{"title":"Influential Factors in Breast Cancer Patients' Performance Using Malaysian Social Network Support Groups","authors":"M. Mirabolghasemi, N. A. Iahad, Thurasamy Ramayah","doi":"10.4018/ijhisi.2019100105","DOIUrl":"https://doi.org/10.4018/ijhisi.2019100105","url":null,"abstract":"Social network communities can serve as a health resource for cancer patients to share and disseminate information. Even so, theory-based research into evaluating cancer patients' performance empirically using social network sites (SNSs) is limited, representing an identifiable knowledge gap. This study proposes a research model that integrates social cognitive theory and task technology fit theory to contribute to the understanding of key factors impacting the performance of breast cancer patients using SNSs. Data were collected via a structured paper-based questionnaire. A total of one hundred seventy-eight (178) participants from six cancer support groups and hospitals in Peninsular Malaysia responded to the administered survey. Survey data were analyzed using the partial least squares (PLS) method while Smart PLS was used to test the hypotheses and to validate the proposed model. Results indicate that outcome expectation, self-efficacy, negative affect, positive affect, social support and task technology fit are significant factors affecting the performance of breast cancer patients vis-à-vis Malaysian social network support groups.","PeriodicalId":56158,"journal":{"name":"International Journal of Healthcare Information Systems and Informatics","volume":"1 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45784115","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":"Utilizing Combined Claims and Clinical Datasets for Research Among Potential Cases of Rare Diseases.","authors":"Kevin J Bennett, Joshua Mann, Lijing Ouyang","doi":"10.4018/ijhisi.2018040101","DOIUrl":"10.4018/ijhisi.2018040101","url":null,"abstract":"<p><p>With data quality issues with administrative claims and medically derived datasets, a dataset derived from a combination of sources may be more effective for research. The purposes of this article is to link an EMR-based data warehouse with state administrative data to study individuals with rare diseases; to describe and compare their characteristics; and to explore research with the data. These methods included subjects with diagnosis codes for one of three rare diseases from the years 2009-2014; Spina Bifida, Muscular Dystrophy, and Fragile X Syndrome. The results from the combined data provides additional information that each dataset, by itself, would not contain. The simultaneous examination of data such as race/ethnicity, physician and other outpatient visit data, charges and payments, and overall utilization was possible in the combined dataset. It is also discussed that combining such datasets can be a useful tool for the study of populations with rare diseases.</p>","PeriodicalId":56158,"journal":{"name":"International Journal of Healthcare Information Systems and Informatics","volume":"13 2","pages":"1-12"},"PeriodicalIF":0.9,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7479970/pdf/nihms-1625111.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38463394","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}
{"title":"Critical Success Factors in Electronic Health Records (EHR) Implementation","authors":"BajwaNavneet Kaur, SinghHarjot, D. Kumar","doi":"10.4018/978-1-5225-9863-3.ch013","DOIUrl":"https://doi.org/10.4018/978-1-5225-9863-3.ch013","url":null,"abstract":"Electronic Health Records EHR has been the subject of much academic discussion in recent times. The impact that a successful implementation of EHR can have on a hospital cannot be overstated. Facto...","PeriodicalId":56158,"journal":{"name":"International Journal of Healthcare Information Systems and Informatics","volume":"1 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41988272","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}
L Rodney Long, Sameer Antani, Thomas M Deserno, George R Thoma
{"title":"Content-Based Image Retrieval in Medicine: Retrospective Assessment, State of the Art, and Future Directions.","authors":"L Rodney Long, Sameer Antani, Thomas M Deserno, George R Thoma","doi":"10.4018/jhisi.2009010101","DOIUrl":"10.4018/jhisi.2009010101","url":null,"abstract":"<p><p>Content-based image retrieval (CBIR) technology has been proposed to benefit not only the management of increasingly large image collections, but also to aid clinical care, biomedical research, and education. Based on a literature review, we conclude that there is widespread enthusiasm for CBIR in the engineering research community, but the application of this technology to solve practical medical problems is a goal yet to be realized. Furthermore, we highlight \"gaps\" between desired CBIR system functionality and what has been achieved to date, present for illustration a comparative analysis of four state-of-the-art CBIR implementations using the gap approach, and suggest that high-priority gaps to be overcome lie in CBIR interfaces and functionality that better serve the clinical and biomedical research communities.</p>","PeriodicalId":56158,"journal":{"name":"International Journal of Healthcare Information Systems and Informatics","volume":"4 1","pages":"1-16"},"PeriodicalIF":0.9,"publicationDate":"2009-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2879660/pdf/nihms-85948.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29032322","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}