Development and Evaluation of a Smartphone Application for Managing Gestational Diabetes Mellitus

Objectives The purpose of this study was to develop and evaluate an application (app) that provides tailored recommendations based on lifestyle and clinical data entered by the user. Methods Knowledge and functions required for the gestational diabetes mellitus (GDM) management app were extracted from clinical practice guidelines and evaluated through an online survey. Common and tailored recommendations were developed and evaluated with a content validity index. Algorithms to link tailored recommendations with a patient\u27s data were developed and evaluated by experts. An Android-based app was developed and evaluated by comparing the process of data entry and recommendation retrieval and the usability of the app. After the app was revised, the user acceptance of the app was evaluated. Results Six domains of knowledge and 14 functions were extracted. Seven common and 49 tailored recommendations were developed. Nine lifestyle and clinical data elements were modeled. Eight algorithms with 18 decision nodes presenting tailored recommendations based on patient\u27s data and 12 user interface screens were developed. All recommendations obtained from the use of app concurred with recommendations derived by algorithms. The average usability score was 69.5 out of 100. The user acceptance score with behavioral intention to use was 5.5, intrinsic motivation 4.3, the perceived ease of use score was 4.6, and the perceived usefulness score was 5.0 out of 7, respectively. Conclusions The GDM management knowledge and tailored recommendations obtained in this study could be of help in managing GDM

Collaborative Efforts for Representing Nursing Concepts in Computer-based Systems: International Perspectives

Current nursing terminology efforts have converged toward meeting the demand for a reference terminology for nursing concepts by building on the foundation of existing interface and administrative terminologies and by collaborating with terminology efforts across the spectrum of health care. In this article, the authors illustrate how collaboration is promoting convergence toward a reference terminology for nursing by briefly summarizing a wide range of exemplary activities. These include: 1) the International Classification of Nursing Practice (ICNP) activities of the International Council of Nurses (ICN), 2) work in Brazil and Korea that has contributed to, and been stimulated by, ICNP developments, 3) efforts in the United States to improve understanding of the different types of terminologies needed in nursing and to promote harmonization and linking among them, and 4) current nursing participation in major multi-disciplinary standards initiatives. Although early nursing terminology work occurred primarily in isolation and resulted in some duplicative efforts, the activities summarized in this article demonstrate a tremendous level of collaboration and convergence not only in the discipline of nursing but in multi-disciplinary standards initiatives. These efforts are an important prerequisite for ensuring that nursing concepts are represented in computer-based systems in a manner that facilitates multi-purpose use at local, national, regional, and international level

Technology developments applied to healthcare/nursing

Future technology developments as applied to healthcare and particularly nursing were discussed. Emerging technologies such as genetics, small unobtrusive monitoring devices, use of information and communication technologies are as tools to not only facilitate but also promote communication among all parties of the healthcare process. These emerging technologies can be used for ubiquitous healthcare (uhealth). The role of nursing in the u-health is fundamental and required for success and growth. Nursing's role will evolve as nurses become 'information- mediators' in a broader-sense than current role. All technologies will ultimately focus on the consumer through 'behind-the-scenes' data collection, which in turn will also allow nurses to analyze these data to improve care. We need to acknowledge an increased presence and or pervasiveness of information technologies as key components of quality healthcare. This sort of acknowledgment will help propel nursing, and healthcare, to increase use of these tools. To develop nurses with these types of skills the nursing education process will require a fundamental change to integrate these technology-sorts of tools as necessary elements for success.info:eu-repo/semantics/publishedVersio

Development of a Provisional Domain Model for the Nursing Process for Use within the Health Level 7 Reference Information Model

Objective: Since 1999, the Nursing Terminology Summits have promoted the development, evaluation, and use of reference terminology for nursing and its integration into comprehensive health care data standards. The use of such standards to represent nursing knowledge, terminology, processes, and information in electronic health records will enhance continuity of care, decision support, and the exchange of comparable patient information. As part of this activity, working groups at the 2001, 2002, and 2003 Summit Conferences examined how to represent nursing information in the Health Level 7 (HL7) Reference Information Model (RIM). Design: The working groups represented the nursing process as a dynamic sequence of phases, each containing information specific to the activities of the phase. They used Universal Modeling Language (UML) to represent this domain knowledge in models. An Activity Diagram was used to create a dynamic model of the nursing process. After creating a structural model of the information used at each stage of the nursing process, the working groups mapped that information to the HL7 RIM. They used a hierarchical structure for the organization of nursing knowledge as the basis for a hierarchical model for "Findings about the patient.” The modeling and mapping reported here were exploratory and preliminary, not exhaustive or definitive. The intent was to evaluate the feasibility of representing some types of nursing information consistently with HL7 standards. Measurements: The working groups conducted a small-scale validation by testing examples of nursing terminology against the HL7 RIM class "Observation.” Results: It was feasible to map patient information from the proposed models to the RIM class "Observation.” Examples illustrate the models and the mapping of nursing terminology to the HL7 RIM. Conclusion: It is possible to model and map nursing information into the comprehensive health care information model, the HL7 RIM. These models must evolve and undergo further validation by clinicians. The integration of nursing information, terminology, and processes in information models is a first step toward rendering nursing information machine-readable in electronic patient records and messages. An eventual practical result, after much more development, would be to create computable, structured information for nursing documentatio

