234,197 research outputs found

    Antidote application: an educational system for treatment of common toxin overdose

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    Poisonings account for almost 1% of emergency room visits each year. Time is a critical factor in dealing with a toxicologic emergency. Delay in dispensing the first antidote dose can lead to life-threatening sequelae. Current toxicological resources that support treatment decisions are broad in scope, time-consuming to read, or at times unavailable. Our review of current toxicological resources revealed a gap in their ability to provide expedient calculations and recommendations about appropriate course of treatment. To bridge the gap, we developed the Antidote Application (AA), a computational system that automatically provides patient-specific antidote treatment recommendations and individualized dose calculations. We implemented 27 algorithms that describe FDA (the US Food and Drug Administration) approved use and evidence-based practices found in primary literature for the treatment of common toxin exposure. The AA covers 29 antidotes recommended by Poison Control and toxicology experts, 19 poison classes and 31 poisons, which represent over 200 toxic entities. To the best of our knowledge, the AA is the first educational decision support system in toxicology that provides patient-specific treatment recommendations and drug dose calculations. The AA is publicly available at http://projects.met- hilab.org/antidote/

    Development of Drug Therapy Management System by the participation of Pharmacist in Multidisciplinary Team: A Participatory Action Research in the Non-communicable Disease Clinic at Damnoensaduak Hospital

