2,596 research outputs found

    Strategies for Applying Electronic Health Records to Achieve Cost Saving Benefits

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    The American Recovery and Reinvestment Act (ARRA) of 2009 authorized the distribution of about 30billionincentivefundstoaccelerateelectronichealthrecord(EHR)applicationstoimprovethequalityofcare,safety,privacy,carecoordination,andpatients2˘7involvementinhealthcare.EHRusehasthepotentialofsaving30 billion incentive funds to accelerate electronic health record (EHR) applications to improve the quality of care, safety, privacy, care coordination, and patients\u27 involvement in healthcare. EHR use has the potential of saving 731 in costs for hospitals per patient admission; however, most hospitals are not applying EHR to reach the level at which cost savings are possible. The purpose of this single case study was to explore strategies that IT leaders in hospitals can use to apply EHR to achieve the cost saving benefits. The participants were IT leaders and EHR super users at a large hospital in Texas with successful experience in applying EHR. Information systems success model formed the conceptual framework for the study. I conducted face-to-face interviews and analyzed organizational documents. I used qualitative textual data analysis method to identify themes. Five themes emerged from this study, which are ensuring information quality, ensuring system quality, assuring service quality, promoting usability, and maximizing net benefits of the EHR system. The findings of this study included four strategies to apply EHR; these strategies include engaging training staff, documenting accurately and in a timely manner, protecting patient data, and enforcing organizational best practice policies to maximize reimbursement and cost savings. The findings of this study could contribute to positive social change for the communities because EHR successful application includes lower cost for hospitals that may lead to the provision of affordable care to more low-income patients

    A safety analysis approach to clinical workflows : application and evaluation

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    Clinical workflows are safety critical workflows as they have the potential to cause harm or death to patients. Their safety needs to be considered as early as possible in the development process. Effective safety analysis methods are required to ensure the safety of these high-risk workflows, because errors that may happen through routine workflow could propagate within the workflow to result in harmful failures of the system’s output. This paper shows how to apply an approach for safety analysis of clinic al workflows to analyse the safety of the workflow within a radiology department and evaluates the approach in terms of usability and benefits. The outcomes of using this approach include identification of the root causes of hazardous workflow failures that may put patients’ lives at risk. We show that the approach is applicable to this area of healthcare and is able to present added value through the detailed information on possible failures, of both their causes and effects; therefore, it has the potential to improve the safety of radiology and other clinical workflows

    We are bitter, but we are better off: Case study of the implementation of an electronic health record system into a mental health hospital in England

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    In contrast to the acute hospital sector, there have been relatively few implementations of integrated electronic health record (EHR) systems into specialist mental health settings. The National Programme for Information Technology (NPfIT) in England was the most expensive IT-based transformation of public services ever undertaken, which aimed amongst other things, to implement integrated EHR systems into mental health hospitals. This paper describes the arrival, the process of implementation, stakeholders' experiences and the local consequences of the implementation of an EHR system into a mental health hospital

    Modeling Clinicians’ Cognitive and Collaborative Work in Post-Operative Hospital Care

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    abstract: Clinicians confront formidable challenges with information management and coordination activities. When not properly integrated into clinical workflow, technologies can further burden clinicians’ cognitive resources, which is associated with medical errors and risks to patient safety. An understanding of workflow is necessary to redesign information technologies (IT) that better support clinical processes. This is particularly important in surgical care, which is among the most clinical and resource intensive settings in healthcare, and is associated with a high rate of adverse events. There are a growing number of tools to study workflow; however, few produce the kinds of in-depth analyses needed to understand health IT-mediated workflow. The goals of this research are to: (1) investigate and model workflow and communication processes across technologies and care team members in post-operative hospital care; (2) introduce a mixed-method framework, and (3) demonstrate the framework by examining two health IT-mediated tasks. This research draws on distributed cognition and cognitive engineering theories to develop a micro-analytic strategy in which workflow is broken down into constituent people, artifacts, information, and the interactions between them. It models the interactions that enable information flow across people and artifacts, and identifies dependencies between them. This research found that clinicians manage information in particular ways to facilitate planned and emergent decision-making and coordination processes. Barriers to information flow include frequent information transfers, clinical reasoning absent in documents, conflicting and redundant data across documents and applications, and that clinicians are burdened as information managers. This research also shows there is enormous variation in how clinicians interact with electronic health records (EHRs) to complete routine tasks. Variation is best evidenced by patterns that occur for only one patient case and patterns that contain repeated events. Variation is associated with the users’ experience (EHR and clinical), patient case complexity, and a lack of cognitive support provided by the system to help the user find and synthesize information. The methodology is used to assess how health IT can be improved to better support clinicians’ information management and coordination processes (e.g., context-sensitive design), and to inform how resources can best be allocated for clinician observation and training.Dissertation/ThesisDoctoral Dissertation Biomedical Informatics 201

