Healthcare Informatics Research最新文献_第8页

FIT4PEDON: Mobile Nutrition Counseling Application Effectiveness and Usability for Childhood Cancer Survivors. FIT4PEDON：儿童癌症幸存者的移动营养咨询应用有效性和可用性。

IF 2.3

Healthcare Informatics Research Pub Date : 2025-01-01 Epub Date: 2025-01-31 DOI: 10.4258/hir.2025.31.1.37

R Bavatharani, V Supriya, Julius Xavier Scott, Suresh Sankaranarayanan

{"title":"FIT4PEDON: Mobile Nutrition Counseling Application Effectiveness and Usability for Childhood Cancer Survivors.","authors":"R Bavatharani, V Supriya, Julius Xavier Scott, Suresh Sankaranarayanan","doi":"10.4258/hir.2025.31.1.37","DOIUrl":"10.4258/hir.2025.31.1.37","url":null,"abstract":"Objectives: Conventional face-to-face nutrition counseling has played a crucial role in promoting healthy habits. However, the emergence of digital health technologies has introduced mobile app-based nutrition counseling as an effective alternative. This research aims to develop and evaluate the usability and effectiveness of the FIT4PEDON mobile nutrition counseling application in promoting healthy dietary behaviors and lifestyle modifications among childhood cancer survivors (CCS).Methods: This study employed a mixed-methods approach, incorporating both survey and qualitative and quantitative analyses. A total of 33 health care professional experts participated. The reliability of the questionnaire was assessed using the Kuder-Richardson method, and its content validity was confirmed through expert evaluation. Usability testing was conducted with a validated questionnaire.Results: The development process resulted in two applications: an Android mobile application and an admin web application. The findings indicated that a significant proportion of experts endorsed the app for dietary management. Statistical analysis showed significant differences between \"yes\" and \"no\" responses. However, no significant differences were found when comparing responses across different sex or age groups.Conclusions: The FIT4PEDON application shows promise in supporting CCS to adopt healthier lifestyles. Nevertheless, the study underscores the necessity for further research, particularly focusing on specific age groups of experts with relevant experience, to achieve more conclusive results. Leveraging technology through mobile apps has the potential to improve the quality of survivorship care and foster sustained engagement in long-term care for pediatric cancer survivors.","PeriodicalId":12947,"journal":{"name":"Healthcare Informatics Research","volume":"31 1","pages":"37-47"},"PeriodicalIF":2.3,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11854622/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143457703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Feature Selection for Hypertension Risk Prediction Using XGBoost on Single Nucleotide Polymorphism Data. 基于单核苷酸多态性数据的XGBoost高血压风险预测特征选择

IF 2.3

Healthcare Informatics Research Pub Date : 2025-01-01 Epub Date: 2025-01-31 DOI: 10.4258/hir.2025.31.1.16

Lailil Muflikhah, Tirana Noor Fatyanosa, Nashi Widodo, Rizal Setya Perdana, Solimun, Hana Ratnawati

{"title":"Feature Selection for Hypertension Risk Prediction Using XGBoost on Single Nucleotide Polymorphism Data.","authors":"Lailil Muflikhah, Tirana Noor Fatyanosa, Nashi Widodo, Rizal Setya Perdana, Solimun, Hana Ratnawati","doi":"10.4258/hir.2025.31.1.16","DOIUrl":"10.4258/hir.2025.31.1.16","url":null,"abstract":"Objectives: Hypertension, commonly known as high blood pressure, is a prevalent and serious condition affecting a significant portion of the adult population globally. It is a chronic medical issue that, if left unaddressed, can lead to severe health complications, including kidney problems, heart disease, and stroke. This study aims to develop a feature selection model using the XGBoost algorithm to identify specific single nucleotide polymorphisms (SNPs) as biomarkers for detecting hypertension risk.Methods: We propose using the high dimensionality of genetic variations (i.e., SNPs) to build a classifier model for prediction. In this study, SNPs were used as markers for hypertension in patients. We utilized the OpenSNP dataset, which includes 19,697 SNPs from 2,052 samples. Extreme gradient boosting (XGBoost) is an ensemble machine learning method employed here for feature selection, which incrementally adjusts weights in a series of steps.Results: The experimental results identified 292 SNPs that exhibited high performance, with an F1-score of 98.55%, precision of 98.73%, recall of 98.38%, and overall accuracy of 98%. This study provides compelling evidence that the XGBoost feature selection method outperforms other representative feature selection methods, such as genetic algorithms, analysis of variance, chi-square, and principal component analysis, in predicting hypertension risk, demonstrating its effectiveness.Conclusions: We developed a model for predicting hypertension using the SNPs dataset. The high dimensionality of SNP data was effectively managed to identify significant features as biomarkers using the XGBoost feature selection method. The results indicate high performance in predicting the risk of hypertension.","PeriodicalId":12947,"journal":{"name":"Healthcare Informatics Research","volume":"31 1","pages":"16-22"},"PeriodicalIF":2.3,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11854617/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143457532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Triage Data-Driven Prediction Models for Hospital Admission of Emergency Department Patients: A Systematic Review. 急诊科患者入院分诊数据驱动预测模型：系统综述。

