Subjects -> COMPUTER SCIENCE (Total: 2313 journals)
    - ANIMATION AND SIMULATION (33 journals)
    - ARTIFICIAL INTELLIGENCE (133 journals)
    - AUTOMATION AND ROBOTICS (116 journals)
    - CLOUD COMPUTING AND NETWORKS (75 journals)
    - COMPUTER ARCHITECTURE (11 journals)
    - COMPUTER ENGINEERING (12 journals)
    - COMPUTER GAMES (23 journals)
    - COMPUTER PROGRAMMING (25 journals)
    - COMPUTER SCIENCE (1305 journals)
    - COMPUTER SECURITY (59 journals)
    - DATA BASE MANAGEMENT (21 journals)
    - DATA MINING (50 journals)
    - E-BUSINESS (21 journals)
    - E-LEARNING (30 journals)
    - ELECTRONIC DATA PROCESSING (23 journals)
    - IMAGE AND VIDEO PROCESSING (42 journals)
    - INFORMATION SYSTEMS (109 journals)
    - INTERNET (111 journals)
    - SOCIAL WEB (61 journals)
    - SOFTWARE (43 journals)
    - THEORY OF COMPUTING (10 journals)

COMPUTER SCIENCE (1305 journals)                  1 2 3 4 5 6 7 | Last

Showing 1 - 200 of 872 Journals sorted alphabetically
3D Printing and Additive Manufacturing     Full-text available via subscription   (Followers: 27)
Abakós     Open Access   (Followers: 3)
ACM Computing Surveys     Hybrid Journal   (Followers: 29)
ACM Inroads     Full-text available via subscription   (Followers: 1)
ACM Journal of Computer Documentation     Free   (Followers: 4)
ACM Journal on Computing and Cultural Heritage     Hybrid Journal   (Followers: 5)
ACM Journal on Emerging Technologies in Computing Systems     Hybrid Journal   (Followers: 11)
ACM SIGACCESS Accessibility and Computing     Free   (Followers: 2)
ACM SIGAPP Applied Computing Review     Full-text available via subscription  
ACM SIGBioinformatics Record     Full-text available via subscription  
ACM SIGEVOlution     Full-text available via subscription  
ACM SIGHIT Record     Full-text available via subscription  
ACM SIGHPC Connect     Full-text available via subscription  
ACM SIGITE Newsletter     Open Access   (Followers: 1)
ACM SIGMIS Database: the DATABASE for Advances in Information Systems     Hybrid Journal  
ACM SIGUCCS plugged in     Full-text available via subscription  
ACM SIGWEB Newsletter     Full-text available via subscription   (Followers: 4)
ACM Transactions on Accessible Computing (TACCESS)     Hybrid Journal   (Followers: 3)
ACM Transactions on Algorithms (TALG)     Hybrid Journal   (Followers: 13)
ACM Transactions on Applied Perception (TAP)     Hybrid Journal   (Followers: 3)
ACM Transactions on Architecture and Code Optimization (TACO)     Hybrid Journal   (Followers: 9)
ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP)     Hybrid Journal  
ACM Transactions on Autonomous and Adaptive Systems (TAAS)     Hybrid Journal   (Followers: 10)
ACM Transactions on Computation Theory (TOCT)     Hybrid Journal   (Followers: 11)
ACM Transactions on Computational Logic (TOCL)     Hybrid Journal   (Followers: 5)
ACM Transactions on Computer Systems (TOCS)     Hybrid Journal   (Followers: 19)
ACM Transactions on Computer-Human Interaction     Hybrid Journal   (Followers: 15)
ACM Transactions on Computing Education (TOCE)     Hybrid Journal   (Followers: 9)
ACM Transactions on Computing for Healthcare     Hybrid Journal  
ACM Transactions on Cyber-Physical Systems (TCPS)     Hybrid Journal   (Followers: 1)
ACM Transactions on Design Automation of Electronic Systems (TODAES)     Hybrid Journal   (Followers: 5)
ACM Transactions on Economics and Computation     Hybrid Journal  
ACM Transactions on Embedded Computing Systems (TECS)     Hybrid Journal   (Followers: 4)
ACM Transactions on Information Systems (TOIS)     Hybrid Journal   (Followers: 18)
ACM Transactions on Intelligent Systems and Technology (TIST)     Hybrid Journal   (Followers: 11)
ACM Transactions on Interactive Intelligent Systems (TiiS)     Hybrid Journal   (Followers: 6)
ACM Transactions on Internet of Things     Hybrid Journal   (Followers: 2)
ACM Transactions on Modeling and Performance Evaluation of Computing Systems (ToMPECS)     Hybrid Journal  
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)     Hybrid Journal   (Followers: 10)
ACM Transactions on Parallel Computing     Full-text available via subscription  
ACM Transactions on Reconfigurable Technology and Systems (TRETS)     Hybrid Journal   (Followers: 6)
ACM Transactions on Sensor Networks (TOSN)     Hybrid Journal   (Followers: 9)
ACM Transactions on Social Computing     Hybrid Journal  
ACM Transactions on Spatial Algorithms and Systems (TSAS)     Hybrid Journal   (Followers: 1)
ACM Transactions on Speech and Language Processing (TSLP)     Hybrid Journal   (Followers: 11)
ACM Transactions on Storage     Hybrid Journal  
ACS Applied Materials & Interfaces     Hybrid Journal   (Followers: 39)
Acta Informatica Malaysia     Open Access  
Acta Universitatis Cibiniensis. Technical Series     Open Access   (Followers: 1)
Ad Hoc Networks     Hybrid Journal   (Followers: 12)
Adaptive Behavior     Hybrid Journal   (Followers: 8)
Additive Manufacturing Letters     Open Access   (Followers: 3)
Advanced Engineering Materials     Hybrid Journal   (Followers: 32)
Advanced Science Letters     Full-text available via subscription   (Followers: 9)
Advances in Adaptive Data Analysis     Hybrid Journal   (Followers: 9)
Advances in Artificial Intelligence     Open Access   (Followers: 31)
Advances in Catalysis     Full-text available via subscription   (Followers: 7)
Advances in Computational Mathematics     Hybrid Journal   (Followers: 20)
Advances in Computer Engineering     Open Access   (Followers: 13)
Advances in Computer Science : an International Journal     Open Access   (Followers: 18)
Advances in Computing     Open Access   (Followers: 3)
Advances in Data Analysis and Classification     Hybrid Journal   (Followers: 52)
Advances in Engineering Software     Hybrid Journal   (Followers: 26)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 19)
Advances in Human-Computer Interaction     Open Access   (Followers: 19)
Advances in Image and Video Processing     Open Access   (Followers: 20)
Advances in Materials Science     Open Access   (Followers: 19)
Advances in Multimedia     Open Access   (Followers: 1)
Advances in Operations Research     Open Access   (Followers: 13)
Advances in Remote Sensing     Open Access   (Followers: 59)
Advances in Science and Research (ASR)     Open Access   (Followers: 8)
Advances in Technology Innovation     Open Access   (Followers: 5)
AEU - International Journal of Electronics and Communications     Hybrid Journal   (Followers: 8)
African Journal of Information and Communication     Open Access   (Followers: 6)
African Journal of Mathematics and Computer Science Research     Open Access   (Followers: 5)
AI EDAM     Hybrid Journal   (Followers: 2)
Air, Soil & Water Research     Open Access   (Followers: 6)
AIS Transactions on Human-Computer Interaction     Open Access   (Followers: 5)
Al-Qadisiyah Journal for Computer Science and Mathematics     Open Access   (Followers: 2)
AL-Rafidain Journal of Computer Sciences and Mathematics     Open Access   (Followers: 3)
Algebras and Representation Theory     Hybrid Journal  
Algorithms     Open Access   (Followers: 13)
American Journal of Computational and Applied Mathematics     Open Access   (Followers: 8)
American Journal of Computational Mathematics     Open Access   (Followers: 6)
American Journal of Information Systems     Open Access   (Followers: 4)
American Journal of Sensor Technology     Open Access   (Followers: 2)
Analog Integrated Circuits and Signal Processing     Hybrid Journal   (Followers: 15)
