Browsing by Author "Kharrazi, Hadi"

Now showing 1 - 9 of 9
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    EXPLORING HEALTH WEBSITE USERS BY WEB MINING
    (Universal Access in Human-Computer Interaction. Applications and Services Lecture Notes in Computer Science, 2011, Volume 6768/2011, 376-383, DOI: 10.1007/978-3-642-21657-2_40, 2011-07) Kong, Wei; Jones, Josette F.; Mahoui, Malika; Kharrazi, Hadi
    With the continuous growth of health information on the Internet, providing user-orientated health service online has become a great challenge to health providers. Understanding the information needs of the users is the first step to providing tailored health service. The purpose of this study is to examine the navigation behavior of different user groups by extracting their search terms and to make some suggestions to reconstruct a website for more customized Web service. This study analyzed five months’ of daily access weblog files from one local health provider’s website, discovered the most popular general topics and health related topics, and compared the information search strategies for both patient/consumer and doctor groups. Our findings show that users are not searching health information as much as was thought. The top two health topics which patients are concerned about are children’s health and occupational health. Another topic that both user groups are interested in is medical records. Also, patients and doctors have different search strategies when looking for information on this website. Patients get back to the previous page more often, while doctors usually go to the final page directly and then leave the page without coming back. As a result, some suggestions to redesign and improve the website are discussed; a more intuitive portal and more customized links for both user groups are suggested.
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    Healthcare Game Design: Behavioral Modeling of Serious Gaming Design for Children with Chronic Diseases
    (2009) Kharrazi, Hadi; Faiola, Anthony; Defazio, Joseph
    This article introduces the design principles of serious games for chronic patients based on behavioral models. First, key features of the targeted chronic condition (Diabetes) are explained. Then, the role of psychological behavioral models in the management of chronic conditions is covered. After a short review of the existing health focused games, two recent health games that are developed based on behavioral models are overviewed in more detail. Furthermore, design principles and usability issues regarding the creation of these health games are discussed. Finally, the authors conclude that designing healthcare games based on behavioral models can increase the usability of the game in order to improve the effectiveness of the game’s desired healthcare outcomes.
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    An Improved Utility Driven Approach Towards K-Anonymity Using Data Constraint Rules
    (2013-08-14) Morton, Stuart Michael; Mahoui, Malika; Palakal, Mathew J.; Gibson, P. Joseph; Kharrazi, Hadi
    As medical data continues to transition to electronic formats, opportunities arise for researchers to use this microdata to discover patterns and increase knowledge that can improve patient care. Now more than ever, it is critical to protect the identities of the patients contained in these databases. Even after removing obvious “identifier” attributes, such as social security numbers or first and last names, that clearly identify a specific person, it is possible to join “quasi-identifier” attributes from two or more publicly available databases to identify individuals. K-anonymity is an approach that has been used to ensure that no one individual can be distinguished within a group of at least k individuals. However, the majority of the proposed approaches implementing k-anonymity have focused on improving the efficiency of algorithms implementing k-anonymity; less emphasis has been put towards ensuring the “utility” of anonymized data from a researchers’ perspective. We propose a new data utility measurement, called the research value (RV), which extends existing utility measurements by employing data constraints rules that are designed to improve the effectiveness of queries against the anonymized data. To anonymize a given raw dataset, two algorithms are proposed that use predefined generalizations provided by the data content expert and their corresponding research values to assess an attribute’s data utility as it is generalizing the data to ensure k-anonymity. In addition, an automated algorithm is presented that uses clustering and the RV to anonymize the dataset. All of the proposed algorithms scale efficiently when the number of attributes in a dataset is large.
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    Indianapolis Emergency Medical Service and the Indiana Network for Patient Care: Evaluating the Patient Match Process
    (2014-01-03) Park, Seong Cheol; Finnell, John T.; Jones, Josette F.; Kharrazi, Hadi
    In 2009, Indianapolis Emergency Medical Service (I-EMS, formerly Wishard Ambulance Service) launched an electronic medical record system within their ambulances and started to exchange patient data with the Indiana Network for Patient Care (INPC). This unique system allows EMS personnel in an ambulance to get important medical information prior to the patient’s arrival to the accepting hospital from incident scene. In this retrospective cohort study, we found EMS personnel made 3,021 patient data requests (14%) of 21,215 EMS transports during a one-year period, with a “success” match rate of 46%, and a match “failure” rate of 17%. The three major factors for causing match “failure” were (1) ZIP code 55%, (2) Patient Name 22%, and (3) Birth Date 12%. This study shows that the ZIP code is not a robust identifier in the patient identification process and Non-ZIP code identifiers may be a better choice due to inaccuracies and changes of the ZIP code in a patient’s record.
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    Mobile Technology to Improve Adherence in Patients with Diabetes: Systematic Review
    (2013-08-20) Portillo, Wilfredo; Kharrazi, Hadi; Jones, Josette F.; Finnell, John T.
