Impact of interactive computerised decision support for hospital antibiotic use (COMPASS): an open-label, cluster-randomised trial in three Swiss hospitals.
Ontology highlight
ABSTRACT:
SUBMITTER: Catho G
PROVIDER: S-EPMC9491854 | biostudies-literature | 2022 Oct
REPOSITORIES: biostudies-literature
Publications
Impact of interactive computerised decision support for hospital antibiotic use (COMPASS): an open-label, cluster-randomised trial in three Swiss hospitals.
Catho Gaud G Sauser Julien J Coray Valentina V Da Silva Serge S Elzi Luigia L Harbarth Stephan S Kaiser Laurent L Marti Christophe C Meyer Rodolphe R Pagnamenta Francesco F Portela Javier J Prendki Virginie V Ranzani Alice A Centemero Nicolò Saverio NS Stirnemann Jerome J Valotti Roberta R Vernaz Nathalie N Suter Brigitte Waldispuehl BW Bernasconi Enos E Huttner Benedikt D BD
The Lancet. Infectious diseases 20220720 10
<h4>Background</h4>Computerised decision-support systems (CDSSs) for antibiotic stewardship could help to assist physicians in the appropriate prescribing of antibiotics. However, high-quality evidence for their effect on the quantity and quality of antibiotic use remains scarce. The aim of our study was to assess whether a computerised decision support for antimicrobial stewardship combined with feedback on prescribing indicators can reduce antimicrobial prescriptions for adults admitted to hos ...[more]
Similar Datasets
Project description:IntroductionInappropriate use of antimicrobials in hospitals contributes to antimicrobial resistance. Antimicrobial stewardship (AMS) interventions aim to improve antimicrobial prescribing, but they are often resource and personnel intensive. Computerised decision supportsystems (CDSSs) seem a promising tool to improve antimicrobial prescribing but have been insufficiently studied in clinical trials.Methods and analysisThe COMPuterized Antibiotic Stewardship Study trial, is a publicly funded, open-label, cluster randomised, controlled superiority trial which aims to determine whether a multimodal CDSS intervention integrated in the electronic health record (EHR) reduces overall antibiotic exposure in adult patients hospitalised in wards of two secondary and one tertiary care centre in Switzerland compared with 'standard-of-care' AMS. Twenty-four hospital wards will be randomised 1:1 to either intervention or control, using a 'pair-matching' approach based on baseline antibiotic use, specialty and centre. The intervention will consist of (1) decision support for the choice of antimicrobial treatment and duration of treatment for selected indications (based on indication entry), (2) accountable justification for deviation from the local guidelines (with regard to the choice of molecules and duration), (3) alerts for self-guided re-evaluation of treatment on calendar day 4 of antimicrobial therapy and (4) monthly ward-level feedback of antimicrobial prescribing indicators. The primary outcome will be the difference in overall systemic antibiotic use measured in days of therapy per admission based on administration data recorded in the EHR over the whole intervention period (12 months), taking into account clustering. Secondary outcomes include qualitative and quantitative antimicrobial use indicators, economic outcomes and clinical, microbiological and patient safety indicators.Ethics and disseminationEthics approval was obtained for all participating sites (Comission Cantonale d'Éthique de la Recherche (CCER)2017-00454). The results of the trial will be submitted for publication in a peer-reviewed journal. Further dissemination activities will be presentations/posters at national and international conferences.Trial registration numberNCT03120975; Pre-results.