Animation Practice, Process & Production     Hybrid Journal   (Followers: 4)
Annals of Combinatorics     Hybrid Journal   (Followers: 3)
Annals of Data Science     Hybrid Journal   (Followers: 14)
Annals of Mathematics and Artificial Intelligence     Hybrid Journal   (Followers: 16)
Annals of Pure and Applied Logic     Open Access   (Followers: 4)
Annals of Software Engineering     Hybrid Journal   (Followers: 12)
Annual Reviews in Control     Hybrid Journal   (Followers: 7)
Anuario Americanista Europeo     Open Access  
Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 3)
Applied and Computational Harmonic Analysis     Full-text available via subscription  
Applied Artificial Intelligence: An International Journal     Hybrid Journal   (Followers: 17)
Applied Categorical Structures     Hybrid Journal   (Followers: 4)
Applied Clinical Informatics     Hybrid Journal   (Followers: 4)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 16)
Applied Computer Systems     Open Access   (Followers: 6)
Applied Computing and Geosciences     Open Access   (Followers: 3)
Applied Mathematics and Computation     Hybrid Journal   (Followers: 31)
Applied Medical Informatics     Open Access   (Followers: 11)
Applied Numerical Mathematics     Hybrid Journal   (Followers: 4)
Applied Soft Computing     Hybrid Journal   (Followers: 13)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 5)
Applied System Innovation     Open Access   (Followers: 1)
Archive of Applied Mechanics     Hybrid Journal   (Followers: 4)
Archive of Numerical Software     Open Access  
Archives and Museum Informatics     Hybrid Journal   (Followers: 97)
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 5)
arq: Architectural Research Quarterly     Hybrid Journal   (Followers: 7)
Array     Open Access   (Followers: 1)
Artifact : Journal of Design Practice     Open Access   (Followers: 8)
Artificial Life     Hybrid Journal   (Followers: 7)
Asian Journal of Computer Science and Information Technology     Open Access   (Followers: 3)
Asian Journal of Control     Hybrid Journal  
Asian Journal of Research in Computer Science     Open Access   (Followers: 4)
Assembly Automation     Hybrid Journal   (Followers: 2)
Automatic Control and Computer Sciences     Hybrid Journal   (Followers: 6)
Automatic Documentation and Mathematical Linguistics     Hybrid Journal   (Followers: 5)
Automatica     Hybrid Journal   (Followers: 13)
Automatika : Journal for Control, Measurement, Electronics, Computing and Communications     Open Access  
Automation in Construction     Hybrid Journal   (Followers: 8)
Balkan Journal of Electrical and Computer Engineering     Open Access  
Basin Research     Hybrid Journal   (Followers: 7)
Behaviour & Information Technology     Hybrid Journal   (Followers: 32)
BenchCouncil Transactions on Benchmarks, Standards, and Evaluations     Open Access   (Followers: 4)
Big Data and Cognitive Computing     Open Access   (Followers: 5)
Big Data Mining and Analytics     Open Access   (Followers: 10)
Biodiversity Information Science and Standards     Open Access   (Followers: 1)
Bioinformatics     Hybrid Journal   (Followers: 219)
Bioinformatics Advances : Journal of the International Society for Computational Biology     Open Access   (Followers: 1)
Biomedical Engineering     Hybrid Journal   (Followers: 11)
Biomedical Engineering and Computational Biology     Open Access   (Followers: 11)
Briefings in Bioinformatics     Hybrid Journal   (Followers: 43)
British Journal of Educational Technology     Hybrid Journal   (Followers: 93)
Bulletin of Taras Shevchenko National University of Kyiv. Series: Physics and Mathematics     Open Access  
c't Magazin fuer Computertechnik     Full-text available via subscription   (Followers: 1)
Cadernos do IME : Série Informática     Open Access  
CALCOLO     Hybrid Journal  
CALICO Journal     Full-text available via subscription   (Followers: 1)
Calphad     Hybrid Journal  
Canadian Journal of Electrical and Computer Engineering     Full-text available via subscription   (Followers: 14)
Catalysis in Industry     Hybrid Journal  
CCF Transactions on High Performance Computing     Hybrid Journal  
CCF Transactions on Pervasive Computing and Interaction     Hybrid Journal  
CEAS Space Journal     Hybrid Journal   (Followers: 6)
Cell Communication and Signaling     Open Access   (Followers: 3)
Central European Journal of Computer Science     Hybrid Journal   (Followers: 4)
CERN IdeaSquare Journal of Experimental Innovation     Open Access  
Chaos, Solitons & Fractals     Hybrid Journal   (Followers: 1)
Chaos, Solitons & Fractals : X     Open Access   (Followers: 1)
Chemometrics and Intelligent Laboratory Systems     Hybrid Journal   (Followers: 13)
ChemSusChem     Hybrid Journal   (Followers: 7)
China Communications     Full-text available via subscription   (Followers: 8)
Chinese Journal of Catalysis     Full-text available via subscription   (Followers: 2)
Chip     Full-text available via subscription   (Followers: 3)
Ciencia     Open Access  
CIN : Computers Informatics Nursing     Hybrid Journal   (Followers: 11)
Circuits and Systems     Open Access   (Followers: 16)
CLEI Electronic Journal     Open Access  
Clin-Alert     Hybrid Journal   (Followers: 1)
Clinical eHealth     Open Access  
Cluster Computing     Hybrid Journal   (Followers: 1)
Cognitive Computation     Hybrid Journal   (Followers: 2)
Cognitive Computation and Systems     Open Access  
COMBINATORICA     Hybrid Journal  
Combinatorics, Probability and Computing     Hybrid Journal   (Followers: 4)
Combustion Theory and Modelling     Hybrid Journal   (Followers: 18)
Communication Methods and Measures     Hybrid Journal   (Followers: 12)
Communication Theory     Hybrid Journal   (Followers: 29)
Communications in Algebra     Hybrid Journal   (Followers: 1)
Communications in Partial Differential Equations     Hybrid Journal   (Followers: 2)
Communications of the ACM     Full-text available via subscription   (Followers: 59)
Communications of the Association for Information Systems     Open Access   (Followers: 15)
Communications on Applied Mathematics and Computation     Hybrid Journal   (Followers: 1)
COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering     Hybrid Journal   (Followers: 4)
Complex & Intelligent Systems     Open Access   (Followers: 1)
Complex Adaptive Systems Modeling     Open Access  
Complex Analysis and Operator Theory     Hybrid Journal   (Followers: 2)
Complexity     Hybrid Journal   (Followers: 8)
Computación y Sistemas     Open Access  
Computation     Open Access   (Followers: 1)
Computational and Applied Mathematics     Hybrid Journal   (Followers: 3)
Computational and Mathematical Methods     Hybrid Journal  
Computational and Mathematical Methods in Medicine     Open Access   (Followers: 2)
Computational and Mathematical Organization Theory     Hybrid Journal   (Followers: 1)
Computational and Structural Biotechnology Journal     Open Access   (Followers: 1)
Computational and Theoretical Chemistry     Hybrid Journal   (Followers: 11)
Computational Astrophysics and Cosmology     Open Access   (Followers: 6)
Computational Biology and Chemistry     Hybrid Journal   (Followers: 13)
Computational Biology Journal     Open Access   (Followers: 6)
Computational Brain & Behavior     Hybrid Journal   (Followers: 1)
Computational Chemistry     Open Access   (Followers: 3)
Computational Communication Research     Open Access   (Followers: 1)
Computational Complexity     Hybrid Journal   (Followers: 5)
Computational Condensed Matter     Open Access   (Followers: 1)

