{"title":"The Rehabilitation Effect of Rehabilitation Nursing Scheme for Sprinters With Knee Ligament Injuries","authors":"Bin Hu, Yoh Murayama","doi":"10.4018/ijhisi.338221","DOIUrl":"https://doi.org/10.4018/ijhisi.338221","url":null,"abstract":"Using the convenient sampling method, the control group and the observation group were established. The control group was given a routine nursing scheme, while the observation group was given rehabilitation nursing scheme. The difference of curative effect between the two groups were compared and the results were analyzed and summarized. Results of the quality of life scores of patients in the two groups were compared. The results showed that the quality of life score of the patients in the observation group were higher than that of the control group (P<0.05); the satisfaction scores of patients was also compared. The results showed that the satisfaction scores of patients in the experimental group were significantly higher than that in the control group (P<0.05), so the patients in the observation group are better than the control group. The rehabilitation nursing scheme has a certain effect on the rehabilitation of knee ligament injury of printing workers.","PeriodicalId":56158,"journal":{"name":"International Journal of Healthcare Information Systems and Informatics","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2024-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139796155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Rehabilitation Effect of Rehabilitation Nursing Scheme for Sprinters With Knee Ligament Injuries","authors":"Bin Hu, Yoh Murayama","doi":"10.4018/ijhisi.338221","DOIUrl":"https://doi.org/10.4018/ijhisi.338221","url":null,"abstract":"Using the convenient sampling method, the control group and the observation group were established. The control group was given a routine nursing scheme, while the observation group was given rehabilitation nursing scheme. The difference of curative effect between the two groups were compared and the results were analyzed and summarized. Results of the quality of life scores of patients in the two groups were compared. The results showed that the quality of life score of the patients in the observation group were higher than that of the control group (P<0.05); the satisfaction scores of patients was also compared. The results showed that the satisfaction scores of patients in the experimental group were significantly higher than that in the control group (P<0.05), so the patients in the observation group are better than the control group. The rehabilitation nursing scheme has a certain effect on the rehabilitation of knee ligament injury of printing workers.","PeriodicalId":56158,"journal":{"name":"International Journal of Healthcare Information Systems and Informatics","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2024-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139856339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Application of Behavior Recognition Technology Based on Deep Learning in Elderly Care","authors":"Shihui Zhang, Jing Mi, Naidi Liu","doi":"10.4018/ijhisi.336548","DOIUrl":"https://doi.org/10.4018/ijhisi.336548","url":null,"abstract":"China is currently one of the countries with the largest elderly population in the world, and the issue of population aging has become a widespread concern. The behavior recognition algorithm based on deep learning is currently the main behavior recognition algorithm and one of the basic technologies in the field of computer vision. In existing research, the method of constructing complex classification models based on manual feature representation can no longer meet the requirements of high recognition accuracy and applicability, and the introduction of deep learning has brought new development directions for behavior recognition. Therefore, this article aims to study how to apply deep learning-based behavior recognition technology more accurately and effectively in the care of elderly people in the context of “artificial intelligence.”","PeriodicalId":56158,"journal":{"name":"International Journal of Healthcare Information Systems and Informatics","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2024-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139605734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Etiology and Nursing Care of Children's Knee Joint Sports Injury Diseases","authors":"Long Liu, Zhankui Zhai, Weihua Zhu","doi":"10.4018/ijhisi.336479","DOIUrl":"https://doi.org/10.4018/ijhisi.336479","url":null,"abstract":"The objective is to explore the etiology, diagnosis, treatment, and prevention of children's knee joint sports injury. The medical records of hospitalized children with sports injuries from 2019 to 2021 were retrospectively analyzed. The total number of hospitalized children with knee joint sports injury increased from 27 in 2019 to 46 in 2021. The main diseases are meniscus injury, dislocation of patella, avulsion fracture of tibial intercondylar crest, ligament injury, articular cartilage injury, and other diseases. Children's sports injuries occur in different ages groups, with the highest incidence in the age group of 7-14, and the incidence rate of boys is about 1.5 times that of girls. Moreover, the number of knee joint sports injury diseases in children is increasing, especially for school-age children. Low energy injury is the most common cause of injury, but high energy injury may lead to serious knee joint function damage, which should be paid great attention.","PeriodicalId":56158,"journal":{"name":"International Journal of Healthcare Information Systems and Informatics","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139526542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Smart Interventions for Opioid Abuse","authors":"N. Singh, U. Varshney","doi":"10.4018/ijhisi.335895","DOIUrl":"https://doi.org/10.4018/ijhisi.335895","url":null,"abstract":"The number of people in the US with opioid abuse exceeds two million, and the total cost is approximately $100B per year. There is a need for smart interventions that can lead to better outcomes for patients and reduce the need for healthcare resources. In this study, the authors present three smart interventions for patients: (a) mobile reminders, (b) electronic monitoring, and (c) composite intervention. More specifically, the authors present a design approach for smart interventions and operationalize the interventions. They have developed an analytical model for evaluating interventions. Interventions are cost-effective for higher values of intervention effectiveness, hospital, and emergency room cost. However, with quality-of-life (QoL) improvement, cost-effectiveness improves significantly. The authors also explored the use of financial incentives for increasing the adoption of interventions. These results will help patients, healthcare professionals, decision-makers, and family members to choose the most suitable intervention to address opioid abuse.","PeriodicalId":56158,"journal":{"name":"International Journal of