Framework for Data Mining In Healthcare Information System in Developing Countries: A Case of Tanzania

\ud Globally the healthcare sector is abundant with data and hence using data mining techniques in this area seems promising. Healthcare sector collects huge amounts of data on a daily basis. Transferring data into secure electronic system of medical health can save lives and reduce the cost of healthcare services as well as early discovery of contagious diseases with advanced collection of medical data. In this study we have proposed a best fit for data mining techniques in healthcare based on a case study. The proposed framework aims to provide self healthcare treatments where by several monitoring equipments using the cyberspace devices have been developed to help patients manage their medical conditions at home for example, diabetic patients can test their blood sugar level by using e-device, which, with the click of a computer mouse, downloads the results to a healthcare practitioner, minimizes time to wait for medical treatments, and minimizes the delay time in providing medical treatments. Data mining is a new technology used in different types of sectors to improve the effectiveness and efficiency of business model as well as solving problems in business world.\u

Flexible home care automation adapting to the personal and evolving needs and situations of the patient

Health monitoring and healthcare provisioning at home (i.e., outside the hospital) have received increasingly attention as a possible and partial solution for addressing the problems of an aging population. There are still many technological issues that need to be solved before home healthcare systems can be really cost-effective and efficient. However, in this paper we will highlight another category of issues which we call architectural challenges. Each patient is unique, and each patient has a unique lifestyle, living environment and course of life. Therefore it should be possible to personalize the services provided by home healthcare systems according to the needs and preferences of each individual patient, and it should be possible to make incremental adaptations at later points in time if this is necessary due to, for example, a changing health condition. The architectural challenges and solution directions related to this has been discussed in this paper

Telehealthcare for chronic obstructive pulmonary disease

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a disease of irreversible airways obstruction in which patients often suffer exacerbations. Sometimes these exacerbations need hospital care: telehealthcare has the potential to reduce admission to hospital when used to administer care to the pateint from within their own home. OBJECTIVES: To review the effectiveness of telehealthcare for COPD compared with usual face‐to‐face care. SEARCH METHODS: We searched the Cochrane Airways Group Specialised Register, which is derived from systematic searches of the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE, CINAHL, AMED, and PsycINFO; last searched January 2010. SELECTION CRITERIA: We selected randomised controlled trials which assessed telehealthcare, defined as follows: healthcare at a distance, involving the communication of data from the patient to the health carer, usually a doctor or nurse, who then processes the information and responds with feedback regarding the management of the illness. The primary outcomes considered were: number of exacerbations, quality of life as recorded by the St George's Respiratory Questionnaire, hospitalisations, emergency department visits and deaths. DATA COLLECTION AND ANALYSIS: Two authors independently selected trials for inclusion and extracted data. We combined data into forest plots using fixed‐effects modelling as heterogeneity was low (I(2) < 40%). MAIN RESULTS: Ten trials met the inclusion criteria. Telehealthcare was assessed as part of a complex intervention, including nurse case management and other interventions. Telehealthcare was associated with a clinically significant increase in quality of life in two trials with 253 participants (mean difference ‐6.57 (95% confidence interval (CI) ‐13.62 to 0.48); minimum clinically significant difference is a change of ‐4.0), but the confidence interval was wide. Telehealthcare showed a significant reduction in the number of patients with one or more emergency department attendances over 12 months; odds ratio (OR) 0.27 (95% CI 0.11 to 0.66) in three trials with 449 participants, and the OR of having one or more admissions to hospital over 12 months was 0.46 (95% CI 0.33 to 0.65) in six trials with 604 participants. There was no significant difference in the OR for deaths over 12 months for the telehealthcare group as compared to the usual care group in three trials with 503 participants; OR 1.05 (95% CI 0.63 to 1.75). AUTHORS' CONCLUSIONS: Telehealthcare in COPD appears to have a possible impact on the quality of life of patients and the number of times patients attend the emergency department and the hospital. However, further research is needed to clarify precisely its role since the trials included telehealthcare as part of more complex packages

Mobile Health Care over 3G Networks: the MobiHealth Pilot System and Service

Health care is one of the most prominent areas for the application of wireless technologies. New services and applications are today under research and development targeting different areas of health care, from high risk and chronic patients’ remote monitoring to mobility tools for the medical personnel. In this direction the MobiHealth project developed and trailed a system and a service that is using UMTS for the continuous monitoring and transmission of vital signals, like Pulse Oximeter sensor , temperature, Marker, Respiratory band, motion/activity detector etc., to the hospital. The system, based on the concept of the Body Area Network, is highly customisable, allowing sensors to be seamlessly connected and transmit the monitored vital signal measurements. The system and service was trialed in 4 European countries and it is presently under market validation

A Novel Framework for Software Defined Wireless Body Area Network

Software Defined Networking (SDN) has gained huge popularity in replacing traditional network by offering flexible and dynamic network management. It has drawn significant attention of the researchers from both academia and industries. Particularly, incorporating SDN in Wireless Body Area Network (WBAN) applications indicates promising benefits in terms of dealing with challenges like traffic management, authentication, energy efficiency etc. while enhancing administrative control. This paper presents a novel framework for Software Defined WBAN (SDWBAN), which brings the concept of SDN technology into WBAN applications. By decoupling the control plane from data plane and having more programmatic control would assist to overcome the current lacking and challenges of WBAN. Therefore, we provide a conceptual framework for SDWBAN with packet flow model and a future direction of research pertaining to SDWBAN.Comment: Presented on 8th International Conference on Intelligent Systems, Modelling and Simulatio