        1 2 3 4 5 6 7 | Last

Similar Journals
Journal Cover
Applied Clinical Informatics
Journal Prestige (SJR): 0.624
Citation Impact (citeScore): 1
Number of Followers: 4  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1869-0327
Published by Thieme Publishing Group Homepage  [233 journals]
  • Veteran and Staff Experience from a Pilot Program of Health Care
           System–Distributed Wearable Devices and Data Sharing

    • Free pre-print version: Loading...

      Authors: Saleem; Jason J., Wilck, Nancy R., Murphy, John J., Herout, Jennifer
      Pages: 532 - 540
      Abstract: Objective The growing trend to use wearable devices to track activity and health data has the potential to positively impact the patient experience with their health care at home and with their care team. As part of a pilot program, the U.S. Department of Veterans Affairs (VA) distributed Fitbits to Veterans through four VA medical centers. Our objective was to assess the program from both Veterans' and clinicians' viewpoints. Specifically, we aimed to understand barriers to Fitbit setup and use for Veterans, including syncing devices with a VA mobile application (app) to share data, and assess the perceived value of the device functions and ability to share information from the Fitbit with their care team. In addition, we explored the clinicians' perspective, including how they expected to use the patient-generated health data (PGHD). Methods We performed semi-structured interviews with 26 Veterans and 16 VA clinicians to assess the program. Responses to each question were summarized in order of frequency of occurrence across participants and audited by an independent analyst for accuracy. Results Our findings reveal that despite setup challenges, there is support for the use of Fitbits to engage Veterans and help manage their health. Clinicians believed there were benefits for having Veterans use the Fitbits and expected to use the PGHD in a variety of ways as part of the Veterans' care plans, including monitoring progress toward health behavior goals. Veterans were overwhelmingly enthusiastic about using the Fitbits; this enthusiasm seems to extend beyond the 3 month “novelty period.” Conclusion The pilot program for distributing Fitbits to Veterans appears to be successful from both Veterans' and clinicians' perspectives and suggests that expanded use of wearable devices should be considered. Future studies will need to carefully consider how to incorporate the PGHD into the electronic health record and clinical workflow.
      Citation: Appl Clin Inform 2022; 13: 532-540
      PubDate: 2022-05-25T00:00:00+01:00
      DOI: 10.1055/s-0042-1748857
      Issue No: Vol. 13, No. 03 (2022)
       
  • Clinical Decision Support Stewardship: Best Practices and Techniques to
           Monitor and Improve Interruptive Alerts

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      Authors: Chaparro; Juan D., Beus, Jonathan M., Dziorny, Adam C., Hagedorn, Philip A., Hernandez, Sean, Kandaswamy, Swaminathan, Kirkendall, Eric S., McCoy, Allison B., Muthu, Naveen, Orenstein, Evan W.
      Pages: 560 - 568
      Abstract: Interruptive clinical decision support systems, both within and outside of electronic health records, are a resource that should be used sparingly and monitored closely. Excessive use of interruptive alerting can quickly lead to alert fatigue and decreased effectiveness and ignoring of alerts. In this review, we discuss the evidence for effective alert stewardship as well as practices and methods we have found useful to assess interruptive alert burden, reduce excessive firings, optimize alert effectiveness, and establish quality governance at our institutions. We also discuss the importance of a holistic view of the alerting ecosystem beyond the electronic health record.
      Citation: Appl Clin Inform 2022; 13: 560-568
      PubDate: 2022-05-25T00:00:00+01:00
      DOI: 10.1055/s-0042-1748856
      Issue No: Vol. 13, No. 03 (2022)
       
  • Diversity in Machine Learning: A Systematic Review of Text-Based
           Diagnostic Applications

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      Authors: Fitzsimmons; Lane, Dewan, Maya, Dexheimer, Judith W.
      Pages: 569 - 582
      Abstract: Objective As the storage of clinical data has transitioned into electronic formats, medical informatics has become increasingly relevant in providing diagnostic aid. The purpose of this review is to evaluate machine learning models that use text data for diagnosis and to assess the diversity of the included study populations. Methods We conducted a systematic literature review on three public databases. Two authors reviewed every abstract for inclusion. Articles were included if they used or developed machine learning algorithms to aid in diagnosis. Articles focusing on imaging informatics were excluded. Results From 2,260 identified papers, we included 78. Of the machine learning models used, neural networks were relied upon most frequently (44.9%). Studies had a median population of 661.5 patients, and diseases and disorders of 10 different body systems were studied. Of the 35.9% (N = 28) of papers that included race data, 57.1% (N = 16) of study populations were majority White, 14.3% were majority Asian, and 7.1% were majority Black. In 75% (N = 21) of papers, White was the largest racial group represented. Of the papers included, 43.6% (N = 34) included the sex ratio of the patient population. Discussion With the power to build robust algorithms supported by massive quantities of clinical data, machine learning is shaping the future of diagnostics. Limitations of the underlying data create potential biases, especially if patient demographics are unknown or not included in the training. Conclusion As the movement toward clinical reliance on machine learning accelerates, both recording demographic information and using diverse training sets should be emphasized. Extrapolating algorithms to demographics beyond the original study population leaves large gaps for potential biases.
      Citation: Appl Clin Inform 2022; 13: 569-582
      PubDate: 2022-05-25T00:00:00+01:00
      DOI: 10.1055/s-0042-1749119
      Issue No: Vol. 13, No. 03 (2022)
       
  • A Data-Driven Assessment of the U.S. Health Informatics Programs and Job
           Market

