Back

Clinicians opinions, views and expectations on radiological reports: multicentre cross-sectional study in Dar es Salaam region.

Danda, A. F.; Nkrumbih, Z.; Fundikira, L.; Hella, J.

2025-11-25 radiology and imaging
10.1101/2025.11.23.25340851 medRxiv
Show abstract

BackgroundRadiology reports are the primary communication tool between radiologists and clinicians. They guide diagnosis, treatment, and follow-up care, yet in many settings there are no formal feedback mechanisms to improve their quality. In Tanzania, where medical imaging capacity is rapidly expanding, evidence on clinicians perceptions of report quality remains scarce. MethodsA multicenter cross-sectional study was conducted in the Dar es Salaam region involving 320 clinicians. Data were collected using a self-administered questionnaire and Google Forms. Descriptive statistics were applied to summarize clinicians responses, and chi-square tests were used to assess associations. ResultsMost clinicians reported positive opinions regarding the understandability (79%), clarity (92%), and relevance (91%) of radiology reports. A standardized report format was preferred by 83% of respondents. Preferences for the location of positive findings were nearly evenly split (54% favored reporting them first vs. 46% at the respective anatomical location). Use of standardized lexicons or grading systems was supported by 93% of clinicians, while 55% valued clarification of radiological terms in the conclusion. Overall, 87% were satisfied with report content and 86% expressed general satisfaction, recognizing radiology reports as critical for clinical decision-making. Report delays and inadequate timely communication of urgent findings were identified as key shortcomings. ConclusionsClinicians in Dar es Salaam expressed overall satisfaction with the clarity, relevance, and structure of radiology reports, while highlighting the need for timely delivery and improved direct communication of critical findings.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.