IF 2.3

Healthcare Informatics Research Pub Date : 2025-01-01 Epub Date: 2025-01-31 DOI: 10.4258/hir.2025.31.1.23

Hyun A Shin, Hyeonji Kang, Mona Choi

{"title":"Triage Data-Driven Prediction Models for Hospital Admission of Emergency Department Patients: A Systematic Review.","authors":"Hyun A Shin, Hyeonji Kang, Mona Choi","doi":"10.4258/hir.2025.31.1.23","DOIUrl":"10.4258/hir.2025.31.1.23","url":null,"abstract":"Objectives: Emergency department (ED) overcrowding significantly impacts healthcare efficiency, safety, and resource management. Predictive models that utilize triage information can streamline the admission process. This review evaluates existing hospital admission prediction models that have been developed or validated using triage data for adult ED patients.Methods: A systematic search of PubMed, Embase, CINAHL, Web of Science, and the Cochrane Library was conducted. Studies were selected if they developed or validated predictive models for hospital admission using triage data from adult ED patients. Data extraction adhered to the CHARMS (Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies), and the risk of bias was evaluated using PROBAST (Prediction model Risk of Bias Assessment Tool).Results: Twenty studies met the inclusion criteria, employing logistic regression and machine learning techniques. Logistic regression was noted for its traditional use and clinical interpretability, whereas machine learning provided enhanced flexibility and potential for better predictive accuracy. Common predictors included patient demographics, triage category, vital signs, and mode of arrival. The area under the curve values for model performance ranged from 0.80 to 0.89, demonstrating strong discriminatory ability. However, external validation was limited, and there was variability in outcome definitions and model generalizability.Conclusions: Predictive models based on triage data show promise in supporting ED operations by facilitating early predictions of hospital admissions, which could help decrease boarding times and enhance patient flow. Further research is necessary to validate these models in various settings to confirm their applicability and reliability.","PeriodicalId":12947,"journal":{"name":"Healthcare Informatics Research","volume":"31 1","pages":"23-36"},"PeriodicalIF":2.3,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11854635/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143457773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Deep Learning Model-Based Detection of Anemia from Conjunctiva Images. 基于深度学习模型的结膜图像贫血检测。

IF 2.3

Healthcare Informatics Research Pub Date : 2025-01-01 Epub Date: 2025-01-31 DOI: 10.4258/hir.2025.31.1.57