Healthcare Information Systems and Informatics","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2024-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139533268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Prevention and Nursing Care of Common Injuries in Long-Distance Running of College Students","authors":"Bin Hu, Gregory T. MacLennan","doi":"10.4018/ijhisi.334120","DOIUrl":"https://doi.org/10.4018/ijhisi.334120","url":null,"abstract":"As a favorite sport of teachers and students, long-distance running can enhance physical fitness. However, due to nonstandard movements in sports, teachers and students get injured psysically. Taking the prevention of long-distance running injuries of teachers and students in colleges and universities as the research goal, this article investigates the teachers and students of a physical education college in Shanxi Province by means of questionnaire survey, counts the functional indexes of teachers and students in long-distance running for one year and analyzes the injuries. The results show that the injury rate of teachers and students is 45.5%; Teachers and students with only one injury are the most, and knee injuries are the most common, with a mild injury rate of 60.98% and concentrated in November-December and June-July. The main reasons for the injuries of teachers and students are poor physical fitness, insufficient warm-up, and poor sports equipment. Through full warm-up exercise and adequate rest, common injuries in long-distance running can be effectively prevented.","PeriodicalId":56158,"journal":{"name":"International Journal of Healthcare Information Systems and Informatics","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139222301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Classification Prediction of Lung Cancer Based on Machine Learning Method","authors":"Dantong Li, Guixin Li, Shuang Li, Ashley Bang","doi":"10.4018/ijhisi.333631","DOIUrl":"https://doi.org/10.4018/ijhisi.333631","url":null,"abstract":"The K-nearest neighbor interpolation method was used to fill in missing data of five indicators of coronary heart disease, diabetes, total cholesterol, triglycerides, and albumin;, and the SMOTE algorithm was used to balance the number of variable indicators. The Relief-F algorithm was used to remove 18 variable indicators and retain 42 variable indicators. LASSO and ridge regression algorithms were used to remove eight variable indicators and retain 52 variable indicators; The prediction accuracy, recall, and AUC values of the linear kernel support vector machine model filtered using Relief-F and LASSO features are high, and the prediction results are optimal; The test result of random forest screened by Relief-F and LASSO features is better than that of the support vector machine model. It is concluded that the random forest model screened by Relief-F features is better as a prediction of lung cancer typing. The research results provide theoretical data support for predicting lung cancer classification using machine learning methods.","PeriodicalId":56158,"journal":{"name":"International Journal of Healthcare Information Systems and Informatics","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2023-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139275637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Assessing the Alignment Between Existing Finnish Patient Portals and the Newly Implemented Finnish Well-Being Reform","authors":"Marlon Luca Machal","doi":"10.4018/ijhisi.333604","DOIUrl":"https://doi.org/10.4018/ijhisi.333604","url":null,"abstract":"Due to the recent implementation of the Finnish well-being reform, there is limited research discussing the reform's aims and its alignment with existing Finnish patient portals. The objective of this research is to assess the alignment between existing Finnish patient portals and the newly implemented well-being reform. This research is supported by the insights gained from monitoring the US health reform survey that was conducted in 2021. By Aligning patient portals with the well-being reform, there is an opportunity to achieve patient-centered care and facilitate improved communication between patients and healthcare providers.","PeriodicalId":56158,"journal":{"name":"International Journal of Healthcare Information Systems and Informatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135192745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Effect of Framing and Feedback Levels on Funding and Emotional Support in Medical Crowdfunding","authors":"Onochie Fan-Osuala","doi":"10.4018/ijhisi.327449","DOIUrl":"https://doi.org/10.4018/ijhisi.327449","url":null,"abstract":"Despite the rise of medical crowdfunding and its benefits to patients, including reducing financial hardships and providing emotional support, limited attention has been paid to how a medical crowdfunding campaign organizer can drive performance. In this study, the authors investigate how the communication style used in a medical crowdfunding campaign can affect the funding performance and emotional support received. They find that emotional framing and the level of feedback communicated positively affect funding and emotional support and discuss its implications.","PeriodicalId":56158,"journal":{"name":"International Journal of Healthcare Information Systems and Informatics","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2023-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45437807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Modeling the Factors That Drive the Need for Inter-Facility Transfers to Downstream Services in US Emergency Departments","authors":"Jeff Shockley, Tobin Turner","doi":"10.4018/ijhisi.327349","DOIUrl":"https://doi.org/10.4018/ijhisi.327349","url":null,"abstract":"Improving emergency department (ED) care coordination requires analytics-based models that can integrate large patient-level and hospital databases to help formulate better transfer processes and policies across different hospital settings. This study develops a new empirical model to analyze over one million heart attack emergency department (ED) encounters between 2006-2014 to understand the factors that drive the need for inter-facility transfers (IFT) in different hospital settings. The resulting model has proven helpful for deriving public policy insights from this information. For instance, while we find that while healthcare IFT inequities and inconsistencies persist with ED discharge decisions because of some specific patient and hospital resource factors, these have been reduced significantly in the more recent post-reform period. We conclude by discussing the implications of using this empirical modeling approach for developing smarter policies and procedures for managing and benchmarking downstream healthcare operations practices in this disease area.","PeriodicalId":56158,"journal":{"name":"International Journal of Healthcare Information Systems and Informatics","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45747066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}