Indicators of clinical deterioration in adult general ward patients from nurses' perspectives: a mixed-methods systematic review.

Background: Early recognition and response to deteriorating patients in general wards are core competencies for nurses. Clinical deterioration is a worsening condition that increases the risk of morbidity and mortality. Although objective measures are commonly used, recent research suggests that subjective data and nurses' intuitions can serve as valuable indicators for early detection of deterioration in patients.

Dementia Ontology Development to Facilitate Collection of High-Quality Dementia Data.

The population of dementia patients is on the rise, as society undergoes rapid aging. This led to an expansion of dementia-related data. This study aims to develop a comprehensive dementia ontology to facilitate the collection and analysis of high-quality dementia data.

Identification of Predictors for Clinical Deterioration in Patients With COVID-19 via Electronic Nursing Records: Retrospective Observational Study.

Background: Few studies have used standardized nursing records with Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT) to identify predictors of clinical deterioration.

Objective: This study aims to standardize the nursing documentation records of patients with COVID-19 using SNOMED CT and identify predictive factors of clinical deterioration in patients with COVID-19 via standardized nursing records.

Methods: In this study, 57,558 nursing statements from 226 patients with COVID-19 were analyzed.

Impact of a Decision Support System on Fall-Prevention Nursing Practices.

Objectives: The aim of this study was to develop a computerized decision support system (CDSS) that could automatically calculate the risk of falls using electronic medical record data and provide evidence-based fall-prevention recommendations based on risk factors. Furthermore, we analyzed the usability and effect of the system on fall-prevention nursing practices.

Methods: A computerized fall-prevention system was developed according to the system development life cycle, and implemented between March and August 2019 in a single medical unit with a high prevalence of falls.

Nurses' Burden of Elimination Care: Sequential Explanatory Mixed-Methods Design.

Background: Inpatients commonly experience problems with elimination due to incontinence, urinary retentions, and complications with indwelling catheters. Although elimination care (EC) is an important nursing area, few studies explore the burden of EC on nurses.

Aim: To identify the burden on EC by analyzing nurses' opinions using sequential explanatory mixed method.

Exploring Nursing Care for Patients With COVID-19 Using International Classification for Nursing Practice-Based Nursing Records.

This study explored nursing care topics for patients with the coronavirus disease 2019 admitted to the wards and intensive care units using International Classification for Nursing Practice-based nursing narratives. A total of 256630 nursing statements from 555 adult patients admitted from December 2019 to June 2022 were extracted from the clinical data warehouse. The International Classification for Nursing Practice concepts mapped to 301 unique nursing statements that accounted for the top 90% of all cumulative nursing narratives were used for analysis.

Mapping Korean National Health Insurance Claim Codes for Laboratory Test to SNOMED CT.

The aim of this study was to map Korean national health insurance claims codes for laboratory tests to SNOMED CT. The mapping source codes were 4,111 claims codes for laboratory test and mapping target codes were the International Edition of SNOMED CT released on July 31, 2020. We used rule-based automated and manual mapping methods.

A SNOMED CT Mapping Guideline for the Local Terms Used to Document Clinical Findings and Procedures in Electronic Medical Records in South Korea: Methodological Study.

Background: South Korea joined SNOMED International as the 39th member country. To ensure semantic interoperability, South Korea introduced SNOMED CT (Systemized Nomenclature of Medicine-Clinical Terms) in 2020. However, there is no methodology to map local Korean terms to SNOMED CT.

Effectiveness of the Use of Standardized Vocabularies on Epilepsy Patient Cohort Generation.

Objectives: This study investigated the effectiveness of using standardized vocabularies to generate epilepsy patient cohorts with local medical codes, SNOMED Clinical Terms (SNOMED CT), and International Classification of Diseases tenth revision (ICD-10)/Korean Classification of Diseases-7 (KCD-7).

Methods: We compared the granularity between SNOMED CT and ICD-10 for epilepsy by counting the number of SNOMED CT concepts mapped to one ICD-10 code. Next, we created epilepsy patient cohorts by selecting all patients who had at least one code included in the concept sets defined using each vocabulary.

Comparisons of Fall Prevention Activities Using Electronic Nursing Records: A Case-Control Study.

Objective: The aim of this study was to compare the current fall prevention nursing practices with the evidence-based practices recommended in clinical practice guidelines according to the risk of falling and specific risk factors.

Methods: The standardized nursing statements of 12,277 patients were extracted from electronic nursing records and classified into groups according to the risk of falling and individual patients' specific risk factors. The mean frequencies of the fall prevention practices in 10 categories derived from clinical practice guidelines were compared among the groups.

Patient-Level Fall Risk Prediction Using the Observational Medical Outcomes Partnership's Common Data Model: Pilot Feasibility Study.

