Literature DB >> 33511485

Structured Digital Self-Assessment of Patient Anamnesis Prior to Computed Tomography: Performance Evaluation and Added Value.

M Kopp1, M Wetzl2, F Geissler2, J P Roth2, R Wallner3,4, D Hoefler3,5, S Faby5, T Allmendinger5, P Amarteifio5,6, W Wuest2,6, A Cavallaro2,6, M Uder2,6, M S May2,6.   

Abstract

The aim of this study was to evaluate the performance of a tablet-based, digitized structured self-assessment (DSSA) of patient anamnesis (PA) prior to computed tomography (CT). Of the 317 patients consecutively referred for CT, the majority (n = 294) was able to complete the tablet-based questionnaire, which consisted of 67 items covering social anamnesis, lifestyle factors (e.g., tobacco abuse), medical history (e.g., kidney diseases), current symptoms, and the usability of the system. Patients were able to mark unclear questions for a subsequent discussion with the radiologist. Critical issues for the CT examination were structured and automatically highlighted as "red flags" (RFs) in order to improve patient interaction. RFs and marked questions were highly prevalent (69.5% and 26%). Missing creatinine values (33.3%), kidney diseases (14.4%), thyroid diseases (10.6%), metformin (5.5%), claustrophobia (4.1%), allergic reactions to contrast agents (2.4%), and pathological TSH values (2.0%) were highlighted most frequently as RFs. Patient feedback regarding the comprehensibility of the questionnaire and the tablet usability was mainly positive (90.9%; 86.2%). With advanced age, however, patients provided more negative feedback for both (p = 0.007; p = 0.039). The time effort was less than 20 min for 85.1% of patients, and faster patients were significantly younger (p = 0.046). Overall, the DSSA of PA prior to CT shows a high success rate and is well accepted by most patients. RFs and marked questions were common and helped to focus patients' interactions and reporting towards decisive aspects.

Entities:  

Keywords:  Computed tomography; Digital informed patient consent; Digital medical history; Mobile devices; Structured anamnesis

Mesh:

Year:  2021        PMID: 33511485      PMCID: PMC7843739          DOI: 10.1007/s10916-020-01690-8

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.460


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