scholarly journals Evaluation of an OPEN Stewardship generated feedback intervention to improve antibiotic prescribing among primary care veterinarians in Ontario, Canada and Israel: protocol for evaluating usability and an interrupted time-series analysis

BMJ Open ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. e039760
Author(s):  
Kamal Raj Acharya ◽  
Gabrielle Brankston ◽  
Jean-Paul R Soucy ◽  
Adar Cohen ◽  
Anette Hulth ◽  
...  
Keyword(s):  
Time Series ◽  
Antibiotic Stewardship ◽  
Negative Binomial ◽  
Interrupted Time Series ◽  
Well Being ◽  
Antibiotic Prescribing ◽  
Feedback Report ◽  
Feedback Intervention ◽  
Scientific Publications ◽  
The Impact

IntroductionAntimicrobial resistance (AMR) impacts the health and well-being of animals, affects animal owners both socially and economically, and contributes to AMR at the human and environmental interface. The overuse and/or inappropriate use of antibiotics in animals has been identified as one of the most important drivers of the development of AMR in animals. Effective antibiotic stewardship interventions such as feedback can be adopted in veterinary practices to improve antibiotic prescribing. However, the provision of dedicated financial and technical resources to implement such systems are challenging. The newly developed web-based Online Platform for Expanding Antibiotic Stewardship (OPEN Stewardship) platform aims to automate the generation of feedback reports and facilitate wider adoption of antibiotic stewardship. This paper describes a protocol to evaluate the usability and usefulness of a feedback intervention among veterinarians and assess its impact on individual antibiotic prescribing.Methods and analysisApproximately 80 veterinarians from Ontario, Canada and 60 veterinarians from Israel will be voluntarily enrolled in a controlled interrupted time-series study and their monthly antibiotic prescribing data accessed. The study intervention consists of targeted feedback reports generated using the OPEN Stewardship platform. After a 3-month preintervention period, a cohort of veterinarians (treatment cohort, n=120) will receive three feedback reports over the course of 6 months while the remainder of the veterinarians (n=20) will be the control cohort. A survey will be administered among the treatment cohort after each feedback cycle to assess the usability and usefulness of various elements of the feedback report. A multilevel negative-binomial regression analysis of the preintervention and postintervention antibiotic prescribing of the treatment cohort will be performed to evaluate the impact of the intervention.Ethics and disseminationResearch ethics board approval was obtained at each participating site prior to the recruitment of the veterinarians. The study findings will be disseminated through open-access scientific publications, stakeholder networks and national/international meetings.

The Impact of a National Antimicrobial Stewardship Program on Antibiotic Prescribing in Primary Care: An Interrupted Time Series Analysis

2018 ◽  
Vol 69 (2) ◽  
pp. 227-232 ◽  
Author(s):  
Violeta Balinskaite ◽  
Alan P Johnson ◽  
Alison Holmes ◽  
Paul Aylin
Keyword(s):  
Primary Care ◽  
Time Series ◽  
Broad Spectrum ◽  
Interrupted Time Series ◽  
Series Data ◽  
Antibiotic Prescribing ◽  
Segmented Regression ◽  
Broad Spectrum Antibiotic ◽  
Stewardship Program ◽  
The Impact

Abstract Background The Quality Premium was introduced in 2015 to financially reward local commissioners of healthcare in England for targeted reductions in antibiotic prescribing in primary care. Methods We used a national antibiotic prescribing dataset from April 2013 until February 2017 to examine the number of antibiotic items prescribed, the total number of antibiotic items prescribed per STAR-PU (specific therapeutic group age/sex-related prescribing units), the number of broad-spectrum antibiotic items prescribed, and broad-spectrum antibiotic items prescribed, expressed as a percentage of the total number of antibiotic items. To evaluate the impact of the Quality Premium on antibiotic prescribing, we used a segmented regression analysis of interrupted time series data. Results During the study period, over 140 million antibiotic items were prescribed in primary care. Following the introduction of the Quality Premium, antibiotic items prescribed decreased by 8.2%, representing 5933563 fewer antibiotic items prescribed during the 23 post-intervention months, as compared with the expected numbers based on the trend in the pre-intervention period. After adjusting for the age and sex distribution in the population, the segmented regression model also showed a significant relative decrease in antibiotic items prescribed per STAR-PU. A similar effect was found for broad-spectrum antibiotics (comprising 10.1% of total antibiotic prescribing), with an 18.9% reduction in prescribing. Conclusions This study shows that the introduction of financial incentives for local commissioners of healthcare to improve the quality of prescribing was associated with a significant reduction in both total and broad-spectrum antibiotic prescribing in primary care in England.