    Constructive eHealth evaluation:Lessons from evaluation of EHR development in 4 Danish hospitals

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    Abstract Background Information and communication sources in the healthcare sector are replaced with new eHealth technologies. This has led to problems arising from the lack of awareness of the importance of end-user involvement in eHealth development and of the difficulties caused by using traditional summative evaluation methods. The Constructive eHealth evaluation method (CeHEM) provides a solution to these problems by offering an evaluation framework for supporting and facilitating end-user involvement during all phases of eHealth development. The aim of this paper is to support this process by sharing experiences of the eHealth evaluation method used in the introduction of electronic health records (EHR) in the North Denmark Region of Denmark. It is the first time the fully developed method and the experiences on using the CeHEM in all five phases of a full lifecycle framework is presented. Methods A case study evaluation of the EHR development process in the North Denmark Region was conducted from 2004 to 2010. The population consisted of clinicians, IT professionals, administrators, and vendors. The study involved 4 hospitals in the region. Data were collected using questionnaires, observations, interviews, and insight gathered from relevant documents. Results The evaluation showed a need for a) Early involvement of clinicians, b) The best possible representation of clinicians, and c) Workload reduction for those involved. The consequences of not providing this were a lack of ownership of decisions and negative attitudes towards the clinical benefits related to these decisions. Further, the result disclosed that by following the above recommendations, and by providing feedback to the 4 actor groups, the physicians’ involvement was improved. As a result they took ownership of decisions and gained a positive attitude to the clinical benefits. Conclusions The CeHEM has proven successful in formative evaluation of EHR development and can point at important issues that need to be taken care of by management. The method provides a framework that takes care of feedback and learning during eHealth development. It can thus support successful eHealth development in a broader context while building on a well-known success factor: end-user involvement in eHealth development

    Conceptualizing Machine Learning for Dynamic Information Retrieval of Electronic Health Record Notes

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    The large amount of time clinicians spend sifting through patient notes and documenting in electronic health records (EHRs) is a leading cause of clinician burnout. By proactively and dynamically retrieving relevant notes during the documentation process, we can reduce the effort required to find relevant patient history. In this work, we conceptualize the use of EHR audit logs for machine learning as a source of supervision of note relevance in a specific clinical context, at a particular point in time. Our evaluation focuses on the dynamic retrieval in the emergency department, a high acuity setting with unique patterns of information retrieval and note writing. We show that our methods can achieve an AUC of 0.963 for predicting which notes will be read in an individual note writing session. We additionally conduct a user study with several clinicians and find that our framework can help clinicians retrieve relevant information more efficiently. Demonstrating that our framework and methods can perform well in this demanding setting is a promising proof of concept that they will translate to other clinical settings and data modalities (e.g., labs, medications, imaging).Comment: To be published in Proceedings of Machine Learning Research Volume 219; accepted to the Machine Learning for Healthcare 2023 conferenc

    A mixed methods evaluation of a tool assessing Adult Learning Theory content in EHR training

