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The aim of this study was to evaluate the effects of a data‐driven clinical productivity system that leverages Electronic Health Record (EHR) data to provide productivity decision support functionality in a real‐world clinical setting. The system was implemented for a large behavioral health care provider seeing over 75,000 distinct clients a year.

The key metric in this system is a “VPU”, which simultaneously optimizes multiple aspects of clinical care. The resulting mathematical value of clinical productivity was hypothesized to tightly link the organization's performance to its expectations and, through transparency and decision support tools at the clinician level, affect significant changes in productivity, quality, and consistency relative to traditional models of clinical productivity.

In only three months, every single variable integrated into the VPU system showed significant improvement, including a 30 percent rise in revenue, 10 percent rise in clinical percentage, a 25 percent rise in treatment plan completion, a 20 percent rise in case rate eligibility, along with similar improvements in compliance/audit issues, outcomes collection, access, etc.

A data‐driven clinical productivity system employing decision support functionality is effective, because of the impact on clinician behavior relative to traditional clinical productivity systems. Critically, the model is also extensible to integration with outcomes‐based productivity.

EHR's are only a first step – the problem is turning that data into useful information. Technology can leverage the data in order to produce actionable information that can inform clinical practice and decision‐making. Without additional technology, EHR's are essentially just copies of paper‐based records stored in electronic form.

The purpose of this paper is to show how a clinical decision support system can help in prescription and knowledge acquisition processes.

An integrated electronic medical records system (iEMRS) is designed to enhance the decision support quality in prescription.

By evaluating the system performance through 135 prescription records collected from a Hong Kong medical organization, iEMRS shows a satisfactory result in suggesting medicines that is properly the same as the decisions made by the physicians.

Compared with the static clinical guidelines built (manually) in the traditional clinical decision support system, knowledge in iEMRS is generated by the knowledge discovery result from professional experiences of various physicians and patient histories, which are more dynamic in nature. A treatment algorithm, designed in data mining technique, is introduced to improve information management in medical organizations by integration of decision support capability and EMRS, and supplement the deficiencies of traditional clinical decision support system.

The progress of initiatives concerned with implementing evaluated clinical research (such as evidence based medicine and clinical effectiveness) is dependent on the way individual health professionals actually acquire, use and value clinical knowledge in routine practice. The findings of two research projects, the Value and EVINCE projects, are compared with studies of the consolidation and application of clinical knowledge in clinical decision making. The Value project was concerned with the ways in which information from NHS libraries might be used in present and future clinical decision making. EVINCE was a similar impact study for nursing professionals. Both studies confirmed the importance of personal clinical knowledge. Health information services need to use a variety of strategies and knowledge management skills to ensure that the evaluated research evidence is assimilated and implemented into practice.

This study proposes targeted modernization of the Department of Defense (DoD's) Joint Forces Ammunition Logistics information system by implementing the optimized innovative information technology open architecture design and integrating Radio Frequency Identification Device data technologies and real-time optimization and control mechanisms as the critical technology components of the solution. The innovative information technology, which pursues the focused logistics, will be deployed in 36 months at the estimated cost of $568 million in constant dollars. We estimate that the Systems, Applications, Products (SAP)-based enterprise integration solution that the Army currently pursues will cost another $1.5 billion through the year 2014; however, it is unlikely to deliver the intended technical capabilities.

We investigate whether information technology (IT) can help physicians more efficiently acquire new knowledge in a clinical environment characterized by information overload. We combine analysis of data from a randomized trial with a theoretical model of the influence that IT has on the acquisition of new medical knowledge. Although the theoretical framework we develop is conventionally microeconomic, the model highlights the non-market and non-pecuniary influence activities that have been emphasized in the sociological literature on technology diffusion. We report three findings. First, empirical evidence and theoretical reasoning suggests that computer-based decision support will speed the diffusion of new medical knowledge when physicians are coping with information overload. Second, spillover effects will likely lead to “underinvestment” in this decision support technology. Third, alternative financing strategies common to new IT, such as the use of marketing dollars to pay for the decision support systems, may lead to undesirable outcomes if physician information overload is sufficiently severe and if there is significant ambiguity in how best to respond to the clinical issues identified by the computer. This is the first paper to analyze empirically and theoretically how computer-based decision support influences the acquisition of new knowledge by physicians.