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      Authors: Patel; Jay S., Vo, Hoa, Nguyen, An, Dzomba, Bari, Wu, Huanmei
      Pages: 327 - 338
      Abstract: Background Health Informatics (HI) is an interdisciplinary field, integrating health sciences, computer science, information science, and cognitive science to assist health information management, analysis, and utilization. As the HI field is broad, it is impossible that a student will be able to master all the diverse HI topics. Thus, it is important to train the HI students based on the offering of the various HI programs and needs of the current market. This project will study the U.S. HI programs, training materials, HI job market, the skillset required by the employers, competencies taught in HI programs, and comparisons between them. Methods We collected the training information for the 238 U.S. universities that offered MS, PhD, or postbaccalaureate certificate programs in HI or related professions. Next, we explored the HI job market by randomly checking 200 jobs and their required skillsets and domain knowledge. Then, we compared these skillsets with those offered by the HI programs and identified the gaps and overlaps for program enhancements. Results Among the 238 U.S. universities, 94 universities offer HI programs: 92 universities with MS (Master of Science), 43 with doctoral, 42 with both MS and doctoral, and 54 with certificate programs. The most offered HI courses are related to practicum, data analytics, research, and ethics. For the HI job postings, the three most technical skillsets required in HI job posting are data analysis, database management, and knowledge of electronic health records. However, only 58% of HI programs offer courses in database management and analytics. Compared with American Medical Informatics Association's recommended 10 fundamental domains, the HI curriculum generally lacks training in socio-technical systems, social-behavioral aspects of health, and interprofessional collaborative practice. Conclusion There are gaps between the industry expectations of HI and the training received in HI programs. Advance level technical courses are needed in HI programs to meet industry expectations.
      Citation: Appl Clin Inform 2022; 13: 327-338
      PubDate: 2022-03-30T00:00:00+01:00
      DOI: 10.1055/s-0042-1743242
      Issue No: Vol. 13, No. 02 (2022)
       
  • Toward a Learning Health Care System: A Systematic Review and
           Evidence-Based Conceptual Framework for Implementation of Clinical
           Analytics in a Digital Hospital

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      Authors: Lim; Han Chang, Austin, Jodie A., van der Vegt, Anton H., Rahimi, Amir Kamel, Canfell, Oliver J., Mifsud, Jayden, Pole, Jason D., Barras, Michael A., Hodgson, Tobias, Shrapnel, Sally, Sullivan, Clair M.
      Pages: 339 - 354
      Abstract: Objective A learning health care system (LHS) uses routinely collected data to continuously monitor and improve health care outcomes. Little is reported on the challenges and methods used to implement the analytics underpinning an LHS. Our aim was to systematically review the literature for reports of real-time clinical analytics implementation in digital hospitals and to use these findings to synthesize a conceptual framework for LHS implementation. Methods Embase, PubMed, and Web of Science databases were searched for clinical analytics derived from electronic health records in adult inpatient and emergency department settings between 2015 and 2021. Evidence was coded from the final study selection that related to (1) dashboard implementation challenges, (2) methods to overcome implementation challenges, and (3) dashboard assessment and impact. The evidences obtained, together with evidence extracted from relevant prior reviews, were mapped to an existing digital health transformation model to derive a conceptual framework for LHS analytics implementation. Results A total of 238 candidate articles were reviewed and 14 met inclusion criteria. From the selected studies, we extracted 37 implementation challenges and 64 methods employed to overcome such challenges. We identified common approaches for evaluating the implementation of clinical dashboards. Six studies assessed clinical process outcomes and only four studies evaluated patient health outcomes. A conceptual framework for implementing the analytics of an LHS was developed. Conclusion Health care organizations face diverse challenges when trying to implement real-time data analytics. These challenges have shifted over the past decade. While prior reviews identified fundamental information problems, such as data size and complexity, our review uncovered more postpilot challenges, such as supporting diverse users, workflows, and user-interface screens. Our review identified practical methods to overcome these challenges which have been incorporated into a conceptual framework. It is hoped this framework will support health care organizations deploying near-real-time clinical dashboards and progress toward an LHS.
      Citation: Appl Clin Inform 2022; 13: 339-354
      PubDate: 2022-04-06T00:00:00+01:00
      DOI: 10.1055/s-0042-1743243
      Issue No: Vol. 13, No. 02 (2022)
       
  • Improving Provisioning of an Inpatient Portal: Perspectives from Nursing
           Staff

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      Authors: Gaughan; Alice A., Walker, Daniel M., Sova, Lindsey N., Vink, Shonda, Moffatt-Bruce, Susan D., McAlearney, Ann Scheck
      Pages: 355 - 362
      Abstract: Background Inpatient portals are recognized to provide benefits for both patients and providers, yet the process of provisioning tablets to patients by staff has been difficult for many hospitals. Objective Our study aimed to identify and describe practices important for provisioning an inpatient portal from the perspectives of nursing staff and provide insight to enable hospitals to address challenges related to provisioning workflow for the inpatient portal accessible on a tablet. Methods Qualitative interviews were conducted with 210 nursing staff members across 26 inpatient units in six hospitals within The Ohio State University Wexner Medical Center (OSUWMC) following the introduction of tablets providing access to an inpatient portal, MyChart Bedside (MCB). Interviews asked questions focused on nursing staffs' experiences relative to MCB tablet provisioning. Verbatim interview transcripts were coded using thematic analysis to identify factors associated with tablet provisioning. Unit provisioning performance was established using data stored in the OSUWMC electronic health record about provisioning status. Provisioning rates were divided into tertiles to create three levels of provisioning performance: (1) higher; (2) average; and (3) lower. Results Three themes emerged as critical strategies contributing to MCB tablet provisioning success on higher-performing units: (1) establishing a feasible process for MCB provisioning; (2) having persistent unit-level MCB tablet champions; and (3) having unit managers actively promote MCB tablets. These strategies were described differently by staff from the higher-performing units when compared with characterizations of the provisioning process by staff from lower-performing units. Conclusion As inpatient portals are recognized as a powerful tool that can increase patients' access to information and enhance their care experience, implementing the strategies we identified may help hospitals' efforts to improve provisioning and increase their patients' engagement in their health care.
      Citation: Appl Clin Inform 2022; 13: 355-362
      PubDate: 2022-04-13T00:00:00+01:00
      DOI: 10.1055/s-0042-1743561
      Issue No: Vol. 13, No. 02 (2022)
       
  • Searching of Clinical Trials Made Easier in cBioPortal Using Patients'
           Genetic and Clinical Profiles

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      Authors: Unberath; Philipp, Mahlmeister, Lukas, Reimer, Niklas, Busch, Hauke, Boerries, Melanie, Christoph, Jan
      Pages: 363 - 369
      Abstract: Background Molecular tumor boards (MTBs) cope with the complexity of an increased usage of genome sequencing data in cancer treatment. As for most of these patients, guideline-based therapy options are exhausted, finding matching clinical trials is crucial. This search process is often performed manually and therefore time consuming and complex due to the heterogeneous and challenging dataset. Objectives In this study, a prototype for a search tool was developed to demonstrate how cBioPortal as a clinical and genomic patient data source can be integrated with ClinicalTrials.gov, a database of clinical studies to simplify the search for trials based on genetic and clinical data of a patient. The design of this tool should rest on the specific needs of MTB participants and the architecture of the integration should be as lightweight as possible and should not require manual curation of trial data in advance with the goal of quickly and easily finding a matching study. Methods Based on a requirements analysis, interviewing MTB experts, a prototype was developed. It was further refined using a user-centered development process with multiple feedback loops. Finally, the usability of the application was evaluated with user interviews including the thinking-aloud protocol and the system usability scale (SUS) questionnaire. Results The integration of ClinicalTrials.gov in cBioPortal is achieved by a new tab in the patient view where the genomic profile for the search is prefilled and additional parameters can be adjusted. These parameters are then used to query the application programming interface (API) of ClinicalTrials.gov. The returned search results subsequently are ranked and presented to the user. The evaluation of the application resulted in an SUS score of 83.5. Conclusion This work demonstrates the integration of cBioPortal with ClinicalTrials.gov to use clinical and genomic patient data to search for appropriate trials within an MTB.
      Citation: Appl Clin Inform 2022; 13: 363-369
      PubDate: 2022-03-30T00:00:00+01:00
      DOI: 10.1055/s-0042-1743560
      Issue No: Vol. 13, No. 02 (2022)
       
