Navigating an ocean of information: how Community Care of North Carolina uses data to improve care and control costs.

Community Care of North Carolina's 14 networks use data analysis to provide relevant solutions that are responsive to unique regional environments. This article describes some of the ways that these networks use data to improve patient self-management, to meet providers' needs, to improve quality of care, and to control costs.

Use of big data by Blue Cross and Blue Shield of North Carolina.

The health care industry is grappling with the challenges of working with and analyzing large, complex, diverse data sets. Blue Cross and Blue Shield of North Carolina provides several promising examples of how big data can be used to reduce the cost of care, to predict and manage health risks, and to improve clinical outcomes.

The value of all-payer claims databases to states.

All-payer claims databases are being developed in states across the nation to fill gaps in information about the health care system. The value of such databases is becoming more apparent as these databases mature and are used more frequently to help states better understand their health care utilization and costs.

Costs of cloud computing for a biometry department. A case study.

BACKGROUND: "Cloud" computing providers, such as the Amazon Web Services (AWS), offer stable and scalable computational resources based on hardware virtualization, with short, usually hourly, billing periods. The idea of pay-as-you-use seems appealing for biometry research units which have only limited access to university or corporate data center resources or grids. OBJECTIVES: This case study compares the costs of an existing heterogeneous on-site hardware pool in a Medical Biometry and Statistics department to a comparable AWS offer. METHODS: The "total cost of ownership", including all direct costs, is determined for the on-site hardware, and hourly prices are derived, based on actual system utilization during the year 2011. Indirect costs, which are difficult to quantify are not included in this comparison, but nevertheless some rough guidance from our experience is given. To indicate the scale of costs for a methodological research project, a simulation study of a permutation-based statistical approach is performed using AWS and on-site hardware. RESULTS: In the presented case, with a system utilization of 25-30 percent and 3-5-year amortization, on-site hardware can result in smaller costs, compared to hourly rental in the cloud dependent on the instance chosen. Renting cloud instances with sufficient main memory is a deciding factor in this comparison. CONCLUSIONS: Costs for on-site hardware may vary, depending on the specific infrastructure at a research unit, but have only moderate impact on the overall comparison and subsequent decision for obtaining affordable scientific computing resources. Overall utilization has a much stronger impact as it determines the actual computing hours needed per year. Taking this into ac count, cloud computing might still be a viable option for projects with limited maturity, or as a supplement for short peaks in demand.

[Facing the challenges of ubiquitous computing in the health care sector]. / Herausforderungen durch ubiquitäres Computing im Gesundheitsbereich.

The steady progress of microelectronics, communications and information technology will enable the realisation of the vision for "ubiquitous computing" where the Internet extends into the real world embracing everyday objects. The necessary technical basis is already in place. Due to their diminishing size, constantly falling price and declining energy consumption, processors, communications modules and sensors are being increasingly integrated into everyday objects today. This development is opening up huge opportunities for both the economy and individuals. In the present paper we discuss possible applications, but also technical, social and economic barriers to a wide-spread use of ubiquitous computing in the health care sector.

A stimulus to define informatics and health information technology.

BACKGROUND: Despite the growing interest by leaders, policy makers, and others, the terminology of health information technology as well as biomedical and health informatics is poorly understood and not even agreed upon by academics and professionals in the field. DISCUSSION: The paper, presented as a Debate to encourage further discussion and disagreement, provides definitions of the major terminology used in biomedical and health informatics and health information technology. For informatics, it focuses on the words that modify the term as well as individuals who practice the discipline. Other categories of related terms are covered as well, from the associated disciplines of computer science, information technology and health information management to the major application categories of applications used. The discussion closes with a classification of individuals who work in the largest segment of the field, namely clinical informatics. SUMMARY: The goal of presenting in Debate format is to provide a starting point for discussion to reach a documented consensus on the definition and use of these terms.

Limited information technology for patient care in physician offices.

Evidence of physicians' use of information technology (IT) to support patient care has been sketchy and anecdotal to date. However, new findings from the Center for Studying Health System Change (HSC) show wide variation in information technology adoption across physician practices, particularly by physician practice size. In 2001, nearly 60 percent of physicians in traditional practice settings--primarily solo or relatively small group practices where the vast majority of Americans receive care--reported that their practice used information technology in no more than one of the five following clinical functions: obtaining treatment guidelines, exchanging clinical data with other physicians, accessing patient notes, generating treatment reminders for the physician's use and writing prescriptions. Highest levels of IT support for patient care were found in staff- and group-model health maintenance organization (HMO) practices, followed by medical school faculty practices and large group practices. Overall rates of information technology adoption may have increased since 2001, but the variation in IT adoption by practice setting is unlikely to have changed

Risk perception during information system development in non-profit health care organizations.

The perception of risk exposure among design team members during the early phases of information system development projects can provide valuable strategic information for clinical organizations. To develop a typology of perceived risks during information system development projects in health care, interviews were performed with key team members from a specialist clinic, primary health care, and an informatics research group, during the requirements specification. Phenomenological data analysis and secondary integration of the results in available theories were performed. System objectives, the user requirements definition procedure, the communication pattern between design team members and project management were found to be perceived as the main risk areas. In the secondary analysis, the technical factors, identified as preventing a maximization of the use of the resources, were lack of informatics knowledge among economic decision makers and differences between customers and suppliers regarding their views on the nature of system design. During the implementation of a given strategy, decision makers may consider the requests of their own sponsors in the first place and maximize the use of the project resources in the second place. Informatics knowledge plays a key role in risk perception during the development of an information system in health care. Political considerations by team members are important to take into regard, since these may influence technical and economic decisions.

High performance computing for the human genome project.

Human Genome Analysis and Image Processing are part of the 'Grand Challenges' in High Performance Computing. The traditional mainframe has become insufficient for these applications in Biocomputing. New scalable parallel processor systems enter the marketplace with superior price/performance. The evaluation process of such a system by an application-oriented benchmark test suite is described. The system is integrated in the client/server structure of the Deutsches Krebsforschungszentrum where 'rightsizing' will eliminate the mainframe completely in the near future.

Managed care and health information networks.

Communication and data exchange among existing health information systems is becoming increasingly important in the health care industry. In a managed care environment, the focus is on delivering value by providing consumers access to high-quality health care at reasonable cost. This article explains how the use of a health information network in the managed care system, which links all related entities, improves the quality of health care by allowing access to critical data on demand and decreases the cost of delivery by enhancing communication among managed care providers.

Evaluating black-boxes as medical decision aids: issues arising from a study of neural networks.

The rigorous evaluation of medical decision aids will be critical to promoting their development, establishing their clinical value and legalizing their use. Many decision aids are transparent in the sense that their internal structure and function can be examined and verified. Some decision aids, however, use complex models of associations in training data to construct 'black-box' systems whose workings are largely impenetrable and inexplicable. The issues surrounding the evaluation of such systems, as exemplified by connectionist (neural network) models, are discussed. For such systems the two major aspects that can be evaluated are the training data from which the system is derived, and its performance on test data. A number of questions about the use of black-box systems as medical decision aids are posed which require consideration by the medical informatics community.