Design of a Tablet Computer App for Facilitation of a Molecular Blood Culture Test in Clinical Microbiology and Preliminary Usability Evaluation
Bibliographic record
Abstract
BACKGROUND: User mobility is an important aspect of the development of clinical information systems for health care professionals. Mobile phones and tablet computers have obtained widespread use by health care professionals, offering an opportunity for supporting the access to patient information through specialized applications (apps) while supporting the mobility of the users. The use of apps for mobile phones and tablet computers may support workflow of complex tasks, for example, molecular-based diagnostic tests in clinical microbiology. Multiplex Blood Culture Test (MuxBCT) is a molecular-based diagnostic test used for rapid identification of pathogens in positive blood cultures. To facilitate the workflow of the MuxBCT, a specialized tablet computer app was developed as an accessory to the diagnostic test. The app aims to reduce the complexity of the test by step-by-step guidance of microscopy and to assist users in reaching an exact bacterial or fungal diagnosis based on blood specimen observations and controls. Additionally, the app allows for entry of test results, and communication thereof to the laboratory information system (LIS). OBJECTIVE: The objective of the study was to describe the design considerations of the MuxBCT app and the results of a preliminary usability evaluation. METHODS: The MuxBCT tablet app was developed and set up for use in a clinical microbiology laboratory. A near-live simulation study was conducted in the clinical microbiology laboratory to evaluate the usability of the MuxBCT app. The study was designed to achieve a high degree of realism as participants carried out a scenario representing the context of use for the MuxBCT app. As the MuxBCT was under development, the scenario involved the use of molecular blood culture tests similar to the MuxBCT for identification of microorganisms from positive blood culture samples. The study participants were observed, and their interactions with the app were recorded. After the study, the participants were debriefed to clarify observations. RESULTS: Four medical laboratory technicians, for example, representative of end users of the app, participated in the clinical simulation study. Using the MuxBCT app, the study participants successfully identified and reported all microorganisms from the positive blood cultures examined. Three of the four participants reported that they found the app useful, while one study participant reported that she would prefer to make notes on paper and later enter them into the LIS. CONCLUSIONS: The preliminary usability evaluation results indicate that use of the MuxBCT tablet app can facilitate the workflow of the MuxBCT diagnostic test.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".