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Gesundheitskarte im Test
(2015)
Restricted Versus Unrestricted Search Space : Experience from Mining a Large Japanese Database
(2015)
The aim of this study was to investigate whether standard Big Data mining methods lead to clinically useful results. An association analysis was performed using the apriori algorithm to discover associations among co-morbidities of diabetes patients. Selected data were further analyzed by using k-means clustering with age, long-term blood sugar and cholesterol values. The association analysis led to a multitude of trivial rules. Cluster analysis detected clusters of well and badly managed diabetes patients both belonging to different age groups. The study suggests the usage of cluster analysis on a restricted space to come to meaningful results.
Although national eHealth strategies have existed now for more than a decade in many countries, they have been implemented with varying success. In Germany, the eHealth strategy so far has resulted in a roll out of electronic health cards for all citizens in the statutory health insurance, but in no clinically meaningful IT-applications. The aim of this study was to test the technical and organisation feasibility, usability, and utility of an eDischarge application embedded into a laboratory Health Telematics Infrastructure (TI). The tests embraced the exchange of eDischarge summaries based on the multiprofessional HL7 eNursing Summary standard between a municipal hospital and a nursing home. All in all, 36 transmissions of electronic discharge documents took place. They demonstrated the technical-organisation feasibility and resulted in moderate usability ratings. A comparison between eDischarge and paper-based summaries hinted at higher ratings of utility and information completeness for eDischarges. Despite problems with handling the electronic health card, the proof-of-concept for the first clinically meaningful IT-application in the German Health TI could be regarded as successful.
Objectives: eHealth and innovation are often regarded as synonyms - not least because eHealth technologies and applications are new to their users. This position paper challenges this view and aims at exploring the nature of eHealth innovation against the background of common definitions of innovation and facts from the biomedical and health informatics literature. A good understanding of what constitutes innovative eHealth developments allows the degree of innovation to be measured and interpreted.
Methods: To this end, relevant biomedical and health informatics literature was searched mainly in Medline and ACM digital library. This paper presents seven facts about implementing and applying new eHealth developments hereby drawing on the experience published in the literature.
Results: The facts are: 1. eHealth innovation is relative. 2. Advanced clinical practice is the yardstick. 3. Only used and usable eHealth technology can give birth to eHealth innovatio. 4. One new single eHealth function does not make a complex eHealth innovation. 5. eHealth innovation is more evolution than revolution. 6. eHealth innovation is often triggered behind the scenes; and 7. There is no eHealth innovation without sociocultural change.
Conclusions: The main conclusion of the seven facts is that eHealth innovations have many ingredients: newness, availability, advanced clinical practice with proven outcomes, use and usability, the supporting environment, other context factors and the stakeholder perspectives. Measuring eHealth innovation is thus a complex matter. To this end we propose the development of a composite score that expresses comprehensively the nature of eHealth innovation and that breaks down its complexity into the three dimensions: i) eHealth adoption, ii) partnership with advanced clinical practice, and iii) use and usability of eHealth. In order to better understand the momentum and mechanisms behind eHealth innovation the fourth dimension, iv) eHealth supporting services and means, needs to be studied. Conceptualising appropriate measurement instruments also requires eHealth innovation to be distinguished from eHealth sophistication, performance and quality, although innovation is intertwined with these concepts. The demanding effort for defining eHealth innovation and measuring it properly seem worthwhile and promise advances in creating better systems. This paper thus intends to stimulate the necessary discussion.
Background: Clinical handovers at changes of shifts are typical scenarios of time restricted and information intensive communication, which are highly cognitively demanding. The currently available applications supporting handovers typically present complex information in a textual checklist-like manner. This presentation style has been criticised for not meeting the specific user requirements.
Objectives: We, therefore, aimed at developing a concept for visualising the overview of a clinical case that serves as an alternative way to checklist-like presentations in clinical handovers. We also aimed at implementing this concept in a handoverEHR in order to support the pre-handover phase, the actual handover, and the post-handover phase as well as at evaluating its usability and attractiveness.
Results: We developed and implemented a concept that draws on Tolman's pioneering work on cognitive maps that we designed in accordance with Gestalt principles. These maps provide a pictorial overview of a clinical case. The application to build, manipulate, and store the cognitive maps was integrated into an openEHR based handover record that extends conventional records with handover specific information. Usability (n = 28) and attractiveness (n = 26) testing with experienced clinicians resulted in good ratings for suitability for the task as well as for attractiveness and pragmatism.
Conclusion: We propose cognitive maps to represent and visualise the clinical case in situations where there is limited time to present complex information.
The demand for evidence-based health informatics and benchmarking of 'good' information systems in health care gives an opportunity to continue reporting on recent papers in the German journal GMS Medical Informatics, Biometry and Epidemiology (MIBE) here. The publications in focus deal with a comparison of benchmarking initiatives in German-speaking countries, use of communication standards in telemonitoring scenarios, the estimation of national cancer incidence rates and modifications of parametric tests. Furthermore papers in this issue of MIM are introduced which originally have been presented at the Annual Conference of the German Society of Medical Informatics, Biometry and Epidemiology. They deal as well with evidence and evaluation of 'good' information systems but also with data harmonization, surveillance in obstetrics, adaptive designs and parametrical testing in statistical analysis, patient registries and signal processing.
Background: Availability and usage of individual IT applications have been studied intensively in the past years. Recently, IT support of clinical processes is attaining increasing attention. The underlying construct that describes the IT support of clinical workflows is clinical information logistics. This construct needs to be better understood, operationalised and measured.
Objectives: It is therefore the aim of this study to propose and develop a workflow composite score (WCS) for measuring clinical information logistics and to examine its quality based on reliability and validity analyses.
Methods: We largely followed the procedural model of MacKenzie and colleagues (2011) for defining and conceptualising the construct domain, for developing the measurement instrument, assessing the content validity, pretesting the instrument, specifying the model, capturing the data and computing the WCS and testing the reliability and validity.
Results: Clinical information logistics was decomposed into the descriptors data and information, function, integration and distribution, which embraced the framework validated by an analysis of the international literature. This framework was refined selecting representative clinical processes. We chose ward rounds, pre- and post-surgery processes and discharge as sample processes that served as concrete instances for the measurements. They are sufficiently complex, represent core clinical processes and involve different professions, departments and settings. The score was computed on the basis of data from 183 hospitals of different size, ownership, location and teaching status. Testing the reliability and validity yielded encouraging results: the reliability was high with r(split-half) = 0.89, the WCS discriminated between groups; the WCS correlated significantly and moderately with two EHR models and the WCS received good evaluation results by a sample of chief information officers (n = 67). These findings suggest the further utilisation of the WCS.
Conclusion: As the WCS does not assume ideal workflows as a gold standard but measures IT support of clinical workflows according to validated descriptors a high portability of the WCS to other hospitals in other countries is very likely. The WCS will contribute to a better understanding of the construct clinical information logistics.