48.2 THE CHILD PSYCHIATRIST AS A CLINICAL INFORMATICIAN: ADAPTING ELECTRONIC HEALTH RECORDS (EHRS) TO ADVANCE CLINICAL DECISION-MAKING FOR CHILDREN’S MENTAL HEALTH

2019 ◽  
Vol 58 (10) ◽  
pp. S68-S69
Author(s):  
Nicole Benson
Keyword(s):  
Mental Health ◽  
Decision Making ◽  
Electronic Health Records ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Children’S Mental Health ◽  
Children's Mental Health ◽  
Child Psychiatrist ◽  
Health Records ◽  
Electronic Health

scholarly journals Closing the Loop: Optimizing Diabetes Care in the Hospital by Addressing Dispersed Information in Electronic Health Records and Using Clinical Decision Support

2018 ◽  
Vol 13 (4) ◽  
pp. 783-789 ◽  
Author(s):  
Ariana R. Pichardo-Lowden ◽  
Paul M. Haidet
Keyword(s):  
Decision Making ◽  
Electronic Health Records ◽  
Clinical Decision Making ◽  
Data Retrieval ◽  
Clinical Decision ◽  
Care Providers ◽  
Health Records ◽  
Data Points ◽  
Closing The Loop ◽  
Electronic Health

Multiple factors hinder the management of diabetes in hospitals. Amid the demands of practice, health care providers must collect, collate, and analyze multiple data points to optimally interpret glucose control and manage insulin dosing. Such data points are commonly dispersed in different sections of electronic health records (EHR), and the system for data display and physician interaction with the EHR are often poorly conducive to seamless clinical decision making. In this perspective article, we examine challenges in the process of EHR data retrieval, interpretation and decision making, using glucose management as an exemplar. We propose a conceptual, systems-based design for closing the loop between data gathering, analysis and decision making in the management of inpatient diabetes. This concept capitalizes on attributes of the EHR that can enable automated recognition of cases and provision of clinical recommendations.

scholarly journals Electronic Health Records’ Support for Primary Care Physicians’ Situation Awareness: A Metanarrative Review

2021 ◽  
pp. 001872082110143
Author(s):  
April Savoy ◽  
Himalaya Patel ◽  
Daniel R. Murphy ◽  
Ashley N. D. Meyer ◽  
Jennifer Herout ◽  
...  
Keyword(s):  
Primary Care ◽  
Decision Making ◽  
Electronic Health Records ◽  
Situation Awareness ◽  
Primary Care Physicians ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Health Records ◽  
Care Plans ◽  
Electronic Health

Objective Situation awareness (SA) refers to people’s perception and understanding of their dynamic environment. In primary care, reduced SA among physicians increases errors in clinical decision-making and, correspondingly, patients’ risk of experiencing adverse outcomes. Our objective was to understand the extent to which electronic health records (EHRs) support primary care physicians (PCPs)’ SA during clinical decision-making. Method We conducted a metanarrative review of papers in selected academic databases, including CINAHL and MEDLINE. Eligible studies included original peer-reviewed research published between January 2012 and August 2020 on PCP–EHR interactions. We iteratively queried, screened, and summarized literature focused on EHRs supporting PCPs’ clinical decision-making and care management for adults. Then, we mapped findings to an established SA framework to classify external factors (individual, task, and system) affecting PCPs’ levels of SA (1–Perception, 2–Comprehension, and 3–Projection) and identified SA barriers. Results From 1504 articles identified, we included and synthesized 19 studies. Study designs were largely noninterventional. Studies described EHR workflow misalignments, usability issues, and communication challenges. EHR information, including lab results and care plans, was characterized as incomplete, untimely, or irrelevant. Unmet information needs made it difficult for PCPs to obtain even basic SA, Level 1 SA. Prevalent barriers to PCPs developing SA with EHRs were errant mental models, attentional tunneling, and data overload. Conclusion Based on our review, EHRs do not support the development of higher levels of SA among PCPs. Review findings suggest SA-oriented design processes for health information technology could improve PCPs’ SA, satisfaction, and decision-making.

scholarly journals Desiderata for computable representations of electronic health records-driven phenotype algorithms

2015 ◽  
Vol 22 (6) ◽  
pp. 1220-1230 ◽  
Author(s):  
Huan Mo ◽  
William K Thompson ◽  
Luke V Rasmussen ◽  
Jennifer A Pacheco ◽  
Guoqian Jiang ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Language Processing ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Relational Algebra ◽  
Common Data Model ◽  
Health Records ◽  
Electronic Health ◽  
Value Sets ◽  
Text Searching

