Browsing by Subject "Medical Informatics Applications"

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    Automatic identification of variables in epidemiological datasets using logic regression.
    (BMC medical informatics and decision making, 2017-04) Lorenz, Matthias W; Abdi, Negin Ashtiani; Scheckenbach, Frank; Pflug, Anja; Bülbül, Alpaslan; Catapano, Alberico L; Agewall, Stefan; Ezhov, Marat; Bots, Michiel L; Kiechl, Stefan; Orth, Andreas; PROG-IMT study group

    Background

    For an individual participant data (IPD) meta-analysis, multiple datasets must be transformed in a consistent format, e.g. using uniform variable names. When large numbers of datasets have to be processed, this can be a time-consuming and error-prone task. Automated or semi-automated identification of variables can help to reduce the workload and improve the data quality. For semi-automation high sensitivity in the recognition of matching variables is particularly important, because it allows creating software which for a target variable presents a choice of source variables, from which a user can choose the matching one, with only low risk of having missed a correct source variable.

    Methods

    For each variable in a set of target variables, a number of simple rules were manually created. With logic regression, an optimal Boolean combination of these rules was searched for every target variable, using a random subset of a large database of epidemiological and clinical cohort data (construction subset). In a second subset of this database (validation subset), this optimal combination rules were validated.

    Results

    In the construction sample, 41 target variables were allocated on average with a positive predictive value (PPV) of 34%, and a negative predictive value (NPV) of 95%. In the validation sample, PPV was 33%, whereas NPV remained at 94%. In the construction sample, PPV was 50% or less in 63% of all variables, in the validation sample in 71% of all variables.

    Conclusions

    We demonstrated that the application of logic regression in a complex data management task in large epidemiological IPD meta-analyses is feasible. However, the performance of the algorithm is poor, which may require backup strategies.
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    ItemOpen Access
    Defining core issues in utilizing information technology to improve access: evaluation and research agenda.
    (Journal of general internal medicine, 2011-11) Jackson, George L; Krein, Sarah L; Alverson, Dale C; Darkins, Adam W; Gunnar, William; Harada, Nancy D; Helfrich, Christian D; Houston, Thomas K; Klobucar, Thomas F; Nazi, Kim M; Poropatich, Ronald K; Ralston, James D; Bosworth, Hayden B
    The Department of Veterans Affairs (VA) has been at the vanguard of information technology (IT) and use of comprehensive electronic health records. Despite the widespread use of health IT in the VA, there are still a variety of key questions that need to be answered in order to maximize the utility of IT to improve patient access to quality services. This paper summarizes the potential of IT to enhance healthcare access, key gaps in current evidence linking IT and access, and methodologic challenges for related research. We also highlight four key issues to be addressed when implementing and evaluating the impact of IT interventions on improving access to quality care: 1) Understanding broader needs/perceptions of the Veteran population and their caregivers regarding use of IT to access healthcare services and related information. 2) Understanding individual provider/clinician needs/perceptions regarding use of IT for patient access to healthcare. 3) System/Organizational issues within the VA and other organizations related to the use of IT to improve access. 4) IT integration and information flow with non-VA entities. While the VA is used as an example, the issues are salient for healthcare systems that are beginning to take advantage of IT solutions.