Embedding Policy and Procedure Hyperlinks Into the Electronic Health Record to Improve Practice, Usability, and Reduce the Risk of Litigation

Lyerla, Frank; Danks, Jamie; Hajdini, Hasima; Henderson, Rochelle

doi:10.1016/j.jopan.2022.01.008

Cited by 3 publications

(1 citation statement)

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“…The widespread adoption of electronic health record (EHR) and with it template and practice prompting has been described with frustrations by health care professionals, including the focus on the EHR rather than the patient (Wisner et al, 2019). Nurses report changes in patient care workflows and with integration of practice standardisation, such as policy and procedure prompting logic from the EHR itself, the question of what drives clinical decision-making, the nurse or the EHR is not far off (Lyerla et al, 2022). Recognition of the limitations of computer systems is something Hubert Dreyfus (1992) (Benner, 2019;Dreyfus & Dreyfus, 1980).…”

Section: Contemporary Challenges To the Development Of Expert Nursing...mentioning

confidence: 99%

Self‐appropriation in nurse engagement: Facilitating the development of expert nurses using Benner and Lonergan

Healy

2024

Nursing Philosophy

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Expert nurses, as described by the work of Patricia Benner, are at the peak of clinical nursing practice and vitally important in ensuring the best possible patient care and clinical outcomes. The development of Benner's theory and its relationship with the Dreyfus model of skill acquisition provides context for understanding the progression necessary for expert development. Contemporary healthcare challenges present implications to the development of advancing levels of nursing practice. Engagement has been identified as critical to achieving expert practice. I propose the incorporation of the philosophical framework of self‐appropriation from Benard Lonergan as a strategy to develop internal engagement in nurses to facilitate expert practice. I outline the synergy between Benner's theory and the work of Lonergan, which provide overlap and opportunity to overcome barriers to developing expert nursing practice. In the challenging climate of healthcare, there is an obligation to promote engagement and facilitate expert nurse development, necessary for patient outcomes as well as clinical role models, preceptors, and leaders to guide future nurses.

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Section: Contemporary Challenges To the Development Of Expert Nursing...mentioning

confidence: 99%

Self‐appropriation in nurse engagement: Facilitating the development of expert nurses using Benner and Lonergan

Healy

2024

Nursing Philosophy

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Digital Healthcare using Blockchain

Ramar

Hariharan³

et al. 2022

2022 1st International Conference on Computational Science and Technology (ICCST)

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21st century (clinical) decision support in nursing and allied healthcare. Developing a learning health system: a reasoned design of a theoretical framework

van Velzen,

de Graaf-Waar,

Ubert

et al. 2023

BMC Med Inform Decis Mak

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In this paper, we present a framework for developing a Learning Health System (LHS) to provide means to a computerized clinical decision support system for allied healthcare and/or nursing professionals. LHSs are well suited to transform healthcare systems in a mission-oriented approach, and is being adopted by an increasing number of countries. Our theoretical framework provides a blueprint for organizing such a transformation with help of evidence based state of the art methodologies and techniques to eventually optimize personalized health and healthcare. Learning via health information technologies using LHS enables users to learn both individually and collectively, and independent of their location. These developments demand healthcare innovations beyond a disease focused orientation since clinical decision making in allied healthcare and nursing is mainly based on aspects of individuals’ functioning, wellbeing and (dis)abilities. Developing LHSs depends heavily on intertwined social and technological innovation, and research and development. Crucial factors may be the transformation of the Internet of Things into the Internet of FAIR data & services. However, Electronic Health Record (EHR) data is in up to 80% unstructured including free text narratives and stored in various inaccessible data warehouses. Enabling the use of data as a driver for learning is challenged by interoperability and reusability.To address technical needs, key enabling technologies are suitable to convert relevant health data into machine actionable data and to develop algorithms for computerized decision support. To enable data conversions, existing classification and terminology systems serve as definition providers for natural language processing through (un)supervised learning.To facilitate clinical reasoning and personalized healthcare using LHSs, the development of personomics and functionomics are useful in allied healthcare and nursing. Developing these omics will be determined via text and data mining. This will focus on the relationships between social, psychological, cultural, behavioral and economic determinants, and human functioning.Furthermore, multiparty collaboration is crucial to develop LHSs, and man-machine interaction studies are required to develop a functional design and prototype. During development, validation and maintenance of the LHS continuous attention for challenges like data-drift, ethical, technical and practical implementation difficulties is required.

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Embedding Policy and Procedure Hyperlinks Into the Electronic Health Record to Improve Practice, Usability, and Reduce the Risk of Litigation

Cited by 3 publications

References 1 publication

Self‐appropriation in nurse engagement: Facilitating the development of expert nurses using Benner and Lonergan

Self‐appropriation in nurse engagement: Facilitating the development of expert nurses using Benner and Lonergan

Digital Healthcare using Blockchain

21st century (clinical) decision support in nursing and allied healthcare. Developing a learning health system: a reasoned design of a theoretical framework

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