Web-services-based resource discovery model and service deployment on HealthGrids

Knowledge Management for Fostering Biostatistical Collaboration within a Research Network: The RTRN Case Study

Purpose: While the intellectual and scientific rationale for research collaboration has been articulated, a paucity of information is available on a strategic approach to facilitate the collaboration within a research network designed to reduce health disparities. This study aimed to (1) develop a conceptual model to facilitate collaboration among biostatisticians in a research network; (2) describe collaborative engagement performed by the Network's Data Coordinating Center (DCC); and (3) discuss potential challenges and opportunities in engaging the collaboration. Methods: Key components of the strategic approach will be developed through a systematic literature review. The Network's initiatives for the biostatistical collaboration will be described in the areas of infrastructure, expertise and knowledge management and experiential lessons will be discussed. Results: Components of the strategic approach model included three Ps (people, processes and programs) which were integrated into expert management, infrastructure management and knowledge management, respectively. Ongoing initiatives for collaboration with non-DCC biostatisticians included both web-based and face-to-face interaction approaches: Network's biostatistical capacities and needs assessment, webinar statistical seminars, mobile statistical workshop and clinics, adjunct appointment program, one-on-one consulting, and on-site workshop. The outreach program, as a face-to-face interaction approach, especially resulted in a useful tool for expertise management and needs assessment as well as knowledge exchange. Conclusions: Although fostering a partnered research culture, sustaining senior management commitment and ongoing monitoring are a challenge for this collaborative engagement, the proposed strategies centrally performed by the DCC may be useful in accelerating the pace and enhancing the quality of the scientific outcomes within a multidisciplinary clinical and translational research network.

Profiling e-health projects in Africa: trends and funding patterns

There is a severe shortage of healthcare provision in Africa. e-Health, the use of Information and Communication Technologies (ICT) to support healthcare, may help to ease this problem. e-Health projects support a wide range of applications ranging from telemedicine to global research collaborations made possible via e-Infrastructures, worldwide systems of integrated advanced high performance networking and computing ICT. To try to understand the state of e-Health in Africa, this paper aims to create a picture and to present an analytical review of some of these initiatives in Africa. A review framework composed of multiple search methods is developed and applied to yield a broad coverage of e-Health projects over the African continent. Seven quantitative analyses on the projects are presented. Major observations include that there is a tendency for e-Health projects to grow in number in some African countries over time; that African countries with larger Gross National Incomes tend to attract more e-Health projects; that e-Health projects in Africa focus on telemedicine, health education and health-related research; that there is a wide range of funding bodies, some of which have a geographical focus, and that the number of m-Health projects has been rising sharply.

Improved glycemic control without hypoglycemia in elderly diabetic patients using the ubiquitous healthcare service, a new medical information system

OBJECTIVE

To improve quality and efficiency of care for elderly patients with type 2 diabetes, we introduced elderly-friendly strategies to the clinical decision support system (CDSS)-based ubiquitous healthcare (u-healthcare) service, which is an individualized health management system using advanced medical information technology.

RESEARCH DESIGN AND METHODS

We conducted a 6-month randomized, controlled clinical trial involving 144 patients aged >60 years. Participants were randomly assigned to receive routine care (control, n = 48), to the self-monitored blood glucose (SMBG, n = 47) group, or to the u-healthcare group (n = 49). The primary end point was the proportion of patients achieving A1C <7% without hypoglycemia at 6 months. U-healthcare system refers to an individualized medical service in which medical instructions are given through the patient's mobile phone. Patients receive a glucometer with a public switched telephone network-connected cradle that automatically transfers test results to a hospital-based server. Once the data are transferred to the server, an automated system, the CDSS rule engine, generates and sends patient-specific messages by mobile phone.

RESULTS

After 6 months of follow-up, the mean A1C level was significantly decreased from 7.8 ± 1.3% to 7.4 ± 1.0% (P < 0.001) in the u-healthcare group and from 7.9 ± 1.0% to 7.7 ± 1.0% (P = 0.020) in the SMBG group, compared with 7.9 ± 0.8% to 7.8 ± 1.0% (P = 0.274) in the control group. The proportion of patients with A1C <7% without hypoglycemia was 30.6% in the u-healthcare group, 23.4% in the SMBG group (23.4%), and 14.0% in the control group (P < 0.05).

CONCLUSIONS

The CDSS-based u-healthcare service achieved better glycemic control with less hypoglycemia than SMBG and routine care and may provide effective and safe diabetes management in the elderly diabetic patients.