A Question Answering Chatbot for Gastric Cancer Patients After Curative Gastrectomy: Development and Evaluation of User Experience and Performance.

Postoperative gastric cancer patients have many questions about managing their daily lives with various symptoms and discomfort. This study aimed to develop a knowledge-based question answering (QA) chatbot for their self-management and to evaluate the user experience and performance of the chatbot. To support the chatbot's natural language processing, we analyzed QA texts from an online self-help group, clinical guidelines, and refined frequently asked questions related to gastric cancer. We developed a named entity classification with seven superconcepts, 4544 subconcepts, and 1415 synonyms. We also developed a knowledge base by linking the users' classified question intents with the experts' answers and knowledge resources, including 677 question intents and scripts with standard QA pairs and similar question phrases. A chatbot called "GastricFAQ" was built, reflecting the question topics of the named entity classification and QA pairs of the knowledge base. User experience evaluation (N = 56) revealed the highest mean score for usefulness (4.41/5.00), with all other items rated 4.00 or higher, except desirability (3.85/5.00). The chatbot's accuracy, precision, recall, and F score ratings were 85.2%, 87.6%, 96.8%, and 92.0%, respectively, with immediate answers. GastricFAQ could be provided as one option to obtain immediate information with relatively high accuracy for postoperative gastric cancer patients.

Effects of communication team training on clinical competence in Korean Advanced Life Support: A randomized controlled trial.

We conducted a randomized controlled trial to study the effects of interprofessional communication team training on clinical competence in the Korean Advanced Life Support provider course using a team communication framework. Our study involved 73 residents and 42 nurses from a tertiary hospital in Seoul. The participants were randomly assigned to the intervention or control group, forming 10 teams per group. The intervention group underwent interprofessional communication team training with a cardiac arrest simulation and standardized communication tools. The control group completed the Korean Advanced Life Support provider course. All participants completed a communication clarity self-reporting questionnaire. Clinical competence was assessed using a clinical competency scale comprising technical and nontechnical tools. Blinding was not possible due to the educational intervention. Data were analyzed using a Mann-Whitney U test and a multivariate Kruskal-Wallis H test. While no significant differences were observed in communication clarity between the two groups, there were significant differences in clinical competence. Therefore, the study confirmed that the intervention can enhance the clinical competence of patient care teams in cardiopulmonary resuscitation.

Current Status of SNOMED CT National Extensions and Terminology Managements.

We reviewed and surveyed 15 SNOMEDCT national member countries for SNOMED CT national extensions and terminology managements. We found that national extensions were used for adding new contents, developing reference sets, translating, and mapping with other classification system; and terminology management varies in composition and content due to healthcare environment of each member country, eHealth strategy, and infrastructure of national release centers.

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. The usability was evaluated 1 month after CDSS implementation. In terms of time and frequency, changes in fall-prevention nursing practices were analyzed using survey data and nursing documentation, respectively. Finally, the incidence of falls before and after system implementation was compared to examine the clinical effectiveness of the CDSS. RESULTS: According to the usability test, the average ease of learning score (5.083 of 7) was the highest among 4 dimensions. The time spent engaged in fall-prevention nursing care per patient per shift increased, particularly for nursing diagnoses and planning. Moreover, the mean frequency of daily documented fall-prevention interventions per patient also increased. Particularly, nursing statements related to nonspecific interventions such as environmental modifications increased. However, the incidence of falls did not decrease after implementation of the CDSS. CONCLUSIONS: Although adoption of the computerized system increased the time spent and number of records created in terms of fall-prevention practices in nurses, no improvement in clinical outcomes was observed, particularly in terms of fall rate reduction.

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. The mapping results were validated by two experts. Out of 4,111 codes, 90.5% were mapped to the concepts of procedure hierarchy in SNOMED CT. Of them, 51.4% of the codes were exactly mapped to SNOMED CT concepts, and 34.8% of the codes were mapped to SNOMED CT concepts as one-to-one mapping.

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. Instead, this is performed sporadically and independently at each local medical institution. The quality of the mapping, therefore, cannot be guaranteed. OBJECTIVE: This study aimed to develop and introduce a guideline to map local Korean terms to the SNOMED CT used to document clinical findings and procedures in electronic health records at health care institutions in South Korea. METHODS: The guidelines were developed from December 2020 to December 2022. An extensive literature review was conducted. The overall structures and contents of the guidelines with diverse use cases were developed by referencing the existing SNOMED CT mapping guidelines, previous studies related to SNOMED CT mapping, and the experiences of the committee members. The developed guidelines were validated by a guideline review panel. RESULTS: The SNOMED CT mapping guidelines developed in this study recommended the following 9 steps: define the purpose and scope of the map, extract terms, preprocess source terms, preprocess source terms using clinical context, select a search term, use search strategies to find SNOMED CT concepts using a browser, classify mapping correlations, validate the map, and build the final map format. CONCLUSIONS: The guidelines developed in this study can support the standardized mapping of local Korean terms into SNOMED CT. Mapping specialists can use this guideline to improve the mapping quality performed at individual local medical institutions.

