Abstract

Living in a world of data, we need to use data wisely and manage it efficiently, as well as never get lost into it, especially in the field of health care. The design of health data management systems is a critical factor. From applications in different fields, we have chosen three that are characteristic of good data management and that may inspire better design of health data management systems: visualize data by mind mapping, track data by timeline, and increase interactivity by “check-in” function.

Safe and cost-effective wearable sensors and healthcare informatics solutions hold great promises and opportunities in tackling non-communicable diseases (NCDs) burden. This paper highlights the future opportunities of wearable sensors and healthcare informatics consolidation platforms implementation, uptake capabilities and needs in non-communicable diseases (NCDs) prevention and management in Africa. Establishing digital wearable technology policy and frameworks requires robust political commitment and financial investment in research and development towards real time, safe and effective prevention and management programs and tools. Leveraging on it added-value in strengthening health systems inefficiencies and low-cost care delivery is imperative in promoting predictive and preventive lifestyle mitigation an adaptation solutions to millions at risk or suffering from chronic illnesses. Also, in promoting participatory patient- professionals-health providers’ relationship and cooperation, monitoring and tracking of medication adherence to pathophysiological disease progression. Furthermore, digital wearable sensors offer another opportunity in generating data, information and knowledge in promoting evidence- based and practical lifestyle adaptations and other health / fitness mitigation programs in revamping the rising NCDs challenges in most vulnerable populations in Afri

Health care spending in the U.S. over the past decade has dramatically increased over the past decade and is expected to rise to 20% of GDP in the United States by the end of the decade. In 2010, the U.S. Congress approved the Health Care Reform Act with a critical component of this legislation being the adoption of health information technologies (i.e. EMRs, EHRs, PHRs, etc.) aimed at transforming the health care system. Consumer-driven health care models are seen as essential to control the escalating costs of health care. The objective of this research is to canvas the landscape of existing standards and guidelines relating to electronic personal health records (PHRs) and to evaluate the level of adoption of these standards and guidelines amongst current vendors. Through this effort, we propose a consensus standard for PHRs consisting of 14 data components, 11 of which should be essential for all PHRs and 3 additional recommended data components. Through a survey of existing PHR vendors, we observe a low level of adoption of existing standards in commercially available PHR products and note a wide variation (36-73%) of inclusion of critical and desired data components. Further, we propose 4 key features and services based upon a review of the existing literature to facilitate consumer adoption and to improve usefulness of PHRs. By proposing a consensus standard for PHR data components and features, we seek to provide clarity to developers and vendors of HIT products to facilitate product development, interoperability, and integration and data exchange with existing EMR/EHR products

Objective: Although it is widely assumed that in the Netherlands patients use public information from websites in their hospital choice, empirical data on the actual use of such information is scarce. Our aim is to describe the process of hospital choice and to study what factors, including social media, are related to hospital choice. Methods: In June 2011, a sample was drawn from patients who were seeking out-patient care from hospital-based clinics in the CWZ hospital in Nijmegen, the Netherlands. These patients were asked to fill in a short, self-administered questionnaire about hospital choice. A total of 419 patients visiting the hospital was included. The response rate was 74% (n=311). Results: Only 1.3% of the patients reported having used public information in their hospital choice. Most patients (85.2%) stated that they had been referred by their GP. Information from the GP, age, previous experience with the hospital and belonging to a specific patient group are much more important in the hospital choice process than written information and social media. Conclusions: So far, the assumption that patients use public information from websites or social media in their hospital choice appears to be unfounded.