An evidence-based tool (PE for PS) for healthcare managers to assess patient engagement for patient safety in healthcare organizations

In 1999, the Institute of Medicine had already warned that medical errors caused between 44,000 and 98,000 avoidable deaths per year in the United States. A similar situation was subsequently in 2000, documented in Canadian hospitals. According to a Canadian Patient Safety Institute report (2016), incidents in both acute and home care settings resulted in additional costs of $2.75 billion each year. Research suggests that Patient Engagement (PE) for Patient Safety (PS) can help address this issue. However, the use of PE in various strategies to promote PS has yet to be fully integrated across healthcare systems in OECD countries. The aim of this study was to develop a tool for managers to assess PE strategies implemented at a health system level to enhance PS. Developing the tool involved 3 phases: (1) creating a framework; (2) building a first version of the tool; (3) validating the tool by an expert committee of PS and PE managers. The final tool consists of 81 questions, divided into four sections: (1) describing the healthcare organization (n=14); (2) gathering general information on PE strategies (n=15); (3) assessing different PE strategies for PS (n=49); and (4) describing the respondent’s involvement in PS committees (n=3). The tool is currently being used (by healthcare professionals working in Risk Management (RM) or PS, or, by task groups that include patients) in a research study in Canada and France, to assist healthcare managers in monitoring the evolution of PE for PS at a system level. Experience Framework This article is associated with the Policy & Measurement lens of The Beryl Institute Experience Framework. (https://www.theberylinstitute.org/ExperienceFramework). Access other PXJ articles related to this lens. Access other resources related to this lens

User-centered visual analysis using a hybrid reasoning architecture for intensive care units

One problem pertaining to Intensive Care Unit information systems is that, in some cases, a very dense display of data can result. To ensure the overview and readability of the increasing volumes of data, some special features are required (e.g., data prioritization, clustering, and selection mechanisms) with the application of analytical methods (e.g., temporal data abstraction, principal component analysis, and detection of events). This paper addresses the problem of improving the integration of the visual and analytical methods applied to medical monitoring systems. We present a knowledge- and machine learning-based approach to support the knowledge discovery process with appropriate analytical and visual methods. Its potential benefit to the development of user interfaces for intelligent monitors that can assist with the detection and explanation of new, potentially threatening medical events. The proposed hybrid reasoning architecture provides an interactive graphical user interface to adjust the parameters of the analytical methods based on the users' task at hand. The action sequences performed on the graphical user interface by the user are consolidated in a dynamic knowledge base with specific hybrid reasoning that integrates symbolic and connectionist approaches. These sequences of expert knowledge acquisition can be very efficient for making easier knowledge emergence during a similar experience and positively impact the monitoring of critical situations. The provided graphical user interface incorporating a user-centered visual analysis is exploited to facilitate the natural and effective representation of clinical information for patient care

Heart Failure Monitoring System Based on Wearable and Information Technologies

In Europe, Cardiovascular Diseases (CVD) are the leading source of death, causing 45% of all deceases. Besides, Heart Failure, the paradigm of CVD, mainly affects people older than 65. In the current aging society, the European MyHeart Project was created, whose mission is to empower citizens to fight CVD by leading a preventive lifestyle and being able to be diagnosed at an early stage. This paper presents the development of a Heart Failure Management System, based on daily monitoring of Vital Body Signals, with wearable and mobile technologies, for the continuous assessment of this chronic disease. The System makes use of the latest technologies for monitoring heart condition, both with wearable garments (e.g. for measuring ECG and Respiration); and portable devices (such as Weight Scale and Blood Pressure Cuff) both with Bluetooth capabilitie

Embedding effective depression care: using theory for primary care organisational and systems change

