27 resultados para medication reconciliation

em CentAUR: Central Archive University of Reading - UK


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Previous research has shown that people's evaluations of explanations about medication and their intention to comply with the prescription are detrimentally affected by the inclusion of information about adverse side effects of the medication. The present study (Experiment 1) examined which particular aspects of information about side effects (their number, likelihood of occurrence, or severity) are likely to have the greatest effect on people's satisfaction, perception of risk, and intention to comply, as well as how the information about side effects interacts with information about the severity of the illness for which the medication was prescribed. Across all measures, it was found that manipulations of side effect severity had the greatest impact on people's judgements, followed by manipulations of side effect likelihood and then number. Experiments 2 and 3 examined how the severity of the diagnosed illness and information about negative side effects interact with two other factors suggested by Social Cognition models of health behaviour to affect people's intention to comply: namely, perceived benefit of taking the prescribed drug, and the perceived level of control over preventing or alleviating the side effects. It was found that providing people with a statement about the positive benefit of taking the medication had relatively little effect on judgements, whereas informing them about how to reduce the chances of experiencing the side effects had an overall beneficial effect on ratings.

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Objectives - To assess the general public's interpretation of the verbal descriptors for side effect frequency recommended for use in medicine information leaflets by a European Union (EU) guideline, and to examine the extent to which differences in interpretation affect people's perception of risk and their judgments of intention to comply with the prescribed treatment. Method - Two studies used a controlled empirical methodology in which people were presented with a hypothetical, but realistic, scenario about visiting their general practitioner and being prescribed medication. They were given an explanation that focused on the side effects of the medicine, together with information about the probability of occurrence using either numerical percentages or the corresponding EU verbal descriptors. Interpretation of the descriptors was assessed. In study 2, participants were also required to make various judgments, including risk to health and intention to comply. Key findings - In both studies, use of the EU recommended descriptors led to significant overestimations of the likelihood of particular side effects occurring. Study 2 further showed that the "overestimation" resulted in significantly increased ratings of perceived severity of side effects and risk to health, as well as significantly reduced ratings of intention to comply, compared with those for people who received the probability information in numerical form. Conclusion - While it is recognised that the current findings require replication in a clinical setting, the European and national authorities should suspend the use of the EU recommended terms until further research is available to allow the use of an evidence-based approach.

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Objective: To describe the use of a multifaceted strategy for recruiting general practitioners (GPs) and community pharmacists to talk about medication errors which have resulted in preventable drug-related admissions to hospital. This is a potentially sensitive subject with medicolegal implications. Setting: Four primary care trusts and one teaching hospital in the UK. Method: Letters were mailed to community pharmacists and general practitioners asking for provisional consent to be interviewed and permission to contact them again should a patient be admitted to hospital as a result of a medication error. In addition, GPs were asked for permission to approach their patients should they be admitted to hospital. A multifaceted approach to recruitment was used including gaining support for the study from professional defence agencies and local champions. Key findings: Eighty-five percent (310/385) of GPs and 62% (93/149) of community pharmacists responded to the letters. Eighty-five percent (266/310) of GPs who responded and 81% (75/93) of community pharmacists who responded gave provisional consent to participate in interviews. All GPs (14 out of 14) and community pharmacists (10 out of 10) who were subsequently asked to participate, when patients were admitted to hospital, agreed to be interviewed. Conclusion: The multifaceted approach to recruitment was associated with an impressive response when asking healthcare professionals to be interviewed about medication errors which have resulted in preventable drug-related morbidity.

