Using text prediction for facilitating input and improving readability of clinical text.
Text prediction has the potential for facilitating and speeding up the documentation work within health care, making it possible for health personnel to allocate less time to documentation and more time to patient care. It also offers a way to produce clinical text with fewer misspellings and abbreviations, increasing readability. We have explored how text prediction can be used for input of clinical text, and how the specific challenges of text prediction in this domain can be addressed. A text prediction prototype was constructed using data from a medical journal and from medical terminologies. This prototype achieved keystroke savings of 26% when evaluated on texts mimicking authentic clinical text. The results are encouraging, indicating that there are feasible methods for text prediction in the clinical domain.
KTH Royal Institute of Technology, Stockholm, Sweden.
Magnus
M
Ahltorp
Maria
M
Skeppstedt
Hercules
H
Dalianis
Maria
M
Kvist
D001185:Artificial Intelligence; D004282:Documentation / Q000379:methods*; D057286:Electronic Health Records / Q000145:classification*; D062527:Meaningful Use; D009323:Natural Language Processing; D010363:Pattern Recognition, Automated / Q000379:methods*; D013548:Sweden; D018875:Vocabulary, Controlled; D015443:Word Processing / Q000379:methods*; D014956:Writing