Background: depression and related disorders represent a significant part of general practitioners (GPs) daily work. Implementing the evidence about what works for depression care into routine practice presents a challenge for researchers and service designers. The emerging consensus is that the transfer of efficacious interventions into routine practice is strongly linked to how well the interventions are based upon theory and take into account the contextual factors of the setting into which they are to be transferred. We set out to develop a conceptual framework to guide change and the implementation of best practice depression care in the primary care setting.Methods: we used a mixed method, observational approach to gather data about routine depression care in a range of primary care settings via: audit of electronic health records; observation of routine clinical care; and structured, facilitated whole of organisation meetings. Audit data were summarised using simple descriptive statistics. Observational data were collected using field notes. Organisational meetings were audio taped and transcribed. All the data sets were grouped, by organisation, and considered as a whole case. Normalisation Process Theory (NPT) was identified as an analytical theory to guide the conceptual framework development.Results: five privately owned primary care organisations (general practices) and one community health centre took part over the course of 18 months. We successfully developed a conceptual framework for implementing an effective model of depression care based on the four constructs of NPT: coherence, which proposes that depression work requires the conceptualisation of boundaries of who is depressed and who is not depressed and techniques for dealing with diffuseness; cognitive participation, which proposes that depression work requires engagement with a shared set of techniques that deal with depression as a health problem; collective action, which proposes that agreement is reached about how care is organised; and reflexive monitoring, which proposes that depression work requires agreement about how depression work will be monitored at the patient and practice level. We describe how these constructs can be used to guide the design and implementation of effective depression care in a way that can take account of contextual differences.Conclusions: ideas about what is required for an effective model and system of depression care in primary care need to be accompanied by theoretically informed frameworks that consider how these can be implemented. The conceptual framework we have presented can be used to guide organisational and system change to develop common language around each construct between policy makers, service users, professionals, and researchers. This shared understanding across groups is fundamental to the effective implementation of change in primary care for depressio

Utilising semantic technologies for decision support in dementia care

The main objective of this work is to discuss our experience in utilising semantic technologies for building decision support in Dementia care systems that are based on the non-intrusive on the non-intrusive monitoring of the patient’s behaviour. Our approach adopts context-aware modelling of the patient’s condition to facilitate the analysis of the patient’s behaviour within the inhabited environment (movement and room occupancy patterns, use of equipment, etc.) with reference to the semantic knowledge about the patient’s condition (history of present of illness, dependable behaviour patterns, etc.). The reported work especially focuses on the critical role of the semantic reasoning engine in inferring medical advice, and by means of practical experimentation and critical analysis suggests important findings related to the methodology of deploying the appropriate semantic rules systems, and the dynamics of the efficient utilisation of complex event processing technology in order to the meet the requirements of decision support for remote healthcare systems

Confronting corruption in the health sector in Vietnam: patterns and prospects

This repository item contains a single issue of the Health and Development Discussion Papers, an informal working paper series that began publishing in 2002 by the Boston University Center for Global Health and Development. It is intended to help the Center and individual authors to disseminate work that is being prepared for journal publication or that is not appropriate for journal publication but might still have value to readers.Corruption in Vietnam is a national concern which could derail health sector goals for equity, access, and quality. Yet, there is little research on vulnerabilities to corruption or associated factors at the sectoral level. This article examines current patterns of corruption in Vietnam’s health sector, identifies key corruption vulnerabilities, and reviews strategies for addressing corruption in the future. The article builds on the findings and discussion at the sixth Anti-Corruption Dialogue between the Vietnamese Government and the international donor community. Development partners, government agencies, Vietnamese and international non-governmental organizations, media representatives and other stakeholders explored what is known about important problems such as informal payments, procurement corruption, and health insurance fraud. The participants proposed corruption-reduction interventions in the areas of administrative oversight, transparency initiatives and civil society participation, and health reforms to change incentives. The analysis assesses the prospects for success of these interventions given the Vietnamese institutional context, and draws conclusions relevant to addressing health sector corruption in other countries

An agent-based architecture for managing the provision of community care - the INCA (Intelligent Community Alarm) experience

Community Care is an area that requires extensive cooperation between independent agencies, each of which needs to meet its own objectives and targets. None are engaged solely in the delivery of community care, and need to integrate the service with their other responsibilities in a coherent and efficient manner. Agent technology provides the means by which effective cooperation can take place without compromising the essential security of both the client and the agencies involved as the appropriate set of responses can be generated through negotiation between the parties without the need for access to the main information repositories that would be necessary with conventional collaboration models. The autonomous nature of agents also means that a variety of agents can cooperate together with various local capabilities, so long as they conform to the relevant messaging requirements. This allows a variety of agents, with capabilities tailored to the carers to which they are attached to be developed so that cost-effective solutions can be provided. </p