Najmus Sehar, Nirmala Krishnamoorthi, C Vinoth Kumar

{"title":"Deep Learning Model-Based Detection of Anemia from Conjunctiva Images.","authors":"Najmus Sehar, Nirmala Krishnamoorthi, C Vinoth Kumar","doi":"10.4258/hir.2025.31.1.57","DOIUrl":"10.4258/hir.2025.31.1.57","url":null,"abstract":"Objectives: Anemia is characterized by a reduction in red blood cells, leading to insufficient levels of hemoglobin, the molecule responsible for carrying oxygen. The current standard method for diagnosing anemia involves analyzing blood samples, a process that is time-consuming and can cause discomfort to participants. This study offers a comprehensive analysis of non-invasive anemia detection using conjunctiva images processed through various machine learning and deep learning models. The focus is on the palpebral conjunctiva, which is highly vascular and unaffected by melanin content.Methods: Conjunctiva images from both anemic and non-anemic participants were captured using a smartphone. A total of 764 conjunctiva images were augmented to 4,315 images using the deep convolutional generative adversarial network model to prevent overfitting and enhance model robustness. These processed and augmented images were then utilized to train and test multiple models, including statistical regression, machine learning algorithms, and deep learning frameworks.Results: The stacking ensemble framework, which includes the models VGG16, ResNet-50, and InceptionV3, achieved a high area under the curve score of 0.97. This score demonstrates the framework's exceptional capability in detecting anemia through a noninvasive approach.Conclusions: This study introduces a noninvasive method for detecting anemia using conjunctiva images obtained with a smartphone and processed using advanced deep learning techniques.","PeriodicalId":12947,"journal":{"name":"Healthcare Informatics Research","volume":"31 1","pages":"57-65"},"PeriodicalIF":2.3,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11854623/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143457614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Extreme Prototyping for a Community Health Worker Medical Application. 社区卫生工作者医疗应用程序的极限原型。

IF 2.3

Healthcare Informatics Research Pub Date : 2025-01-01 Epub Date: 2025-01-31 DOI: 10.4258/hir.2025.31.1.88

Jan Noel Molon

{"title":"Extreme Prototyping for a Community Health Worker Medical Application.","authors":"Jan Noel Molon","doi":"10.4258/hir.2025.31.1.88","DOIUrl":"10.4258/hir.2025.31.1.88","url":null,"abstract":"Objectives: Noncommunicable diseases (NCDs) pose a significant burden, especially in low- and middle-income countries such as the Philippines. To tackle this issue, the Department of Health launched the Philippine Package of Essential Non-Communicable Disease Interventions (PhilPEN), which includes the use of the Noncommunicable Disease Risk Assessment Form. However, healthcare workers have encountered difficulties due to the form's complexity and the lengthy process required. This study aimed to create a mobile medical app for community health workers by adapting the PhilPEN Noncommunicable Disease Risk Assessment Form using the extreme prototyping framework. The focus was on simplifying data collection and improving the usability of health technology solutions.Methods: The study employed a qualitative research methodology, which included key informant interviews, linguistic validation, and cognitive debriefing. The extreme prototyping framework was utilized for app development, comprising static prototype, dynamic prototype, and service implementation phases. The app was developed with HTML5, CSS3, JavaScript, and Apache Cordova, adhering to World Health Organization (WHO) guidelines and PhilHealth Circular.Results: The development process involved three prototype cycles, each consisting of multiple mini-cycles of feedback, system design, coding, and testing. Version 1.xx was aligned with WHO guidelines, Version 2.xx integrated the Department of Health NCD Risk Assessment Form, and Version 3.xx adapted to the updated form with expanded requirements.Conclusions: The extreme prototyping framework was effectively applied in the development of a medical mobile app, facilitating the integration of health science and information technology. Future research should continue to validate the effectiveness of this approach and identify specific nuances related to health science applications.","PeriodicalId":12947,"journal":{"name":"Healthcare Informatics Research","volume":"31 1","pages":"88-95"},"PeriodicalIF":2.3,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11854624/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143457529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Era of Digital Healthcare: Emergence of the Smart Patient. 数字医疗时代：智能患者的出现。

IF 2.3

Healthcare Informatics Research Pub Date : 2025-01-01 Epub Date: 2025-01-31 DOI: 10.4258/hir.2025.31.1.107

Dooyoung Huhh, Kwangsoo Shin, Miyeong Kim, Jisan Lee, Hana Kim, Jinho Choi, Suyeon Ban

引用次数: 0

Weightage Identified Network of Keywords Technique: A Structured Approach in Identifying Keywords for Systematic Reviews. 关键词权重识别网络技术：系统评价中识别关键词的结构化方法。

IF 2.3

Healthcare Informatics Research Pub Date : 2025-01-01 Epub Date: 2025-01-31 DOI: 10.4258/hir.2025.31.1.48

