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Impact of Clinical Decision Support on Radiography for Acute Ankle Injuries: A Randomized Trial.

ABSTRACT: While only 15-20% of patients with foot and ankle injuries presenting to urgent care centers have clinically significant fractures, most undergo radiography. We examined the impact of electronic point-of-care clinical decision support (CDS) on adherence to the Ottawa Ankle Rules (OAR), as well as use and yield of foot and ankle radiographs in patients with acute ankle injury.We obtained institutional review board approval for this randomized controlled study performed April 18, 2012-December 15, 2013. All ordering providers credentialed at an urgent care affiliated with a quaternary care academic hospital were randomized to either receive or not receive CDS, based on the OAR and integrated into the physician order-entry system, with feedback at the time of imaging order. If the patient met OAR low-risk criteria, providers were advised against imaging and could either cancel the order or ignore the alert. We identified patients with foot and ankle complaints via ICD-9 billing codes and electronic health records and radiology reports reviewed for those who were eligible. Chi-square was used to compare adherence to the OAR (primary outcome), radiography utilization rate and radiography yield of foot and ankle imaging (secondary outcomes) between the intervention and control groups.Of 14,642 patients seen at urgent care during the study period, 613 (4.2%, representing 632 visits) presented with acute ankle injury and were eligible for application of the OAR; 374 (59.2%) of these were seen by control-group providers. In the intervention group, CDS adherence was higher for both ankle (239/258=92.6% vs. 231/374=61.8%, p=0.02) and foot radiography (209/258=81.0% vs. 238/374=63.6%; p<0.01). However, ankle radiography use was higher in the intervention group (166/258=64.3% vs. 183/374=48.9%; p<0.01), while foot radiography use (141/258=54.6% vs. 202/374=54.0%; p=0.95) was not. Radiography yield was also higher in the intervention group (26/307=8.5% vs. 18/385=4.7%; p=0.04).Clinical decision support, previously demonstrated to improve guideline adherence for high-cost imaging, can also improve guideline adherence for radiography - as demonstrated by increased OAR adherence and increased imaging yield.

SUBMITTER: Tajmir S

PROVIDER: S-EPMC5391900 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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Impact of Clinical Decision Support on Radiography for Acute Ankle Injuries: A Randomized Trial.

Tajmir Shahein S Raja Ali S AS Ip Ivan K IK Andruchow James J Silveira Patricia P Smith Stacy S Khorasani Ramin R

The western journal of emergency medicine 20170307 3

<h4>Introduction</h4>While only 15-20% of patients with foot and ankle injuries presenting to urgent care centers have clinically significant fractures, most undergo radiography. We examined the impact of electronic point-of-care clinical decision support (CDS) on adherence to the Ottawa Ankle Rules (OAR), as well as use and yield of foot and ankle radiographs in patients with acute ankle injury.<h4>Methods</h4>We obtained institutional review board approval for this randomized controlled study ...[more]

PMID: 28435501

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Project description:BackgroundClinical decision support (CDS) is a promising tool for reducing antibiotic prescribing for acute respiratory infections (ARIs).ObjectiveTo assess the impact of previously effective CDS on antibiotic-prescribing rates for ARIs when adapted and implemented in diverse primary care settings.DesignCluster randomized clinical trial (RCT) implementing a CDS tool designed to guide evidence-based evaluation and treatment of streptococcal pharyngitis and pneumonia.SettingTwo large academic health system primary care networks with a mix of providers.ParticipantsAll primary care practices within each health system were invited. All providers within participating clinic were considered a participant. Practices were randomized selection to a control or intervention group.InterventionsIntervention practice providers had access to an integrated clinical prediction rule (iCPR) system designed to determine the risk of bacterial infection from reason for visit of sore throat, cough, or upper respiratory infection and guide evidence-based evaluation and treatment.Main outcome(s)Change in overall antibiotic prescription rates.Measure(s)Frequency, rates, and type of antibiotics prescribed in intervention and controls groups.Results33 primary care practices participated with 541 providers and 100,573 patient visits. Intervention providers completed the tool in 6.9% of eligible visits. Antibiotics were prescribed in 35% and 36% of intervention and control visits, respectively, showing no statistically significant difference. There were also no differences in rates of orders for rapid streptococcal tests (RR, 0.94; P = 0.11) or chest X-rays (RR, 1.01; P = 0.999) between groups.ConclusionsThe iCPR tool was not effective in reducing antibiotic prescription rates for upper respiratory infections in diverse primary care settings. This has implications for the generalizability of CDS tools as they are adapted to heterogeneous clinical contexts.Trial registrationClinicaltrials.gov (NCT02534987). Registered August 26, 2015 at https://clinicaltrials.gov.

Project description:RationaleClinical decision support (CDS) tools leveraging electronic health records (EHRs) have been an approach for addressing challenges in asthma care but remain under-studied through clinical trials.ObjectivesTo assess the effectiveness and efficiency of Asthma-Guidance and Prediction System (A-GPS), an Artificial Intelligence (AI)-assisted CDS tool, in optimizing asthma management through a randomized clinical trial (RCT).MethodsThis was a single-center pragmatic RCT with a stratified randomization design conducted for one year in the primary care pediatric practice of the Mayo Clinic, MN. Children (<18 years) diagnosed with asthma receiving care at the study site were enrolled along with their 42 primary care providers. Study subjects were stratified into three strata (based on asthma severity, asthma care status, and asthma diagnosis) and were blinded to the assigned groups.MeasurementsIntervention was a quarterly A-GPS report to clinicians including relevant clinical information for asthma management from EHRs and machine learning-based prediction for risk of asthma exacerbation (AE). Primary endpoint was the occurrence of AE within 1 year and secondary outcomes included time required for clinicians to review EHRs for asthma management.Main resultsOut of 555 participants invited to the study, 184 consented for the study and were randomized (90 in intervention and 94 in control group). Median age of 184 participants was 8.5 years. While the proportion of children with AE in both groups decreased from the baseline (P = 0.042), there was no difference in AE frequency between the two groups (12% for the intervention group vs. 15% for the control group, Odds Ratio: 0.82; 95%CI 0.374-1.96; P = 0.626) during the study period. For the secondary end points, A-GPS intervention, however, significantly reduced time for reviewing EHRs for asthma management of each participant (median: 3.5 min, IQR: 2-5), compared to usual care without A-GPS (median: 11.3 min, IQR: 6.3-15); p<0.001). Mean health care costs with 95%CI of children during the trial (compared to before the trial) in the intervention group were lower than those in the control group (-$1,036 [-$2177, $44] for the intervention group vs. +$80 [-$841, $1000] for the control group), though there was no significant difference (p = 0.12). Among those who experienced the first AE during the study period (n = 25), those in the intervention group had timelier follow up by the clinical care team compared to those in the control group but no significant difference was found (HR = 1.93; 95% CI: 0.82-1.45, P = 0.10). There was no difference in the proportion of duration when patients had well-controlled asthma during the study period between the intervention and the control groups.ConclusionsWhile A-GPS-based intervention showed similar reduction in AE events to usual care, it might reduce clinicians' burden for EHRs review resulting in efficient asthma management. A larger RCT is needed for further studying the findings.Trial registrationClinicalTrials.gov Identifier: NCT02865967.

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Impact of Clinical Decision Support on Radiography for Acute Ankle Injuries: A Randomized Trial.

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Impact of Clinical Decision Support on Radiography for Acute Ankle Injuries: A Randomized Trial.

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