Abstract Background Electronic health records (EHRs) are increasingly used for clinical and translational research through the creation of phenotype algorithms. Currently, phenotype algorithms are most commonly represented as noncomputable descriptive documents and knowledge artifacts that detail the protocols for querying diagnoses, symptoms, procedures, medications, and/or text-driven medical concepts, and are primarily meant for human comprehension. We present desiderata for developing a computable phenotype representation model (PheRM). Methods A team of clinicians and informaticians reviewed common features for multisite phenotype algorithms published in PheKB.org and existing phenotype representation platforms. We also evaluated well-known diagnostic criteria and clinical decision-making guidelines to encompass a broader category of algorithms. Results We propose 10 desired characteristics for a flexible, computable PheRM: (1) structure clinical data into queryable forms; (2) recommend use of a common data model, but also support customization for the variability and availability of EHR data among sites; (3) support both human-readable and computable representations of phenotype algorithms; (4) implement set operations and relational algebra for modeling phenotype algorithms; (5) represent phenotype criteria with structured rules; (6) support defining temporal relations between events; (7) use standardized terminologies and ontologies, and facilitate reuse of value sets; (8) define representations for text searching and natural language processing; (9) provide interfaces for external software algorithms; and (10) maintain backward compatibility. Conclusion A computable PheRM is needed for true phenotype portability and reliability across different EHR products and healthcare systems. These desiderata are a guide to inform the establishment and evolution of EHR phenotype algorithm authoring platforms and languages.

scholarly journals Integrating Genomic Resources with Electronic Health Records using the HL7 Infobutton Standard

2016 ◽  
Vol 07 (03) ◽  
pp. 817-831 ◽  
Author(s):  
Casey Overby ◽  
Guilherme Del Fiol ◽  
Wendy Rubinstein ◽  
Donna Maglott ◽  
Tristan Nelson ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Search Interface ◽  
Health Records ◽  
Knowledge Resources ◽  
Genomic Resources ◽  
Full Compliance ◽  
Genomic Knowledge ◽  
Electronic Health

SummaryThe Clinical Genome Resource (ClinGen) Electronic Health Record (EHR) Workgroup aims to integrate ClinGen resources with EHRs. A promising option to enable this integration is through the Health Level Seven (HL7) Infobutton Standard. EHR systems that are certified according to the US Meaningful Use program provide HL7-compliant infobutton capabilities, which can be leveraged to support clinical decision-making in genomics.To integrate genomic knowledge resources using the HL7 infobutton standard. Two tactics to achieve this objective were: (1) creating an HL7-compliant search interface for ClinGen, and (2) proposing guidance for genomic resources on achieving HL7 Infobutton standard accessibility and compliance.We built a search interface utilizing OpenInfobutton, an open source reference implementation of the HL7 Infobutton standard. ClinGen resources were assessed for readiness towards HL7 compliance. Finally, based upon our experiences we provide recommendations for publishers seeking to achieve HL7 compliance.Eight genomic resources and two sub-resources were integrated with the ClinGen search engine via OpenInfobutton and the HL7 infobutton standard. Resources we assessed have varying levels of readiness towards HL7-compliance. Furthermore, we found that adoption of standard terminologies used by EHR systems is the main gap to achieve compliance.Genomic resources can be integrated with EHR systems via the HL7 Infobutton standard using OpenInfobutton. Full compliance of genomic resources with the Infobutton standard would further enhance interoperability with EHR systems. Citation: Heale BSE, Overby CL, Del Fiol G, Rubinstein WS, Maglott DR, Nelson TH, Milosavljevic A, Martin CL, Goehringer SR, Freimuth RR, Williams MS. Integrating genomic resources with electronic health records using the HL7 Infobutton standard.

scholarly journals Convergence of Blockchain, Autonomous Agents, and Knowledge Graph to Share Electronic Health Records

2021 ◽  
Vol 4 ◽  
Author(s):  
Yao Yao ◽  
Meghana Kshirsagar ◽  
Gauri Vaidya ◽  
Jens Ducrée ◽  
Conor Ryan
Keyword(s):  
Electronic Health Records ◽  
Autonomous Agents ◽  
Knowledge Integration ◽  
Clinical Decision Making ◽  
User Authentication ◽  
Clinical Decision ◽  
Knowledge Graph ◽  
Autonomous Agent ◽  
Health Records ◽  
Electronic Health