  • Visualizing Opioid-Use Variation in a Pediatric Perioperative Dashboard

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      Authors: Safranek; Conrad W., Feitzinger, Lauren, Joyner, Alice Kate Cummings, Woo, Nicole, Smith, Virgil, Souza, Elizabeth De, Vasilakis, Christos, Anderson, Thomas Anthony, Fehr, James, Shin, Andrew Y., Scheinker, David, Wang, Ellen, Xie, James
      Pages: 370 - 379
      Abstract: Background Anesthesiologists integrate numerous variables to determine an opioid dose that manages patient nociception and pain while minimizing adverse effects. Clinical dashboards that enable physicians to compare themselves to their peers can reduce unnecessary variation in patient care and improve outcomes. However, due to the complexity of anesthetic dosing decisions, comparative visualizations of opioid-use patterns are complicated by case-mix differences between providers. Objectives This single-institution case study describes the development of a pediatric anesthesia dashboard and demonstrates how advanced computational techniques can facilitate nuanced normalization techniques, enabling meaningful comparisons of complex clinical data. Methods We engaged perioperative-care stakeholders at a tertiary care pediatric hospital to determine patient and surgical variables relevant to anesthesia decision-making and to identify end-user requirements for an opioid-use visualization tool. Case data were extracted, aggregated, and standardized. We performed multivariable machine learning to identify and understand key variables. We integrated interview findings and computational algorithms into an interactive dashboard with normalized comparisons, followed by an iterative process of improvement and implementation. Results The dashboard design process identified two mechanisms—interactive data filtration and machine-learning-based normalization—that enable rigorous monitoring of opioid utilization with meaningful case-mix adjustment. When deployed with real data encompassing 24,332 surgical cases, our dashboard identified both high and low opioid-use outliers with associated clinical outcomes data. Conclusion A tool that gives anesthesiologists timely data on their practice patterns while adjusting for case-mix differences empowers physicians to track changes and variation in opioid administration over time. Such a tool can successfully trigger conversation amongst stakeholders in support of continuous improvement efforts. Clinical analytics dashboards can enable physicians to better understand their practice and provide motivation to change behavior, ultimately addressing unnecessary variation in high impact medication use and minimizing adverse effects.
      Citation: Appl Clin Inform 2022; 13: 370-379
      PubDate: 2022-03-23T00:00:00+0100
      DOI: 10.1055/s-0042-1744387
      Issue No: Vol. 13, No. 02 (2022)
       
  • Design, Usability, and Acceptability of a Needs-Based, Automated Dashboard
           to Provide Individualized Patient-Care Data to Pediatric Residents

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      Authors: Yarahuan; Julia K.W., Lo, Huay-Ying, Bass, Lanessa, Wright, Jeff, Hess, Lauren M.
      Pages: 380 - 390
      Abstract: Background and Objectives Pediatric residency programs are required by the Accreditation Council for Graduate Medical Education to provide residents with patient-care and quality metrics to facilitate self-identification of knowledge gaps to prioritize improvement efforts. Trainees are interested in receiving this data, but this is a largely unmet need. Our objectives were to (1) design and implement an automated dashboard providing individualized data to residents, and (2) examine the usability and acceptability of the dashboard among pediatric residents. Methods We developed a dashboard containing individualized patient-care data for pediatric residents with emphasis on needs identified by residents and residency leadership. To build the dashboard, we created a connection from a clinical data warehouse to data visualization software. We allocated patients to residents based on note authorship and created individualized reports with masked identities that preserved anonymity. After development, we conducted usability and acceptability testing with 11 resident users utilizing a mixed-methods approach. We conducted interviews and anonymous surveys which evaluated technical features of the application, ease of use, as well as users' attitudes toward using the dashboard. Categories and subcategories from usability interviews were identified using a content analysis approach. Results Our dashboard provides individualized metrics including diagnosis exposure counts, procedure counts, efficiency metrics, and quality metrics. In content analysis of the usability testing interviews, the most frequently mentioned use of the dashboard was to aid a resident's self-directed learning. Residents had few concerns about the dashboard overall. Surveyed residents found the dashboard easy to use and expressed intention to use the dashboard in the future. Conclusion Automated dashboards may be a solution to the current challenge of providing trainees with individualized patient-care data. Our usability testing revealed that residents found our dashboard to be useful and that they intended to use this tool to facilitate development of self-directed learning plans.
      Citation: Appl Clin Inform 2022; 13: 380-390
      PubDate: 2022-03-16T00:00:00+0100
      DOI: 10.1055/s-0042-1744388
      Issue No: Vol. 13, No. 02 (2022)
       
  • Qualitative Analysis of Team Communication with a Clinical Texting System
           at a Midwestern Academic Hospital

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      Authors: Lee; Joy L., Kara, Areeba, Huffman, Monica, Matthias, Marianne S., Radecki, Bethany, Savoy, April, Schaffer, Jason T., Weiner, Michael
      Pages: 391 - 397
      Abstract: Background Hospitals are increasingly replacing pagers with clinical texting systems that allow users to use smartphones to send messages while maintaining compliance for privacy and security. As more institutions adopt such systems, the need to understand the impact of such transitions on team communication becomes ever more significant. Methods We conducted focus groups with hospitalists and individual interviews with nurses at one academic medical center in the Midwest. All interviews and focus groups were audiorecorded, transcribed, and deidentified for analysis. All transcripts and notes were independently read by two members of the research team and coded for themes. Results Twenty-one hospitalists and eight nurses participated in the study. Although study participants spoke favorably of texting, they identified more dissatisfactions with texting than benefits. There were disagreements regarding appropriate texting practices both within and between the hospitalists and nurses. Conclusion Despite the benefits of texting, there is room for improving team communication and understanding in the realm of clinical texting. A lack of shared understanding regarding when and how to use texting may require long-term solutions that address teamwork and appropriateness.
      Citation: Appl Clin Inform 2022; 13: 391-397
      PubDate: 2022-03-16T00:00:00+0100
      DOI: 10.1055/s-0042-1744389
      Issue No: Vol. 13, No. 02 (2022)
       
  • The Clinical Informatics Practice Pathway Should Be Maintained for Now but
           Transformed into an Alternative to In-Place Fellowships

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      Appl Clin Inform 2022; 13: 398-399
      DOI: 10.1055/s-0042-1745722



      Georg Thieme Verlag KG Rüdigerstraße 14, 70469 Stuttgart, Germany

      Artikel in Thieme eJournals:
      Inhaltsverzeichnis     Volltext

      Appl Clin Inform 2022; 13: 398-3992022-03-23T00:00:00+0100
      Issue No: Vol. 13, No. 02 (2022)
       
  • Improving COVID-19 Research of University Hospitals in Germany: Formative
           Usability Evaluation of the CODEX Feasibility Portal