Interrupted Time-Series Analysis to Evaluate the Impact of a National Antimicrobial Stewardship Campaign on Antibiotic Prescribing: A Typical Practice in China’s Primary Care

2020 ◽  
Author(s):  
Hui Li ◽  
Yanhong Gong ◽  
Jing Han ◽  
Shengchao Zhang ◽  
Shanquan Chen ◽  
...  
Keyword(s):  
Primary Care ◽  
Time Series ◽  
Antimicrobial Stewardship ◽  
Broad Spectrum ◽  
Interrupted Time Series ◽  
Antibiotic Prescribing ◽  
Interrupted Time Series Analysis ◽  
Targeted Interventions ◽  
The Impact ◽  
Outpatient Prescriptions

Abstract Background After implementing the 2011 national antimicrobial stewardship campaign, few studies focused on evaluating its effect in China’s primary care facilities. Methods We randomly selected 11 community health centers in Shenzhen, China, and collected all outpatient prescriptions of these centers from 2010–2015. To evaluate the impact of local interventions on antibiotic prescribing, we used a segmented regression model of interrupted time series to analyze seven outcomes, i.e., percentage of prescriptions with antibiotics, and percentages of prescriptions with broad-spectrum antibiotics, with parenteral antibiotics, and with two or more antibiotics in all prescriptions or antibiotics-containing prescriptions. Results Overall, 1 482 223 outpatient prescriptions were obtained. The intervention was associated with a significant immediate change (–5.2%, P=.04) and change in slope (–3.1% per month, P<.01) for the percentage of prescriptions with antibiotics, and its relative cumulative effect at the end of the study was –74.0% (95% confidence interval, –79.0% to –69.1%). After the intervention, the percentage of prescriptions with broad-spectrum, and with parenteral antibiotics decreased dramatically by 36.7% and 77.3%, respectively, but their percentages in antibiotic-containing prescriptions decreased insignificantly. Percentage of prescriptions with two or more antibiotics in all prescriptions or antibiotics-containing prescriptions only showed immediate changes, but significant changes in slope were not observed. Conclusions A typical practice in Shenzhen, China, showed that strict enforcement of antimicrobial stewardship campaign could effectively reduce antibiotic prescribing in primary care with a stable long-term effect. However, prescribing of broad-spectrum and parenteral antibiotics was still prevalent. More targeted interventions are required to promote appropriate antibiotic use.

scholarly journals 1086Methodological challenges using routine aggregated data in a primary care implementation trial on opioid prescribing

2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Tracey Farragher ◽  
Sarah Alderson ◽  
Paul Carder ◽  
Tom Willis ◽  
Robbie Foy
Keyword(s):  
Primary Care ◽  
Time Series ◽  
Routine Data ◽  
Interrupted Time Series ◽  
Data Sources ◽  
Research Database ◽  
Feedback Intervention ◽  
Opioid Prescribing ◽  
Number Of Patients ◽  
The Impact

Abstract Focus of Presentation There is international concern over rising trends in opioid prescribing, largely attributed to prescribing for chronic non-cancer pain. We conducted a controlled interrupted time series study on anonymised, aggregated practice data to evaluate the effect of the Campaign to Reduce Opioid Prescribing (CROP) in reducing the number of patients taking opioid medication in West Yorkshire UK practices targeted by the feedback intervention, compared to practices outside of West Yorkshire. We will discuss the methodological challenges addressed in the collection and analysis of these data, and the implications for using routine data in trials. Findings Primary care data sources for feedback interventions include large-scale databases (General Practice Research Database), high-level nationally gathered databases (OpenPrescribing.com) or data extracted directly from electronic health records (EHR). We will discuss the implications of the different sources of data and compare the results from each, in understanding the impact of the feedback intervention of reducing opioid prescribing over time. The consequences of the heterogeneity of the data sources on the interrupted time series analysis undertaken will also be discussed and solutions outlined. Conclusions/Implications Routine data are heterogeneous, with different purposes, structures and collection methods, which have considerable implications on their use, analysis and interpretation. Researchers need to understand that the utility of routine data sources have implications (both practically and methodologically) in conducting pragmatic trials, which should be considered when planning and conducting future studies using routine data.