Hospitals' Adoption of Mobile-Based Personal Health Record Systems and Patients' Characteristics: A Cross-Sectional Study Analyzing National Healthcare Big Data.

Insufficient information exists on the associations between hospitals' adoption of mobile-based personal health record (mPHR) systems and patients' characteristics. This study explored the associations between patients' characteristics and hospitals' adoption of mPHR systems in Korea. This cross-sectional study used 316 hospitals with 100 or more beds as the unit of analysis. Previously collected data on mPHR adoption from May 1 to June 30, 2020 were analyzed. National health insurance claims data for 2019 were also used to analyze patients' characteristics. The dependent variable was mPHR system adoption (0 vs 1) and the main independent variables were the number of patients, age distribution, and proportions of patients with cancer, diabetes, and hypertension among inpatients and outpatients. The number of inpatients was significantly associated with mPHR adoption (adjusted odds ratio [aOR]: 1.174; 1.117-1.233, P < .001), as was the number of outpatients (aOR: 1.041; 1.028-1.054, P < .001). The proportion of inpatients aged 31 to 60 years to those aged 31 years and older was also associated with hospital mPHR adoption (aOR: 1.053; 1.022-1.085, P = .001). mPHR system adoption was significantly associated with the proportion of inpatients (aOR: 1.089; 1.012-1.172, P = .024) and outpatients (aOR: 1.138; 1.026-1.263, P = .015) with cancer and outpatients (aOR: 1.271; 1.101-1.466, P = .001) with hypertension. Although mPHR systems are useful for the management of chronic diseases such as diabetes and hypertension, the number of patients, younger age distribution, and the proportion of cancer patients were closely associated with hospitals' introduction of mPHR systems.

Use of the clinical care classification in South Korean nursing practice: Challenges and opportunities.

BACKGROUND AND OBJECTIVES: A government-driven standardization of nursing terminology including the Clinical Care Classification (CCC) was endorsed in South Korea in 2015, but the number of hospitals who have adopted this standard terminology remains unknown. This study aimed to determine the CCC awareness, adoption, and utilization statuses and its association with patient experience in South Korea. DESIGN, SETTING, AND PARTICIPANTS: A nationwide telephone survey was conducted from January 13 to February 12, 2022 among 217 tertiary and secondary hospitals participating in the health information exchange network. The survey questionnaire included 22 items in 3 categories: current status of electronic nursing records, awareness and adoption of standard terminology, and open-ended questions regarding standard usage and dissemination. General characteristics and experience scores of the patients of the surveyed hospitals were collected from the publicly available data sources. Data analysis was performed using descriptive statistics, t-test, and generalized linear regression. MAIN OUTCOMES AND MEASURES: The rates of awareness and adoption in hospitals to the nursing terminology standard of the CCC were calculated, and the current status of electronic nursing records used in practice was examined. The relationships between CCC awareness and the characteristics of hospitals in their patient experiences of health services were also identified. RESULTS: The survey response rate was 24.9 % (54/217). Two out of three hospitals (68.5 %) were aware of the CCC. These hospitals had 800 beds or more, and higher scores for patient experience. CCC awareness was significantly related to increases in the overall scores for patient experiences (t = 2.70, p =.0103), but no significance with sub-score for nursing service (t = 1.23, p =.1594). CONCLUSIONS: With a high adoption rate of electronic medical record systems, two-third hospitals acknowledged their CCC awareness, but were still lagged in adoption and usage of it in practice with operational challenges. The CCC awareness has potential relationships with positive patient experience.

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

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 'Procedure' 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.

Mapping Korean National Health Insurance Pharmaceutical Claim Codes to SNOMED CT.

The objective of this study was to map pharmaceutical claim codes to SNOMED CT and thereby facilitate multicenter collaborative research and improve semantic interoperability. The claim codes were mapped to SNOMED CT using rule-based automated and manual methods. The maps were internally validated by terminologists and a pharmacist. Finally, 80% of all claim codes were mapped to the concepts of Pharmaceutical/biologic product hierarchy in SNOMED CT. Of them, 50.6% of the codes were exactly mapped to one clinical drug branch concept.