Factors of quality of care and their association with smartphone based PHR adoption in South Korean hospitals

Background Healthcare organizations have begun to adopt personal health records (PHR) systems to engage patients, but little is known about factors associated with the adoption of PHR systems at an organizational level. The objective of this study is to investigate factors associated with healthcare organizations’ adoption of PHR systems in South Korea. Methods The units of analysis were hospitals with more than 100 beds. Study data of 313 hospitals were collected from May 1 to June 30, 2020. The PHR adoption status for each hospital was collected from PHR vendors and online searches. Adoption was then confirmed by downloading the hospital’s PHR app and the PHR app was examined to ascertain its available functions. One major outcome variable was PHR adoption status at hospital level. Data were analysed by logistic regressions using SAS 9.4 version. Results Out of 313 hospitals, 103 (32.9%) hospitals adopted PHR systems. The nurse-patient ratio was significantly associated with PHR adoption (OR 0.758; 0.624 to 0.920, p = 0.005). The number of health information management staff was associated with PHR adoption (OR 1.622; 1.228 to 2.141, p = 0.001). The number of CTs was positively associated with PHR adoption (OR 5.346; 1.962 to 14.568, p = 0.001). Among the hospital characteristics, the number of beds was significantly related with PHR adoption in the model of standard of nursing care (OR 1.003; 1.001 to 1.005, p < 0.001), HIM staff (OR 1.004; 1.002 to 1.006, p < 0.001), and technological infrastructure (OR 1.050; 1.003 to 1.006, p < 0.001). Conclusions One-third of study hospitals had adopted PHR systems. Standard of nursing care as well as information technology infrastructure in terms of human resources for health information management and advanced technologies were significantly associated with adoption of PHR systems. A favourable environment for adopting new technologies in general may be associated with the adoption and use of PHR systems.This study was supported for two years by a Pusan National University Research Grant

Discussion of "Evidence-based health informatics:how do we know what we know?"

This article is part of a For-Discussion-Section of Methods of Information in Medicine about the paper "Evidence-based Health Informatics: How Do We Know What We Know?" written by Elske Ammenwerth [1]. It is introduced by an editorial. This article contains the combined commentaries invited to independently comment on the Ammenwerth paper. In subsequent issues the discussion can continue through letters to the editor. With these comments on the paper "Evidence-based Health Informatics: How do we know what we know?", written by Elske Ammenwerth [1], the journal seeks to stimulate a broad discussion on the challenges of evaluating information processing and information technology in health care. An international group of experts has been invited by the editor of Methods to comment on this paper. Each of the invited commentaries forms one section of this paper.11 page(s

Advancing nursing informatics in the next 5-10 years: What are the next steps?

© 2016 IMIA and IOS Press. Objective: This panel will explore expert perspectives on what is needed to advance nursing informatics (NI) based on results of an international survey conducted by the IMIA-NISIG Student Group in 2015. This panel will build on results of the survey's thematic analysis findings, highlighting: research, practice, education, collaboration, and visibility, as key areas needing action. Scope: Each expert panelist will speak to one of the identified themes in the context of the survey results. Each panelist will then provide perspectives on additional areas of opportunities, potential challenges, and offer actionable recommendations.Target audience: nursing informatics leaders, educators, policymakers, researchers, clinicians, students

Development and Evaluation of a Prototype CDSS for Fall Prevention

We developed a prototype CDSS that 1) provides tailored recommendations by combining a fall-risk prediction model, patients data, and evidence from CPGs, and 2) helps nurses to plan nursing care and document their activities for fall prevention. The accuracy of rules in knowledge base and inference engine was verified using ten scenarios and heuristics of user interface evaluated by four experts. We are currently evaluating the effects of the system on nurses&apos; workflow and patient outcomes.N

Mapping Korean National Health Insurance Reimbursement Claim Codes for Therapeutic and Surgical Procedures to SNOMED-CT to Facilitate Data Reuse

© 2022 International Medical Informatics Association (IMIA) and IOS Press.South Korea has a public and single-payer system for healthcare services based on fee-for-service payments. The National Health Insurance (NHI) reimbursement claim codes are used by all healthcare providers for reimbursement. This study mapped NHI reimbursement claim codes for therapeutic and surgical procedures to the Systematized Nomenclature of Medicine Clinical Terms (SNOMED-CT) to facilitate semantic interoperability and data reuse for research. The Source codes for mapping were 2,500 reimbursement claim codes for therapeutic and surgical procedures such as surgery, endoscopic procedures, and interventional radiology. The target terminology for mapping was the &apos;Procedure&apos; hierarchy of the international edition of SNOMED-CT released in July 2019. We translated Korean terms into English, clarified their meaning, extracted characteristics of the source codes, and mapped them to pre-coordinated concepts. If a source concept was not mapped to a pre-coordinated concept, we mapped it to a post-coordinated expression. The mapping results were validated internally using dual independent mapping and group discussion by trained terminologists, and by two physicians with experience of SNOMED-CT mapping. Out of 2,500 source codes, 1,298 (51.9%) codes were mapped to pre-coordinated concepts, and 1,202 (48.1%) codes were mapped to post-coordinated expressions. The mapping of the NHI reimbursement claim codes for therapeutic and surgical procedures to SNOMED-CT is expected to support clinical research by facilitating the utilization of health insurance claim data.N