Browsing by Subject "Healthcare"

Now showing 1 - 10 of 55
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    The Academic Model Providing Access To Healthcare (AMPATH) in Kenya
    (Global Livestock CRSP, UC Davis, 2008-11) Nyandiko, Winstone; Siika, Abraham; Ernst, Judith A.; Ettyang, Grace; Neumann, Charlotte; Yiannoutsos, Constantin
    In sub-Saharan Africa, an estimated 28 million people are living with the human immunodeficiency virus (HIV) and acquired immunodeficiency syndrome (AIDS). In 2001, Moi University in Eldoret, Kenya joined with Kenya’s second national referral hospital, Moi Teaching and Referral Hospital (MTRH) and Indiana University (IU) to establish the Academic Model Providing Access To Healthcare (AMPATH). AMPATH’s missions were to (1) provide high-quality patient care; (2) educate patients and health care providers; and (3) establish a laboratory for clinical research in HIV/AIDS (http://medicine.iupui.edu/kenya/hiv.aids.html). Leveraging the power of an academic medical partnership, AMPATH has quickly become one of the largest and most comprehensive HIV/AIDS control systems in sub-Saharan Africa, providing a comprehensive system of care that has been described as a model of sustainable development (Tobias, 2006). Delivery of services occurs in the public sector through hospitals and health centers run by Kenya’s Ministry of Health. AMPATH currently implements prevention activities that touch the lives of millions of persons in a wide geographic area. The research arm of AMPATH, created to facilitate and manage the international research agenda being generated by Kenyan and US faculty, includes the Global Livestock CRSP’s HIV Nutrition Project (HNP), “Increasing Animal Source Foods in Diets of HIV-infected Kenyan Women and Their Children,” which is a collaborative initiative between AMPATH and faculty from Moi University, Indiana University and the University of California, Los Angeles.
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    Activity Theory Analysis of Heart Failure Self-Care
    (Taylor & Francis, 2018) Cornet, Victor; Voida, Stephen; Holden, Richard J.; Medicine, School of Medicine
    The management of chronic health conditions such as heart failure is a complex process emerging from the activity of a network of individuals and artifacts. This article presents an Activity Theory-based secondary analysis of data from a geriatric heart failure management study. Twenty-one patients' interviews and clinic visit observations were analyzed to uncover eight configurations of roles and activities involving patients, clinicians, and others in the sociotechnical network. For each configuration or activity pattern, we identify points of tension and propose guidelines for developing interventions for future computer-supported healthcare systems.
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    Applications of Data Mining in Healthcare
    (2019-05) Peng, Bo; Mohler, George; Dundar, Murat; Zheng, Jiang Yu
    With increases in the quantity and quality of healthcare related data, data mining tools have the potential to improve people’s standard of living through personalized and predictive medicine. In this thesis we improve the state-of-the-art in data mining for several problems in the healthcare domain. In problems such as drug-drug interaction prediction and Alzheimer’s Disease (AD) biomarkers discovery and prioritization, current methods either require tedious feature engineering or have unsatisfactory performance. New effective computational tools are needed that can tackle these complex problems. In this dissertation, we develop new algorithms for two healthcare problems: high-order drug-drug interaction prediction and amyloid imaging biomarker prioritization in Alzheimer’s Disease. Drug-drug interactions (DDIs) and their associated adverse drug reactions (ADRs) represent a significant detriment to the public h ealth. Existing research on DDIs primarily focuses on pairwise DDI detection and prediction. Effective computational methods for high-order DDI prediction are desired. In this dissertation, I present a deep learning based model D 3 I for cardinality-invariant and order-invariant high-order DDI pre- diction. The proposed models achieve 0.740 F1 value and 0.847 AUC value on high-order DDI prediction, and outperform classical methods on order-2 DDI prediction. These results demonstrate the strong potential of D 3 I and deep learning based models in tackling the prediction problems of high-order DDIs and their induced ADRs. The second problem I consider in this thesis is amyloid imaging biomarkers discovery, for which I propose an innovative machine learning paradigm enabling precision medicine in this domain. The paradigm tailors the imaging biomarker discovery process to individual characteristics of a given patient. I implement this paradigm using a newly developed learning-to-rank method PLTR. The PLTR model seamlessly integrates two objectives for joint optimization: pushing up relevant biomarkers and ranking among relevant biomarkers. The empirical study of PLTR conducted on the ADNI data yields promising results to identify and prioritize individual-specific amyloid imaging biomarkers based on the individual’s structural MRI data. The resulting top ranked imaging biomarkers have the potential to aid personalized diagnosis and disease subtyping.
