Background: Home care professionals regularly observe drug-related problems during home care provision. Problems related to the process of the medication therapy could involve discrepancies in medication prescriptions between the hospital discharge letter and the medication administration record lists (MARL) or insufficient drug delivery. The objective of this study is to determine the potential clinical consequences of medication process problems observed by home care professionals, since those consequences have not been assessed before. Methods: A retrospective descriptive study design was performed. An expert panel performed an assessment procedure on the clinical consequences of medication process problems. Such problems were reported by home care professionals during routine care (May 2016 until May 2017) using the eHOME system, which is a digital system developed to assist in the reporting and monitoring of drug-related problems. Using a three-point scale, an expert panel assessed the potential clinical consequences of those medication process problems among older home care patients (aged 65 years and over). Results: 309 medication process problems in 120 out of 451 patients were assessed for potential discomfort or clinical deterioration. The problems involved the following: medication discrepancies (new prescription not listed on the MARL [n = 69, 36.7%]; medication stopped by the prescriber but still listed on the MARL [n = 43, 22.9%]; discrepant time of intake [n = 25, 13.3%]; frequency [n = 24, 12.8%]; and dose [n = 21, 11.2%], therapeutic duplication listed on the MARL [n = 5, 2.6%]; and discrepant information on route of administration [n = 1, 0.5%]); an undelivered MARL [n = 103, 33.3%]; undelivered medication [n = 16, 5.2%]; and excessive medication delivery [n = 2, 0.7%]. Furthermore, 180 (58.2%) out of 309 medication process problems were assessed as having the potential for moderate or severe discomfort or clinical deterioration in patients. Conclusions: The majority of medication process problems may result in patient discomfort or clinical deterioration.
Genomics has multiplied the number of targets for new therapeutic interventions, but this has not yet lead to a marked increase of pharma pipeline outputs. The complexity of protein function in higher order biological systems is often underestimated. Translation from in vitro and in vivo results to the human setting frequently fails due to unforeseen toxicity and efficacy issues. Biosimulation addresses these issues by capturing the complex dynamics of interacting molecules and cells in mechanistic, predictive models. A central concept is that of the virtual patient, an encapsulation of a specific pathophysiological behaviour in a biosimulation model. The authors describe how virtual patients are being used in target identification, target validation and clinical development, and discuss challenges for the acceptance of biosimulation methods.
Purpose: The aims of this study were to investigate how a variety of research methods is commonly employed to study technology and practitioner cognition. User-interface issues with infusion pumps were selected as a case because of its relevance to patient safety. Methods: Starting from a Cognitive Systems Engineering perspective, we developed an Impact Flow Diagram showing the relationship of computer technology, cognition, practitioner behavior, and system failure in the area of medical infusion devices. We subsequently conducted a systematic literature review on user-interface issues with infusion pumps, categorized the studies in terms of methods employed, and noted the usability problems found with particular methods. Next, we assigned usability problems and related methods to the levels in the Impact Flow Diagram. Results: Most study methods used to find user interface issues with infusion pumps focused on observable behavior rather than on how artifacts shape cognition and collaboration. A concerted and theorydriven application of these methods when testing infusion pumps is lacking in the literature. Detailed analysis of one case study provided an illustration of how to apply the Impact Flow Diagram, as well as how the scope of analysis may be broadened to include organizational and regulatory factors. Conclusion: Research methods to uncover use problems with technology may be used in many ways, with many different foci. We advocate the adoption of an Impact Flow Diagram perspective rather than merely focusing on usability issues in isolation. Truly advancing patient safety requires the systematic adoption of a systems perspective viewing people and technology as an ensemble, also in the design of medical device technology.
