Modeling healthcare authorization and claim submissions using the openEHR dual-model approach

<p>Abstract</p> <p>Background</p> <p>The TISS standard is a set of mandatory forms and electronic messages for healthcare authorization and claim submissions among healthcare plans and providers in Brazil. It is not based on formal models as the new generation of health informatics standards suggests. The objective of this paper is to model the TISS in terms of the openEHR archetype-based approach and integrate it into a patient-centered EHR architecture.</p> <p>Methods</p> <p>Three approaches were adopted to model TISS. In the first approach, a set of archetypes was designed using ENTRY subclasses. In the second one, a set of archetypes was designed using exclusively ADMIN_ENTRY and CLUSTERs as their root classes. In the third approach, the openEHR ADMIN_ENTRY is extended with classes designed for authorization and claim submissions, and an ISM_TRANSITION attribute is added to the COMPOSITION class. Another set of archetypes was designed based on this model. For all three approaches, templates were designed to represent the TISS forms.</p> <p>Results</p> <p>The archetypes based on the openEHR RM (Reference Model) can represent all TISS data structures. The extended model adds subclasses and an attribute to the COMPOSITION class to represent information on authorization and claim submissions. The archetypes based on all three approaches have similar structures, although rooted in different classes. The extended openEHR RM model is more semantically aligned with the concepts involved in a claim submission, but may disrupt interoperability with other systems and the current tools must be adapted to deal with it.</p> <p>Conclusions</p> <p>Modeling the TISS standard by means of the openEHR approach makes it aligned with ISO recommendations and provides a solid foundation on which the TISS can evolve. Although there are few administrative archetypes available, the openEHR RM is expressive enough to represent the TISS standard. This paper focuses on the TISS but its results may be extended to other billing processes. A complete communication architecture to simulate the exchange of TISS data between systems according to the openEHR approach still needs to be designed and implemented.</p

Design of a graphical and interactive interface for facilitating access to drug contraindications, cautions for use, interactions and adverse effects

<p>Abstract</p> <p>Background</p> <p>Drug iatrogeny is important but could be decreased if contraindications, cautions for use, drug interactions and adverse effects of drugs described in drug monographs were taken into account. However, the physician's time is limited during consultations, and this information is often not consulted. We describe here the design of "Mister VCM", a graphical interface based on the VCM graphical language, facilitating access to drug monographs. We also provide an assessment of the usability of this interface.</p> <p>Methods</p> <p>The "Mister VCM" interface was designed by dividing the screen into two parts: a graphical interactive one including VCM icons and synthetizing drug properties, a textual one presenting on demand drug monograph excerpts. The interface was evaluated over 11 volunteer general practitioners, trained in the use of "Mister VCM". They were asked to answer clinical questions related to fictitious randomly generated drug monographs, using a textual interface or "Mister VCM". When answering the questions, correctness of the responses and response time were recorded.</p> <p>Results</p> <p>"Mister VCM" is an interactive interface that displays VCM icons organized around an anatomical diagram of the human body with additional mental, etiological and physiological areas. Textual excerpts of the drug monograph can be displayed by clicking on the VCM icons. The interface can explicitly represent information implicit in the drug monograph, such as the absence of a given contraindication. Physicians made fewer errors with "Mister VCM" than with text (factor of 1.7; <it>p </it>= 0.034) and responded to questions 2.2 times faster (<it>p </it>< 0.001). The time gain with "Mister VCM" was greater for long monographs and questions with implicit replies.</p> <p>Conclusion</p> <p>"Mister VCM" seems to be a promising interface for accessing drug monographs. Similar interfaces could be developed for other medical domains, such as electronic patient records.</p

Tracking the polio virus down the Congo River: a case study on the use of Google Earth™ in public health planning and mapping