In this article, we discuss a data sharing and knowledge integration framework through autonomous agents with blockchain for implementing Electronic Health Records (EHR). This will enable us to augment existing blockchain-based EHR Systems. We discuss how major concerns in the health industry, i.e., trust, security and scalability, can be addressed by transitioning from existing models to convergence of the three technologies – blockchain, agent-based modeling, and knowledge graph in a decentralized ecosystem. Each autonomous agent is responsible for instantiating key processes, such as user authentication and authorization, smart contracts, and knowledge graph generation through data integration among the participating stakeholders in the network. We discuss a layered approach for the design of the proposed system leading to an enhanced, safer clinical decision-making system. This can pave the way toward more informed and engaged patients and citizens by delivering personalized healthcare.

scholarly journals Data-Driven Activities Involving Electronic Health Records: An Activity and Task Analysis Framework for Interactive Visualization Tools

2020 ◽  
Vol 4 (1) ◽  
pp. 7 ◽  
Author(s):  
Neda Rostamzadeh ◽  
Sheikh S. Abdullah ◽  
Kamran Sedig
Keyword(s):  
Electronic Health Records ◽  
Clinical Decision Making ◽  
Interactive Visualization ◽  
Clinical Decision ◽  
Data Driven ◽  
Reference List ◽  
Health Records ◽  
Visualization Tools ◽  
Electronic Health ◽  
Almost All

Electronic health records (EHRs) can be used to make critical decisions, to study the effects of treatments, and to detect hidden patterns in patient histories. In this paper, we present a framework to identify and analyze EHR-data-driven tasks and activities in the context of interactive visualization tools (IVTs)—that is, all the activities, sub-activities, tasks, and sub-tasks that are and can be supported by EHR-based IVTs. A systematic literature survey was conducted to collect the research papers that describe the design, implementation, and/or evaluation of EHR-based IVTs that support clinical decision-making. Databases included PubMed, the ACM Digital Library, the IEEE Library, and Google Scholar. These sources were supplemented by gray literature searching and reference list reviews. Of the 946 initially identified articles, the survey analyzes 19 IVTs described in 24 articles that met the final selection criteria. The survey includes an overview of the goal of each IVT, a brief description of its visualization, and an analysis of how sub-activities, tasks, and sub-tasks blend and combine to accomplish the tool’s main higher-level activities of interpreting, predicting, and monitoring. Our proposed framework shows the gaps in support of higher-level activities supported by existing IVTs. It appears that almost all existing IVTs focus on the activity of interpreting, while only a few of them support predicting and monitoring—this despite the importance of these activities in assisting users in finding patients that are at high risk and tracking patients’ status after treatment.

scholarly journals Utilisation of Electronic Health Records for Public Health in Asia: A Review of Success Factors and Potential Challenges

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Lesley Dornan ◽  
Kanokporn Pinyopornpanish ◽  
Wichuda Jiraporncharoen ◽  
Ahmar Hashmi ◽  
Nisachol Dejkriengkraikul ◽  
...  
Keyword(s):  
Public Health ◽  
Electronic Health Records ◽  
Success Factors ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Direct Patient Care ◽  
Health Records ◽  
Middle Income ◽  
Implementation Challenges ◽  
Electronic Health

Introduction. Electronic health records offer a valuable resource to improve health surveillance and evaluation as well as informing clinical decision making. They have been introduced in many different settings, including low- and middle-income countries, yet little is known of the progress and effectiveness of similar information systems within Asia. This study examines the implementation of EHR systems for use at a population health level in Asia and to identify their current role within public health, key success factors, and potential barriers in implementation. Material and Methods. A systematic search process was implemented. Five databases were searched with MeSH key terms and Boolean phrases. Articles selected for this review were based on hospital provider electronic records with a component of implementation, utilisation, or evaluation for health systems or at least beyond direct patient care. A proposed analytic framework considered three interactive components: the content, the process, and the context. Results. Thirty-two articles were included in the review. Evidence suggests that benefits are significant but identifying and addressing potential challenges are critical for success. A comprehensive preparation process is necessary to implement an effective and flexible system. Discussion. Electronic health records implemented for public health can allow the identification of disease patterns, seasonality, and global trends as well as risks to vulnerable populations. Addressing implementation challenges will facilitate the development and efficacy of public health initiatives in Asia to identify current health needs and mitigate future risks.

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