RFID Localisation For Internet Of Things Smart Homes: A Survey

The Internet of Things (IoT) enables numerous business opportunities in fields as diverse as e-health, smart cities, smart homes, among many others. The IoT incorporates multiple long-range, short-range, and personal area wireless networks and technologies into the designs of IoT applications. Localisation in indoor positioning systems plays an important role in the IoT. Location Based IoT applications range from tracking objects and people in real-time, assets management, agriculture, assisted monitoring technologies for healthcare, and smart homes, to name a few. Radio Frequency based systems for indoor positioning such as Radio Frequency Identification (RFID) is a key enabler technology for the IoT due to its costeffective, high readability rates, automatic identification and, importantly, its energy efficiency characteristic. This paper reviews the state-of-the-art RFID technologies in IoT Smart Homes applications. It presents several comparable studies of RFID based projects in smart homes and discusses the applications, techniques, algorithms, and challenges of adopting RFID technologies in IoT smart home systems.Comment: 18 pages, 2 figures, 3 table

EuroEco (European Health Economic Trial on Home Monitoring in ICD Patients): a provider perspective in five European countries on costs and net financial impact of follow-up with or without remote monitoring

Aim: Remote follow-up (FU) of implantable cardiac defibrillators (ICDs) allows for fewer in-office visits in combination with earlier detection of relevant findings. Its implementation requires investment and reorganization of care. Providers (physicians or hospitals) are unsure about the financial impact. The primary end-point of this randomized prospective multicentre health economic trial was the total FU-related cost for providers, comparing Home Monitoring facilitated FU (HM ON) to regular in-office FU (HM OFF) during the first 2 years after ICD implantation. Also the net financial impact on providers (taking national reimbursement into account) and costs from a healthcare payer perspective were evaluated. Methods and results: Atotal of 312 patients with VVI-or DDD-ICD implants from 17 centres in six EU countries were randomised to HMON or OFF, of which 303 were eligible for data analysis. For all contacts (in-office, calendar-or alert-triggered web-based review, discussions, calls) time-expenditure was tracked. Country-specific cost parameters were used to convert resource use into monetary values. Remote FU equipment itself was not included in the cost calculations. Given only two patients from Finland (one in each group) a monetary valuation analysis was not performed for Finland. Average age was 62.4 +/- 13.1 years, 81% were male, 39% received a DDD system, and 51% had a prophylactic ICD. Resource use with HM ON was clearly different: less FU visits (3.79 +/- 1.67 vs. 5.53 +/- 2.32; P < 0.001) despite a small increase of unscheduled visits (0.95 +/- 1.50 vs. 0.62 +/- 1.25; P < 0.005), more non-office-based contacts (1.95+3.29 vs. 1.01 +/- 2.64; P < 0.001), more Internet sessions (11.02 +/- 15.28 vs. 0.06 +/- 0.31; P < 0.001) and more in-clinic discussions (1.84 +/- 4.20 vs. 1.28 +/- 2.92; P < 0.03), but with numerically fewer hospitalizations (0.67 +/- 1.18 vs. 0.85 +/- 1.43, P = 0.23) and shorter length-of-stay (6.31 +/- 15.5 vs. 8.26 +/- 18.6; P = 0.27), although not significant. For the whole study population, the total FU cost for providers was not different for HM ON vs. OFF [mean (95% CI): (sic)204 169-238) vs. (sic)213 (182-243); range for difference ((sic)-36 to 54), NS]. From a payer perspective, FU-related costs were similar while the total cost per patient (including other physician visits, examinations, and hospitalizations) was numerically (but not significantly) lower. There was no difference in the net financial impact on providers [profit of (sic)408 (327-489) vs. (sic)400 (345-455); range for difference ((sic)-104 to 88), NS], but there was heterogeneity among countries, with less profit for providers in the absence of specific remote FU reimbursement (Belgium, Spain, and the Netherlands) and maintained or increased profit in cases where such reimbursement exists (Germany and UK). Quality of life (SF-36) was not different. Conclusion: For all the patients as a whole, FU-related costs for providers are not different for remote FU vs. purely in-office FU, despite reorganized care. However, disparity in the impact on provider budget among different countries illustrates the need for proper reimbursement to ensure effective remote FU implementation

How 5G wireless (and concomitant technologies) will revolutionize healthcare?

The need to have equitable access to quality healthcare is enshrined in the United Nations (UN) Sustainable Development Goals (SDGs), which defines the developmental agenda of the UN for the next 15 years. In particular, the third SDG focuses on the need to “ensure healthy lives and promote well-being for all at all ages”. In this paper, we build the case that 5G wireless technology, along with concomitant emerging technologies (such as IoT, big data, artificial intelligence and machine learning), will transform global healthcare systems in the near future. Our optimism around 5G-enabled healthcare stems from a confluence of significant technical pushes that are already at play: apart from the availability of high-throughput low-latency wireless connectivity, other significant factors include the democratization of computing through cloud computing; the democratization of Artificial Intelligence (AI) and cognitive computing (e.g., IBM Watson); and the commoditization of data through crowdsourcing and digital exhaust. These technologies together can finally crack a dysfunctional healthcare system that has largely been impervious to technological innovations. We highlight the persistent deficiencies of the current healthcare system and then demonstrate how the 5G-enabled healthcare revolution can fix these deficiencies. We also highlight open technical research challenges, and potential pitfalls, that may hinder the development of such a 5G-enabled health revolution