Background: Falls in acute care settings threaten patients' safety. Researchers have been developing fall risk prediction models and exploring risk factors to provide evidence-based fall prevention practices; however, such efforts are hindered by insufficient samples, limited covariates, and a lack of standardized methodologies that aid study replication.

Objective: The objectives of this study were to (1) convert fall-related electronic health record data into the standardized Observational Medical Outcome Partnership's (OMOP) common data model format and (2) develop models that predict fall risk during 2 time periods.

Strategies for Adopting and Implementing SNOMED CT in Korea.

Objectives: The objective of this study was to introduce the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT), to describe use cases of SNOMED CT with the barriers and facilitators, and finally, to propose strategies for adopting and implementing SNOMED CT in Korea as a member of SNOMED International.

Methods: We reviewed a collection of SNOMED CT documents, such as introductory materials, practical guides, technical specifications, and reference materials provided by SNOMED International and the literature on SNOMED CT published by researchers to identify use cases of SNOMED CT with barriers and facilitators. We also surveyed the attendees of SNOMED CT education and training series offered by the Korea Human Resource Development Institute for Health and Welfare to identify perceived barriers to adopting SNOMED CT in Korea.

Improving Prediction of Fall Risk Using Electronic Health Record Data With Various Types and Sources at Multiple Times.

Inpatient falls are among the most common adverse events threatening patient safety. Although many studies have developed predictive models for fall risk, there are some drawbacks. First, most previous studies have relied on an incident-reporting system alone to identify fall events.

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' workflow and patient outcomes.

Digital Epidemiology: Use of Digital Data Collected for Non-epidemiological Purposes in Epidemiological Studies.

Objectives: We reviewed digital epidemiological studies to characterize how researchers are using digital data by topic domain, study purpose, data source, and analytic method.

Methods: We reviewed research articles published within the last decade that used digital data to answer epidemiological research questions. Data were abstracted from these articles using a data collection tool that we developed.

Testing the Predictive Validity of the Hendrich II Fall Risk Model.

Cumulative data on patient fall risk have been compiled in electronic medical records systems, and it is possible to test the validity of fall-risk assessment tools using these data between the times of admission and occurrence of a fall. The Hendrich II Fall Risk Model scores assessed during three time points of hospital stays were extracted and used for testing the predictive validity: (a) upon admission, (b) when the maximum fall-risk score from admission to falling or discharge, and (c) immediately before falling or discharge. Predictive validity was examined using seven predictive indicators.

Use of EHR Data to Identify Factors Affecting the Time to Fall.

Although there are many studies of falls occurring in a hospital setting, research on factors affecting time to fall after admission is scarce. It is important for nurses to identify factors contributing to an early fall so that they can pay particular attention to patients with such factors. In this study, patients who sustained a fall were extracted from an adverse event reporting system and narrative nursing records of those hospitalized between January 2015 and May 2016.

Ontology-Based Approach to Social Data Sentiment Analysis: Detection of Adolescent Depression Signals.

Background: Social networking services (SNSs) contain abundant information about the feelings, thoughts, interests, and patterns of behavior of adolescents that can be obtained by analyzing SNS postings. An ontology that expresses the shared concepts and their relationships in a specific field could be used as a semantic framework for social media data analytics.

Objective: The aim of this study was to refine an adolescent depression ontology and terminology as a framework for analyzing social media data and to evaluate description logics between classes and the applicability of this ontology to sentiment analysis.

2016 Year-in-Review of Clinical and Consumer Informatics: Analysis and Visualization of Keywords and Topics.

Objectives: The objective of this study was to review and visualize the medical informatics field over the previous 12 months according to the frequencies of keywords and topics in papers published in the top four journals in the field and in , an official journal of the Korean Society of Medical Informatics.

Methods: A six-person team conducted an extensive review of the literature on clinical and consumer informatics. The literature was searched using keywords employed in the American Medical Informatics Association year-in-review process and organized into 14 topics used in that process.

Development and Evaluation of an Adolescents' Depression Ontology for Analyzing Social Data.

This study aims to develop and evaluate an ontology for adolescents' depression to be used for collecting and analyzing social data. The ontology was developed according to the 'ontology development 101' methodology. Concepts were extracted from clinical practice guidelines and related literatures.

Current Status of Nursing Informatics Education in Korea.

Objectives: This study presents the current status of nursing informatics education, the content covered in nursing informatics courses, the faculty efficacy, and the barriers to and additional supports for teaching nursing informatics in Korea.

Methods: A set of questionnaires consisting of an 18-item questionnaire for nursing informatics education, a 6-item questionnaire for faculty efficacy, and 2 open-ended questions for barriers and additional supports were sent to 204 nursing schools via email and the postal service. Nursing schools offering nursing informatics were further asked to send their syllabuses.