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      Authors: Sedlmayr; Brita, Sedlmayr, Martin, Kroll, Björn, Prokosch, Hans-Ulrich, Gruendner, Julian, Schüttler, Christina
      Pages: 400 - 409
      Abstract: Background Within the German “Network University Medicine,” a portal is to be developed to enable researchers to query on novel coronavirus disease 2019 (COVID-19) data from university hospitals for assessing the feasibility of a clinical study. Objectives The usability of a prototype for federated feasibility queries was evaluated to identify design strengths and weaknesses and derive improvement recommendations for further development. Methods In the course of a remote usability test with the thinking-aloud method and posttask interviews, 15 clinical researchers evaluated the usability of a prototype of the Feasibility Portal. The identified usability problems were rated according to severity, and improvement recommendations were derived. Results The design of the prototype was rated as simple, intuitive, and as usable with little effort. The usability test reported a total of 26 problems, 8 of these were rated as “critical.” Usability problems and revision recommendations focus primarily on improving the visual distinguishability of selected inclusion and exclusion criteria, enabling a flexible approach to criteria linking, and enhancing the free-text search. Conclusion Improvement proposals were developed for these user problems which will guide further development and the adaptation of the portal to user needs. This is an important prerequisite for correct and efficient use in everyday clinical work in the future. Results can provide developers of similar systems with a good starting point for interface conceptualizations. The methodological approach/the developed test guideline can serve as a template for similar evaluations.
      Citation: Appl Clin Inform 2022; 13: 400-409
      PubDate: 2022-04-20T00:00:00+01:00
      DOI: 10.1055/s-0042-1744549
      Issue No: Vol. 13, No. 02 (2022)
       
  • An Exploratory Study of Allied Health Students' Experiences of Electronic
           Medical Records During Placements

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      Authors: Baysari; Melissa Therese, Wells, Jacqueline, Ekpo, Ernest, Makeham, Meredith, Penm, Jonathan, Alexander, Nathaniel, Holden, Alexander, Ubeja, Raj, McAllister, Sue
      Pages: 410 - 418
      Abstract: Background Allowing students to access and document in electronic medical records (eMRs) during clinical placements is viewed as critical for ensuring that graduates have a high level of digital proficiency prior to entering the workforce. Limited studies have explored student access to eMRs in health disciplines outside of medicine and nursing. Objective Our main objective was to examine allied health students' experiences and perceptions of the opportunity to develop eMR competencies during their placement, across a range of allied health disciplines and placement settings. Methods An explanatory sequential design was used, comprising a quantitative survey (n = 102) followed by qualitative semi-structured interviews (n = 6) with senior allied health students to explore their experiences and perceptions of eMR access during placements. Results Of the 93 students who responded to the question about their placement eMR, nine (10%) reported their placement site did not use an eMR and four students reported that they were not allowed to access the eMR during their placement. Most students (64%, 54 out of 84) accessed the system using their own credentials, but 31% (26 out of 84) used someone else's log-in and password. Students were satisfied with the eMR training and support received while on placement, but there was significant variability across sites on the level of training and support provided. All students believed that eMR access was beneficial for learning and preparation for work, improved delivery of care, taking ownership of work, and feeling responsible for patient care. Conclusion Providing students with access to eMRs during placements is fundamental to the development of a student's professional identity and to recognizing their role in the delivery of interprofessional patient care. For graduates to be equipped to effectively contribute to multi-disciplinary care in a digital health environment, universities need to work with practice partners to standardize and formalize eMR access, registration, training, and support, and to provide students with early exposure and training on eMRs in university courses.
      Citation: Appl Clin Inform 2022; 13: 410-418
      PubDate: 2022-04-06T00:00:00+01:00
      DOI: 10.1055/s-0042-1744550
      Issue No: Vol. 13, No. 02 (2022)
       
  • Impact of a Vendor-Developed Opioid Clinical Decision Support Intervention
           on Adherence to Prescribing Guidelines, Opioid Prescribing, and Rates of
           Opioid-Related Encounters

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      Authors: Pierce; Robert P., Eskridge, Bernie, Ross, Brandi, Wright, Matthew, Selva, Thomas
      Pages: 419 - 430
      Abstract: Background Provider prescribing practices contribute to an excess of opioid-related deaths in the United States. Clinical guidelines exist to assist providers with improving prescribing practices and promoting patient safety. Clinical decision support systems (CDSS) may promote adherence to these guidelines and improve prescribing practices. The aim of this project was to improve opioid guideline adherence, prescribing practices, and rates of opioid-related encounters through the implementation of an opioid CDSS. Methods A vendor-developed, provider-targeted CDSS package was implemented in a multi-location academic health center. An interrupted time-series analysis was performed, evaluating 30 weeks pre- and post-implementation time periods. Outcomes were derived from vendor-supplied key performance indicators and directly from the electronic health record (EHR) database. Opioid-prescribing outcomes included count of opioid prescriptions, morphine milligram equivalents per prescription, counts of opioids with concurrent benzodiazepines, and counts of short-acting opioids in opioid-naïve patients. Encounter outcomes included rates of encounters for opioid abuse and dependence and rates of encounters for opioid poisoning and overdose. Guideline adherence outcomes included rates of provision of naloxone and documentation of opioid treatment agreements. Results The opioid CDSS generated an average of 1,637 alerts per week. Rates of provision of naloxone and opioid treatment agreements improved after CDSS implementation. Vendor-supplied prescribing outcomes were consistent with prescribing outcomes derived directly from the EHR, but all prescribing and encounter outcomes were unchanged. Conclusion A vendor-developed, provider-targeted opioid CDSS did not improve opioid-prescribing practices or rates of opioid-related encounters. The CDSS improved some measures of provider adherence to opioid-prescribing guidelines. Further work is needed to determine the optimal configuration of opioid CDSS so that opioid-prescribing patterns are appropriately modified and encounter outcomes are improved.
      Citation: Appl Clin Inform 2022; 13: 419-430
      PubDate: 2022-04-20T00:00:00+01:00
      DOI: 10.1055/s-0042-1745830
      Issue No: Vol. 13, No. 02 (2022)
       
  • Monitoring Approaches for a Pediatric Chronic Kidney Disease Machine
           Learning Model

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      Authors: Morse; Keith E., Brown, Conner, Fleming, Scott, Todd, Irene, Powell, Austin, Russell, Alton, Scheinker, David, Sutherland, Scott M., Lu, Jonathan, Watkins, Brendan, Shah, Nigam H., Pageler, Natalie M., Palma, Jonathan P.
      Pages: 431 - 438
      Abstract: Objective The purpose of this study is to evaluate the ability of three metrics to monitor for a reduction in performance of a chronic kidney disease (CKD) model deployed at a pediatric hospital. Methods The CKD risk model estimates a patient's risk of developing CKD 3 to 12 months following an inpatient admission. The model was developed on a retrospective dataset of 4,879 admissions from 2014 to 2018, then run silently on 1,270 admissions from April to October, 2019. Three metrics were used to monitor its performance during the silent phase: (1) standardized mean differences (SMDs); (2) performance of a “membership model”; and (3) response distribution analysis. Observed patient outcomes for the 1,270 admissions were used to calculate prospective model performance and the ability of the three metrics to detect performance changes. Results The deployed model had an area under the receiver-operator curve (AUROC) of 0.63 in the prospective evaluation, which was a significant decrease from an AUROC of 0.76 on retrospective data (p = 0.033). Among the three metrics, SMDs were significantly different for 66/75 (88%) of the model's input variables (p
      Citation: Appl Clin Inform 2022; 13: 431-438
      PubDate: 2022-05-04T00:00:00+01:00
      DOI: 10.1055/s-0042-1746168
      Issue No: Vol. 13, No. 02 (2022)
       
  • 25 × 5 Symposium to Reduce Documentation Burden:
           Report-out and Call for Action