| S-EPMC6042555 | biostudies-literature
Project description:BackgroundInappropriate antimicrobial use has been shown to be an important determinant of the emergence of antimicrobial resistance (AMR). Health information technology (HIT) in the form of Computerised Decision Support (CDS) represents an option for improving antimicrobial prescribing and containing AMR.ObjectivesTo evaluate the evidence for CDS in improving quantitative and qualitative measures of antibiotic prescribing in inpatient hospital settings.MethodsA systematic literature search was conducted of articles published from inception to 20th December 2014 using eight electronic databases: MEDLINE, EMBASE, PUBMED, Web of Science, CINAHL, Cochrane Library, HMIC and PsychINFo. An updated systematic literature search was conducted from January 1st 2015 to October 1st 2016 using PUBMED. The search strategy used combinations of the following terms: (electronic prescribing) OR (clinical decision support) AND (antibiotic or antibacterial or antimicrobial) AND (hospital or secondary care or inpatient). Studies were evaluated for quality using a 10-point rating scale.ResultsEighty-one studies were identified matching the inclusion criteria. Seven outcome measures were evaluated: adequacy of antibiotic coverage, mortality, volume of antibiotic usage, length of stay, antibiotic cost, compliance with guidelines, antimicrobial resistance, and CDS implementation and uptake. Meta-analysis of pooled outcomes showed CDS significantly improved the adequacy of antibiotic coverage (n = 13; odds ratio [OR], 2.11 [95% CI, 1.67 to 2.66, p ≤ 0.00001]). Also, CDS was associated with marginally lowered mortality (n = 20; OR, 0.85 [CI, 0.75 to 0.96, p = 0.01]). CDS was associated with lower antibiotic utilisation, increased compliance with antibiotic guidelines and reductions in antimicrobial resistance. Conflicting effects of CDS on length of stay, antibiotic costs and system uptake were also noted.ConclusionsCDS has the potential to improve the adequacy of antibiotic coverage and marginally decrease mortality in hospital-related settings.
| S-EPMC5570266 | biostudies-literature
Project description:Antibiotic computerised decision support systems (CDSSs) are shown to improve antibiotic prescribing, but evidence of beneficial patient outcomes is limited. We conducted a prospective cohort study in a 1500-bed tertiary-care hospital in Singapore, to evaluate the effectiveness of the hospital's antibiotic CDSS on patients' clinical outcomes, and the modification of these effects by patient factors. To account for clustering, we used multilevel logistic regression models. One-quarter of 1886 eligible inpatients received CDSS-recommended antibiotics. Receipt of antibiotics according to CDSS's recommendations seemed to halve mortality risk of patients (OR 0.54, 95% CI 0.26-1.10, P = 0.09). Patients aged ≤65 years had greater mortality benefit (OR 0.45, 95% CI 0.20-1.00, P = 0.05) than patients that were older than 65 (OR 1.28, 95% CI 0.91-1.82, P = 0.16). No effect was observed on incidence of Clostridium difficile (OR 1.02, 95% CI 0.34-3.01), and multidrug-resistant organism (OR 1.06, 95% CI 0.42-2.71) infections. No increase in infection-related readmission (OR 1.16, 95% CI 0.48-2.79) was found in survivors. Receipt of CDSS-recommended antibiotics reduced mortality risk in patients aged 65 years or younger and did not increase the risk in older patients. Physicians should be informed of the benefits to increase their acceptance of CDSS recommendations.
| S-EPMC4663624 | biostudies-literature
Project description:ObjectiveTo evaluate effectiveness, safety and cost-effectiveness of Computerised Clinical Decision Support (CCDS) for paramedics attending older people who fall.DesignCluster trial randomised by paramedic; modelling.Setting13 ambulance stations in two UK emergency ambulance services.Participants42 of 409 eligible paramedics, who attended 779 older patients for a reported fall.InterventionsIntervention paramedics received CCDS on Tablet computers to guide patient care. Control paramedics provided care as usual. One service had already installed electronic data capture.Main outcome measuresEffectiveness: patients referred to falls service, patient reported quality of life and satisfaction, processes of care.SafetyFurther emergency contacts or death within one month.Cost-effectivenessCosts and quality of life. We used findings from published Community Falls Prevention Trial to model cost-effectiveness.Results17 intervention paramedics used CCDS for 54 (12.4%) of 436 participants. They referred 42 (9.6%) to falls services, compared with 17 (5.0%) of 343 participants seen by 19 control paramedics [Odds ratio (OR) 2.04, 95% CI 1.12 to 3.72]. No adverse events were related to the intervention. Non-significant differences between groups included: subsequent emergency contacts (34.6% versus 29.1%; OR 1.27, 95% CI 0.93 to 1.72); quality of life (mean SF12 differences: MCS -0.74, 95% CI -2.83 to +1.28; PCS -0.13, 95% CI -1.65 to +1.39) and non-conveyance (42.0% versus 36.7%; OR 1.13, 95% CI 0.84 to 1.52). However ambulance job cycle time was 8.9 minutes longer for intervention patients (95% CI 2.3 to 15.3). Average net cost of implementing CCDS was £208 per patient with existing electronic data capture, and £308 without. Modelling estimated cost per quality-adjusted life-year at £15,000 with existing electronic data capture; and £22,200 without.ConclusionsIntervention paramedics referred twice as many participants to falls services with no difference in safety. CCDS is potentially cost-effective, especially with existing electronic data capture.Trial registrationISRCTN Register ISRCTN10538608.