Sasidharan Sivakumar, Gowardhan Sivakumar

{"title":"Weightage Identified Network of Keywords Technique: A Structured Approach in Identifying Keywords for Systematic Reviews.","authors":"Sasidharan Sivakumar, Gowardhan Sivakumar","doi":"10.4258/hir.2025.31.1.48","DOIUrl":"10.4258/hir.2025.31.1.48","url":null,"abstract":"Objectives: The objective of this study was to develop the weightage identified network of keywords (WINK) technique for selecting and utilizing keywords to perform systematic reviews more efficiently. This technique aims to improve the thoroughness and precision of evidence synthesis by employing a more rigorous approach to keyword selection.Methods: The WINK methodology involves generating network visualization charts to analyze the interconnections among keywords within a specific domain. This process integrates both computational analysis and subject expert insights to enhance the accuracy and relevance of the findings. In the example considered, the networking strength between the contexts of environmental pollutants with endocrine function as Q1 and systemic health with oral health-related terms as Q2 was examined, and keywords with limited networking strength were excluded. Utilizing the Medical Subject Headings (MeSH) terms identified from the WINK technique, a search string was built and compared to an initial search with fewer keywords.Results: The application of the WINK technique in building the search string yielded 69.81% and 26.23% more articles for Q1 and Q2, respectively, compared to conventional approaches. This significant increase demonstrates the technique's effectiveness in identifying relevant studies and ensuring comprehensive evidence synthesis.Conclusions: By prioritizing keywords with higher weightage and utilizing network visualization charts, the WINK technique ensures comprehensive evidence synthesis and enhances accuracy in systematic reviews. Its effectiveness in identifying relevant studies marks a significant advancement in systematic review methodology, offering a more robust and efficient approach to keyword selection.","PeriodicalId":12947,"journal":{"name":"Healthcare Informatics Research","volume":"31 1","pages":"48-56"},"PeriodicalIF":2.3,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11854614/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143457717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Development and Usability Evaluation of COVID-Iran: A Mobile Application for Mitigating COVID-19 Misinformation. COVID-Iran 的开发和可用性评估：减少 COVID-19 误报的移动应用程序。

IF 2.3

Healthcare Informatics Research Pub Date : 2024-10-01 Epub Date: 2024-10-31 DOI: 10.4258/hir.2024.30.4.312

Raheleh Salari, Farhad Fatehi, Hamed Mehdizadeh

{"title":"Development and Usability Evaluation of COVID-Iran: A Mobile Application for Mitigating COVID-19 Misinformation.","authors":"Raheleh Salari, Farhad Fatehi, Hamed Mehdizadeh","doi":"10.4258/hir.2024.30.4.312","DOIUrl":"10.4258/hir.2024.30.4.312","url":null,"abstract":"Objectives: The spread of misinformation through the internet can lead to dangerous behavioral changes and erode trust in reliable sources, especially during public health crises like coronavirus disease 2019 (COVID-19). To combat this issue, innovative strategies that leverage information technology are essential. This study focused on developing and evaluating a mobile application (app), COVID-Iran, aimed at countering COVID-19 misinformation by delivering accurate, reliable, and credible information.Methods: The development of the app involved a multi-step, user-centered approach that integrated qualitative expert consultations with quantitative survey research to pinpoint and validate key features. The app was initially prototyped using Enterprise Architect software and subsequently developed using Android Studio and MySQL. We conducted a usability evaluation using the System Usability Scale (SUS), where participants engaged in various tasks related to information seeking, self-assessment, and health management. Data were analyzed using descriptive statistics in SPSS version 19.Results: The findings revealed a high usability level (SUS score of 81.35), with participants reporting ease of use and learnability. The app effectively countered misinformation by providing access to trusted sources and evidence-based counterarguments. User feedback emphasized the app's strengths in clarity, accuracy, trustworthiness, and its comprehensive approach. Plans for future improvements include the integration of artificial intelligence to deliver personalized content.Conclusions: Despite limitations such as the small sample size and potential self-selection bias, this study highlights the significant potential of mHealth apps to provide reliable health information and combat misinformation.","PeriodicalId":12947,"journal":{"name":"Healthcare Informatics Research","volume":"30 4","pages":"312-323"},"PeriodicalIF":2.3,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11570658/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142647910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mobile Application for Digital Health Coaching in the Self-Management of Older Adults with Multiple Chronic Conditions: A Development and Usability Study. 在患有多种慢性疾病的老年人的自我管理中，数字健康指导的移动应用程序：开发与可用性研究

IF 2.3

Healthcare Informatics Research Pub Date : 2024-10-01 Epub Date: 2024-10-31 DOI: 10.4258/hir.2024.30.4.344

