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BackgroundThe openEHR approach can improve the interoperability of electronic health record (EHR) through two-level modeling. Developing archetypes for the complete EHR dataset is essential for implementing a large-scale interoperable EHR system with the openEHR approach. Although the openEHR approach has been applied in different domains, the feasibility of archetyping a complete EHR dataset in a hospital has not been reported in academic literature, especially in a country where using openEHR is still in its infancy stage, like China. This paper presents a case study of modeling an EHR in China aiming to investigate the feasibility and challenges of archetyping a complete EHR dataset with the openEHR approach.MethodsWe proposed an archetype modeling method including an iterative process of collecting requirements, normalizing data elements, organizing concepts, searching corresponding archetypes, editing archetypes and reviewing archetypes. Two representative EHR systems from Chinese vendors and the existing Chinese EHR standards have been used as resources to identify the requirements of EHR in China, and a case study of modeling EHR in China has been conducted. Based on the models developed in this case study, we have implemented a clinical data repository (CDR) to verify the feasibility of modeling EHR with archetypes.ResultsSixty four archetypes were developed to represent all requirements of a complete EHR dataset. 59 (91%) archetypes could be found in Clinical Knowledge Manager (CKM), of which 35 could be reused directly without change, and 23 required further development including two revisions, two new versions, 18 extensions and one specialization. Meanwhile, 6 (9%) archetypes were newly developed. The legacy data of the EHR system in hospitals could be integrated into the CDR developed with these archetypes successfully.ConclusionsThe existing archetypes in CKM can faithfully represent most of the EHR requirements in China except customizations for local hospital management. This case study verified the feasibility of modeling EHR with the openEHR approach and identified the fact that the challenges such as localization, tool support, and an agile publishing process still exist for a broader application of the openEHR approach.

Desalination by solar steam generation (SSG) has emerged as one of the most efficient approaches to address the issue of global water shortage. In this work, novel graphene oxide (GO)-based solar steam generators (GO-SSGs) with aligned channels were prepared by directional freezing and simple carbonization of a hydrogel composed of GO and poly(vinyl alcohol) (PVA). Benefitting from their excellent light absorption (light absorption efficiency exceeds 94%), better thermal insulation (thermal conductivity, 0.259 W/(m K)), and suitable porous structure, which facilitates rapid water transportation, the GO-SSGs show superior SSG performance with a high solar energy conversion efficiency of up to 92% achieved under an irradiation of 1.0 kW/m 2 . Interestingly, uniquely aligned channels endow them with good salt-rejection performance; the solar energy conversion efficiency of GO-SSGs in 20 wt % NaCl, KCl, and MgCl 2 brine can reach more than 85%. To improve their antifouling performance, a chemically hydrophilic and oleophobic modification was conducted, making it possible to run SSG even in oily wastewater; for instance, a solar energy conversion efficiency of 84% was obtained in an aqueous solution containing 10 wt % n-hexadecane. Compared with the existing photothermal materials, these materials show advantages of simple manufacture, high SSG efficiency, superior salt tolerance, and antifouling performance, which make them promising candidates as a kind of new high-performance photothermal materials for desalination even in oily wastewater, thus further expanding the scope of their practical SSG application.

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