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    āļ§āļąāļ•āļ–āļļāļ›āļĢāļ°āļŠāļ‡āļ„āđŒ: āđ€āļžāļ·āđˆāļ­āļžāļąāļ’āļ™āļēāļĢāļ°āļšāļšāļāļēāļĢāļ”āļđāđāļĨāļ”āđ‰āļēāļ™āļĒāļēāđ‚āļ”āļĒāđ€āļ āļŠāļąāļŠāļāļĢāđƒāļ™āļ„āļĨāļīāļ™āļīāļāđ‚āļĢāļ„āđ„āļĄāđˆāļ•āļīāļ”āļ•āđˆāļ­āđ€āļĢāļ·āđ‰āļ­āļĢāļąāļ‡āļ—āļĩāđˆāļĄāļĩāļ„āļ§āļēāļĄāđ€āļŦāļĄāļēāļ°āļŠāļĄāļāļąāļšāļšāļĢāļīāļšāļ—āļ‚āļ­āļ‡āđ‚āļĢāļ‡āļžāļĒāļēāļšāļēāļĨāļ”āļģāđ€āļ™āļīāļ™āļŠāļ°āļ”āļ§āļ āļ§āļīāļ˜āļĩāļāļēāļĢāļĻāļķāļāļĐāļē: āļāļēāļĢāļ§āļīāļˆāļąāļĒāđ€āļŠāļīāļ‡āļ›āļāļīāļšāļąāļ•āļīāļāļēāļĢāđāļšāļšāļĄāļĩāļŠāđˆāļ§āļ™āļĢāđˆāļ§āļĄāđāļĨāļ°āļāļĢāļ°āļšāļ§āļ™āļāļēāļĢāļžāļąāļ’āļ™āļēāđāļšāļšāļ•āđˆāļ­āđ€āļ™āļ·āđˆāļ­āļ‡ āđ€āļāđ‡āļšāļ‚āđ‰āļ­āļĄāļđāļĨāļĢāļ°āļŦāļ§āđˆāļēāļ‡āļžāļĪāļĻāļˆāļīāļāļēāļĒāļ™ 2559 āļ–āļķāļ‡āļāļąāļ™āļĒāļēāļĒāļ™ 2560 āļˆāļēāļāļšāļļāļ„āļĨāļēāļāļĢāļ—āļēāļ‡āļāļēāļĢāđāļžāļ—āļĒāđŒ 14 āļ„āļ™ āļĢāđˆāļ§āļĄāļāļąāļ™āļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāļ›āļąāļāļŦāļē āļ­āļ­āļāđāļšāļšāđāļĨāļ°āļ—āļ”āļŠāļ­āļšāļĢāļ°āļšāļš āđāļĨāđ‰āļ§āļ™āļģāļĢāļ°āļšāļšāļ—āļĩāđˆāļžāļąāļ’āļ™āļēāļ‚āļķāđ‰āļ™āđ„āļ›āļ”āļđāđāļĨāļœāļđāđ‰āļ›āđˆāļ§āļĒāđ‚āļĢāļ„āđ„āļĄāđˆāļ•āļīāļ”āļ•āđˆāļ­āđ€āļĢāļ·āđ‰āļ­āļĢāļąāļ‡ āļ•āļēāļĄāđāļ™āļ§āļ„āļīāļ”āļ­āļ‡āļ„āđŒāļ›āļĢāļ°āļāļ­āļš CCM āđāļĨāļ°āļāļēāļĢāļžāļąāļ’āļ™āļēāđāļšāļšāļ§āļ‡āļĨāđ‰āļ­ PDCA āļœāļĨāļāļēāļĢāļĻāļķāļāļĐāļē: āļĢāļ°āļšāļšāļāļēāļĢāļ”āļđāđāļĨāļ”āđ‰āļēāļ™āļĒāļēāđ‚āļ”āļĒāđ€āļ āļŠāļąāļŠāļāļĢāļ—āļĩāđˆāļžāļąāļ’āļ™āļēāļ‚āļķāđ‰āļ™āļ›āļĢāļ°āļāļ­āļšāļ”āđ‰āļ§āļĒāļāļēāļĢāļ—āļģāļ‡āļēāļ™āļ‚āļ­āļ‡āđ€āļ āļŠāļąāļŠāļāļĢ 3 āļ‚āļąāđ‰āļ™āļ•āļ­āļ™ āļ„āļ·āļ­ 1. āļāļēāļĢāļ„āļąāļ”āļāļĢāļ­āļ‡āļ›āļąāļāļŦāļēāļ”āđ‰āļēāļ™āļĒāļēāđ‚āļ”āļĒāđƒāļŠāđ‰āļĢāļ°āļšāļšāđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāļŠāļēāļĢāļŠāļ™āđ€āļ—āļĻāđāļĨāļ°āļˆāļēāļāļāļēāļĢāļ‹āļąāļāļ›āļĢāļ°āļ§āļąāļ•āļīāļ‚āļ­āļ‡āđ€āļ āļŠāļąāļŠāļāļĢ 2. āļāļēāļĢāļˆāļąāļ”āļāļēāļĢāļ”āđ‰āļēāļ™āļĒāļē āđāļĨāļ° 3. āļāļēāļĢāļŠāđˆāļ‡āļ•āđˆāļ­āļ‚āđ‰āļ­āļĄāļđāļĨāđāļāđˆāļšāļļāļ„āļĨāļēāļāļĢāļ—āļēāļ‡āļāļēāļĢāđāļžāļ—āļĒāđŒāđāļĨāļ°āļœāļđāđ‰āļ›āđˆāļ§āļĒ āđƒāļ™āļāļēāļĢāļžāļąāļ’āļ™āļēāļĢāļ°āļšāļšāļ­āļēāļĻāļąāļĒāļ—āļļāļāļ­āļ‡āļ„āđŒāļ›āļĢāļ°āļāļ­āļšāļ‚āļ­āļ‡āļĢāļđāļ›āđāļšāļšāļāļēāļĢāļ”āļđāđāļĨāđ‚āļĢāļ„āđ€āļĢāļ·āđ‰āļ­āļĢāļąāļ‡ āđ‚āļ”āļĒāļĄāļĩāđ€āļ›āđ‰āļēāļŦāļĄāļēāļĒāđāļĨāļ°āļ—āļīāļĻāļ—āļēāļ‡āđ€āļ›āđ‡āļ™āļ­āļ‡āļ„āđŒāļ›āļĢāļ°āļāļ­āļšāđ€āļĢāļīāđˆāļĄāļ•āđ‰āļ™āđƒāļ™āļāļēāļĢāļžāļąāļ’āļ™āļē āļ‹āļķāđˆāļ‡āļĢāļ°āļŦāļ§āđˆāļēāļ‡āļāļēāļĢāļ”āļģāđ€āļ™āļīāļ™āļ‡āļēāļ™āļ•āđ‰āļ­āļ‡āđƒāļŠāđ‰āļ—āļąāđ‰āļ‡āļĢāļ°āļšāļšāļŠāļēāļĢāļŠāļ™āđ€āļ—āļĻ āļāļēāļĢāļ›āļĢāļąāļšāļĢāļ°āļšāļšāđāļĨāļ°āļāļĢāļ°āļšāļ§āļ™āļāļēāļĢāļšāļĢāļīāļāļēāļĢ āļĢāļ°āļšāļšāļāļēāļĢāļŠāļ™āļąāļšāļŠāļ™āļļāļ™āļāļēāļĢāļˆāļąāļ”āļāļēāļĢāļ•āļ™āđ€āļ­āļ‡ āđāļĨāļ°āļĢāļ°āļšāļšāļāļēāļĢāļŠāļ™āļąāļšāļŠāļ™āļļāļ™āļāļēāļĢāļ•āļąāļ”āļŠāļīāļ™āđƒāļˆ āļžāļšāļ§āđˆāļēāļĢāļ°āļšāļšāļŠāļēāļĢāļŠāļ™āđ€āļ—āļĻāļĄāļĩāļ„āļ§āļēāļĄāļŠāļģāļ„āļąāļāļ•āđˆāļ­āļāļēāļĢāļžāļąāļ’āļ™āļēāļĢāļ°āļšāļšāļāļēāļĢāļ”āļđāđāļĨāļ”āđ‰āļēāļ™āļĒāļēāļĄāļēāļāļ—āļĩāđˆāļŠāļļāļ” āļĢāļ°āļšāļšāļ—āļĩāđˆāļžāļąāļ’āļ™āļēāļ‚āļķāđ‰āļ™āļŠāļēāļĄāļēāļĢāļ–āļ„āļąāļ”āļāļĢāļ­āļ‡āļ›āļąāļāļŦāļēāļ—āļĩāđˆāļ„āļēāļ”āļ§āđˆāļēāđ€āļāļĩāđˆāļĒāļ§āļ‚āđ‰āļ­āļ‡āļāļąāļšāļĒāļēāļāđˆāļ­āļ™āļ§āļąāļ™āļ™āļąāļ”āđ„āļ”āđ‰āļĢāđ‰āļ­āļĒāļĨāļ° 17.8 āđāļĨāļ°āđƒāļ™āļ§āļąāļ™āļ™āļąāļ”āļ„āļąāļ”āļāļĢāļ­āļ‡āđ„āļ”āđ‰āļĢāđ‰āļ­āļĒāļĨāļ° 42.7 āļ›āļąāļāļŦāļēāļŠāđˆāļ§āļ™āđƒāļŦāļāđˆāļ—āļĩāđˆāļžāļš āļ„āļ·āļ­ āļœāļđāđ‰āļ›āđˆāļ§āļĒāļšāļĢāļīāļŦāļēāļĢāļĒāļēāļœāļīāļ” (āļĢāđ‰āļ­āļĒāļĨāļ° 67.6) āļžāļšāļ§āđˆāļēāđāļžāļ—āļĒāđŒāđƒāļŦāđ‰āļāļēāļĢāļĢāļąāļāļĐāļēāļ—āļĩāđˆāļŠāļ­āļ”āļ„āļĨāđ‰āļ­āļ‡āļāļąāļšāļ‚āđ‰āļ­āļĄāļđāļĨāļ—āļĩāđˆāļŠāđˆāļ‡āļ•āđˆāļ­āđƒāļŦāđ‰āļĢāđ‰āļ­āļĒāļĨāļ° 63.6 āļŠāļĢāļļāļ›: āļšāļ—āļšāļēāļ—āđ€āļ āļŠāļąāļŠāļāļĢāđƒāļ™āļ—āļĩāļĄāļŠāļŦāļŠāļēāļ‚āļēāļ§āļīāļŠāļēāļŠāļĩāļžāđ‚āļ”āļĒāļāļēāļĢāļ—āļģāļ‡āļēāļ™āđ€āļŠāļīāļ‡āļĢāļļāļāļ­āļēāļĻāļąāļĒāļĢāļ°āļšāļšāđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāļŠāļēāļĢāļŠāļ™āđ€āļ—āļĻāđāļĨāļ°āļāļēāļĢāļ‹āļąāļāļ›āļĢāļ°āļ§āļąāļ•āļīāđ‚āļ”āļĒāđ€āļ āļŠāļąāļŠāļāļĢāļĢāđˆāļ§āļĄāļāļąāļ™āļŠāļēāļĄāļēāļĢāļ–āļŠāļ™āļąāļšāļŠāļ™āļļāļ™āđƒāļŦāđ‰āļāļēāļĢāļˆāļąāļ”āļāļēāļĢāļ”āđ‰āļēāļ™āļĒāļēāđƒāļ™āļœāļđāđ‰āļ›āđˆāļ§āļĒāđ‚āļĢāļ„āļ•āļīāļ”āļ•āđˆāļ­āđ€āļĢāļ·āđ‰āļ­āļĢāļąāļ‡āđ„āļ”āđ‰āđ€āļŦāļĄāļēāļ°āļŠāļĄāļĒāļīāđˆāļ‡āļ‚āļķāđ‰āļ™āļ„āļģāļŠāļģāļ„āļąāļ : āļĢāļ°āļšāļšāļāļēāļĢāļ”āļđāđāļĨāļ”āđ‰āļēāļ™āļĒāļē, āļ§āļīāļˆāļąāļĒāđāļšāļšāļĄāļĩāļŠāđˆāļ§āļ™āļĢāđˆāļ§āļĄ, āđ€āļ āļŠāļąāļŠāļāļĢ, āļ—āļĩāļĄāļŠāļŦāļŠāļēāļ‚āļēāļ§āļīāļŠāļēāļŠāļĩāļž, āđ‚āļĢāļ„āđ„āļĄāđˆāļ•āļīāļ”āļ•āđˆāļ­āđ€āļĢāļ·āđ‰āļ­āļĢāļąāļ‡, āļ§āļ‡āļˆāļĢāļžāļĩāļ”āļĩāļ‹āļĩāđ€āļ­, āđ‚āļĄāđ€āļ”āļĨāļāļēāļĢāļ”āļđāđāļĨāđ‚āļĢāļ„āđ€āļĢāļ·āđ‰āļ­āļĢāļąāļ‡Objective: To develop a drug therapy management system with pharmacist participating in multidisciplinary team suitable for the non-communicable disease (NCD) clinic of Damnoensaduak Hospital. Method: This participatory action research (PAR) was performed from November 2016 to September 2017. Fourteen healthcare providers were selected to be in the PAR team to coordinate analysis, design based on the components of Chronic Care Model (CCM) concept, and implementation of the developed system using the Plan-Do-Check-Act (PDCA) cycle. Results: The developed drug therapy management system consisted of three roles of pharmacists, namely (1) screening drug related problems (DRP) using information technology and history taking, (2) drug therapy management, and (3) communication of the patient’s information to the team and patient. All components of CCM could be implemented. Resource and policy were the initial components for development. During the ongoing process, other components namely clinical information systems, delivery system design, self-care support and decision-making support were applied with the information system component as the most important one. The developed system could screen 17.8% and 42.7% DRPs before and on the appointment day, respectively. Most DRPs were errors in patient’s self-administration (67.6%). The physician responded to the DRP in agreement with the information communicated by pharmacist by 63.6%. Conclusion: The proactive role of pharmacist using the information technology and history taking in the multidisciplinary team could offer an effective drug therapy in NCD patients. Keywords: drug therapy management system,participatory action research,pharmacist, multidisciplinary team, non-communicable disease, PDCA cycle, chronic care mode

