Utilizing RxNorm to Support Practical Computing Applications: Capturing Medication History in Live Electronic Health Records

RxNorm was utilized as the basis for direct-capture of medication history data in a live EHR system deployed in a large, multi-state outpatient behavioral healthcare provider in the United States serving over 75,000 distinct patients each year across 130 clinical locations. This tool incorporated auto-complete search functionality for medications and proper dosage identification assistance. The overarching goal was to understand if and how standardized terminologies like RxNorm can be used to support practical computing applications in live EHR systems. We describe the stages of implementation, approaches used to adapt RxNorm's data structure for the intended EHR application, and the challenges faced. We evaluate the implementation using a four-factor framework addressing flexibility, speed, data integrity, and medication coverage. RxNorm proved to be functional for the intended application, given appropriate adaptations to address high-speed input/output (I/O) requirements of a live EHR and the flexibility required for data entry in multiple potential clinical scenarios. Future research around search optimization for medication entry, user profiling, and linking RxNorm to drug classification schemes holds great potential for improving the user experience and utility of medication data in EHRs.Comment: Appendix (including SQL/DDL Code) available by author request. Keywords: RxNorm; Electronic Health Record; Medication History; Interoperability; Unified Medical Language System; Search Optimizatio

The Standard Problem

Crafting, adhering to, and maintaining standards is an ongoing challenge. This paper uses a framework based on common models to explore the standard problem: the impossibility of creating, implementing or maintain definitive common models in an open system. The problem arises from uncertainty driven by variations in operating context, standard quality, differences in implementation, and drift over time. Fitting work by conformance services repairs these gaps between a standard and what is required for interoperation, using several strategies: (a) Universal conformance (all agents access the same standard); (b) Mediated conformance (an interoperability layer supports heterogeneous agents) and (c) Localized conformance, (autonomous adaptive agents manage their own needs). Conformance methods include incremental design, modular design, adaptors, and creating interactive and adaptive agents. Machine learning should have a major role in adaptive fitting. Choosing a conformance service depends on the stability and homogeneity of shared tasks, and whether common models are shared ahead of time or are adjusted at task time. This analysis thus decouples interoperability and standardization. While standards facilitate interoperability, interoperability is achievable without standardization.Comment: Keywords: information standard, interoperability, machine learning, technology evaluation 25 Pages Main text word Count: 5108 Abstract word count: 206 Tables: 1 Figures: 7 Boxes: 2 Submitted to JAMI

Improve Intra-Operative Nurse-to-Nurse Communication Using a Safety Checklist

Poor and inadequate handoff, or transfer of care of the surgical patient care from the primary to the relief operating room registered nurse circulators, can result in irreversible patient harm, or sentinel events, such as retained foreign items. In this study, Rogers\u27 diffusion of innovation theory was the framework for implementing the handoff safety checklist. Also, Donabedian\u27s structure process and outcome was the model to investigate the feasibility, acceptability, and improvement in the quality of patient handoff communication and improvement of nurse satisfaction over time. Nineteen-statement surveys, conducted at multiple timeframes, were completed by volunteer operating room nurse participants. In comparison, outcomes of the pre-intervention and post-intervention surveys illustrated significance in the quality of nurse communication and satisfaction of the handoff safety checklist. The value of standardized handoff safety checklists is evident in the study. However, further research of handoff safety checklists in the intraoperative arena is warranted