scholarly journals The indirect impact of COVID-19 pandemic on inpatient admissions in 204 Kenyan hospitals: An interrupted time series analysis

2021 ◽  
Vol 1 (11) ◽  
pp. e0000029
Author(s):  
Steven Wambua ◽  
Lucas Malla ◽  
George Mbevi ◽  
Amen-Patrick Nwosu ◽  
Timothy Tuti ◽  
...  
Keyword(s):  
Time Series ◽  
Negative Binomial ◽  
Interrupted Time Series ◽  
Public Hospitals ◽  
Hospital Ownership ◽  
Private Hospitals ◽  
Live Births ◽  
Inpatient Services ◽  
First Case ◽  
The Impact

The first case of severe acute respiratory coronavirus 2 (SARS-CoV-2) was identified in March 2020 in Kenya resulting in the implementation of public health measures (PHM) to prevent large-scale epidemics. We aimed to quantify the impact of COVID-19 confinement measures on access to inpatient services using data from 204 Kenyan hospitals. Data on monthly admissions and deliveries from the District Health Information Software version 2 (DHIS 2) were extracted for the period January 2018 to March 2021 stratified by hospital ownership (public or private) and adjusting for missing data using multiple imputation (MI). We used the COVID-19 event as a natural experiment to examine the impact of COVID-19 and associated PHM on use of health services by hospital ownership. We estimated the impact of COVID-19 using two approaches; Statistical process control (SPC) charts to visualize and detect changes and Interrupted time series (ITS) analysis using negative-binomial segmented regression models to quantify the changes after March 2020. Sensitivity analysis was undertaken to test robustness of estimates using Generalised Estimating Equations (GEE) and impact of national health workers strike on observed trends. SPC charts showed reductions in most inpatient services starting April 2020. ITS modelling showed significant drops in April 2020 in monthly volumes of live-births (11%), over-fives admissions for medical (29%) and surgical care (25%) with the greatest declines in the under-five’s admissions (59%) in public hospitals. Similar declines were apparent in private hospitals. Health worker strikes had a significant impact on post-COVID-19 trends for total deliveries, live-births and caesarean section rate in private hospitals. COVID-19 has disrupted utilization of inpatient services in Kenyan hospitals. This might have increased avoidable morbidity and mortality due to non-COVID-19-related illnesses. The declines have been sustained. Recent data suggests a reversal in trends with services appearing to be going back to pre- COVID levels.

scholarly journals Evaluation of an automated feedback intervention to improve antimicrobial prescribing among primary care physicians (OPEN Stewardship): protocol for an interrupted time-series and usability analysis in Ontario, Canada and Southern Israel

BMJ Open ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. e039810
Author(s):  
Jean-Paul R Soucy ◽  
Marcelo Low ◽  
Kamal Raj Acharya ◽  
Moriah Ellen ◽  
Anette Hulth ◽  
...  
Keyword(s):  
Primary Care ◽  
Time Series ◽  
Primary Care Physicians ◽  
Bacterial Infections ◽  
Negative Binomial ◽  
Interrupted Time Series ◽  
New Drugs ◽  
Feedback Intervention ◽  
Antimicrobial Prescribing ◽  
Automated Feedback

IntroductionAntimicrobial resistance undermines our ability to treat bacterial infections, leading to longer hospital stays, increased morbidity and mortality, and a mounting burden to the healthcare system. Antimicrobial stewardship is increasingly important to safeguard the efficacy of existing drugs, as few new drugs are in the developmental pipeline. While significant progress has been made with respect to stewardship in hospitals, relatively little progress has been made in the primary care setting, where the majority of antimicrobials are prescribed. OPEN Stewardship is an international collaboration to develop an automated feedback platform to improve responsible antimicrobial prescribing among primary care physicians and capable of being deployed across heterogeneous healthcare settings. We describe the protocol for an evaluation of this automated feedback intervention with two main objectives: assessing changes in antimicrobial prescribing among participating physicians and determining the usability and usefulness of the reports.Methods and analysisA non-randomised evaluation of the automated feedback intervention (OPEN Stewardship) will be conducted among approximately 150 primary care physicians recruited from Ontario, Canada and Southern Israel, based on a series of targeted stewardship messages sent using the platform. Using a controlled interrupted time-series analysis and multilevel negative binomial modelling, we will compare the antimicrobial prescribing rates of participants before and after the intervention, and also to the prescribing rates of non-participants (from the same healthcare network) during the same period. We will examine outcomes targeted by the stewardship messages, including prescribing for antimicrobials with duration longer than 7 days and prescribing for indications where antimicrobials are typically unnecessary. Participants will also complete a series of surveys to determine the usability and usefulness of the stewardship reports.Ethics and disseminationAll sites have obtained ethics committee approval to recruit providers and access anonymised prescribing data. Dissemination will occur through open-access publication, stakeholder networks and national/international meetings.

scholarly journals The impact of COVID-19 on outpatient antibiotic prescriptions in Ontario, Canada; An interrupted time series analysis

2021 ◽  
Author(s):  
Taito Kitano ◽  
Kevin A Brown ◽  
Nick Daneman ◽  
Derek R MacFadden ◽  
Bradley J Langford ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Respiratory Infections ◽  
Population Level ◽  
Interrupted Time Series ◽  
Relative Reduction ◽  
Antibiotic Prescribing ◽  
Interrupted Time Series Analysis ◽  
Series Analysis ◽  
The Impact

Abstract Background The COVID-19 pandemic has potentially impacted outpatient antibiotic prescribing. Investigating this impact may identify stewardship opportunities in the ongoing COVID-19 period and beyond. Methods We conducted an interrupted time series analysis on outpatient antibiotic prescriptions and antibiotic prescriptions/patient visits in Ontario, Canada between January 2017 and December 2020 to evaluate the impact of the COVID-19 pandemic on population-level antibiotic prescribing by prescriber’s specialty, patient demographics and conditions. Results In the evaluated COVID-19 period (March-December 2020), there was a 31.2% [95% CI: 27.0%–35.1%] relative reduction in total antibiotic prescriptions. Total outpatient antibiotic prescriptions decreased during the COVID-19 period by 37.1% [32.5%–41.3%] among family physicians, 30.7% [25.8%–35.2%] among sub-specialist physicians, 12.1% [4.4%–19.2%] among dentists and 25.7% [21.4%–29.8%] among other prescribers. Antibiotics indicated for respiratory infections decreased by 43.7% [38.4–48.6%]. Total patient visits and visits for respiratory infections decreased by 10.7% [5.4%–15.6%] and 49.9% [43.1%%–55.9%]). Total antibiotic prescriptions/1,000 visits decreased by 27.5% [21.5%–33.0%], while antibiotics indicated for respiratory infections/1,000 visits with respiratory infections only decreased by 6.8% [2.7%–10.8%]. Conclusion The reduction in outpatient antibiotic prescribing during the COVID-19 pandemic was driven by less antibiotic prescribing for respiratory indications and largely explained by decreased visits for respiratory infections.

scholarly journals COVID-19 and Antibiotic Prescribing in Pediatric Primary Care

PEDIATRICS ◽  
2022 ◽  
Author(s):  
Lauren Dutcher ◽  
Yun Li ◽  
Giyoung Lee ◽  
Robert Grundmeier ◽  
Keith W. Hamilton ◽  
...  
Keyword(s):  
Primary Care ◽  
Time Series ◽  
Time Series Analysis ◽  
Interrupted Time Series ◽  
The United States ◽  
Pediatric Primary Care ◽  
Antibiotic Prescribing ◽  
Interrupted Time Series Analysis ◽  
Series Analysis ◽  
The Impact

