cohort of primary care physicians from Ontario, Canada and Southern Israel from October 2020 to December 2021. The results showed that physicians who received personalized feedback reports prescribed shorter courses of antibiotics compared to controls, although they did not write fewer antibiotic prescriptions. While the COVID-19 pandemic presented logistical and analytical challenges, our study suggests that our intervention meaningfully improved an important aspect of antibiotic prescribing. The OPEN Stewardship platform stands as an automated, scalable intervention for improving antibiotic prescribing in primary care, where needs are diverse and technical capacity is limited.

Assessment of implementation strategies adopted for antimicrobial stewardship interventions in long-term care facilities: a systematic review

BACKGROUND

The implementation of antimicrobial stewardship (AMS) interventions in long-term care facilities (LTCFs) is influenced by multi-level factors (resident, organizational, and external) making their effectiveness sensitive to the implementation context.

OBJECTIVES

This study assessed the strategies adopted for the implementation of AMS interventions in LTCFs, whether they considered organizational characteristics, and their effectiveness.

DATA SOURCES

Electronic databases until April 2022.

STUDY ELIGIBILITY CRITERIA

Articles covering implementation of AMS interventions in LTCFs.

ASSESSMENT OF RISK OF BIAS

Mixed Methods Appraisal Tool for empirical studies.

METHODS OF DATA SYNTHESIS

Data were collected on AMS interventions and context characteristics (e.g. type of facility, staffing, and residents). Implementation strategies and outcomes were mapped according to the Expert Recommendations for Implementing Change (ERIC) framework and validated taxonomy for implementation outcomes. Implementation and clinical effectiveness were assessed according to the primary and secondary outcomes results provided in each study.

RESULTS

Among 48 studies included in the analysis, 19 (40%) used implementation strategies corresponding to one to three ERIC domains, including education and training (n = 36/48, 75%), evaluative and iterative strategies (n = 24/48, 50%), and support clinicians (n = 23/48, 48%). Only 8/48 (17%) studies made use of implementation theories, frameworks, or models. Fidelity and sustainability were reported respectively in 21 (70%) and 3 (10%) of 27 studies providing implementation outcomes. Implementation strategy was considered effective in 11/27 (41%) studies, mainly including actions to improve use (n = 6/11, 54%) and education (n = 4/11, 36%). Of the 42 interventions, 18/42 (43%) were deemed clinically effective. Among 21 clinically effective studies, implementation was deemed effective in four and partially effective in five. Two studies were clinically effective despite having non-effective implementation.

CONCLUSIONS

The effectiveness of AMS interventions in LTCFs largely differed according to the interventions' content and implementation strategies adopted. Implementation frameworks should be considered to adapt and tailor interventions and strategies to the local context.