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Search Results: 1 - 10 of 1609 matches for " healthcare "
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State of Content: Healthcare Executive’s Role in Information Technology Adoption  [PDF]
Mary B. Burns, Snehamay Banerjee, Neset Hikmet
Journal of Service Science and Management (JSSM) , 2012, DOI: 10.4236/jssm.2012.52016
Abstract: Over the past 30 years, researchers have demonstrated that health care information technology (HIT) can improve patient safety and quality of care. More recently, attention has turned increasingly to the role of information and communication technology as a means to improve clinical decision-making as well as organizational efficiency and effective- ness. Despite these streams of research, there is a lack of investigation that look at why and how health care executives leverage HIT. In this paper, the researchers investigate factors that may have an impact on health care executives’ intentions to further adopt HIT in their workplace. The analysis of collected data suggests that these factors play a significant role in increased HIT adoption in the future.
Leadership for healthcare
Amy Tan Bee Choo,Jason Cheah
International Journal of Integrated Care , 2011,
Abstract:
Gaps in Goals: The History of Goal-setting in Health Care in India
K.R. Nayar
Oman Medical Journal , 2011,
Abstract:
How Much the Quality of Healthcare Costs? A Challenging Question!
Ismail Al Rashdi
Oman Medical Journal , 2011,
Abstract:
Health Care Discrimination in HIV Care  [PDF]
Jayakumar Palanisamy, Senthilkumar Subramanian
World Journal of AIDS (WJA) , 2011, DOI: 10.4236/wja.2011.13015
Abstract: Human Immunodeficiency Virus (HIV) infected population is experiencing enormous amount of social discrimination and stigmatization compared to other patients with any other chronic illness. Healthcare setup is not an exception where the HIV infected patients are shuttled from one place to another to get their basic services compared to HIV negative patients. This referral game of manipulation imparts additional stress to the already stressed HIV infected population. The physical and psychological impacts caused by other chronic conditions will be supplemented by social impact in the HIV infected population. This referral game in healthcare can cause the HIV infected to avoid their health seeking behavior and it may bring them back to their high risk activities, which can result in higher mortality/morbidity and failure in prevention and intervention strategies.
Physical activity and dietary behaviors of health clinic workers trying to lose weight  [PDF]
Tan Leng Goh, Trever Ball, Janet M. Shaw, James C. Hannon
Health (Health) , 2012, DOI: 10.4236/health.2012.48079
Abstract: Health clinic workers are potential agents of change for weight loss to patients, yet their behaviors are not well known. This study examined physical activity (PA) levels and dietary habits of health clinic workers who were and who were not trying to lose weight. Participants were 64 community health clinic workers (58 females and 6 males). Moderate-to-vigorous intensity (MVI) time spent in PA was assessed by triaxial accelerometry over 7 consecutive days. Dietary habits and weight loss efforts were determined by a food frequency questionnaire. Differences in MVI and nutrition variables were assessed by One-way ANOVA, comparing those trying to lose weight and those not trying to lose weight. 48 out of 64 health clinic workers (approximately 75%) indicated that they were currently trying to lose weight. There were significant differences (p < 0.05) in Body Mass Index (BMI), daily energy (Kcal) and fat (g) intake between those trying to lose weight and those not trying to lose weight. There were no significant differences in MVI, daily sugar intake (g), vegetable and fruit servings, and daily fiber intake (g) between groups. Health clinic workers trying to lose weight appear to be engaging in some appropriate dietary but not PA behaviors.
MAEB: Routing Protocol for IoT Healthcare  [PDF]
Haoru Su, Zhiliang Wang, Sunshin An
Advances in Internet of Things (AIT) , 2013, DOI: 10.4236/ait.2013.32A002
Abstract:

Healthcare is one of the most promising applications of Internet of Things. This paper describes a prototype for the IoT healthcare systems. We propose the Movement-Aided Energy-Balance (MAEB) routing protocol. The movement and energy information of the neighbor Coordinators are collected and stored in the neighbor discovery procedure. The MAEB forwarding is used to select the most suitable neighbor to forward the data. The simulation results show that the proposed protocol has better performance than the other three routing protocols.

