Users’ Perspectives on a Picture Archiving and Communication System (PACS): An In-Depth Study in a Teaching Hospital in Kuwait
Bibliographic record
Abstract
BACKGROUND: Picture archiving and communication system (PACS) is a well-known imaging informatics application in health care organizations, specifically designed for the radiology department. Health care providers have exhibited willingness toward evaluating PACS in hospitals to ascertain the critical success and failure of the technology, considering that evaluation is a basic requirement. OBJECTIVE: This study aimed at evaluating the success of a PACS in a regional teaching hospital of Kuwait, from users' perspectives, using information systems success criteria. METHODS: An in-depth study was conducted by using quantitative and qualitative methods. This mixed-method study was based on: (1) questionnaires, distributed to all radiologists and technologists and (2) interviews, conducted with PACS administrators. RESULTS: In all, 60 questionnaires were received from the respondents. These included 39 radiologists (75% response rate) and 21 technologists (62% response rate), with the results showing almost three-quarters (74%, 44 of 59) of the respondents rating PACS positively and as user friendly. This study's findings revealed that the demographic data, including computer experience, was an insignificant factor, having no influence on the users' responses. The findings were further substantiated by the administrators' interview responses, which supported the benefits of PACS, indicating the need for developing a unified policy aimed at streamlining and improving the departmental workflow. CONCLUSIONS: The PACS had a positive and productive impact on the radiologists' and technologists' work performance. They were endeavoring to resolve current problems while keeping abreast of advances in PACS technology, including teleradiology and mobile image viewer, which is steadily increasing in usage in the Kuwaiti health system.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".