[Optimizing radiological diagnostic management via mobile devices in trauma surgery]. / Anforderung von radiologischer Diagnostik in der Unfallchirurgie mittels mobiler Endgeräte.

BACKGROUND: Time is a scarce resource for physicians. One medical task is the request for radiological diagnostics. This process is characterized by high administrative complexity and sometimes considerable time consumption. Measures that lead to an administrative relief in favor of patient care have so far been lacking. AIM OF THE STUDY: Process optimization of the request for radiological diagnostics. As a proof of concept the request for radiological diagnostics was conducted using a mobile, smartphone and tablet-based application with dedicated voice recognition software in the Department of Trauma Surgery at the University Hospital of Würzburg (UKW). MATERIAL AND METHODS: In a prospective study, time differences and efficiency of the mobile app-based method (ukw.mobile based Application = UMBA) compared to the PC-based method (PC-based application = PCBA) for requesting radiological services were analyzed. The time from the indications to the completed request and the time required to create the request on the device were documented and assessed. Due to the non-normal distribution of the data, a Mann-Whitney U test was performed. RESULTS: The time from the indications to the completed request was significantly (p < 0.05) reduced using UMBA compared to PCBA (PCBA: mean ± standard difference [SD] 19.57 ± 33.24 min, median 3.00 min, interquartile range [IQR] 1.00-30.00 min vs. UMBA: 9.33 ± 13.94 min, median 1.00 min, IQR 0.00-20.00 min). The time to complete the request on the device was also significantly reduced using UMBA (PCBA: mean ± SD 63.77 ± 37.98 s, median 51.96 s, IQR 41.68-68.93 s vs. UMBA: 25.21 ± 11.18 s, median 20.00 s, IQR 17.27-29.00 s). CONCLUSION: The mobile, voice-assisted request process leads to a considerable time reduction in daily clinical routine and illustrates the potential of user-oriented, targeted digitalization in healthcare. In future, the process will be supported by artificial intelligence.

Usability of a mHealth Solution using Speech Recognition for Point-of-care Diagnostic Management.

The administrative burden for physicians in the hospital can affect the quality of patient care. The Service Center Medical Informatics (SMI) of the University Hospital Würzburg developed and implemented the smartphone-based mobile application (MA) ukw.mobile1 that uses speech recognition for the point-of-care ordering of radiological examinations. The aim of this study was to examine the usability of the MA workflow for the point-of-care ordering of radiological examinations. All physicians at the Department of Trauma and Plastic Surgery at the University Hospital Würzburg, Germany, were asked to participate in a survey including the short version of the User Experience Questionnaire (UEQ-S) and the Unified Theory of Acceptance and Use of Technology (UTAUT). For the analysis of the different domains of user experience (overall attractiveness, pragmatic quality and hedonic quality), we used a two-sided dependent sample t-test. For the determinants of the acceptance model, we employed regression analysis. Twenty-one of 30 physicians (mean age 34 ± 8 years, 62% male) completed the questionnaire. Compared to the conventional desktop application (DA) workflow, the new MA workflow showed superior overall attractiveness (mean difference 2.15 ± 1.33), pragmatic quality (mean difference 1.90 ± 1.16), and hedonic quality (mean difference 2.41 ± 1.62; all p < .001). The user acceptance measured by the UTAUT (mean 4.49 ± 0.41; min. 1, max. 5) was also high. Performance expectancy (beta = 0.57, p = .02) and effort expectancy (beta = 0.36, p = .04) were identified as predictors of acceptance, the full predictive model explained 65.4% of its variance. Point-of-care mHealth solutions using innovative technology such as speech-recognition seem to address the users' needs and to offer higher usability in comparison to conventional technology. Implementation of user-centered mHealth innovations might therefore help to facilitate physicians' daily work.

Point-of-Care Speech-Recognition Based mHealth Solution to Facilitate Physicians' Daily Work.

We developed and implemented a smartphone-based mobile application that uses speech recognition for the point-of-care ordering of radiological examinations. 21 out of 30 physicians completed a usability questionnaire including the Short version of the User Experience Questionnaire (UEQ-S) and the Unified Theory of Acceptance and Use of Technology (UTAUT). The mobile application showed high user acceptance and superior user experience when compared to the conventional workflow. Due to the high usability of our mHealth solution, it might help to facilitate the physician's daily work.

Nanogels Enable Efficient miRNA Delivery and Target Gene Downregulation in Transfection-Resistant Multiple Myeloma Cells.

Multiple myeloma is a common plasma-cell-derived hematologic neoplasm. While the delivery of growth-inhibiting miRNA to multiple myeloma cells would be a promising strategy to evaluate treatment options, most multiple myeloma cells are transfection-resistant with established methods. Nonviral nanoparticulate transfection systems are particularly promising in this context, but so far struggle with transfection and knockdown efficiency. Here, we present poly(glycidol)-based nanogels with covalently bound cell-penetrating peptide TAT (transactivator of transcription from HIV). TAT facilitated a varying internalization efficiency of the nanogels depending on the cell line. The positively charged peptide also served as complexation agent for miRNA and enabled covalent binding of the TAT/miR-34a complex in the nanogels. These TAT/miRNA-loaded nanogels delivered and released miR-34a with high efficiency into OPM-2 multiple myeloma cells that are known as transfection-resistant. Delivery resulted in efficient downregulation of known target genes such as Notch1, Hey1, Hes6, and Hes1. Thus, these nanogel constructs offer a new tool to enhance gene delivery into multiple myeloma cells with immediate value in cancer research.