    BACKGROUND: The pathophysiology of diabetes mellitus and the need for vigilant monitoring of serum glucose levels lends itself well to prompt medical intervention by healthcare providers that can significantly reduce morbidity and mortality and improve patient quality of life. The effect of intervention in diabetes can be assessed by following objective laboratory measurements such as hemoglobin A1C, which is abnormal with poorly controlled diabetes and returns to normal with proper management. There are mobile technologies now available that allow for self-monitoring and intervention in this patient population. Using a systematic approach this paper will assess the benefits of Short Message Services and mobile technology in managing patients with diabetes and improving adherence and other outcomes. OBJECTIVE: To assess the benefits and disadvantages the use of mobile technology could have in the management of diabetes. METHODOLOGY: A systematic review of articles on this topic was performed. A total of 759 articles were initially identified by searching various search engines, from which only 39 articles met all of the inclusion/exclusion criteria of this systematic review. FINDINGS: The initial review of literature indicated that the use of mobile technology in patients with diabetes resulted in improved disease outcomes as indicated by parameters such as a decrease in hemoglobin A1C, and an increase in sustainable blood glucose levels. CONCLUSION: Mobile technology is found to be a promising tool in the management of diabetes, but further research is needed because there is a lack of reliable studies, trials, and systematic reviews. Physicians and other healthcare professionals are rapidly adopting mobile technology for use in clinical practice because they understand the rising phenomenon of mobile technology.
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    A Novel Visualization Tool for Evaluating Medication Side-Effects in Multi-drug Regimens
    (2009) Duke, Jon; Faiola, Anthony; Kharrazi, Hadi
    The evaluation and management of medication side-effects is a common and complex task for physicians. Information visualization has the potential to increase the efficiency and reduce the cognitive load involved in this process. We describe the design and development of Rxplore, a novel tool for assessing medication side-effects. Rxplore supports simultaneous lookup of multiple medications and an intuitive visual representation of query results. In a pilot study of Rxplore’s usability and utility, physicians rated the system highly for efficiency, intuitiveness, and clinical value.
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    An ontology for formal representation of medication adherence-related knowledge : case study in breast cancer
    (2018-08-02) Sawesi, Suhila; MacDorman, Karl F.; Jones, Josette F.; Carpenter, Janet S.; Kharrazi, Hadi; Duncan, William D.
    Medication non-adherence is a major healthcare problem that negatively impacts the health and productivity of individuals and society as a whole. Reasons for medication non-adherence are multi-faced, with no clear-cut solution. Adherence to medication remains a difficult area to study, due to inconsistencies in representing medicationadherence behavior data that poses a challenge to humans and today’s computer technology related to interpreting and synthesizing such complex information. Developing a consistent conceptual framework to medication adherence is needed to facilitate domain understanding, sharing, and communicating, as well as enabling researchers to formally compare the findings of studies in systematic reviews. The goal of this research is to create a common language that bridges human and computer technology by developing a controlled structured vocabulary of medication adherence behavior—“Medication Adherence Behavior Ontology” (MAB-Ontology) using breast cancer as a case study to inform and evaluate the proposed ontology and demonstrating its application to real-world situation. The intention is for MAB-Ontology to be developed against the background of a philosophical analysis of terms, such as belief, and desire to be human, computer-understandable, and interoperable with other systems that support scientific research. The design process for MAB-Ontology carried out using the METHONTOLOGY method incorporated with the Basic Formal Ontology (BFO) principles of best practice. This approach introduces a novel knowledge acquisition step that guides capturing medication-adherence-related data from different knowledge sources, including adherence assessment, adherence determinants, adherence theories, adherence taxonomies, and tacit knowledge source types. These sources were analyzed using a systematic approach that involved some questions applied to all source types to guide data extraction and inform domain conceptualization. A set of intermediate representations involving tables and graphs was used to allow for domain evaluation before implementation. The resulting ontology included 629 classes, 529 individuals, 51 object property, and 2 data property. The intermediate representation was formalized into OWL using Protégé. The MAB-Ontology was evaluated through competency questions, use-case scenario, face validity and was found to satisfy the requirement specification. This study provides a unified method for developing a computerized-based adherence model that can be applied among various disease groups and different drug categories.
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    What’s Past Is Prologue: A Scoping Review of Recent Public Health and Global Health Informatics Literature
    (2015) Dixon, Brian E.; Pina, Jamie; Kharrazi, Hadi; Gharghabi, Fardad; Department of Epidemiology, Richard M. Fairbanks School of Public Health
    Objective: To categorize and describe the public health informatics (PHI) and global health informatics (GHI) literature between 2012 and 2014. Methods: We conducted a semi-systematic review of articles published between January 2012 and September 2014 where information and communications technologies (ICT) was a primary subject of the study or a main component of the study methodology. Additional inclusion and exclusion criteria were used to filter PHI and GHI articles from the larger biomedical informatics domain. Articles were identified using MEDLINE as well as personal bibliographies from members of the American Medical Informatics Association PHI and GHI working groups. Results: A total of 85 PHI articles and 282 GHI articles were identified. While systems in PHI continue to support surveillance activities, we identified a shift towards support for prevention, environmental health, and public health care services. Furthermore, articles from the U.S. reveal a shift towards PHI applications at state and local levels. GHI articles focused on telemedicine, mHealth and eHealth applications. The development of adequate infrastructure to support ICT remains a challenge, although we observed a small but growing set of articles that measure the impact of ICT on clinical outcomes. Discussion: There is evidence of growth with respect to both implementation of information systems within the public health enterprise as well as a widening of scope within each informatics discipline. Yet the articles also illuminate the need for more primary research studies on what works and what does not as both searches yielded small numbers of primary, empirical articles. Conclusion: While the body of knowledge around PHI and GHI continues to mature, additional studies of higher quality are needed to generate the robust evidence base needed to support continued investment in eHealth by governmental health agencies.