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. We additionally analyzed the differences in the mean frequencies of tailored fall prevention practices according to individual patients' specific risk factors. RESULTS: The nurses documented more fall prevention practices for patients at a high risk of falling and nonfallers than for patients at a low risk of falling and fallers. Specifically, the difference in nursing practices related to environmental modifications was largest between patients at a high risk of falling and those at a low risk of falling. There were also large differences in the nursing practices related to mental status, dizziness/vertigo, and mobility limitations between fallers and nonfallers. There was more documentation of tailored fall prevention practices related to mobility limitations for patient with mild lower limb weakness than for those with good power and balance. In contrast, patients with severe lower limb weakness had received fewer fall prevention practices related to mobility limitations. CONCLUSIONS: The present findings emphasize that individual risk-specific nursing interventions in addition to universal precautions are crucial for preventing falls among patients.

Development of a prediction models for chemotherapy-induced adverse drug reactions: A retrospective observational study using electronic health records.

PURPOSE: Chemotherapy-induced adverse drug reactions (ADRs) are common and diverse, and not only affect changes or interruptions to treatment schedules, but also negatively affect the patient's quality of life. This study aimed to predict eight chemotherapy-induced ADRs based on electronic health records (EHR) data using machine-learning algorithms. METHODS: We used EHR data of 6812 chemotherapy cycles for 935 adult patients receiving four different chemotherapy regimens (FOLFOX, 5-fluorouracil + oxaliplatin + leucovorin; FOLFIRI, 5-fluorouracil + irinotecan + leucovorin; paclitaxel; and GP, gemcitabine + cisplatin) at a tertiary teaching hospital between January 2015 and June 2016. The predicted ADRs included nausea-vomiting, fatigue-anorexia, diarrhea, peripheral neuropathy, hypersensitivity, stomatitis, hand-foot syndrome, and constipation. Three machine learning algorithms were used to developed prediction models: logistic regression, decision tree, and artificial neural network. We compared the performance of the models with area of under the ROC (Receiver Operating Characteristic) curve (AUC) and accuracy. RESULTS: The AUCs of the logistic regression, decision tree, and artificial neural network models were 0.62-0.83, 0.61-0.83, and 0.62-0.83, respectively, and the accuracies were 0.59-0.84, 0.55-0.88, and 0.57-0.88, respectively. Among the algorithms, the logistic regression models performed best and had the highest AUC for six ADRs (range 0.67-0.83). The nausea-vomiting prediction models performed best with an AUC of 0.83 for the three algorithms. CONCLUSIONS: The prediction models for chemotherapy-induced ADRs were able to predict eight ADRs using EHR data. The logistic regression models were best suited to predict ADRs. The models developed in this study can be used to predict the risk of ADRs in patients receiving chemotherapy.

Relationships Between Nurses' Work System, Safety-Related Performance, and Outcomes: A Structural Equation Model.

OBJECTIVES: We examined relationships between nurses' work system, safety-related performance, and outcomes based on a modified Systems Engineering Initiative for Patient Safety model. METHODS: A cross-sectional survey was conducted with 408 nurses from 2 general hospitals. Data on work system factors (person, organization, environment, tools, and task), processes (safety-related performance), and outcomes (staff and clinical outcomes) were collected. Structural equation modeling was used to determine the relationships between nurses' work system factors, safety-related processes, and outcomes. RESULTS: Structural equation modeling yielded a comparative fit index of 0.918, standardized root mean square residual of 0.055, and root mean square error of approximation of 0.054, indicating an acceptable model fit. The person factor had a significant positive direct effect on nurses' safety-related performance, and significant negative direct and indirect effects on the clinical outcome. The organization factor had significant positive direct effects on nurses' safety-related performance and staff outcome, and a negative indirect effect on the clinical outcome. The task factor had a significant positive direct effect on staff outcome. However, the environment and tools factors had no significant effects on safety-related performance or outcomes. CONCLUSIONS: The findings demonstrated the usefulness of the Systems Engineering Initiative on Patient Safety model to explain safety-related performance and outcomes, indicating differential effects of work system factors. Although the person factor significantly affected safety performance and clinical outcomes, the organization factor was the most influential component for promoting safety-related performance and staff and clinical outcomes. These results can be used to prioritize activities for patient safety.

Mapping the Korean National Health Checkup Questionnaire to Standard Terminologies.