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Patients want and need comprehensive and accurate information about their medicines so that they can participate in decisions about their healthcare: In particular, they require information about the likely risks and benefits that are associated with the different treatment options. However, to provide this information in a form that people can readily understand and use is a considerable challenge to healthcare professionals. One recent attempt to standardise the Language of risk has been to produce sets of verbal descriptors that correspond to specific probability ranges, such as those outlined in the European Commission (EC) Pharmaceutical Committee guidelines in 1998 for describing the incidence of adverse effects. This paper provides an overview of a number of studies involving members of the general public, patients, and hospital doctors, that evaluated the utility of the EC guideline descriptors (very common, common, uncommon, rare, very rare). In all studies it was found that people significantly over-estimated the likelihood of adverse effects occurring, given specific verbal descriptors. This in turn resulted in significantly higher ratings of their perceived risks to health and significantly lower ratings of their likelihood of taking the medicine. Such problems of interpretation are not restricted to the EC guideline descriptors. Similar levels of misinterpretation have also been demonstrated with two other recently advocated risk scales (Caiman's verbal descriptor scale and Barclay, Costigan and Davies' lottery scale). In conclusion, the challenge for risk communicators and for future research will be to produce a language of risk that is sufficiently flexible to take into account different perspectives, as well as changing circumstances and contexts of illness and its treatments. In the meantime, we urge the EC and other legislative bodies to stop recommending the use of specific verbal labels or phrases until there is a stronger evidence base to support their use.

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Two experiments, using a controlled empirical methodology, investigated the effects of presenting information about medicines using a more personalised style of expression. In both studies, members of the general public were given a hypothetical scenario about visiting the doctor, being diagnosed with a particular illness, and being prescribed a medication. They were also given a written explanation about the medicine and were asked to provide ratings on a number of measures, including satisfaction, perceived risk to health, and intention to comply. In Experiment 1 the explanation focused only on possible side effects of the medicine, whereas in Experiment 2 a fuller explanation was provided, which included information about the illness, prescribed drug, its dosage and contraindications as well as its side effects. In both studies, use of a more personalised style resulted in significantly higher ratings of satisfaction and significantly lower ratings of likelihood of side effects occurring and of perceived risk to health. In Experiment 2 it also led to significantly improved recall for the written information.

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Two experiments compared people's interpretation of verbal and numerical descriptions of the risk of medication side effects occurring. The verbal descriptors were selected from those recommended for use by the European Union (very common, common, uncommon, rare, very rare). Both experiments used a controlled empirical methodology, in which nearly 500 members of the general population were presented with a fictitious (but realistic) scenario about visiting the doctor and being prescribed medication, together with information about the medicine's side effects and their probability of occurrence. Experiment 1 found that, in all three age groups tested (18 - 40, 41 - 60 and over 60), participants given a verbal descriptor (very common) estimated side effect risk to be considerably higher than those given a comparable numerical description. Furthermore, the differences in interpretation were reflected in their judgements of side effect severity, risk to health, and intention to comply. Experiment 2 confirmed these findings using two different verbal descriptors (common and rare) and in scenarios which described either relatively severe or relatively mild side effects. Strikingly, only 7 out of 180 participants in this study gave a probability estimate which fell within the EU assigned numerical range. Thus, large scale use of the descriptors could have serious negative consequences for individual and public health. We therefore recommend that the EU and National authorities suspend their recommendations regarding these descriptors until a more substantial evidence base is available to support their appropriate use.

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This study investigates whether, and how, people's perception of risk and intended health behaviours are affected by whether a medicine is prescribed for themselves or for a young child. The question is relevant to the issue of whether it is beneficial to produce medicines information that is tailored to particular subgroups of the population, such as parents of young children. In the experiment, participants read scenarios which referred either to themselves or their (imagined) 1-year-old child, and were required to make a number of risk judgements. The results showed that both parents and non-parents were less satisfied, perceived side effects to be more severe and more likely to occur, risk to health to be higher, and said that they would be less likely to take (or give) the medicine when the recipient was the child. On the basis of the findings, it is suggested that it may well be beneficial to tailor materials to broader classes of patient type.

