609. Implementation of Bayesian Software for Vancomycin Dosing Integrated into an Electronic Medical Record

Background New vancomycin dosing guidelines recommend using a 24-hour area under the curve (AUC) goal of 400-600mg*h/L rather than a serum trough concentration 10-20 mg/L. This target has the potential to lower troughs and the occurrence of acute kidney injury (AKI). In summer 2020, we were the first to integrate DoseMeRx® Bayesian software into Epic OneChart®, our electronic medical record, to assist with dosing vancomycin. We sought to determine how doses and trough concentrations changed after software implementation. The study also aimed to establish the sample size needed to assess AKI rates. Methods This quasi-experimental study evaluated patients receiving ≥3 vancomycin doses before software integration (Q1 2020) and after (Q4 2020). Fifty patients in whom an adult 1-compartment model could be used and a trough concentration was measured were randomly selected from each period. Patients age ≤18 years, ≥200kg, or with pre-existing renal failure were excluded. AKI was defined using AKIN criteria of an increase in Scr of ≥ 0.3 mg/dL over 48 hours. Student’s t-test was used for continuous variables and Fischer exact test for categorical outcomes. Results In Q1, 299 patients had ≥3 vancomycin doses with 107 reviewed to reach 50 meeting inclusion criteria. In Q4, 346 had ≥3 doses and 94 were reviewed to include 50 patients. The primary reason for exclusion was no trough concentration. Demographics and indications for vancomycin were well matched. Skin/soft tissue infection was the most common indication for vancomycin (n=16, both Q1 and Q4). Sixteen patients were in the ICU with 8 on vasopressors before integration. There were 10 patients in the ICU and 6 on vasopressors after. Results in Table 1 were not significantly different (all p >0.05). AKI occurred in 5 (10%) patients before integration and 3 (6%) after. Based on this, a sample of 1442 patients, or approximately 15 months of vancomycin AUC-based dosing, will need to be analyzed to achieve 80% power to detect a significant difference in AKI. Table 1. Results related to vancomycin dosing before and after software integration Values reported as mean and standard deviation (SD) unless noted Conclusion Vancomycin doses and trough concentrations were similar in the two groups and AKI rates were numerically lower. This serves as an exploratory analysis to inform a larger study on the effects of integrating Bayesian dosing software for vancomycin dosing. Disclosures Bryan Alexander, PharmD, Astellas Pharma (Advisor or Review Panel member) Trevor C. Van Schooneveld, MD, FACP, BioFire (Individual(s) Involved: Self): Consultant, Scientific Research Study Investigator; Insmed (Individual(s) Involved: Self): Scientific Research Study Investigator; Merck (Individual(s) Involved: Self): Scientific Research Study Investigator; Rebiotix (Individual(s) Involved: Self): Scientific Research Study Investigator Scott J. Bergman, PharmD, FCCP, FIDSA, BCPS, BCIDP, Merck & Co., Inc (Grant/Research Support) Scott J. Bergman, PharmD, FCCP, FIDSA, BCPS, BCIDP, Merck & Co., Inc (Individual(s) Involved: Self): Research Grant or Support

Implementing an Application Programming Interface for PROMIS Measures at Three Medical Centers

Background There is an increasing body of literature advocating for the collection of patient-reported outcomes (PROs) in clinical care. Unfortunately, there are many barriers to integrating PRO measures, particularly computer adaptive tests (CATs), within electronic health records (EHRs), thereby limiting access to advances in PRO measures in clinical care settings. Objective To address this obstacle, we created and evaluated a software integration of an Application Programming Interface (API) service for administering and scoring Patient-Reported Outcomes Measurement Information System (PROMIS) measures with the EHR system. Methods We created a RESTful API and evaluated the technical feasibility and impact on clinical workflow at three academic medical centers. Results Collaborative teams (i.e., clinical, information technology [IT] and administrative staff) performed these integration efforts addressing issues such as software integration as well as impact on clinical workflow. All centers considered their implementation successful based on the high rate of completed PROMIS assessments (between January 2016 and January 2021) and minimal workflow disruptions. Conclusion These case studies demonstrate not only the feasibility but also the pathway for the integration of PROMIS CATs into the EHR and routine clinical care. All sites utilized diverse teams with support and commitment from institutional leadership, initial implementation in a single clinic, a process for monitoring and optimization, and use of custom software to minimize staff burden and error.

Integrated Design Methodology of Automated Guided Vehicles Based on Swarm Robotics

In recent years, collaborative robots have become one of the main drivers of Industry 4.0. Compared to industrial robots, automated guided vehicles (AGVs) are more productive, flexible, versatile, and safer. They are used in the smart factory to transport goods. Today, many producers and developers of industrial robots have entered the AGV sector. However, they face several challenges in designing AGV systems, such as the complexity and discontinuity of the design process, as well as the difficulty of defining a decentralized system decision. In this paper, we propose a new integrated design methodology based on swarm robotics to address the challenges of functional, physical, and software integration. This methodology includes two phases: a top-down phase from requirements specification to functional and structural modeling using the systems modeling language (SysML); with a bottom-up phase for model integration and implementation in the robot operating system (ROS). A case study of an automated guided vehicle (AGV) system was chosen to validate our design methodology and illustrate its contributions to the efficient design of AGVs. The novelty of this proposed methodology is the combination of SysML and ROS to address traceability management between the different design levels of AGV systems, in order to achieve functional, physical and software integration.

Matching Subsequence Music Retrieval in a Software Integration Environment

This paper firstly introduces the basic knowledge of music, proposes the detailed design of a music retrieval system based on the knowledge of music, and analyzes the feature extraction algorithm and matching algorithm by using the features of music. Feature extraction of audio data is the important research of this paper. In this paper, the main melody features, MFCC features, GFCC features, and rhythm features, are extracted from audio data and a feature fusion algorithm is proposed to achieve the fusion of GFCC features and rhythm features to form new features under the processing of principal component analysis (PCA) dimensionality reduction. After learning the main melody features, MFCC features, GFCC features, and rhythm features, based on the property that PCA dimensionality reduction can effectively reduce noise and improve retrieval efficiency, this paper proposes vector fusion by dimensionality reduction of GFCC features and rhythm features. The matching retrieval of audio features is an important task in music retrieval. In this paper, the DTW algorithm is chosen as the main algorithm for retrieving music. The classification retrieval of music is also achieved by the K-nearest neighbor algorithm. In this paper, after implementing the research and improvement of algorithms, these algorithms are integrated into the system to achieve audio preprocessing, feature extraction, feature postprocessing, and matching retrieval. This article uses 100 different kinds of MP3 format music as the music library and randomly selects 4 pieces each time, and it tests the system under different system parameters, recording duration, and environmental noise. Through the research of this paper, the efficiency of music retrieval is improved and theoretical support is provided for the design of music retrieval software integration system.

Position and force self-sensing piezoelectric valve with hysteresis compensation

This paper presents an approach for self-sensing piezoelectric valves. Both displacement and actuation force of piezoelectric valve can be simultaneously estimated from measurements of the charge and driving voltage. Only simple calibration is required before engineering application. The charge is obtained by software integration of the piezoelectric current sampled by DAQ card, which has the advantage of compensating leakage current by pre-estimating the leakage resistance. A PID controller is used to track the displacement, and a feedfoward compensation using Prandtl–Ishlinskii model is taken to compensate the piezoelectric hysteresis. The experimental results show that the controller can track target displacement within 2.03% of error, track force within 1.80% of error, and the maximum hysteresis of actuator is compensated from 27% to 3.75%.