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    Sophisticated Electronic Health Record (EHR) applications, such as Computerized Physician Order Entry, (CPOE) are being rapidly implemented in a variety of clinical settings. While there is a lack of published research to guide the design, execution and evaluation of strategies for the teaching and learning of EHRs, researchers have identified training gaps as a potential cause of EHR implementation problems. The significance of this research stems from the unprecedented numbers of physicians, nurses, and other clinicians engaged in training for Electronics Health Records. This explosion in EHR training is due in large part to Medicare and Medicaid EHR Incentive Programs established through the Recovery Act/HITECH Act of 2009. With incentive payments tied to the "Meaningful Use" of EHRs rather than simply to their implementation, a focus on effective and efficient training has come to the forefront. Adult Learning Theory (ALT) is well established in the literature as an important framework in the education and training of adult populations. Research into the design and delivery of EHR training programs in the context of clinicians as adult learners is needed. The study will use a scoring tool previously developed and validated to assess documents for evidence of ALT principles in the design and delivery of Continuing Medical Education (CME) programs, Reporting of Adult Learning Principles (RALP). The study design is a formative evaluation using mixed methods to assess the feasibility of the RALP tool to assess the presence of ALT principles in hospitals' CPOE training programs. The addition of a tool that evaluates EHR Training Programs based on their content, rather than perception surveys, will expand future researchers' abilities to evaluate EHR training programs, and explore the relationship between the inclusion of ALT principles and training outcomes. The study finds the RALP to a reliable instrument for the evaluation of ALT principles in EHR training program content. The study identifies future research opportunities for the use and adaptation of the RALP instrument. Finally, the study also identifies potential for the research to be useful in related fields of study, such as instructional design and workforce development.Includes bibliographical references (pages 126-133)

    Exploring the Emergence of Open Platforms in Healthcare: Design Considerations and Experiences from an Initial Case in Norwegian Primary Care

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    Despite significant efforts on improving interoperability of health information and lowering socio-technical cost of replacing clinical applications, healthcare organizations and professionals struggle with fragmented and non-interoperable Health Information Technologies. This paper describes the emergence of open platforms, which may alleviate challenges related to interoperability issues, weak integrations, siloed data repositories, and numerous legacy systems within healthcare. Using a proposed platform initiative in Norway, we explore the open platform phenomenon with a socio-technical lens, and highlights four key topics that have produced tension and merits consideration from the involved stakeholders: i) Procurement strategy and vendor neutrality, ii) Ability to facilitate flexible use, iii) The use of standards and separation of data and application, and iv) Strategies for development and governance of standards. We further discuss the related implications and design considerations necessary to support complex patient pathways and provide clinicians more flexible and effective systems

    Improving the Coordination of Care for Periprocedural Antithrombotic Medication Management in Patients Undergoing Elective Surgery

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    Background: Arranging periprocedural antithrombotic medication (ATM) management is a frequently encountered complex clinical challenge. Often, there is limited time between the pre-admission clinic visit and the surgical date to coordinate ATM management and communicate the plan to the patient. This increases the risk of perioperative adverse events, case delays and cancellations, and is a patient safety concern. A quality improvement project was undertaken to address improving ATM periprocedural care coordination for patients taking ATM undergoing elective surgery. A review of the literature found clinical decision support system (CDSS) alerts to be an effective strategy. The aim of the project was to improve the quality and safety of ATM by optimizing the care coordination pathway for periprocedural ATM management. Methods: A multidisciplinary team was formed to collaborate on the project aims,intervention, and implementation plan. The intervention was a computer application for auto-identification and flagging of ATM to deploy a CDSS alert for referral to an online workflow organization tool (list manager) to coordinate ATM periprocedural management. Current state analysis was conducted. Results. Qualitative and quantitative evidence demonstrated variation across surgical services in coordinating periprocedural ATM management. This data supported project approval by senior leadership. Request for programming was submitted. Planning for piloting the intervention in two clinical areas where bleeding is of critical concern continues. Conclusion. The project was complex in both scope and design, affecting multiple stakeholders with competing concerns. In the first iteration, the request for programming the CDSS alert was denied. This required the project team to pivot to an alternative solution, an online workflow organization tool (list manager) and extended the project timeline. Recommendations: This quality improvement project demonstrates the need for further quality improvement initiatives and research on improving the coordination of periprocedural ATM management. It highlights the complexity of this care coordination process
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