Health Systems最新文献

Hospital information systems are increasingly used as part of decision support tools for planning at strategic, tactical and operational decision levels. Clinical pathways are an effective and efficient approach in standardising the progression of treatment, to support patient care and facilitate clinical decision making. This literature review proposes a taxonomy of problems related to clinical pathways and explores the intersection between Information Systems (IS), Operational Research (OR) and industrial engineering. A structured search identified 175 papers included in the taxonomy and analysed in this review. The findings suggest that future work should consider industrial engineering integrated with OR techniques, with an aim to improving the handling of multiple scopes within one model, while encouraging interaction between the disjoint care levels and with a more direct focus on patient outcomes. Achieving this would continue to bridge the gap between OR, IS and industrial engineering, for clinical pathways to aid decision support.

Many primary care clinics suffer from chaos. In scheduling, providers are continually trying unsuccessfully to balance supply and demand, and in execution, to manage disruptions to provider focus and patient flow. In this research the theory of constraints' (TOC) three processes of ongoing improvement (POOGI) provide a direction for the solution to achieving more, cheaper, better, and faster healthcare. This research is the second of a two-part study examining the appointment scheduling literature, identifying the core problem (using a case study for validation) and providing a generic process for developing effective provider appointment scheduling systems (PASS). In the first part, PASS design was studied and in this second part PASS execution is studied. A strawman process is developed to apply across outpatient medical practices. With this generic process implemented across outpatient scheduling systems cost could be reduced significantly while the quality and timeliness could be increased significantly.

The dashboards of electronic health record (EHR) systems could potentially support the chart biopsy that occurs before or after physician handoffs. In this study, we conducted a simulation handoff study and recorded the participants' navigation patterns in an EHR system mock-up. We analyzed the navigation patterns of dashboard use in terms of duration, frequency, and sequence, and we examined the relationship between dashboard use in chart biopsy and the errors identified after handoffs. The results show that the participants frequently used the dashboard as an information hub and as an information resource to help them navigate the EHR system and answer the questions in a nursing call. Moreover, using the dashboard as an information hub can help reduce imprecision and factual errors in handoffs. Our findings suggest the need for a "context-aware" dashboard to accommodate dynamic navigation patterns and to support clinical work as well as to reduce medical errors.

The purpose of this study was to understand the user experience with a computerized septic shock protocol relative to the workflow of Paediatric Intensive Care Unit clinicians. The need for data-driven, condition-specific, computerized protocols in the intensive care unit helps improve decision-making at the bedside. PICU clinicians were interviewed and given pre-and post-implementation surveys asking their opinions on the current PICU septic shock protocol, as well as the current electronic health record being used at [Paediatric Academic Medical Center]. User preferences guided adjustments toward improved usability of the septic shock protocol. Computerized Physician Order Entry, a critical component of the septic shock protocol, allows for more streamlined processes, more complete records, and more time to care for patients. This study revealed that although clinicians had an unfavorable view of the EHR in general, the computerized septic shock protocol was very well-received with an overall usability score of 82.

The aim of this paper is to demonstrate the potential of the systemic innovations approach for transforming transplantation systems. It explores potential leverage points for intervening in the LTx-system as well as possible paths of transformation. We present possible transition pathways giving the example of the German Lung transplantation system that teeters on the brink of collapse due to system failures and organ scarcity and illustrate systemic innovations as core mechanisms for systems change in health systems. Desk research and semi-structured experts interviews provided qualitative data for a deductive-inductive coding and a rigorous qualitative content analysis of the data. Depending on the systemic innovations chosen to achieve systems change, transplant systems follow different transformational paths: from a collapse to a leapfrogging towards a non-human transplantation system. Thus, global health areas like transplantation benefit from analysis on systemic innovations as these support researchers, public policy and regulators by developing transformative strategies in healthcare systems.

An increase in the reliability of Health Information Technology (HIT) will facilitate institutional trust and credibility of the systems. In this paper, we present an end-to-end framework for improving the reliability and performance of HIT systems. Specifically, we describe the system model, present some of the methods that drive the model, and discuss an initial implementation of two of the proposed methods using data from the Veterans Affairs HIT and Corporate Data Warehouse systems. The contributions of this paper, thus, include (1) the design of a system model for monitoring and detecting hazards in HIT systems, (2) a data-driven approach for analysing the health care data warehouse, (3) analytical methods for characterising and analysing failures in HIT systems, and (4) a tool architecture for generating and reporting hazards in HIT systems. Our goal is to work towards an automated system that will help identify opportunities for improvements in HIT systems.

Variation in the performance of providers across healthcare systems is pervasive. It is recognised as both a major concern and an opportunity for learning and improvement. Variation between providers is broadly considered to be due to management practices and contextual factors such as catchment-area demographics. However, there is little understanding of the ways in which these impact on performance and how they can be measured. We use recent developments in both regression trees and panel regression techniques to explore and then statistically test complementary alignments of management practices whilst taking into account contextual factors. We apply this to 5 years of NHS hospital trust data, examining performance on short-notice cancellation rates. We find that different alignments of management practices give rise to quite different short-notice cancellation rates between trusts, with some being substantially lower. Our research offers a data-driven approach for identifying optimal clusters of management practices.

Sensitive data from health research surveys need to be protected from loss, damage or unwanted release, especially when data include personally identifying information, protected health information or other private material. Researchers and practitioners must ensure privacy and confidentiality in the architecture of data systems and in access to the data. Internal and external risks may be deliberate or accidental, involving unintended loss, modification or exposure. To prevent risk while allowing access requires balancing concerns against providing an environment that does not impede work. The authors' purpose in this paper is to draw attention to basic data security needs for health survey data from the perspective of both the health researcher/practitioner and infrastructure/programming staff to ensure that data are securely and adequately protected. We describe risk classifications and how they affect system architecture, drawing on recent experience with systems for storage of and access to electronic health survey data.

Health market reforms necessitate continuous re-evaluation of initiatives, competitive regulations, and antitrust policies. Synergistic implications, evolution, and behaviour changes associated with the market competition are often overlooked due to methodological limitations. To rectify these limitations, parallels between defining features of health care markets (HCM) and complex adaptive systems (CAS) are drawn. The science of CAS develops complex system-level models of dynamic interactions to allow insights for heterogeneous agents and emergent behaviours. Agent-based modelling (ABM) is a computational tool of CAS science suitable for investigating competition in HCM. The proposed agent-based framework conceptualises agents, environment, and interactions, and formalises agent-specific attributes and modules that achieve agent roles to recreate HCM dynamics. The framework conceptualises competition in HCM into an implementable ABM for a CAS assessment, identifies data sources, and develops face-validity procedures. Developments in data, computational power, and decisions theory compel CAS approach to complement studies on pressing HCM issues.

Healthcare professionals are continuously being challenged to address the triple aim necessary for effective patient care: improving the quality and satisfaction of patients, improving the health of populations, and reducing per capita cost of healthcare. Today, innovation and cost-effective methods are a requirement to meet the triple aim given the current economic climate and financial limitations. Healthcare simulation is currently underutilised, particularly during the space or facility planning process in healthcare. This position paper will describe the process of implementing space simulations that were conducted between 2016 and 2018 in six different clinical settings that identified patient and provider safety concerns, and patient and provider needs. Simulation design and development along with the methodology for data collection and data analyses will be presented. Qualitative results will be presented to demonstrate the impact of the use of simulation to prevent critical and non-critical safety events.