Medical telematics

This quantitative research study explored the impact of the COVID-19 pandemic on the utilization of telehealth in mental health services, focusing on the Veterans Health Administration (VHA) of the U.S. Department of Veterans Affairs. The study assessed changes in appointment types across location, modality, gender, age, race, and rurality. Drawing on the Technology Acceptance Model (TAM) and introducing a COVID-19 moderation factor, the study investigates the adoption of telehealth technology and its effects on traditionally underserved groups. The research method involved a quantitative analysis of de-identified patient appointment data from FY 2017 to FY 2022, encompassing 66 million appointments. Empirical research was assessed for any impact of the coronavirus disease 2019 (COVID-19) pandemic on the proliferation of the telehealth modality in mental health. The study incorporated statistical analyses, including time series regression, to test the hypothesis that telehealth positively influenced mental health service delivery, with the COVID-19 pandemic as a moderating factor. Descriptive statistics were used to present the mean and standard deviation scores for the independent and dependent variables. Frequency statistics were used to describe the independent variables for the study further. Three regression models were used to answer the hypotheses. Comprehensive results were presented, showcasing the impact of the pandemic on telehealth adoption, and behavioral intentions. Specifically, the COVID-19 pandemic has fundamentally altered the landscape of doctoral healthcare provider visits, generally decreased in-person visits while substantially increased video and phone visits. The findings highlighted sizable shifts in healthcare dynamics, emphasizing the influence of demographic factors on visit types and the complex interplay with COVID-19. This study contributed valuable insights into the transformative role of telehealth in mental health care, especially during global health crises like the COVID-19 pandemic.

This effort studies the implementation of a biocompatible Planar Inverted-F Antenna
(PIF A) for the Medical Instrument Communication System (MICS) frequency band of
402 to 405 MHz for RFID applications. The basic electromagnetic properties of human
tissues are investigated at 403 .5 MHz. Then, the radiation characteristics of submerged
wire antenna are evaluated in order to approximate the effects of multilayered media on a
PIFA's performance. The PIFA is assessed using Ansoft's Finite Element Method based
electromagnetic evaluation software, HFSS v.l 0. The electrical parameters of the
antenna in relation to the surrounding environment, notably air, silicone capsule, and a
three-layered bio-media, are presented. The analysis shows that the resonant frequency
as well as the electrical performance of the design is significantly affected by the physical
dimensions and the relative permittivity of the dielectric materials covering the antenna.

In this thesis, importance of Intelligent Data Repository (IDR) and its real life applications are studied. We proposed an IDR for oncology applications which can handle large datasets and which can be used on both the intranet and the Internet. It is designed to provide one or multiple medical institutions on a global scale a common platform for patient care and consultation. The proposed application consists of two key models, Body Surface Area model and Search model, which are described in detail and their results are discussed. We have implemented the proposed IDR for oncology application using ColdFusion MX. Existing research in this area have been studied and compared. Framework of the proposed IDR, structure, front-end user interface and back-end database schema of the proposed oncology application are explained in this thesis.

With the increasing demands of rising medical costs in combination with a boom in elderly patients in need of quality patient care medical practices are being stressed. Patient to nurse ratios are increasing and government spending in the medical domain is at an all-time high threatening the futures of government medical programs such as Medicare and Medicaid. In this thesis we propose a framework for the monitoring of a patient's vital statistics in a home-based setting using a mobile smart device. We believe that in taking advantage of the wireless sensor technology which is readily available today we can provide a solution that is both economically and socially viable offering a solid quality of healthcare in a comfortable and familiar environment. Our framework exposes both 802.11 and Bluetooth wireless protocol transmitting medical sensor devices using an Android platform device as a monitoring hub.