OBJECTIVES: An increasing emphasis has been placed on the integration of clinical data and patient-generated health data (PGHD), which are generated outside of hospitals. This study explored the possibility of using standard terminologies to represent PGHD for data integration. METHODS: We chose the 2020 general health checkup questionnaire of the Korean Health Screening Program as a resource. We divided every component of the questionnaire into entities and values, which were mapped to standard terminologies-Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) version 2020-07-31 and Logical Observation Identifiers Names and Codes (LOINC) version 2.68. RESULTS: Eighty-nine items were derived from the 17 questions of the 2020 health examination questionnaire, of which 76 (85.4%) were mapped to standard terms. Fifty-two items were mapped to SNOMED CT and 24 items were mapped to LOINC. Among the items mapped to SNOMED CT, 35 were mapped to pre-coordinated expressions and 17 to post-coordinated expressions. Forty items had one-to-one relationships, and 17 items had one-to-many relationships. CONCLUSIONS: We achieved a high mapping rate (85.4%) by using both SNOMED CT and LOINC. However, we noticed some issues while mapping the Korean general health checkup questionnaire (i.e., lack of explanations, vague questions, and overly narrow concepts). In particular, items combining two or more concepts into a single item were not appropriate for mapping using standard terminologies. Although it is not the case that all items need to be expressed in standard terminology, essential items should be presented in a way suitable for mapping to standard terminology by revising the questionnaire in the future.

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.

Correction: A Determinants-of-Fertility Ontology for Detecting Future Signals of Fertility Issues From Social Media Data: Development of an Ontology.

[This corrects the article DOI: 10.2196/25028.].

A Determinants-of-Fertility Ontology for Detecting Future Signals of Fertility Issues From Social Media Data: Development of an Ontology.

BACKGROUND: South Korea has the lowest fertility rate in the world despite considerable governmental efforts to boost it. Increasing the fertility rate and achieving the desired outcomes of any implemented policies requires reliable data on the ongoing trends in fertility and preparations for the future based on these trends. OBJECTIVE: The aims of this study were to (1) develop a determinants-of-fertility ontology with terminology for collecting and analyzing social media data; (2) determine the description logics, content coverage, and structural and representational layers of the ontology; and (3) use the ontology to detect future signals of fertility issues. METHODS: An ontology was developed using the Ontology Development 101 methodology. The domain and scope of the ontology were defined by compiling a list of competency questions. The terms were collected from Korean government reports, Korea's Basic Plan for Low Fertility and Aging Society, a national survey about marriage and childbirth, and social media postings on fertility issues. The classes and their hierarchy were defined using a top-down approach based on an ecological model. The internal structure of classes was defined using the entity-attribute-value model. The description logics of the ontology were evaluated using Protégé (version 5.5.0), and the content coverage was evaluated by comparing concepts extracted from social media posts with the list of ontology classes. The structural and representational layers of the ontology were evaluated by experts. Social media data were collected from 183 online channels between January 1, 2011, and June 30, 2015. To detect future signals of fertility issues, 2 classes of the ontology, the socioeconomic and cultural environment, and public policy, were identified as keywords. A keyword issue map was constructed, and the defined keywords were mapped to identify future signals. R software (version 3.5.2) was used to mine for future signals. RESULTS: A determinants-of-fertility ontology comprised 236 classes and terminology comprised 1464 synonyms of the 236 classes. Concept classes in the ontology were found to be coherently and consistently defined. The ontology included more than 90% of the concepts that appeared in social media posts on fertility policies. Average scores for all of the criteria for structural and representations layers exceeded 4 on a 5-point scale. Violence and abuse (socioeconomic and cultural factor) and flexible working arrangement (fertility policy) were weak signals, suggesting that they could increase rapidly in the future. CONCLUSIONS: The determinants-of-fertility ontology developed in this study can be used as a framework for collecting and analyzing social media data on fertility issues and detecting future signals of fertility issues. The future signals identified in this study will be useful for policy makers who are developing policy responses to low fertility.

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. RESULTS: We identified the barriers and facilitators to adopt SNOMED CT experienced by international terminology experts and prospective Korean users. They were related to governance and infrastructure, support services for use, education and training programs, use cases, and vendor capability to implement SNOMED CT. Based on these findings, we identified strategies for adopting and implementing SNOMED CT in Korea. They included the establishment of SNOMED CT management infrastructure, the development of SNOMED CT education and training programs for various user groups, the provision of support services for SNOMED CT use, and the development of SNOMED CT use cases. CONCLUSIONS: These strategies for the adoption and implementation of SNOMED CT need to be executed step by step.