| S-EPMC4162545 | biostudies-literature
Project description:BackgroundAntibiotic resistance is a major health threat. Inappropriate antibiotic use has been shown to be an important determinant of the emergence of antibiotic resistance. Decision support systems for antimicrobial management can support clinicians to optimize antibiotic prescription.ObjectiveThe aim of this systematic review is to identify factors influencing the implementation of decision support systems for antibiotic prescription in hospitals.MethodsA systematic search of factors impeding or facilitating successful implementation of decision support systems for antibiotic prescription was performed in January 2022 in the databases PubMed, Web of Science and The Cochrane Library. Only studies were included which comprised decision support systems in hospitals for prescribing antibiotic therapy, published in English with a qualitative, quantitative or mixed-methods study design and between 2011 and 2021. Factors influencing the implementation were identified through text analysis by two reviewers.ResultsA total of 14 publications were identified matching the inclusion criteria. The majority of factors relate to technological and organizational aspects of decision support system implementation. Some factors include the integration of the decision support systems into existing systems, system design, consideration of potential end-users as well as training and support for end-users. In addition, user-related factors, like user attitude towards the system, computer literacy and prior experience with the system seem to be important for successful implementation of decision support systems for antibiotic prescription in hospitals.ConclusionThe results indicate a broad spectrum of factors of decision support system implementation for antibiotic prescription and contributes to the literature by identifying important organizational as well as user-related factors. Wider organizational dimensions as well as the interaction between user and technology appear important for supporting implementation.
| S-EPMC9903563 | biostudies-literature
Project description:BackgroundCluster headache (CH) is a disabling primary headache disorder characterized by severe periorbital pain. A subset of patients does not respond to established pharmacological therapy. This study examines outcomes of a cohort of mainly chronic CH patients treated with sphenopalatine ganglion (SPG) stimulation.MethodsPatients were followed in an open-label prospective study for 12 months. Ninety-seven CH patients (88 chronic, 9 episodic) underwent trans-oral insertion of a microstimulator targeting the SPG. Patients recorded stimulation effect prospectively for individual attacks. Frequency, use of preventive and acute medications, headache impact (HIT-6) and quality of life measures (SF-36v2) were monitored at clinic visits. Per protocol, frequency responders experienced ≥ 50% reduction in attack frequency and acute responders treated ≥ 50% of attacks. HIT-6 responders experienced an improvement ≥ 2.3 units and SF-36 responders ≥ 4 units vs. baseline.ResultsEighty-five patients (78 chronic, 7 episodic) remained implanted and were evaluated for effectiveness at 12 months. In total, 68% of all patients were responders, 55% of chronic patients were frequency responders and 32% of all patients were acute responders. 67% of patients using acute treatments were able to reduce the use of these by 52% and 74% of chronic patients were able to stop, reduce or remain off all preventive medications. 59% of all patients were HIT-6 responders, 67% were SF-36 responders.ConclusionsThis open-label registry corroborates that SPG stimulation is an effective therapy for CH patients providing therapeutic benefits and improvements in use of medication as well as headache impact and quality of life.
