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(2020)
IT-Standard für das pflegerische Entlassmanagement.
Der von der Hochschule Osnabrück entwickelte „ePflegebericht“ kann die bisherigen unterschiedlichen papierbasierten Überleitungen ablösen, indem die entsprechenden IT-Systeme interoperabel Dokumente austauschen. Die Pflege erhält mit diesem IT-Standard erstmals einen möglichen Zugang zur Telematikinfrastruktur, um zwischen Einrichtungen und über Sektorengrenzen hinweg pflegerisch relevante Informationen schnell und sicher zu übermitteln.
Objective: The more people there are who use clinical information systems (CIS) beyond their traditional intramural confines, the more promising the benefits are, and the more daunting the risks will be. This review thus explores the areas of ethical debates prompted by CIS conceptualized as smart systems reaching out to patients and citizens. Furthermore, it investigates the ethical competencies and education needed to use these systems appropriately.
Methods: A literature review covering ethics topics in combination with clinical and health information systems, clinical decision support, health information exchange, and various mobile devices and media was performed searching the MEDLINE database for articles from 2016 to 2019 with a focus on 2018 and 2019. A second search combined these keywords with education.
Results: By far, most of the discourses were dominated by privacy, confidentiality, and informed consent issues. Intertwined with confidentiality and clear boundaries, the provider-patient relationship has gained much attention. The opacity of algorithms and the lack of explicability of the results pose a further challenge. The necessity of sociotechnical ethics education was underpinned in many studies including advocating education for providers and patients alike. However, only a few publications expanded on ethical competencies. In the publications found, empirical research designs were employed to capture the stakeholders’ attitudes, but not to evaluate specific implementations.
Conclusion: Despite the broad discourses, ethical values have not yet found their firm place in empirically rigorous health technology evaluation studies. Similarly, sociotechnical ethics competencies obviously need detailed specifications. These two gaps set the stage for further research at the junction of clinical information systems and ethics.
Background
Diabetes mellitus is a major global health issue with a growing prevalence. In this context, the number of diabetic complications is also on the rise, such as diabetic foot ulcers (DFU), which are closely linked to the risk of lower extremity amputation (LEA). Statistical prediction tools may support clinicians to initiate early tertiary LEA prevention for DFU patients. Thus, we designed Bayesian prediction models, as they produce transparent decision rules, quantify uncertainty intuitively and acknowledge prior available scientific knowledge.
Method
A logistic regression using observational collected according to the standardised PEDIS classification was utilised to compute the six-month amputation risk of DFU patients for two types of LEA: 1.) any-amputation and 2.) major-amputation. Being able to incorporate information which is available before the analysis, the Bayesian models were fitted following a twofold strategy. First, the designed prediction models waive the available information and, second, we incorporated the a priori available scientific knowledge into our models. Then, we evaluated each model with respect to the effect of the predictors and validity of the models. Next, we compared the performance of both models with respect to the incorporation of prior knowledge.
Results
This study included 237 patients. The mean age was 65.9 (SD 12.3), and 83.5% were male. Concerning the outcome, 31.6% underwent any- and 12.2% underwent a major-amputation procedure. The risk factors of perfusion, ulcer extent and depth revealed an impact on the outcomes, whereas the infection status and sensation did not. The major-amputation model using prior information outperformed the uninformed counterpart (AUC 0.765 vs AUC 0.790, Cohen’s d 2.21). In contrast, the models predicting any-amputation performed similarly (0.793 vs 0.790, Cohen’s d 0.22).
Conclusions
Both of the Bayesian amputation risk models showed acceptable prognostic values, and the major-amputation model benefitted from incorporating a priori information from a previous study. Thus, PEDIS serves as a valid foundation for a clinical decision support tool for the prediction of the amputation risk in DFU patients. Furthermore, we demonstrated the use of the available prior scientific information within a Bayesian framework to establish chains of knowledge.
Introduction: Handovers are a central process for ensuring information continuity in patient care and, therefore, possess a major influence on patient safety as errors due to poor handovers can lead to life-threatening events. Education to improve handovers and ensure safe patient care can be supported by using critical incident reporting systems (CIRS). The aim of the study is to perform a content analysis of a national CIRS-database with regard to identifying adverse events in handovers situations and to derive competencies for the development of continuing education from these findings.
Methods: A meta model served as a research framework to merge the empirical findings with the London protocol of analysing critical events and the Canadian framework of safety competencies. Relevant cases to be investigated were searched in a freely accessible German CIRS database.
Results: A total of 253 case descriptions were found and analysed. Team factors emerged as the most frequently reported influencing factors following the analysis of the London protocol. Communication errors and missing information as well as a lack of appropriate standards and processes appeared to be the main reasons for critical events to occur. Most of the events happened in units involving surgery and intensive care. A mapping of patient safety competences with the reasons for critical events was conducted in order to determine the practical, concrete and handover related competencies.
Conclusion: Data from a CIRS database and theoretical frameworks can be combined to extract meaningful information about patient safety risks in handover situations. The results are useful for developing curricula to improve handovers based on patient safety competencies.
Background
Against the background of a steadily increasing degree of digitalization in health care, a professional information management (IM) is required to successfully plan, implement, and evaluate information technology (IT). At its core, IM has to ensure a high quality of health data and health information systems to support patient care.
Objectives
The goal of the present study was to define what constitutes professional IM as a construct as well as to propose a reliable and valid measurement instrument.
Methods
To develop and validate the construct of professionalism of information management (PIM) and itsmeasurement, a stepwise approach followed an established procedure from information systems and behavioral research. The procedure included an analysis of the pertaining literature and expert rounds on the construct and the
instrument, two consecutive and comprehensive surveys at the national and international level, exploratory and confirmatory factor analyses as well as reliability and validity testing.
Results
Professionalism of information management was developed as a construct consisting of the three dimensions of strategic, tactical, and operational IMas well as of the regularity and cyclical phases of IM procedures as the two elements of professionalism.
The PIM instrument operationalized the construct providing items that incorporated IM procedures along the three dimensions and cyclical phases. These procedures had to be evaluated against their degree of regularity in the instrument. The instrument proved to be reliable and valid in two consecutive measurement phases
and across three countries.
Conclusion
It can be concluded that professionalism of information management is a meaningful construct that can be operationalized in a scientifically rigorous manner. Both science and practice can benefit from these developments in terms of improved self-assessment, benchmarking capabilities, and eventually, obtaining a better understanding of health IT maturity.