<p>Abstract</p> <p>Background</p> <p>The use of GIS in public health is growing, a consequence of a rapidly evolving technology and increasing accessibility to a wider audience. Google Earth™ (GE) is becoming an important mapping infrastructure for public health. However, generating traditional public health maps for GE is still beyond the reach of most public health professionals. In this paper, we explain, through the example of polio eradication activities in the Democratic Republic of Congo, how we used GE Earth as a planning tool and we share the methods used to generate public health maps.</p> <p>Results</p> <p>The use of GE improved field operations and resulted in better dispatch of vaccination teams and allocation of resources. It also allowed the creation of maps of high quality for advocacy, training and to help understand the spatiotemporal relationship between all the entities involved in the polio outbreak and response.</p> <p>Conclusion</p> <p>GE has the potential of making mapping available to a new set of public health users in developing countries. High quality and free satellite imagery, rich features including Keyhole Markup Language or image overlay provide a flexible but yet powerful platform that set it apart from traditional GIS tools and this power is still to be fully harnessed by public health professionals.</p

Use of Google Earth™ to Strengthen Public Health Capacity and Facilitate Management of Vector-Borne Diseases in Resource-Poor Environments

Novel, inexpensive solutions are needed for improved management of vector-borne and other diseases in resource-poor environments. Emerging free software providing access to satellite imagery and simple editing tools (e.g. Google Earth™) complement existing geographic information system (GIS) software and provide new opportunities for: (i) strengthening overall public health capacity through development of information for city infrastructures; and (ii) display of public health data directly on an image of the physical environment. Collaborators include: Saul Lozano-Fuentes, Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO, USA; Darwin Elizondo-Quiroga, Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO, USA; Jose Arturo Farfan-Ale, Laboratorio de Arbovirologia, Universidad Autónoma de Yucatan, Merida, Yucatan, Mexico; Maria Alba Loroño-Pino, Laboratorio de Arbovirologia, Universidad Autónoma de Yucatan, Merida, Yucatan, Mexico; Julian Garcia-Rejon, Laboratorio de Arbovirologia, Universidad Autónoma de Yucatan, Merida, Yucatan, Mexico; Salvador Gomez-Carro, Servicios de Salud de Yucatan, Merida, Yucatan, Mexico; Victor Lira-Zumbardo, Servicios de Salud de Yucatan, Merida, Yucatan, Mexico; Rosario Najera-Vazquez, Servicios de Salud de Yucatan, Merida, Yucatan, Mexico; Ildefonso Fernandez-Salas, Laboratorio de Entomología Medica, Universidad Autonoma de Nuevo Leon, Monterrey, Nuevo Leon, Mexico; Joaquin Calderon-Martinez, Servicios Estatales de Salud de Quintana Roo, Chetumal, Quintana Roo, Mexico; Marco Dominguez-Galera, Servicios Estatales de Salud de Quintana Roo, Chetumal, Quintana Roo, Mexico; Pedro Mis-Avila, Servicios Estatales de Salud de Quintana Roo, Chetumal, Quintana Roo, Mexico; Natashia Morris, Malaria Research Programme, Medical Research Council, Durban, South Africa; Michael Coleman, Liverpool School of Tropical Medicine, Liverpool, England; Chester G Moore, Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO, USA; Barry J Beaty, Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO, USA; and Lars Eisen, Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO, US

Long-term biosignals visualization and processing

Thesis submitted in the fulfillment of the requirements for the Degree of Master in Biomedical EngineeringLong-term biosignals acquisitions are an important source of information about the patients’state and its evolution. However, long-term biosignals monitoring involves managing extremely large datasets, which makes signal visualization and processing a complex task. To overcome these problems, a new data structure to manage long-term biosignals was developed. Based on this new data structure, dedicated tools for long-term biosignals visualization and processing were implemented. A multilevel visualization tool for any type of biosignals, based on subsampling is presented, focused on four representative signal parameters (mean, maximum, minimum and standard deviation error). The visualization tool enables an overview of the entire signal and a more detailed visualization in specific parts which we want to highlight, allowing an user friendly interaction that leads to an easier signal exploring. The ”map” and ”reduce” concept is also exposed for long-term biosignal processing. A processing tool (ECG peak detection) was adapted for long-term biosignals. In order to test the developed algorithm, long-term biosignals acquisitions (approximately 8 hours each) were carried out. The visualization tool has proven to be faster than the standard methods, allowing a fast navigation over the different visualization levels of biosignals. Regarding the developed processing algorithm, it detected the peaks of long-term ECG signals with fewer time consuming than the nonparalell processing algorithm. The non-specific characteristics of the new data structure, visualization tool and the speed improvement in signal processing introduced by these algorithms makes them powerful tools for long-term biosignals visualization and processing