This investigation aimed at determining whether an acoustic quantification of the oral diadochokinetic (DDK) task may be used to predict the perceived level of speech impairment when speakers with Parkinson's disease (PD) are reading a standard passage. DDK sequences with repeated [pa], [ta], and [ka] syllables were collected from 108 recordings (68 unique speakers with PD), along with recordings of the speakers reading a standardized text. The passage readings were assessed in five dimensions individually by four speech-language pathologists in a blinded and randomized procedure. The 46 acoustic DDK measures were merged with the perceptual ratings of read speech in the same recording session. Ordinal regression models were trained repeatedly on 80% of ratings and acoustic DDK predictors per dimension in 10-folds, and evaluated in testing data. The models developed from [ka] sequences achieved the best performance overall in predicting the clinicians' ratings of passage readings. The developed [pa] and [ta] models showed a much lower performance across all dimensions. The addition of samples with severe impairments and further automation of the procedure is required for the models to be used for screening purposes by non-expert clinical staff.