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      Authors: Hobensack; Mollie, Levy, Deborah R., Cato, Kenrick, Detmer, Don E., Johnson, Kevin B., Williamson, Jeffrey, Murphy, Judy, Moy, Amanda, Withall, Jennifer, Lee, Rachel, Rossetti, Sarah Collins, Rosenbloom, Samuel Trent
      Pages: 439 - 446
      Abstract: Background The widespread adoption of electronic health records and a simultaneous increase in regulatory demands have led to an acceleration of documentation requirements among clinicians. The corresponding burden from documentation requirements is a central contributor to clinician burnout and can lead to an increased risk of suboptimal patient care. Objective To address the problem of documentation burden, the 25 by 5: Symposium to Reduce Documentation Burden on United States Clinicians by 75% by 2025 (Symposium) was organized to provide a forum for experts to discuss the current state of documentation burden and to identify specific actions aimed at dramatically reducing documentation burden for clinicians. Methods The Symposium consisted of six weekly sessions with 33 presentations. The first four sessions included panel presentations discussing the challenges related to documentation burden. The final two sessions consisted of breakout groups aimed at engaging attendees in establishing interventions for reducing clinical documentation burden. Steering Committee members analyzed notes from each breakout group to develop a list of action items. Results The Steering Committee synthesized and prioritized 82 action items into Calls to Action among three stakeholder groups: Providers and Health Systems, Vendors, and Policy and Advocacy Groups. Action items were then categorized into as short-, medium-, or long-term goals. Themes that emerged from the breakout groups' notes include the following: accountability, evidence is critical, education and training, innovation of technology, and other miscellaneous goals (e.g., vendors will improve shared knowledge databases). Conclusion The Symposium successfully generated a list of interventions for short-, medium-, and long-term timeframes as a launching point to address documentation burden in explicit action-oriented ways. Addressing interventions to reduce undue documentation burden placed on clinicians will necessitate collaboration among all stakeholders.
      Citation: Appl Clin Inform 2022; 13: 439-446
      PubDate: 2022-05-11T00:00:00+01:00
      DOI: 10.1055/s-0042-1746169
      Issue No: Vol. 13, No. 02 (2022)
       
  • Clinician Acceptance of Order Sets for Pain Management: A Survey in Two
           Urban Hospitals

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      Authors: Liu; Yifan, Hao, Haijing, Sharma, Mohit M., Harris, Yonaka, Scofi, Jean, Trepp, Richard, Farmer, Brenna, Ancker, Jessica S., Zhang, Yiye
      Pages: 447 - 455
      Abstract: Background Order sets are a clinical decision support (CDS) tool in computerized provider order entry systems. Order set use has been associated with improved quality of care. Particularly related to opioids and pain management, order sets have been shown to standardize and reduce the prescription of opioids. However, clinician-level barriers often limit the uptake of this CDS modality. Objective To identify the barriers to order sets adoption, we surveyed clinicians on their training, knowledge, and perceptions related to order sets for pain management. Methods We distributed a cross-sectional survey between October 2020 and April 2021 to clinicians eligible to place orders at two campuses of a major academic medical center. Survey questions were adapted from the widely used framework of Unified Theory of Acceptance and Use of Technology. We hypothesize that performance expectancy (PE) and facilitating conditions (FC) are associated with order set use. Survey responses were analyzed using logistic regression. Results The intention to use order sets for pain management was associated with PE to existing order sets, social influence (SI) by leadership and peers, and FC for electronic health record (EHR) training and function integration. Intention to use did not significantly differ by gender or clinician role. Moderate differences were observed in the perception of the effort of, and FC for, order set use across gender and roles of clinicians, particularly emergency medicine and internal medicine departments. Conclusion This study attempts to identify barriers to the adoption of order sets for pain management and suggests future directions in designing and implementing CDS systems that can improve order sets adoption by clinicians. Study findings imply the importance of order set effectiveness, peer influence, and EHR integration in determining the acceptability of the order sets.
      Citation: Appl Clin Inform 2022; 13: 447-455
      PubDate: 2022-04-27T00:00:00+01:00
      DOI: 10.1055/s-0042-1745828
      Issue No: Vol. 13, No. 02 (2022)
       
  • Usability and Acceptability of Clinical Decision Support Based on the
           KIIDS-TBI Tool for Children with Mild Traumatic Brain Injuries and
           Intracranial Injuries

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      Authors: Greenberg; Jacob K., Otun, Ayodamola, Kyaw, Pyi Theim, Carpenter, Christopher R., Brownson, Ross C., Kuppermann, Nathan, Limbrick, David D, Foraker, Randi E., Yen, Po-Yin
      Pages: 456 - 467
      Abstract: Background The Kids Intracranial Injury Decision Support tool for Traumatic Brain Injury (KIIDS-TBI) tool is a validated risk prediction model for managing children with mild traumatic brain injuries (mTBI) and intracranial injuries. Electronic clinical decision support (CDS) may facilitate the clinical implementation of this evidence-based guidance. Objective Our objective was to evaluate the acceptability and usability of an electronic CDS tool for managing children with mTBI and intracranial injuries. Methods Emergency medicine and neurosurgery physicians (10 each) from 10 hospitals in the United States were recruited to participate in usability testing of a novel CDS prototype in a simulated electronic health record environment. Testing included a think-aloud protocol, an acceptability and usability survey, and a semi-structured interview. The prototype was updated twice during testing to reflect user feedback. Usability problems recorded in the videos were categorized using content analysis. Interview transcripts were analyzed using thematic analysis. Results Among the 20 participants, most worked at teaching hospitals (80%), freestanding children's hospitals (95%), and level-1 trauma centers (75%). During the two prototype updates, problems with clarity of terminology and navigating through the CDS interface were identified and corrected. Corresponding to these changes, the number of usability problems decreased from 35 in phase 1 to 8 in phase 3 and the number of mistakes made decreased from 18 (phase 1) to 2 (phase 3). Through the survey, participants found the tool easy to use (90%), useful for determining a patient's level of care (95%), and likely to improve resource use (90%) and patient safety (79%). Interview themes related to the CDS's ability to support evidence-based decision-making and improve clinical workflow proposed implementation strategies and potential pitfalls. Conclusion After iterative evaluation and refinement, the KIIDS-TBI CDS tool was found to be highly usable and useful for aiding the management of children with mTBI and intracranial injuries.
      Citation: Appl Clin Inform 2022; 13: 456-467
      PubDate: 2022-04-27T00:00:00+01:00
      DOI: 10.1055/s-0042-1745829
      Issue No: Vol. 13, No. 02 (2022)
       
  • Generating and Reporting Electronic Clinical Quality Measures from
           Electronic Health Records: Strategies from EvidenceNOW Cooperatives

