Zoekresultaten

Transforming Clinical Practice Guideline Usage Through the Use of a Clinical Decision Support System: An explorative study at the University Medical Centre Utrecht

Factors influencing in-hospital prescribing errors

Aim: In-hospital prescribing errors (PEs) may result in patient harm, prolonged hospitalization and hospital (re)admission. These events are associated with pressure on healthcare services and significant healthcare costs. To develop targeted interventions to prevent or reduce in-hospital PEs, identification and understanding of facilitating and protective factors influencing in-hospital PEs in current daily practice is necessary, adopting a Safety-II perspective. The aim of this systematic review was to create an overview of all factors reported in the literature, both protective and facilitating, as influencing in-hospital PEs. Methods: PubMed, EMBASE.com and the Cochrane Library (via Wiley) were searched, according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement, for studies that identified factors influencing in-hospital PEs. Both qualitative and quantitative study designs were included. Results: Overall, 19 articles (6 qualitative and 13 quantitative studies) were included and 40 unique factors influencing in-hospital PEs were identified. These factors were categorized into five domains according to the Eindhoven classification (‘organization-related’, ‘prescriber-related’, ‘prescription-related’, ‘technologyrelated’ and ‘unclassified’) and visualized in an Ishikawa (Fishbone) diagram. Most of the identified factors (87.5%; n = 40) facilitated in-hospital PEs. The most frequently identified facilitating factor (39.6%; n = 19) was ‘insufficient (drug) knowledge, prescribing skills and/or experience of prescribers’. Conclusion: The findings of this review could be used to identify points of engagement for future intervention studies and help hospitals determine how to optimize prescribing. A multifaceted intervention, targeting multiple factors might help to circumvent the complex challenge of in-hospital PEs.

eHealth education in primary care practice : part 3

eHealth education should be integrated into vocational training and continuous professional development programmes. In this opinion article, we aim to support organisers of Continuing Professional Development (CPD) and teachers delivering medical vocational training by providing recommendations for eHealth education. First, we describe what is required to help primary care professionals and trainees learn about eHealth. Second, we elaborate on how eHealth education might be provided

Harmonizing and improving European education in prescribing

Aim: Improvement and harmonization of European clinical pharmacology and therapeutics (CPT) education is urgently required. Because digital educational resources can be easily shared, adapted to local situations and re-used widely across a variety of educational systems, they may be ideally suited for this purpose. Methods: With a cross-sectional survey among principal CPT teachers in 279 out of 304 European medical schools, an overview and classification of digital resources was compiled. Results: Teachers from 95 (34%) medical schools in 26 of 28 EU countries responded, 66 (70%) of whom used digital educational resources in their CPT curriculum. A total of 89 of such resources were described in detail, including e-learning (24%), simulators to teach pharmacokinetics and/or pharmacodynamics (10%), virtual patients (8%), and serious games (5%). Together, these resources covered 235 knowledge-based learning objectives, 88 skills, and 13 attitudes. Only one third (27) of the resources were in-part or totally free and only two were licensed open educational resources (free to use, distribute and adapt). A narrative overview of the largest, free and most novel resources is given. Conclusion: Digital educational resources, ranging from e-learning to virtual patients and games, are widely used for CPT education in EU medical schools. Learning objectives are based largely on knowledge rather than skills or attitudes. This may be improved by including more real-life clinical case scenarios. Moreover, the majority of resources are neither free nor open. Therefore, with a view to harmonizing international CPT education, more needs to be learned about why CPT teachers are not currently sharing their educational materials.

Improving Routine Immunization Coverage Through Optimally Designed Predictive Models

Routine immunization (RI) of children is the most effective and timely public health intervention for decreasing child mortality rates around the globe. Pakistan being a low-and-middle-income-country (LMIC) has one of the highest child mortality rates in the world occurring mainly due to vaccine-preventable diseases (VPDs). For improving RI coverage, a critical need is to establish potential RI defaulters at an early stage, so that appropriate interventions can be targeted towards such population who are identified to be at risk of missing on their scheduled vaccine uptakes. In this paper, a machine learning (ML) based predictive model has been proposed to predict defaulting and non-defaulting children on upcoming immunization visits and examine the effect of its underlying contributing factors. The predictive model uses data obtained from Paigham-e-Sehat study having immunization records of 3,113 children. The design of predictive model is based on obtaining optimal results across accuracy, specificity, and sensitivity, to ensure model outcomes remain practically relevant to the problem addressed. Further optimization of predictive model is obtained through selection of significant features and removing data bias. Nine machine learning algorithms were applied for prediction of defaulting children for the next immunization visit. The results showed that the random forest model achieves the optimal accuracy of 81.9% with 83.6% sensitivity and 80.3% specificity. The main determinants of vaccination coverage were found to be vaccine coverage at birth, parental education, and socio-economic conditions of the defaulting group. This information can assist relevant policy makers to take proactive and effective measures for developing evidence based targeted and timely interventions for defaulting children.

Quality indicators for appropriate in-hospital pharmacotherapeutic stewardship

Aims: In-hospital prescribing errors may result in patient harm, such as prolonged hospitalisation and hospital (re)admission, and may be an emotional burden for the prescribers and healthcare professionals involved. Despite efforts, in-hospital prescribing errors and related harm still occur, necessitating an innovative approach. We therefore propose a novel approach, in-hospital pharmacotherapeutic stewardship (IPS). The aim of this study was to reach consensus on a set of quality indicators (QIs) as a basis for IPS. Methods: A three-round modified Delphi procedure was performed. Potential QIs were retrieved from two systematic searches of the literature, in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement. In two written questionnaires and a focus meeting (held between the written questionnaire rounds), potential QIs were appraised by an international, multidisciplinary expert panel composed of members of the European Association for Clinical Pharmacology and Therapeutics (EACPT). Results: The expert panel rated 59 QIs and four general statements, of which 35 QIs were accepted with consensus rates ranging between 79% and 97%. These QIs describe the activities of an IPS programme, the team delivering IPS, the patients eligible for the programme and the outcome measures that should be used to evaluate the care delivered. Conclusions: A framework of 35 QIs for an IPS programme was systematically developed. These QIs can guide hospitals in setting up a pharmacotherapeutic stewardship programme to reduce in-hospital prescribing errors and improve in-hospital medication safety.