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  • 1.
    Ekberg, Joakim
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Health Sciences.
    Gursky, Elin A.
    Analytic Services Inc., Arlington, VA, USA.
    Timpka, Toomas
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Health and Developmental Care, Center for Public Health.
    Pre-launch evaluation checklist for online health-promoting communities2014In: Journal of Biomedical Informatics, ISSN 1532-0464, E-ISSN 1532-0480, Vol. 47, p. 11-17Article in journal (Refereed)
    Abstract [en]

    BACKGROUND:

    Despite the apparent potential of online health-promoting communities (OHPC), there is limited guidance available for developers on the basic design features that contribute to successful applications. The aim of this study was to develop a checklist for a pre-launch evaluation of OHPCs incorporating the perspectives of both the user and the health services communities.

    METHODS:

    The study was based on an action research design. Constructs previously applied to evaluate information system success were used as the basis for checklist development. The constructs were adapted for the OHPC context and formatively evaluated in a case study project. Evaluation data were collected from participatory observations and analyzed using qualitative methods.

    RESULTS:

    The initial OHPC checklist included the constructs information quality, service quality, and subjective norms. The contextual adaptation of the information quality construct resulted in items for content area, trust, and format; the adaptation of the service quality construct in items for staff competence, prompt service and empathy; and the adaptation of the subject norms construct in items for social facilitation, interconnectivity and communication. The formative evaluation demonstrated the critical need to balance the autonomy of the online community with the professional control of health services quality expressed in the information and service quality constructs.

    CONCLUSIONS:

    A pre-launch OHPC evaluation checklist has been designed for use in practical development of health promotion web resources. Research on instruments for OHPC evaluations is warranted.

  • 2.
    Irestig, Magnus
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, MDALAB - Human Computer Interfaces.
    Timpka, Toomas
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Division of Preventive and Social Medicine and Public Health Science. Östergötlands Läns Landsting, FHVC - Folkhälsovetenskapligt centrum.
    Politics and technology in health information systems development: A discourse analysis of conflicts addressed in a systems design group2008In: Journal of Biomedical Informatics, ISSN 1532-0464, E-ISSN 1532-0480, Vol. 41, no 1, p. 82-94Article in journal (Refereed)
    Abstract [en]

    Different types of disagreements must be managed during the development of health information systems. This study examines the antagonisms discussed during the design of an information system for 175,000 users in a public health context. Discourse analysis methods were used for data collection and analysis. Three hundred and twenty-six conflict events were identified from four design meetings and divided into 16 categories. There were no differences regarding the types of conflicts that the different participants brought into the design discussions. Instead, conflict occurrence was primarily affected by the agendas that set the stage for examinations and debates. The results indicate that the selection of design method and the structure used for the meetings are important factors for the manner in which conflicts are brought into consideration during health information system design. Further studies comparing participatory and non-participatory information system design practices in health service settings are warranted. © 2007 Elsevier Inc. All rights reserved.

  • 3. Martin-Sanchez, F.
    et al.
    Babic, Ankica
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Doupi, P.
    Orphanoudakis, S.
    de Moor, G.
    Kulikowski, C.
    Iakovidis, I.
    Sarachan, B.
    Hermosilla, I.
    Sousa, A.
    Thireos, G.
    Abraham-Fuchs, K.
    Engelbrecht, R.
    Lampe, K.
    de Groen, P.
    Cinquin, P.
    Van der Lei, J.
    Vicente, F.J.
    Baud, R.
    Jehenson, P.
    Zahlmann, G.
    Jones, T.
    Breton, V.
    Ghazal, P.
    Dugas, M.
    Eils, R.
    Nörager, S.
    Apweiler, R.
    Rossing, N.
    Zvarova, J.
    Spekowius, G.
    Maojo, V.
    Synergy between medical informatics and bioinformatics: Facilitating genomic medicine for future health care2004In: Journal of Biomedical Informatics, ISSN 1532-0464, E-ISSN 1532-0480, Vol. 37, no 1, p. 30-42Article in journal (Refereed)
    Abstract [en]