Optimising medication data collection in a large-scale clinical trial

© 2019 Lockery et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Objective: Pharmaceuticals play an important role in clinical care. However, in community-based research, medication data are commonly collected as unstructured free-text, which is prohibitively expensive to code for large-scale studies. The ASPirin in Reducing Events in the Elderly (ASPREE) study developed a two-pronged framework to collect structured medication data for 19,114 individuals. ASPREE provides an opportunity to determine whether medication data can be cost-effectively collected and coded, en masse from the community using this framework. Methods: The ASPREE framework of type-to-search box with automated coding and linked free text entry was compared to traditional method of free-text only collection and post hoc coding. Reported medications were classified according to their method of collection and analysed by Anatomical Therapeutic Chemical (ATC) group. Relative cost of collecting medications was determined by calculating the time required for database set up and medication coding. Results Overall, 122,910 participant structured medication reports were entered using the type-tosearch box and 5,983 were entered as free-text. Free-text data contributed 211 unique medications not present in the type-to-search box. Spelling errors and unnecessary provision of additional information were among the top reasons why medications were reported as freetext. The cost per medication using the ASPREE method was approximately USD $0.03 compared with USD$0.20 per medication for the traditional method. Conclusion Implementation of this two-pronged framework is a cost-effective alternative to free-text only data collection in community-based research. Higher initial set-up costs of this combined method are justified by long term cost effectiveness and the scientific potential for analysis and discovery gained through collection of detailed, structured medication data

Approaching Economic Issues through Epidemiology–An Introduction to Business Epidemiology

In the tradition of transferring models and concepts from one science to another, our research explores the possibility of importing some concepts, definitions and approaches from human epidemiology to economic research, based on the extensive usage of medical terms and concepts in economy. The article explores some basic epidemiology concepts and their possible relevance to economic research, with the final goal to provide a new viewpoint over the economic phenomena, usable in economic crisis. The article introduces the concept of “business epidemiology” as a possible scientific approach to the economic crisis.epidemiology; business disease; company health; research methodology; financial contagion

A LITERATURE REVIEW ON THE CURRENT STATE OF SECURITY AND PRIVACY OF MEDICAL DEVICES AND SENSORS WITH BLUETOOTH LOW ENERGY

Technology use in healthcare is an integral part of diagnosis and treatment. The use of technology in medical devices and sensors is growing. These devices include implantable medical devices, and consumer health and fitness tracking devices and applications. Bluetooth Low Energy (BLE) is the most commonly used communication method in medical devices and sensors. Security and privacy are important, especially in healthcare technologies that can impact morbidity. There is an increasing need to evaluate the security and privacy of healthcare technology, especially with devices and sensors that use Bluetooth Low Energy due to the increasing prevalence and use of medical devices and sensors. Therefore, more robust security analysis is needed to evaluate security and privacy aspects of medical devices and sensors that use Bluetooth Low Energy

A LITERATURE REVIEW ON THE CURRENT STATE OF SECURITY AND PRIVACY OF MEDICAL DEVICES AND SENSORS WITH BLUETOOTH LOW ENERGY

Technology use in healthcare is an integral part of diagnosis and treatment. The use of technology in medical devices and sensors is growing. These devices include implantable medical devices, and consumer health and fitness tracking devices and applications. Bluetooth Low Energy (BLE) is the most commonly used communication method in medical devices and sensors. Security and privacy are important, especially in healthcare technologies that can impact morbidity. There is an increasing need to evaluate the security and privacy of healthcare technology, especially with devices and sensors that use Bluetooth Low Energy due to the increasing prevalence and use of medical devices and sensors. Therefore, more robust security analysis is needed to evaluate security and privacy aspects of medical devices and sensors that use Bluetooth Low Energy

The Emerging Internet of Things Marketplace From an Industrial Perspective: A Survey

The Internet of Things (IoT) is a dynamic global information network consisting of internet-connected objects, such as Radio-frequency identification (RFIDs), sensors, actuators, as well as other instruments and smart appliances that are becoming an integral component of the future internet. Over the last decade, we have seen a large number of the IoT solutions developed by start-ups, small and medium enterprises, large corporations, academic research institutes (such as universities), and private and public research organisations making their way into the market. In this paper, we survey over one hundred IoT smart solutions in the marketplace and examine them closely in order to identify the technologies used, functionalities, and applications. More importantly, we identify the trends, opportunities and open challenges in the industry-based the IoT solutions. Based on the application domain, we classify and discuss these solutions under five different categories: smart wearable, smart home, smart, city, smart environment, and smart enterprise. This survey is intended to serve as a guideline and conceptual framework for future research in the IoT and to motivate and inspire further developments. It also provides a systematic exploration of existing research and suggests a number of potentially significant research directions.Comment: IEEE Transactions on Emerging Topics in Computing 201