| S-EPMC5773459 | biostudies-literature
Project description:BackgroundMedication safety in patients with polypharmacy at transitions of care is a focus of the current Third WHO Global Patient Safety Challenge. Medication review and communication between health care professionals are key targets to reduce medication-related harm.ObjectiveTo study whether a hospital discharge intervention combining medication review with enhanced information transfer between hospital and primary care physicians can delay hospital readmission and impact health care utilization or other health-related outcomes of older inpatients with polypharmacy.DesignCluster-randomized controlled trial in 21 Swiss hospitals between January 2019 and September 2020, with 6 months follow-up.ParticipantsSixty-eight senior physicians and their blinded junior physicians included 609 patients ≥ 60 years taking ≥ 5 drugs.InterventionsParticipating hospitals were randomized to either integrate a checklist-guided medication review and communication stimulus into their discharge processes, or follow usual discharge routines.Main measuresPrimary outcome was time-to-first-readmission to any hospital within 6 months, analyzed using a shared frailty model. Secondary outcomes covered readmission rates, emergency department visits, other medical consultations, mortality, drug numbers, proportions of patients with potentially inappropriate medication, and the patients' quality of life.Key resultsAt admission, 609 patients (mean age 77.5 (SD 8.6) years, 49.4% female) took a mean of 9.6 (4.2) drugs per patient. Time-to-first-readmission did not differ significantly between study arms (adjusted hazard ratio 1.14 (intervention vs. control arm), 95% CI [0.75-1.71], p = 0.54), nor did the 30-day hospital readmission rates (6.7% [3.3-10.1%] vs. 7.0% [3.6-10.3%]). Overall, there were no clinically relevant differences between study arms at 1, 3, and 6 months after discharge.ConclusionsThe combination of a structured medication review with enhanced information transfer neither delayed hospital readmission nor improved other health-related outcomes of older inpatients with polypharmacy. Our results may help researchers in balancing practicality versus stringency of similar hospital discharge interventions.Study registrationISRCTN18427377, https://doi.org/10.1186/ISRCTN18427377.
| S-EPMC9432794 | biostudies-literature
Project description:BackgroundEmerging resistance to antibiotics renders therapy of Typhoid Fever (TF) increasingly challenging. The current single-drug regimens exhibit prolonged fever clearance time (FCT), imposing a great burden on both patients and health systems, and potentially contributing to the development of antibiotic resistance and the chronic carriage of the pathogens. The aim of our study was to assess the efficacy of combining third-generation cephalosporin therapy with azithromycin on the outcomes of TF in patients living in an endemic region.MethodsAn open-label, comparative trial was conducted at Dhulikhel Hospital, Nepal, between October 2012 and October 2014. Only culture-confirmed TF cases were eligible. Patients were alternately allocated to one of four study arms: hospitalized patients received either intravenous ceftriaxone or a combination of ceftriaxone and oral azithromycin, while outpatients received either oral azithromycin or a combination of oral azithromycin and cefexime. The primary outcome evaluated was FCT and the secondary outcomes included duration of bacteremia.Results105 blood culture-confirmed patients, of whom 51 were treated as outpatients, were eligible for the study. Of the 88 patients who met the inclusion criteria for FCT analysis 41 patients received a single-agent regimen, while 47 patients received a combined regimen. Results showed that FCT was significantly shorter for the latter (95 versus 88 hours, respectively, p = 0·004), and this effect was exhibited in both the hospitalized and the outpatient sub-groups. Repeat blood cultures, drawn on day 3, were positive for 8/47 (17%) patients after monotherapy, versus 2/51 (4%) after combination therapy (p = 0·045). No severe complications or fatalities occurred in any of the groups.ConclusionsCombined therapy of third-generation cephalosporins and azithromycin for TF may surpass monotherapy in terms of FCT and time to elimination of bacteremia.Trial registrationTrial registration number: NCT02224040.