Ga Eun Park, Yeon-Hwan Park, Kwang Gi Kim, Jeong Yun Park, Minhwa Hwang, Seonghyeon Lee

{"title":"Mobile Application for Digital Health Coaching in the Self-Management of Older Adults with Multiple Chronic Conditions: A Development and Usability Study.","authors":"Ga Eun Park, Yeon-Hwan Park, Kwang Gi Kim, Jeong Yun Park, Minhwa Hwang, Seonghyeon Lee","doi":"10.4258/hir.2024.30.4.344","DOIUrl":"10.4258/hir.2024.30.4.344","url":null,"abstract":"Objectives: This study was conducted to develop a mobile application for digital health coaching to support self-management in older adults with multiple chronic conditions. Additionally, the usability of this application was evaluated.Methods: The HAHA2022 mobile application was developed through a multidisciplinary team approach, incorporating digital health coaching strategies targeting community-dwelling older adults with multiple chronic conditions. Usability was assessed with the Korean version of the Mobile Application Rating Scale. The usability tests involved eight expert panel members and 10 older adults (mean age, 74 ± 3 years; 90% women) from one senior welfare center.Results: HAHA2022 is an Android-based mobile application that is also integrated into wearable devices to track physical activity. It features an age-friendly design and includes five main menus: Home, Action Plan, Education, Health Log, and Community. The average overall usability test scores-covering engagement, functionality, aesthetics, and information-were 4.27 of 5 for the expert panel and 4.53 of 5 for the older adults.Conclusions: The HAHA2022 application was developed to improve self-management among communitydwelling older adults with multiple chronic conditions. Usability tests indicate that the application is highly acceptable and feasible for use by this population. Consequently, HAHA2022 is anticipated to be widely implemented. Nonetheless, further research is required to confirm its effectiveness through digital health intervention.","PeriodicalId":12947,"journal":{"name":"Healthcare Informatics Research","volume":"30 4","pages":"344-354"},"PeriodicalIF":2.3,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11570659/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142646638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Service Design and Evaluation of OpenNotes for Craniofacial Deformity Management in Patients and their Caregivers. 针对颅面畸形患者及其护理人员管理的 OpenNotes 服务设计与评估。

IF 2.3

Healthcare Informatics Research Pub Date : 2024-10-01 Epub Date: 2024-10-31 DOI: 10.4258/hir.2024.30.4.333

Hana Kim, Jisan Lee, Sukwha Kim, Deok-Yeol Kim

{"title":"Service Design and Evaluation of OpenNotes for Craniofacial Deformity Management in Patients and their Caregivers.","authors":"Hana Kim, Jisan Lee, Sukwha Kim, Deok-Yeol Kim","doi":"10.4258/hir.2024.30.4.333","DOIUrl":"10.4258/hir.2024.30.4.333","url":null,"abstract":"Objectives: This study aimed to assess the feasibility of implementing OpenNotes in Korea. It involved developing and evaluating the Open-CHA service, which provides clinical summary information to patients diagnosed with craniofacial deformities and their caregivers following outpatient visits.Methods: The study included 109 patients diagnosed with craniofacial deformities, along with their caregivers. The Open-CHA service was developed by referencing OpenNotes and involved a user needs assessment, a pilot test, and an evaluation of its effectiveness. Data were analyzed using descriptive statistics and the paired t-test.Results: Short message service templates for the Open-CHA service based on a user needs assessment conducted with patients, caregivers, and healthcare professionals. These templates were refined and improved following a pilot test. After the implementation of the Open-CHA service, most participants evaluated OpenNotes positively. Additionally, there were observed increases in health knowledge and efficacy in patient-physician interactions. A statistically significant improvement in mobile health literacy was also confirmed.Conclusions: The implementation of the Open-CHA service significantly enhanced mobile health literacy among patients with craniofacial deformities and their caregivers, indicating positive outcomes for the potential adoption of OpenNotes in Korea. This suggests that introducing OpenNotes into the Korean healthcare system is appropriate.","PeriodicalId":12947,"journal":{"name":"Healthcare Informatics Research","volume":"30 4","pages":"333-343"},"PeriodicalIF":2.3,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11570661/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142647244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0