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      Authors: Richardson; Joshua E., Rasmussen, Luke V., Dorr, David A., Sirkin, Jenna T., Shelley, Donna, Rivera, Adovich, Wu, Winfred, Cykert, Samuel, Cohen, Deborah J., Kho, Abel N.
      Pages: 485 - 494
      Abstract: Background Electronic clinical quality measures (eCQMs) from electronic health records (EHRs) are a key component of quality improvement (QI) initiatives in small-to-medium size primary care practices, but using eCQMs for QI can be challenging. Organizational strategies are needed to effectively operationalize eCQMs for QI in these practice settings. Objective This study aimed to characterize strategies that seven regional cooperatives participating in the EvidenceNOW initiative developed to generate and report EHR-based eCQMs for QI in small-to-medium size practices. Methods A qualitative study comprised of 17 interviews with representatives from all seven EvidenceNOW cooperatives was conducted. Interviewees included administrators were with both strategic and cooperative-level operational responsibilities and external practice facilitators were with hands-on experience helping practices use EHRs and eCQMs. A subteam conducted 1-hour semistructured telephone interviews with administrators and practice facilitators, then analyzed interview transcripts using immersion crystallization. The analysis and a conceptual model were vetted and approved by the larger group of coauthors. Results Cooperative strategies consisted of efforts in four key domains. First, cooperative adaptation shaped overall strategies for calculating eCQMs whether using EHRs, a centralized source, or a “hybrid strategy” of the two. Second, the eCQM generation described how EHR data were extracted, validated, and reported for calculating eCQMs. Third, practice facilitation characterized how facilitators with backgrounds in health information technology (IT) delivered services and solutions for data capture and quality and practice support. Fourth, performance reporting strategies and tools informed QI efforts and how cooperatives could alter their approaches to eCQMs. Conclusion Cooperatives ultimately generated and reported eCQMs using hybrid strategies because they determined neither EHRs alone nor centralized sources alone could operationalize eCQMs for QI. This required cooperatives to devise solutions and utilize resources that often are unavailable to typical small-to-medium-sized practices. The experiences from EvidenceNOW cooperatives provide insights into how organizations can plan for challenges and operationalize EHR-based eCQMs.
      Citation: Appl Clin Inform 2022; 13: 485-494
      PubDate: 2022-05-04T00:00:00+01:00
      DOI: 10.1055/s-0042-1748145
      Issue No: Vol. 13, No. 02 (2022)
       
  • Reporting Outcomes of Pediatric Intensive Care Unit Patients to Referring
           Physicians via an Electronic Health Record-Based Feedback System

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      Authors: Cifra; Christina L., Tigges, Cody R., Miller, Sarah L., Curl, Nathaniel, Monson, Christopher D., Dukes, Kimberly C., Reisinger, Heather S., Pennathur, Priyadarshini R., Sittig, Dean F., Singh, Hardeep
      Pages: 495 - 503
      Abstract: Background Many critically ill children are initially evaluated in front-line settings by clinicians with variable pediatric training before they are transferred to a pediatric intensive care unit (PICU). Because clinicians learn from past performance, communicating outcomes of patients back to front-line clinicians who provide pediatric emergency care could be valuable; however, referring clinicians do not consistently receive this important feedback. Objectives Our aim was to determine the feasibility, usability, and clinical relevance of a semiautomated electronic health record (EHR)-supported system developed at a single institution to deliver timely and relevant PICU patient outcome feedback to referring emergency department (ED) physicians. Methods Guided by the Health Information Technology Safety Framework, we iteratively designed, implemented, and evaluated a semiautomated electronic feedback system leveraging the EHR in one institution. After conducting interviews and focus groups with stakeholders to understand the PICU-ED health care work system, we designed the EHR-supported feedback system by translating stakeholder, organizational, and usability objectives into feedback process and report requirements. Over 6 months, we completed three cycles of implementation and evaluation, wherein we analyzed EHR access logs, reviewed feedback reports sent, performed usability testing, and conducted physician interviews to determine the system's feasibility, usability, and clinical relevance. Results The EHR-supported feedback process is feasible with timely delivery and receipt of feedback reports. Usability testing revealed excellent Systems Usability Scale scores. According to physicians, the process was well-integrated into their clinical workflows and conferred minimal additional workload. Physicians also indicated that delivering and receiving consistent feedback was relevant to their clinical practice. Conclusion An EHR-supported system to deliver timely and relevant PICU patient outcome feedback to referring ED physicians was feasible, usable, and important to physicians. Future work is needed to evaluate impact on clinical practice and patient outcomes and to investigate applicability to other clinical settings involved in similar care transitions.
      Citation: Appl Clin Inform 2022; 13: 495-503
      PubDate: 2022-05-11T00:00:00+01:00
      DOI: 10.1055/s-0042-1748147
      Issue No: Vol. 13, No. 02 (2022)
       
  • Electronic Health Record-Embedded, Behavioral Science-Informed System for
           Smoking Cessation for the Parents of Pediatric Patients

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      Authors: Jenssen; Brian P., Karavite, Dean J., Kelleher, Shannon, Nekrasova, Ekaterina, Thayer, Jeritt G., Ratwani, Raj, Shea, Judy, Nabi-Burza, Emara, Drehmer, Jeremy E., Winickoff, Jonathan P., Grundmeier, Robert W., Schnoll, Robert A., Fiks, Alexander G.
      Pages: 504 - 515
      Abstract: Background Helping parents quit smoking is a public health priority. However, parents are rarely, if ever, offered tobacco use treatment through pediatric settings. Clinical decision support (CDS) systems developed for the workflows of pediatric primary care may support consistent screening, treatment, and referral. Objectives This study aimed to develop a CDS system by using human-centered design (HCD) that identifies parents who smoke, provides motivational messages to quit smoking (informed by behavioral science), and supports delivery of evidence-based tobacco treatment. Methods Our multidisciplinary team applied a rigorous HCD process involving analysis of the work environment, user involvement in formative design, iterative improvements, and evaluation of the system's use in context with the following three cohorts: (1) parents who smoke, (2) pediatric clinicians, and (3) clinic staff. Participants from each cohort were presented with scenario-based, high-fidelity mockups of system components and then provided input related to their role in using the CDS system. Results We engaged 70 representative participants including 30 parents, 30 clinicians, and 10 clinic staff. A key theme of the design review sessions across all cohorts was the need to automate functions of the system. Parents emphasized a system that presented information in a simple way, highlighted benefits of quitting smoking, and allowed direct connection to treatment. Pediatric clinicians emphasized automating tobacco treatment. Clinical staff emphasized screening for parent smoking via several modalities prior to the patient's visit. Once the system was developed, most parents (80%) reported that it was easy to use, and the majority of pediatricians reported that they would use the system (97%) and were satisfied with it (97%). Conclusion A CDS system to support parental tobacco cessation in pediatric primary care, developed through an HCD process, proved easy to use and acceptable to parents, clinicians, and office staff. This preliminary work justifies evaluating the impact of the system on helping parents quit smoking.
      Citation: Appl Clin Inform 2022; 13: 504-515
      PubDate: 2022-05-18T00:00:00+01:00
      DOI: 10.1055/s-0042-1748148
      Issue No: Vol. 13, No. 02 (2022)
       
  • Applied Clinical Informatics Journal: A Brief History

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      Authors: Lehmann; Christoph U., Ball, Marion J., Haux, Reinhold, Lehmann, Jenna S.
      Pages: 516 - 520
      Abstract: In 2009, Schattauer Verlag in Stuttgart, Germany first published the Applied Clinical Informatics (ACI) Journal. ACI has served since its inception as an official journal of the International Medical Informatics Association. Later, the American Medical Informatics Association and the European Federation for Medical Informatics named ACI as an official journal. This manuscript describes the history of the journal from its inception to present day including publication measures, challenges, and successes.
      Citation: Appl Clin Inform 2022; 13: 516-520
      PubDate: 2022-05-18T00:00:00+01:00
      DOI: 10.1055/s-0042-1749165
      Issue No: Vol. 13, No. 02 (2022)
       
 
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