This chapter proposes an optimized innovative information technology as a means for achieving operational functionalities of real-time portable electronic health records, system interoperability, longitudinal health-risks research cohort and surveillance of adverse events infrastructure, and clinical, genome regions – disease and interventional prevention infrastructure. In application to the Dod-VA (Department of Defense and Veteran's Administration) health information systems, the proposed modernization can be carried out as an “add-on” expansion (estimated at $288 million in constant dollars) or as a “stand-alone” innovative information technology system (estimated at $489.7 million), and either solution will prototype an infrastructure for nation-wide health information systems interoperability, portable real-time electronic health records (EHRs), adverse events surveillance, and interventional prevention based on targeted single nucleotide polymorphisms (SNPs) discovery.

The study explores how Taiwan’s electronic health data systems can be used to build algorithms that reduce or eliminate medical errors and to advance precision medicine.

This study is a narrative review of the literature.

The body of medical knowledge has grown far too large for human clinicians to parse. In theory, electronic health records could augment clinical decision-making with electronic clinical decision support systems (CDSSs). However, computer scientists and clinicians have made remarkably little progress in building CDSSs, because health data tend to be siloed across many different systems that are not interoperable and cannot be linked using common identifiers. As a result, medicine in the USA is often practiced inconsistently with poor adherence to the best preventive and clinical practices. Poor information technology infrastructure contributes to medical errors and waste, resulting in suboptimal care and tens of thousands of premature deaths every year. Taiwan’s national health system, in contrast, is underpinned by a coordinated system of electronic data systems but remains underutilized. In this paper, the authors present a theoretical path toward developing artificial intelligence (AI)-driven CDSS systems using Taiwan’s National Health Insurance Research Database. Such a system could in theory not only optimize care and prevent clinical errors but also empower patients to track their progress in achieving their personal health goals.

While research teams have previously built AI systems with limited applications, this study provides a framework for building global AI-based CDSS systems using one of the world’s few unified electronic health data systems.

This paper provides an overview of the range and development of health informatics, with examples from the literature world wide covering the types of information involved, the areas of application, the impact of evidence based medicine and other professional issues, integrated information systems, and the needs of the public, patients and their carers. While medical informatics certainly comprises a major part of health informatics it is not the main focus of this paper. Medical informatics is the older term and involves the use of information technology and computing specifically for medical science research, and the diagnosis and treatment of disease involving, for example, X‐rays, imaging, resonance, and magnetic scanning techniques. Rather, the scope of this review is the literature relating to the wider concept of the management of information through the interdisciplinary application of information science and technology for the benefit of patients, scientists, managers, staff, and carers involved in the whole range of healthcare activity.

This paper looks at a number of approaches to health informatics that support decision‐making relevant to the integrated development and management of information systems with clinical and managerial practices in healthcare. Its main aim is to explore three such approaches for integrated development, the soft information systems and technologies methodology, participative simulation modelling and stakeholder analysis. A description of the health informatics research and development environment in the UK is given as necessary background to the paper. Organisational and social aspects are examined through these approaches including information and clinical process development, telemedicine, ethical issues of drug use and management, health policies and information management and strategies, tele‐education and modelling structures. In the conclusion the synergies between the three approaches are discussed and some principles are extracted for future research and development in integrated approaches to health informatics research.

States that risk and risk management in general practice in the UK are now integral parts of the clinical effectiveness and clinical governance agenda, rather than being primarily concerned with negligence and malpractice. Notes that this has led to the introduction of a variety of technologies for improving care and thus reducing risk. Considers the frequency, nature and causes of adverse incidents in general practice, and the rise of evidence‐based practice and clinical practice guidelines, and then looks at some of those technologies currently in use. Concludes that technology seems to have a growing impact on the practice of primary care medicine and the management of clinical risk.