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    Applied Artificial Intelligence in Healthcare: A Review of Computer Vision Technology Application in Hospital Settings
    (MDPI, 2024-03-28) Lindroth, Heidi; Nalaie, Keivan; Raghu, Roshini; Ayala, Ivan N.; Busch, Charles; Bhattacharyya, Anirban; Franco, Pablo Moreno; Diedrich, Daniel A.; Pickering, Brian W.; Herasevich, Vitaly; School of Nursing
    Computer vision (CV), a type of artificial intelligence (AI) that uses digital videos or a sequence of images to recognize content, has been used extensively across industries in recent years. However, in the healthcare industry, its applications are limited by factors like privacy, safety, and ethical concerns. Despite this, CV has the potential to improve patient monitoring, and system efficiencies, while reducing workload. In contrast to previous reviews, we focus on the end-user applications of CV. First, we briefly review and categorize CV applications in other industries (job enhancement, surveillance and monitoring, automation, and augmented reality). We then review the developments of CV in the hospital setting, outpatient, and community settings. The recent advances in monitoring delirium, pain and sedation, patient deterioration, mechanical ventilation, mobility, patient safety, surgical applications, quantification of workload in the hospital, and monitoring for patient events outside the hospital are highlighted. To identify opportunities for future applications, we also completed journey mapping at different system levels. Lastly, we discuss the privacy, safety, and ethical considerations associated with CV and outline processes in algorithm development and testing that limit CV expansion in healthcare. This comprehensive review highlights CV applications and ideas for its expanded use in healthcare.
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    Attacking the Drug Epidemic: Healthcare Delivery Perspective
    (2017) Oruche, Ukamaka M.
    Addiction is a chronic and recurring brain disease. Despite the associated symptoms and behaviors, prevention works, treatment is effective, and recovery is possible for everyone. Together we can attack current drug epidemic using a public health framework of integrated, comprehensive and multipronged approach appropriate to each person’s need.
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    Big data in healthcare - the promises, challenges and opportunities from a research perspective: A case study with a model database
    (AMIA, 2018-04-16) Adibuzzaman, Mohammad; DeLaurentis, Poching; Hill, Jennifer; Benneyworth, Brian D.; Pediatrics, School of Medicine
    Recent advances in data collection during routine health care in the form of Electronic Health Records (EHR), medical device data (e.g., infusion pump informatics, physiological monitoring data, and insurance claims data, among others, as well as biological and experimental data, have created tremendous opportunities for biological discoveries for clinical application. However, even with all the advancement in technologies and their promises for discoveries, very few research findings have been translated to clinical knowledge, or more importantly, to clinical practice. In this paper, we identify and present the initial work addressing the relevant challenges in three broad categories: data, accessibility, and translation. These issues are discussed in the context of a widely used detailed database from an intensive care unit, Medical Information Mart for Intensive Care (MIMIC III) database.