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Measured process data normally contain inaccuracies because the measurements are obtained using imperfect instruments. As well as random errors one can expect systematic bias caused by miscalibrated instruments or outliers caused by process peaks such as sudden power fluctuations. Data reconciliation is the adjustment of a set of process data based on a model of the process so that the derived estimates conform to natural laws. In this paper, techniques for the detection and identification of both systematic bias and outliers in dynamic process data are presented. A novel technique for the detection and identification of systematic bias is formulated and presented. The problem of detection, identification and elimination of outliers is also treated using a modified version of a previously available clustering technique. These techniques are also combined to provide a global dynamic data reconciliation (DDR) strategy. The algorithms presented are tested in isolation and in combination using dynamic simulations of two continuous stirred tank reactors (CSTR).

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The use of data reconciliation techniques can considerably reduce the inaccuracy of process data due to measurement errors. This in turn results in improved control system performance and process knowledge. Dynamic data reconciliation techniques are applied to a model-based predictive control scheme. It is shown through simulations on a chemical reactor system that the overall performance of the model-based predictive controller is enhanced considerably when data reconciliation is applied. The dynamic data reconciliation techniques used include a combined strategy for the simultaneous identification of outliers and systematic bias.

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This paper describes a method for dynamic data reconciliation of nonlinear systems that are simulated using the sequential modular approach, and where individual modules are represented by a class of differential algebraic equations. The estimation technique consists of a bank of extended Kalman filters that are integrated with the modules. The paper reports a study based on experimental data obtained from a pilot scale mixing process.

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In this paper the implementation of dynamic data reconciliation techniques for sequential modular models is described. The paper is organised as follows. First, an introduction to dynamic data reconciliation is given. Then, the online use of rigorous process models is introduced. The sequential modular approach to dynamic simulation is briefly discussed followed by a short review of the extended Kalman filter. The second section describes how the modules are implemented. A simulation case study and its results are also presented.

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Background: Medication errors are common in primary care and are associated with considerable risk of patient harm. We tested whether a pharmacist-led, information technology-based intervention was more effective than simple feedback in reducing the number of patients at risk of measures related to hazardous prescribing and inadequate blood-test monitoring of medicines 6 months after the intervention. Methods: In this pragmatic, cluster randomised trial general practices in the UK were stratified by research site and list size, and randomly assigned by a web-based randomisation service in block sizes of two or four to one of two groups. The practices were allocated to either computer-generated simple feedback for at-risk patients (control) or a pharmacist-led information technology intervention (PINCER), composed of feedback, educational outreach, and dedicated support. The allocation was masked to general practices, patients, pharmacists, researchers, and statisticians. Primary outcomes were the proportions of patients at 6 months after the intervention who had had any of three clinically important errors: non-selective non-steroidal anti-inflammatory drugs (NSAIDs) prescribed to those with a history of peptic ulcer without co-prescription of a proton-pump inhibitor; β blockers prescribed to those with a history of asthma; long-term prescription of angiotensin converting enzyme (ACE) inhibitor or loop diuretics to those 75 years or older without assessment of urea and electrolytes in the preceding 15 months. The cost per error avoided was estimated by incremental cost-eff ectiveness analysis. This study is registered with Controlled-Trials.com, number ISRCTN21785299. Findings: 72 general practices with a combined list size of 480 942 patients were randomised. At 6 months’ follow-up, patients in the PINCER group were significantly less likely to have been prescribed a non-selective NSAID if they had a history of peptic ulcer without gastroprotection (OR 0∙58, 95% CI 0∙38–0∙89); a β blocker if they had asthma (0∙73, 0∙58–0∙91); or an ACE inhibitor or loop diuretic without appropriate monitoring (0∙51, 0∙34–0∙78). PINCER has a 95% probability of being cost eff ective if the decision-maker’s ceiling willingness to pay reaches £75 per error avoided at 6 months. Interpretation: The PINCER intervention is an effective method for reducing a range of medication errors in general practices with computerised clinical records. Funding: Patient Safety Research Portfolio, Department of Health, England.