    Step towards multiplatform framework for supporting pediatric and neonatology care unit decision process

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    Children are an especially vulnerable population, particularly in respect to drug administration. It is estimated that neonatal and pediatric patients are at least three times more vulnerable to damage due to adverse events and medication errors than adults are. With the development of this framework, it is intended the provision of a Clinical Decision Support System based on a prototype already tested in a real environment. The framework will include features such as preparation of Total Parenteral Nutrition prescriptions, table pediatric and neonatal emergency drugs, medical scales of morbidity and mortality, anthropometry percentiles (weight, length/height, head circumference and BMI), utilities for supporting medical decision on the treatment of neonatal jaundice and anemia and support for technical procedures and other calculators and widespread use tools. The solution in development means an extension of INTCare project. The main goal is to provide an approach to get the functionality at all times of clinical practice and outside the hospital environment for dissemination, education and simulation of hypothetical situations. The aim is also to develop an area for the study and analysis of information and extraction of knowledge from the data collected by the use of the system. This paper presents the architecture, their requirements and functionalities and a SWOT analysis of the solution proposed.CT - FundaçÃĢo para a CiÊncia e Tecnologia within the Project Scope UID/CEC/00319/2013 and PTDC/EEI - SII/1302/2012 (INTCare II

    Fusing drug enforcement: a study of the El Paso Intelligence Center

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    This article examines the evolution of the El Paso Intelligence Center (EPIC), a key intelligence component of the Drug Enforcement Administration, to shed light on fusion efforts in drug enforcement. Since 1974, EPIC has strived to fuse the resources and capabilities of multiple government agencies to counter drug trafficking and related threats along the Southwest US border. While undergoing a steady growth, the Center has confronted a host of challenges that illuminate the uses and limits of multi-agency endeavors in drug enforcement. An evaluative study of the Center shows that it is well aligned with the federal government priorities in the realm of drug enforcement; however the extent to which the Center’s activities support the government’s efforts in this domain is not so clear. The Center needs to improve the way it reviews its own performance to better adapt and serve its customers

    Evaluation Research and Institutional Pressures: Challenges in Public-Nonprofit Contracting

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    This article examines the connection between program evaluation research and decision-making by public managers. Drawing on neo-institutional theory, a framework is presented for diagnosing the pressures and conditions that lead alternatively toward or away the rational use of evaluation research. Three cases of public-nonprofit contracting for the delivery of major programs are presented to clarify the way coercive, mimetic, and normative pressures interfere with a sound connection being made between research and implementation. The article concludes by considering how public managers can respond to the isomorphic pressures in their environment that make it hard to act on data relating to program performance.This publication is Hauser Center Working Paper No. 23. The Hauser Center Working Paper Series was launched during the summer of 2000. The Series enables the Hauser Center to share with a broad audience important works-in-progress written by Hauser Center scholars and researchers

    Medication administration errors for older people in long-term residential care

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    Background Older people in long-term residential care are at increased risk of medication errors. The purpose of this study was to evaluate a computerised barcode medication management system designed to improve drug administrations in residential and nursing homes, including comparison of error rates and staff awareness in both settings. Methods All medication administrations were recorded prospectively for 345 older residents in thirteen care homes during a 3-month period using the computerised system. Staff were surveyed to identify their awareness of administration errors prior to system introduction. Overall, 188,249 attempts to administer medication were analysed to determine the prevalence of potential medication administration errors (MAEs). Error classifications included attempts to administer medication at the wrong time, to the wrong person or discontinued medication. Analysis compared data at residential and nursing home level and care and nursing staff groups. Results Typically each resident was exposed to 206 medication administration episodes every month and received nine different drugs. Administration episodes were more numerous (p < 0.01) in nursing homes (226.7 per resident) than in residential homes (198.7). Prior to technology introduction, only 12% of staff administering drugs reported they were aware of administration errors being averted in their care home. Following technology introduction, 2,289 potential MAEs were recorded over three months. The most common MAE was attempting to give medication at the wrong time. On average each resident was exposed to 6.6 potential errors. In total, 90% of residents were exposed to at least one MAE with over half (52%) exposed to serious errors such as attempts to give medication to the wrong resident. MAEs rates were significantly lower (p < 0.01) in residential homes than nursing homes. The level of non-compliance with system alerts was low in both settings (0.075% of administrations) demonstrating virtually complete error avoidance. Conclusion Potentially inappropriate administration of medication is a serious problem in long-term residential care. A computerised barcode system can accurately and automatically detect inappropriate attempts to administer drugs to residents. This tool can reliably be used by care staff as well as nurses to improve quality of care and patient safety
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