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    Burosumab treatment in adults with X-linked hypophosphataemia: 96-week patient-reported outcomes and ambulatory function from a randomised phase 3 trial and open-label extension
    (BMJ, 2021) Briot, Karine; Portale, Anthony A.; Brandi, Maria Luisa; Carpenter, Thomas O.; Cheong, Hae Ii; Cohen-Solal, Martine; Crowley, Rachel K.; Eastell, Richard; Imanishi, Yasuo; Ing, Steven; Insogna, Karl; Ito, Nobuaki; de Beur, Suzanne Jan; Javaid, Muhammad K.; Kamenicky, Peter; Keen, Richard; Kubota, Takuo; Lachmann, Robin H.; Perwad, Farzana; Pitukcheewanont, Pisit; Ralston, Stuart H.; Takeuchi, Yasuhiro; Tanaka, Hiroyuki; Weber, Thomas J.; Yoo, Han-Wook; Nixon, Annabel; Nixon, Mark; Sun, Wei; Williams, Angela; Imel, Erik A.; Medicine, School of Medicine
    Objectives: To report the impact of burosumab on patient-reported outcomes (PROs) and ambulatory function in adults with X-linked hypophosphataemia (XLH) through 96 weeks. Methods: Adults diagnosed with XLH were randomised 1:1 in a double-blinded trial to receive subcutaneous burosumab 1 mg/kg or placebo every 4 weeks for 24 weeks (NCT02526160). Thereafter, all subjects received burosumab every 4 weeks until week 96. PROs were measured using the Western Ontario and the McMaster Universities Osteoarthritis Index (WOMAC), Brief Pain Inventory-Short Form (BPI-SF) and Brief Fatigue Inventory (BFI), and ambulatory function was measured with the 6 min walk test (6MWT). Results: Subjects (N=134) were randomised to burosumab (n=68) or placebo (n=66) for 24 weeks. At baseline, subjects experienced pain, stiffness, and impaired physical and ambulatory function. At week 24, subjects receiving burosumab achieved statistically significant improvement in some BPI-SF scores, BFI worst fatigue (average and greatest) and WOMAC stiffness. At week 48, all WOMAC and BPI-SF scores achieved statistically significant improvement, with some WOMAC and BFI scores achieving meaningful and significant change from baseline. At week 96, all WOMAC, BPI-SF and BFI achieved statistically significant improvement, with selected scores in all measures also achieving meaningful change. Improvement in 6MWT distance and percent predicted were statistically significant at all time points from 24 weeks. Conclusions: Adults with XLH have substantial burden of disease as assessed by PROs and 6MWT. Burosumab treatment improved phosphate homoeostasis and was associated with a steady and consistent improvement in PROs and ambulatory function.
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    Changes in healthcare managing COVID and non-COVID-19 patients during the pandemic: striking the balance
    (Elsevier, 2020-07-18) Al-Tawfiq, Jaffar A.; Al-Yami, Saeed S.; Rigamonti, Daniele; Medicine, School of Medicine
    Following the emergence of the coronavirus disease 19 (COVID-19) pandemic, healthcare organizations began concentrating on the preparation for and management of the surge of COVID-19 cases while trying to protect the healthcare workers and other patients from getting COVID-19. Changing the way people work requires innovative approaches and questioning some long-held medical practices. There are multiple factors contributing to the apparent reduced utilization of healthcare services to non–COVID-19 patients. The current world crisis is highlighting the need of re-engineering the way we deliver inpatient and outpatient health care, including bolstering social support, in order to be prepared when the next calamity will present itself.
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    COVID-19 and healthcare lessons already learned
    (Oxford University Press, 2020-05-04) Terry, Nicolas P.; Robert H. McKinney School of Law
    COVID-19 has exposed deep-rooted flaws in our health system regarding healthcare financing and delivery. This essay uses COVID-19 as a frame to reflect on the growth in our uninsured population, the flaws inherent in healthcare federalism, how “Trumpcare” has made things worse, the magnified importance of Medicaid, and the problems inherent in relying primarily on private actors.
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    Daily Situational Brief, December 23, 2014
    (MESH Coalition, 12/23/14) MESH Coalition