| S-EPMC5912710 | biostudies-literature
Project description:BackgroundInappropriate antimicrobial use, such as antibiotic intake in viral infections, incorrect dosing and incorrect dosing cycles, has been shown to be an important determinant of the emergence of antimicrobial resistance. Artificial intelligence-based decision support systems represent a potential solution for improving antimicrobial prescribing and containing antimicrobial resistance by supporting clinical decision-making thus optimizing antibiotic use and improving patient outcomes.ObjectiveThe aim of this research was to examine implementation factors of artificial intelligence-based decision support systems for antibiotic prescription in hospitals from the perspective of the hospital managers, who have decision-making authority for the organization.MethodsAn online survey was conducted between December 2022 and May 2023 with managers of German hospitals on factors for decision support system implementation. Survey responses were analyzed from 118 respondents through descriptive statistics.ResultsSurvey participants reported openness towards the use of artificial intelligence-based decision support systems for antibiotic prescription in hospitals but little self-perceived knowledge in this field. Artificial intelligence-based decision support systems appear to be a promising opportunity to improve quality of care and increase treatment safety. Along with the Human-Organization-Technology-fit model attitudes were presented. In particular, user-friendliness of the system and compatibility with existing technical structures are considered to be important for implementation. The uptake of decision support systems also depends on the ability of an organization to create a facilitating environment that helps to address the lack of user knowledge as well as trust in and skepticism towards these systems. This includes the training of user groups and support of the management level. Besides, it has been assessed to be important that potential users are open towards change and perceive an added value of the use of artificial intelligence-based decision support systems.ConclusionThe survey has revealed the perspective of hospital managers on different factors that may help to address implementation challenges for artificial intelligence-based decision support systems in antibiotic prescribing. By combining factors of user perceptions about the systems´ perceived benefits with external factors of system design requirements and contextual conditions, the findings highlight the need for a holistic implementation framework of artificial intelligence-based decision support systems.
| S-EPMC11020884 | biostudies-literature
Project description:BackgroundNational quality indicators show little change in the overuse of antibiotics for uncomplicated acute bronchitis. We compared the effect of 2 decision support strategies on antibiotic treatment of uncomplicated acute bronchitis.MethodsWe conducted a 3-arm cluster randomized trial among 33 primary care practices belonging to an integrated health care system in central Pennsylvania. The printed decision support intervention sites (11 practices) received decision support for acute cough illness through a print-based strategy, the computer-assisted decision support intervention sites (11 practices) received decision support through an electronic medical record-based strategy, and the control sites (11 practices) served as a control arm. Both intervention sites also received clinician education and feedback on prescribing practices, as well as patient education brochures at check-in. Antibiotic prescription rates for uncomplicated acute bronchitis in the winter period (October 1, 2009, through March 31, 2010) following introduction of the intervention were compared with the previous 3 winter periods in an intent-to-treat analysis.ResultsCompared with the baseline period, the percentage of adolescents and adults prescribed antibiotics during the intervention period decreased at the printed decision support intervention sites (from 80.0% to 68.3%) and at the computer-assisted decision support intervention sites (from 74.0% to 60.7%) but increased slightly at the control sites (from 72.5% to 74.3%). After controlling for patient and clinician characteristics, as well as clustering of observations by clinician and practice site, the differences for the intervention sites were statistically significant from the control sites (P = .003 for control sites vs printed decision support intervention sites and P = .01 for control sites vs computer-assisted decision support intervention sites) but not between themselves (P = .67 for printed decision support intervention sites vs computer-assisted decision support intervention sites). Changes in total visits, 30-day return visit rates, and proportion diagnosed as having uncomplicated acute bronchitis were similar among the study sites.ConclusionsImplementation of a decision support strategy for acute bronchitis can help reduce the overuse of antibiotics in primary care settings. The effect of printed vs computer-assisted decision support strategies for providing decision support was equivalent.Trial registrationclinicaltrials.gov Identifier: NCT00981994.
| S-EPMC3582762 | biostudies-literature