Addressing the Quality and Safety Gap Part II: How Nurses Are Shaping, and Being Shaped by, Health Information Technologies

Explores the role of health information technologies (HIT) in improving patient safety and the role of nurses in designing, implementing, and educating clinicians to use HIT, including electronic health records and bar code medication administration

A systematic review of speech recognition technology in health care

BACKGROUND To undertake a systematic review of existing literature relating to speech recognition technology and its application within health care. METHODS A systematic review of existing literature from 2000 was undertaken. Inclusion criteria were: all papers that referred to speech recognition (SR) in health care settings, used by health professionals (allied health, medicine, nursing, technical or support staff), with an evaluation or patient or staff outcomes. Experimental and non-experimental designs were considered. Six databases (Ebscohost including CINAHL, EMBASE, MEDLINE including the Cochrane Database of Systematic Reviews, OVID Technologies, PreMED-LINE, PsycINFO) were searched by a qualified health librarian trained in systematic review searches initially capturing 1,730 references. Fourteen studies met the inclusion criteria and were retained. RESULTS The heterogeneity of the studies made comparative analysis and synthesis of the data challenging resulting in a narrative presentation of the results. SR, although not as accurate as human transcription, does deliver reduced turnaround times for reporting and cost-effective reporting, although equivocal evidence of improved workflow processes. CONCLUSIONS SR systems have substantial benefits and should be considered in light of the cost and selection of the SR system, training requirements, length of the transcription task, potential use of macros and templates, the presence of accented voices or experienced and in-experienced typists, and workflow patterns.Funding for this study was provided by the University of Western Sydney. NICTA is funded by the Australian Government through the Department of Communications and the Australian Research Council through the ICT Centre of Excellence Program. NICTA is also funded and supported by the Australian Capital Territory, the New South Wales, Queensland and Victorian Governments, the Australian National University, the University of New South Wales, the University of Melbourne, the University of Queensland, the University of Sydney, Griffith University, Queensland University of Technology, Monash University and other university partners

Nursing's Prescription for a Reformed Health System: Use Exemplary Nursing Initiatives to Expand Access, Improve Quality, Reduce Costs, and Promote Prevention

Highlights innovative nursing initiatives designed, led, or implemented by nurses that expand access, improve quality, promote prevention, and reduce costs as guidance for health reform efforts. Considers the role of nurses and policy implications

Speech Recognition Technology: Improving Speed and Accuracy of Emergency Medical Services Documentation to Protect Patients

Because hospital errors, such as mistakes in documentation, cause one in six deaths each year in the United States, the accuracy of health records in the emergency medical services (EMS) must be improved. One possible solution is to incorporate speech recognition (SR) software into current tools used by EMS first responders. The purpose of this research was to determine if SR software could increase the efficiency and accuracy of EMS documentation to improve the safety of patients of EMS. An initial review of the literature on the performance of current SR software demonstrated that this software was not 99% accurate, and therefore, errors in the medical documentation produced by the software could harm patients. The literature review also identified weaknesses of SR software that could be overcome so that the software would be accurate enough for use in EMS settings. These weaknesses included the inability to differentiate between similar phrases and the inability to filter out background noise. To find a solution, an analysis of natural language processing algorithms showed that the bag-of-words post processing algorithm has the ability to differentiate between similar phrases. This algorithm is best suited for SR applications because it is simple yet effective compared to machine learning algorithms that required a large amount of training data. The findings suggested that if these weaknesses of current SR software are solved, then the software would potentially increase the efficiency and accuracy of EMS documentation. Further studies should integrate the bag-of-words post processing method into SR software and field test its accuracy in EMS settings

Technology Target Studies: Technology Solutions to Make Patient Care Safer and More Efficient

Presents findings on technologies that could enhance care delivery, including patient records and medication processes; features and functionality nurses require, including tracking, interoperability, and hand-held capability; and best practices

A comparison of electronic health records at two major Peking University Hospitals in China to United States meaningful use objectives

BACKGROUND: In accordance with the People’s Republic of China’s (China) National Health Reform Plan of 2009, two of the nation’s leading hospitals, located in Beijing, have implemented electronic medical record (EMR) systems from different vendors. To inform future EMR adoption and policy in China, as well as informatics research in the US, this study compared the United State’s Hospital Meaningful Use (MU) Objectives (phase 1) objectives to the EMR functionality of two early hospital EMR adopters in China. METHODS: At both hospitals, the researchers observed a physician using the EMR and noted MU functionality that was seen and functionality that was not seen yet was available in the EMR. The information technology department was asked about the availability of functionality neither observed nor known to the physician. RESULTS AND CONCLUSIONS: Approximately half the MU objectives were available in each EMR. Some differences between the EMRs in the study and MU objectives were attributed to operational differences between the health systems and the cultures in the two countries

Outlook Magazine, Summer 2018

https://digitalcommons.wustl.edu/outlook/1204/thumbnail.jp

Nanoinformatics: developing new computing applications for nanomedicine

Nanoinformatics has recently emerged to address the need of computing applications at the nano level. In this regard, the authors have participated in various initiatives to identify its concepts, foundations and challenges. While nanomaterials open up the possibility for developing new devices in many industrial and scientific areas, they also offer breakthrough perspectives for the prevention, diagnosis and treatment of diseases. In this paper, we analyze the different aspects of nanoinformatics and suggest five research topics to help catalyze new research and development in the area, particularly focused on nanomedicine. We also encompass the use of informatics to further the biological and clinical applications of basic research in nanoscience and nanotechnology, and the related concept of an extended ?nanotype? to coalesce information related to nanoparticles. We suggest how nanoinformatics could accelerate developments in nanomedicine, similarly to what happened with the Human Genome and other -omics projects, on issues like exchanging modeling and simulation methods and tools, linking toxicity information to clinical and personal databases or developing new approaches for scientific ontologies, among many others

Nursing Students\u27 Self-Efficacy and Attitude: Examining the Influence ofthe Omaha System In Nurse Managed Centers

Self-efficacy, or confidence, as an outcome behavior has been identified as influencing nursing job satisfaction and retention. Clinical learning environments and teaching strategies that build and support perceived self-efficacy are critical aspects of preparing new nurses for their entry and continuing role as professional nurses in today\u27s information-intensive data-management healthcare environment. The purpose of this pre-test post-test study is to measure, using the C-scale (Grundy, 1992), nursing students\u27 self-efficacy to perform patient assessment in Nurse Managed Centers (NMC) after one semester of using the Omaha System documentation framework. Nursing students\u27 attitudes of preparation for using Standardized Nursing Languages (SNL) in the future was also examined. Bandura\u27s (1977, 19986) theoretical model of self-efficacy provided the conceptual framework. Students\u27 overall self-efficacy scores increased significantly over the 12 week study. Use of the Omaha System \u27prepared a little\u27 to \u27very prepared\u27 90% of student nurses for future use of SNL. Continued use of the Omaha System documentation framework in Nurse Managed Center clinicals as a tool for understanding SNL is recommended.