BACKGROUND AND OBJECTIVES: With the onset of the coronavirus disease 2019 (COVID-19) pandemic, pediatric ambulatory encounter volume and antibiotic prescribing both decreased; however, the durability of these reductions in pediatric primary care in the United States has not been assessed. METHODS: We conducted a retrospective observational study to assess the impact of the COVID-19 pandemic and associated public health measures on antibiotic prescribing in 27 pediatric primary care practices. Encounters from January 1, 2018, through June 30, 2021, were included. The primary outcome was monthly antibiotic prescriptions per 1000 patients. Interrupted time series analysis was performed. RESULTS: There were 69 327 total antibiotic prescriptions from April through December in 2019 and 18 935 antibiotic prescriptions during the same months in 2020, a 72.7% reduction. The reduction in prescriptions at visits for respiratory tract infection (RTI) accounted for 87.3% of this decrease. Using interrupted time series analysis, overall antibiotic prescriptions decreased from 31.6 to 6.4 prescriptions per 1000 patients in April 2020 (difference of −25.2 prescriptions per 1000 patients; 95% CI: −32.9 to −17.5). This was followed by a nonsignificant monthly increase in antibiotic prescriptions, with prescribing beginning to rebound from April to June 2021. Encounter volume also immediately decreased, and while overall encounter volume quickly started to recover, RTI encounter volume returned more slowly. CONCLUSIONS: Reductions in antibiotic prescribing in pediatric primary care during the COVID-19 pandemic were sustained, only beginning to rise in 2021, primarily driven by reductions in RTI encounters. Reductions in viral RTI transmission likely played a substantial role in reduced RTI visits and antibiotic prescriptions.

scholarly journals Correction to: Measuring the impact of the Afordable Care Act Medicaid expansion on access to primary care using an interrupted time series approach

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Elizabeth A. Brown ◽  
Brandi M. White ◽  
Walter J. Jones ◽  
Mulugeta Gebregziabher ◽  
Kit N. Simpson
Keyword(s):  
Primary Care ◽  
Time Series ◽  
Interrupted Time Series ◽  
Medicaid Expansion ◽  
Time Series Approach ◽  
Access To Primary Care ◽  
The Impact

An amendment to this paper has been published and can be accessed via the original article.

scholarly journals Does admission prevalence change after reconfiguration of inpatient services? An interrupted time series analysis of the impact of reconfiguration in five centres

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Joanne Martin ◽  
Edwin Amalraj Raja ◽  
Steve Turner
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Emergency Admission ◽  
Interrupted Time Series ◽  
Interrupted Time Series Analysis ◽  
Emergency Admissions ◽  
Series Analysis ◽  
Inpatient Services ◽  
The Impact ◽  
Admission Prevalence

Abstract Background Service reconfiguration of inpatient services in a hospital includes complete and partial closure of all emergency inpatient facilities. The “natural experiment” of service reconfiguration may give insight into drivers for emergency admissions to hospital. This study addressed the question does the prevalence of emergency admission to hospital for children change after reconfiguration of inpatient services? Methods There were five service reconfigurations in Scottish hospitals between 2004 and 2018 where emergency admissions to one “reconfigured” hospital were halted (permanently or temporarily) and directed to a second “adjacent” hospital. The number of emergency admissions (standardised to /1000 children in the regional population) per month to the “reconfigured” and “adjacent” hospitals was obtained for five years prior to reconfiguration and up to five years afterwards. An interrupted time series analysis considered the association between reconfiguration and admissions across pairs comprised of “reconfigured” and “adjacent” hospitals, with adjustment for seasonality and an overall rising trend in admissions. Results Of the five episodes of reconfiguration, two were immediate closure, two involved closure only to overnight admissions and one with overnight closure for a period and then closure. In “reconfigured” hospitals there was an average fall of 117 admissions/month [95% CI 78, 156] in the year after reconfiguration compared to the year before, and in “adjacent” hospitals admissions rose by 82/month [32, 131]. Across paired reconfigured and adjacent hospitals, in the months post reconfiguration, the overall number of admissions to one hospital pair slowed, in another pair admissions accelerated, and admission prevalence was unchanged in three pairs. After reconfiguration in one hospital, there was a rise in admissions to a third hospital which was closer than the named “adjacent” hospital. Conclusions There are diverse outcomes for the number of emergency admissions post reconfiguration of inpatient facilities. Factors including resources placed in the community after local reconfiguration, distance to the “adjacent” hospital and local deprivation may be important drivers for admission pathways after reconfiguration. Policy makers considering reconfiguration might consider a number of factors which may be important determinants of admissions post reconfiguration.

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