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Ensuring medical support of patients of advanced age in rural areas is a major challenge. Moreover, the number of registered doctors—medical specialists in particular—will decrease in such areas over the next years. These unmet medical needs in combination with communication deficiencies among different types of health-care professionals pose threats to the quality of patient treatment. This work presents a novel solution combining telemedicine, telecooperation, and IHE profiles to tackle these challenges. We present a telecooperation platform that supports longitudinal electronic patient records and allows for intersectoral cooperation based on shared electronic medication charts and other documents. Furthermore, the conceived platform allows for an integration into the planned German telematics infrastructure.

This work investigates, whether openEHR with its reference model, archetypes and templates is suitable for the digital representation of demographic as well as clinical data. Moreover, it elaborates openEHR as a tool for modelling Hospital Information Systems on a regional level based on a national logical infrastructure. OpenEHR is a dual model approach developed for the modelling of Hospital Information Systems enabling semantic interoperability. A holistic solution to this represents the use of dual model based Electronic Healthcare Record systems. Modelling data in the field of obstetrics is a challenge, since different regions demand locally specific information for the process of treatment. Smaller health units in developing countries like Brazil or Malaysia, which until recently handled automatable processes like the storage of sensitive patient data in paper form, start organizational reconstruction processes. This archetype proof-of-concept investigation has tried out some elements of the openEHR methodology in cooperation with a health unit in Colombo, Brazil. Two legal forms provided by the Brazilian Ministry of Health have been analyzed and classified into demographic and clinical data. LinkEHR-Ed editor was used to read, edit and create archetypes. Results show that 33 clinical and demographic concepts, which are necessary to cover data demanded by the Unified National Health System, were identified. Out of the concepts 61% were reused and 39% modified to cover domain requirements. The detailed process of reuse, modification and creation of archetypes is shown. We conclude that, although a major part of demographic and clinical patient data were already represented by existing archetypes, a significant part required major modifications. In this study openEHR proved to be a highly suitable tool in the modelling of complex health data. In combination with LinkEHR-Ed software it offers user-friendly and highly applicable tools, although the complexity built by the vast specifications requires expert networks to define generally excepted clinical models. Finally, this project has pointed out main benefits enclosing high coverage of obstetrics data on the Clinical Knowledge Manager, simple modelling, and wide network and support using openEHR. Moreover, barriers described are enclosing the allocation of clinical content to respective archetypes, as well as stagnant adaption of changes on the Clinical Knowledge Manager leading to redundant efforts in data contribution that need to be addressed in future works., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Improving the effectiveness and efficiency of acute healthcare is very important nowadays. Optimization of clinical pathways regarding quality, time and costs is one of the key management strategies of critical diseases such as heart attack and stroke. To identify workflow bottlenecks requires a thorough understanding about both the hospital environment (e.g. IT-systems) and processes (e.g. clinical pathways). Having in mind the interoperability issues in hospitals, the standardized division- and system-crossing time measurement is still a challenge. Therefore this paper presents a novel way of structured and standardized retrieval of timing information along the clinical pathway of time-critical diseases in the context of hospital IT-systems, which represents a promising opportunity to identify workflow bottlenecks over several departmental and system borders.