Evaluating Natural Language Processing Packages for Predicting Hospital-Acquired Pressure Injuries From Clinical Notes.

Incidence of hospital-acquired pressure injury, a key indicator of nursing quality, is directly proportional to adverse outcomes, increased hospital stays, and economic burdens on patients, caregivers, and society. Thus, predicting hospital-acquired pressure injury is important. Prediction models use structured data more often than unstructured notes, although the latter often contain useful patient information. We hypothesize that unstructured notes, such as nursing notes, can predict hospital-acquired pressure injury. We evaluate the impact of using various natural language processing packages to identify salient patient information from unstructured text. We use named entity recognition to identify keywords, which comprise the feature space of our classifier for hospital-acquired pressure injury prediction. We compare scispaCy and Stanza, two different named entity recognition models, using unstructured notes in Medical Information Mart for Intensive Care III, a publicly available ICU data set. To assess the impact of vocabulary size reduction, we compare the use of all clinical notes with only nursing notes. Our results suggest that named entity recognition extraction using nursing notes can yield accurate models. Moreover, the extracted keywords play a significant role in the prediction of hospital-acquired pressure injury.

Complications of thermal energy in knee surgery--Part II.

With the theoretical and reported complications of thermal energy use in the knee, an analysis of potential risks and benefits should be done on a case-by-case basis. Many of the basic science studies may not be directly applicable to clinical practice because they use normal (i.e., not diseased) tissues in animal models. Clinical studies are also dependent on surgical technique and equipment settings. With the benefits listed previously, however, it is likely that thermal energy will continue to play an important role in arthroscopic orthopedic surgery, and there are studies that strongly support its safety and efficacy. Janecki performed a retrospective review of 504 laser chondroplasties to determine safe parameters for Ho:YAG laser use in the knee [10]. In their series, they found an 88% patient satisfaction rate, no significant changes in the articular cartilage lesions in the failure group who underwent repeat arthroscopy, and no new cases of osteonecrosis. They concluded that the Ho:YAG laser was safe and recommended energy settings of less than or equal to 1 joule when performing chondroplasties, noncontact and tangential delivery of the laser beam, and maximizing laser spot size as methods for further decreasing complication rates. We agree with the above recommendations and with using the minimal power settings required to afford the desired surgical result. More studies are required to fully define the indications and consequences of thermal energy use in the knee.