Development of a computerised decisions support system for renal risk drugs targeting primary healthcare. Issue 7 (6th July 2015) - Helldén, Anders; Al-Aieshy, Fadiea; Bastholm-Rahmner, Pia; Bergman, Ulf; Gustafsson, Lars L; Höök, Hans; Sjöviker, Susanne; Söderström, Anders; Odar-Cederlöf, Ingegerd
Abstract : Objectives: To assess general practitioners (GPs) experience from the implementation and use of a renal computerised decision support system (CDSS) for drug dosing, developed for primary healthcare, integrated into the patient's electronic health record (EHR), and building on estimation of the patient's creatinine clearance (ClCG ). Design: Qualitative research design by a questionnaire and a focus group discussion. Setting and participants: Eight GPs at two primary healthcare centres (PHCs). Interventions: The GP at PHC 1, and the project group, developed and tested the technical solution of the CDSS. Proof-of-concept was tested by seven GPs at PHC 2. They also participated in a group discussion and answered a questionnaire. A web window in the EHR gave drug and dosage in relation to ClCG . Each advice was according to three principles: If? Why? Because. Outcome measures: (1) The GPs' experience of 'easiness to use' and 'perceived usefulness' at PHC 2, based on loggings of use, answers from a questionnaire using a 5-point Likert scale, and answers from a focus group discussion. (2) The number of patients aged 65 years and older with an estimation of ClCG before and after the implementation of the CDSS. Results: The GPs found the CDSS fast, simple and easy to use. They appreciated the automatic presentation of the CICG status on opening the medication list, and the ability to actively look up specific drug recommendations in two steps. The CDSS scored high on the Likert scale. All GPs wanted to continue the use of the CDSS and to recommend it to others. The number of patients with an estimated ClCG increased 1.6-fold. Conclusions: Acceptance of the simple graphical interface of this push and pull renal CDSS was high among the primary care physicians evaluating this proof of concept. The graphical model should be useful for further development of renal decision support systems.