iPhone Independent Real Time Localization System Research and Its Healthcare Application  [PDF]
Xintong Lu, Wei Liu, Yongliang Guan
Advances in Internet of Things (AIT) , 2013, DOI: 10.4236/ait.2013.34008
Abstract: This project studied several popular localization algorithms on iPhone and, according to the demands, specifically designed it to improve healthcare IT system in hospitals. The challenge of this project was to realize the different localization systems on iPhone and to make balance between its response time and localization accuracy. We implemented three popular localization algorithms, namely nearest neighbor (NN), K-nearest neighbor (KNN), and probability phase, and we compared their performance on iPhone. Furthermore, we also implemented a real-time localization system using the ZigBee technology on iPhone. Thus, the whole system could realize not only self-localization but also others-localization. To fulfill the healthcare needs, we developed an application, which can be used to improve the hospital IT, system. The whole project included three phases. The first phase was to localize iPhone’s position using the received WiFi signal by iPhone, compare and optimize their performances. During the second phase, we implemented a ZigBee RFID localization system and combined it with the WiFi system. Finally, we combined new features of the system with a healthcare IT system. We believe that this application on iPhone can be a useful and advanced application in hospitals.
Sensors Applied in Healthcare Environments  [PDF]
Wei Vivien Shi
Journal of Computer and Communications (JCC) , 2016, DOI: 10.4236/jcc.2016.45015
Abstract:

In this paper, the recent advances of sensors applied in healthcare environments are presented. Based on the function and operation of modern health and wellness measurement and monitoring and mHealth solutions, a variety of sensors are described with their features and applications. Further improvements and future trend are pointed out and discussed.

Cigarette Smoking and Attitudes Concerning Its Control among Healthcare Workers in Enugu, South-East, Nigeria  [PDF]
I. B. Omotowo, E. O. Ndibuagu, U. Ezeoke
Health (Health) , 2016, DOI: 10.4236/health.2016.811108
Abstract: Introduction: Cigarette smoking is an established risk factor for many diseases, and according to World Health Organization, health care workers can influence positively or negatively the smoking habits of the community. Objective: The purpose of the study was to investigate the prevalence of cigarette smoking and attitudes regarding its control among healthcare workers in Enugu, South-East Nigeria. Methods: This cross sectional study was conducted among 369 healthcare providers randomly selected in primary, secondary and tertiary health facilities. Data were collected using a self reported questionnaire on cigarette smoking, and were analysed using SPSS Version 21, and statistical significance of association between variables was assessed using chi-square test at p < 0.05. Ethical clearance from University of Nigeria Teaching Hospital, Enugu and informed written consent was obtained from the participants. Results: Overall, 369 respondents returned the completed questionnaires. 54.2% were males, 75.9% were aged between 20 to 40 years, while their mean age was 27.5 ± 6.2 years. Overall life time prevalence of smoking among healthcare workers was 21.1% with (95% confidence interval 17.3 - 25.6), currently smoking was 6.5% with (95% confidence interval 5.8 - 7.4), while life time prevalence among physicians was 31.7% with (95% ci 28.8 - 33.6). The highest smoking rate was among the internists 72.7% in the physicians group. More smokers significantly agreed that the followings should be banned: cigarette sales (X2 = 22.134, df = 6, P = 0.003), advertising cigarettes (X2 = 42.532, df = 28, P = 0.040), cigarettes smoking in restaurants (X2 = 42.560, df = 20, P = 0.001), and smoking in all enclosed places (X2 = 33.257, df = 20, P = 0.025), but not statistically significant for health professionals to serve as role models (X2 = 24.420, df = 8, P = 0.086). Conclusion: Our results showed high percentage of cigarette smoking among healthcare providers. Smoking cessation programs should be introduced among healthcare providers.
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