    In this paper, we review the results of BIOINFOMED, a study funded by the European Commission (EC) with the purpose to analyse the different issues and challenges in the area where Medical Informatics and Bioinformatics meet. Traditionally, Medical Informatics has been focused on the intersection between computer science and clinical medicine, whereas Bioinformatics have been predominantly centered on the intersection between computer science and biological research. Although researchers from both areas have occasionally collaborated, their training, objectives and interests have been quite different. The results of the Human Genome and related projects have attracted the interest of many professionals, and introduced new challenges that will transform biomedical research and health care. A characteristic of the 'post genomic' era will be to correlate essential genotypic information with expressed phenotypic information. In this context, Biomedical Informatics (BMI) has emerged to describe the technology that brings both disciplines (BI and MI) together to support genomic medicine. In recognition of the dynamic nature of BMI, institutions such as the EC have launched several initiatives in support of a research agenda, including the BIOINFOMED study.

  • 4.
    Oluoch, Tom
    et al.
    US Centre Disease Control and Prevent, Kenya.
    de Keizer, Nicolette
    University of Amsterdam, Netherlands.
    Langat, Patrick
    Kenya Govt Medical Research Centre, Kenya.
    Alaska, Irene
    Kenya Govt Medical Research Centre, Kenya.
    Ochieng, Kenneth
    Kenya Govt Medical Research Centre, Kenya.
    Okeyo, Nicky
    Kenya Govt Medical Research Centre, Kenya.
    Kwaro, Daniel
    Kenya Govt Medical Research Centre, Kenya.
    Cornet, Ronald
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Faculty of Science & Engineering. University of Amsterdam, Netherlands.
    A structured approach to recording AIDS-defining illnesses in Kenya: A SNOMED CT based solution2015In: Journal of Biomedical Informatics, ISSN 1532-0464, E-ISSN 1532-0480, Vol. 56, p. 387-394Article in journal (Refereed)
    Abstract [en]

    Introduction: Several studies conducted in sub-Saharan Africa (SSA) have shown that routine clinical data in HIV clinics often have errors. Lack of structured and coded documentation of diagnosis of AIDS defining illnesses (ADIs) can compromise data quality and decisions made on clinical care. Methods: We used a structured framework to derive a reference set of concepts and terms used to describe ADIs. The four sources used were: (i) CDC/Accenture list of opportunistic infections, (ii) SNOMED Clinical Terms (SNOMED CT), (iii) Focus Group Discussion (FGD) among clinicians and nurses attending to patients at a referral provincial hospital in western Kenya, and (iv) chart abstraction from the Maternal Child Health (MCH) and HIV clinics at the same hospital. Using the January 2014 release of SNOMED CT, concepts were retrieved that matched terms abstracted from approach iii and iv, and the content coverage assessed. Post-coordination matching was applied when needed. Results: The final reference set had 1054 unique ADI concepts which were described by 1860 unique terms. Content coverage of SNOMED CT was high (99.9% with pre-coordinated concepts; 100% with post-coordination). The resulting reference set for ADIs was implemented as the interface terminology on OpenMRS data entry forms. Conclusion: Different sources demonstrate complementarity in the collection of concepts and terms for an interface terminology. SNOMED CT provides a high coverage in the domain of ADIs. Further work is needed to evaluate the effect of the interface terminology on data quality and quality of care.

  • 5.
    Petersson, Håkan
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Gill, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Åhlfeldt, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    A variance-based measure of inter-rater agreement in medical databases2002In: Journal of Biomedical Informatics, ISSN 1532-0464, E-ISSN 1532-0480, Vol. 35, no 5-6, p. 331-342Article in journal (Refereed)
    Abstract [en]

    The increasing use of encoded medical data requires flexible tools for data quality assessment. Existing methods are not always adequate, and this paper proposes a new metric for inter-rater agreement of aggregated diagnostic data. The metric, which is applicable in prospective as well as retrospective coding studies, quantifies the variability in the coding scheme, and the variation can be differentiated in categories and in coders. Five alternative definitions were compared in a set of simulated coding situations and in the context of mortality statistics. Two of them were more effective, and the choice between them must be made according to the situation. The metric is more powerful for larger numbers of coded cases, and Type I errors are frequent when coding situations include different numbers of cases. We also show that it is difficult to interpret the meaning of variation when the structures of the compared coding schemes differ.

  • 6.
    Rosenbeck Goeg, Kirstine
    et al.
    Aalborg University, Denmark.
    Cornet, Ronald
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Faculty of Science & Engineering. University of Amsterdam, Netherlands.
    Kjaer Andersen, Stig
    Aalborg University, Denmark.
    Clustering clinical models from local electronic health records based on semantic similarity2015In: Journal of Biomedical Informatics, ISSN 1532-0464, E-ISSN 1532-0480, Vol. 54, p. 294-304Article in journal (Refereed)
    Abstract [en]

    Background: Clinical models in electronic health records are typically expressed as templates which support the multiple clinical workflows in which the system is used. The templates are often designed using local rather than standard information models and terminology, which hinders semantic interoperability. Semantic challenges can be solved by harmonizing and standardizing clinical models. However, methods supporting harmonization based on existing clinical models are lacking. One approach is to explore semantic similarity estimation as a basis of an analytical framework. Therefore, the aim of this study is to develop and apply methods for intrinsic similarity-estimation based analysis that can compare and give an overview of multiple clinical models. Method: For a similarity estimate to be intrinsic it should be based on an established ontology, for which SNOMED CT was chosen. In this study, Lin similarity estimates and Sokal and Sneath similarity estimates were used together with two aggregation techniques (average and best-match-average respectively) resulting in a total of four methods. The similarity estimations are used to hierarchically cluster templates. The test material consists of templates from Danish and Swedish EHR systems. The test material was used to evaluate how the four different methods perform. Result and discussion: The best-match-average aggregation technique performed better in terms of clustering similar templates than the average aggregation technique. No difference could be seen in terms of the choice of similarity estimate in this study, but the finding may be different for other datasets. The dendrograms resulting from the hierarchical clustering gave an overview of the templates and a basis of further analysis. Conclusion: Hierarchical clustering of templates based on SNOMED CT and semantic similarity estimation with best-match-average aggregation technique can be used for comparison and summarization of multiple templates. Consequently, it can provide a valuable tool for harmonization and standardization of clinical models.

  • 7.
    Ölvingson, Christina
    et al.
    Linköping University, Department of Computer and Information Science. Linköping University, The Institute of Technology.
    Hallberg, Jonas
    Linköping University, Department of Computer and Information Science. Linköping University, The Institute of Technology.
    Timpka, Toomas
    Linköping University, Department of Computer and Information Science. Linköping University, Department of Department of Health and Society. Linköping University, The Institute of Technology.
    Lindqvist, Kent
    Linköping University, Department of Computer and Information Science. Linköping University, Department of Department of Health and Society. Linköping University, The Institute of Technology.
    Ethical issues in public health informatics: implications for system design when sharing geographic information2002In: Journal of Biomedical Informatics, ISSN 1532-0464, E-ISSN 1532-0480, Vol. 35, no 3, p. 178-185Article in journal (Refereed)
    Abstract [en]

    Public health programs today constitute a multi-professional inter-organizational environment, where both health service and other organizations are involved. Developing information systems, including the IT security measures needed to suit this complex context, is a challenge. To ensure that all involved organizations work together towards a common goal, i.e., promotion of health, an intuitive strategy would be to share information freely in these programs. However, in practice it is seldom possible to realize this ideal scenario. One reason may be that ethical issues are often ignored in the system development process. This investigation uses case study methods to explore ethical obstacles originating in the shared use of geographic health information in public health programs and how this affects the design of information systems. Concerns involving confidentiality caused by geographically referenced health information and influences of professional and organizational codes are discussed. The experience presented shows that disregard of ethical issues can result in a prolonged development process for public health information systems. Finally, a theoretical model of design issues based on the case study results is presented.

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