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Creative activities
Published in Jan Woodhouse, Dorothy Marriss, Strategies for Healthcare Education, 2019
In addition to the above, the concept of neurolinguistic programming (NLP) considers that individuals use a preferred mode of thinking – in sounds, pictures and feeling.10 So while one student might enjoy music, another might prefer using paints to produce some artwork, and yet another might prefer a tactile experience such as using clay or different fabrics.
Nail lichen planus
Published in Archana Singal, Shekhar Neema, Piyush Kumar, Nail Disorders, 2019
Iffat Hassan, Mohammad Abid Keen, Yasmeen Jabeen Bhat
Treatment of NLP is difficult and disappointing. Treatment depends on the stage and severity of nail damage (Table 14.5). Topical corticosteroid therapy is commonly considered as a first-line treatment for NLP, although it is usually ineffective. If more than three nails are involved, systemic corticosteroids (oral prednisone and intramuscular triamcinolone acetonide) are considered as a first-line treatment; however, prolonged or repeated use of systemic corticosteroids may cause considerable side effects.23 Intralesional steroid injections have also been seen to be efficacious in treating NLP.24 For involvement of up to three nails, intralesional steroid injections can be considered, but such injections are very painful and relapses are common.25 Topical tacrolimus has been seen to be effective in treating NLP and was found to be more effective than topical corticosteroids.26 Patients not responding to corticosteroids can be treated with second line medications like antimalarials,27 retinoids like acitretin,28 or alitretinoin29 and cyclosporine.30 Etanercept has been found to be an effective treatment modality for LP limited particularly to the nails.31 Severe cases with permanent damage to the nail matrix that has resulted in scarring and pterygium formation can only be treated with surgery. There are two methods to repair a split nail depending on the width of the cicatricial pterygium: excision with a meticulous repair or free matrix graft.32
Checkpoint 1 (Connecting): rapport-building skills
Published in Roger Neighbour, The Inner Consultation, 2018
Many of the items in this diagram you will be perfectly familiar with. I should like, however, to explain its general concept, and some of the items which may not at first seem relevant. Many of the ideas it incorporates have been extensively developed in a therapeutic approach called ‘Neuro-Linguistic Programming (NLP).1
Incurable Blindness: The Final Frontier in Vision Restoration
Published in Seminars in Ophthalmology, 2023
Currently, there are no vision restorative procedures for patients with NLP. Newer treatments such as gene therapy, nerve regeneration procedures, or whole eyeball transplantation represent a ray of hope to all who need radical vision restoration. Some of these have found mention among the “audacious goals” initiative of the National Eye Institute (NEI).17 Regenerative therapy, retinal and ciliary body transplantation and whole eyeball transplantation are strategies that must be developed to aid patients who currently have no possibility of restoring vision, even though preventive actions can somewhat lessen the problem. Just as important is an epidemiological understanding of the causes of such profoundly impairing conditions. While their numbers are small relative to the overall disease burden, sight restoration for people with NLP blindness can transform lives and push forward the frontiers of medicine.
Clinical documentation of patient-reported medical cannabis use in primary care: Toward scalable extraction using natural language processing methods
Published in Substance Abuse, 2022
David S. Carrell, David J. Cronkite, Mary Shea, Malia Oliver, Casey Luce, Theresa E. Matson, Jennifer F. Bobb, Clarissa Hsu, Ingrid A. Binswanger, Kendall C. Browne, Andrew J. Saxon, Jennifer McCormack, Eve Jelstrom, Udi E. Ghitza, Cynthia I. Campbell, Katharine A. Bradley, Gwen T. Lapham
We considered an NLP algorithm with ≥90% positive predictive value (PPV, at the mention-level, defined here as the proportion of medical use descriptions identified by the algorithm that truly document medical use according to the gold standard) and ≥90% sensitivity (the proportion of actual medical use descriptions in the corpus identified by the algorithm) to be suitable for determining which screens describe medical use and which do not because performance at these levels approach that of manual review. We did not know whether developing such a high-performing NLP algorithm was possible. However, we were confident that a gold standard annotated corpus could be used to calibrate an algorithm with high mention-level PPV—at the expense of sensitivity—and that algorithm performance could be validated in a random subset of the annotated gold standard corpus set aside specifically for such evaluation. An algorithm with high mention-level PPV and low sensitivity would still be useful for identifying positive documentation of medical use, but could not be used to determine when such documentation was absent since low sensitivity yields unacceptably high rates of false negatives (i.e., concluding that descriptions of medical use were absent when in fact they existed). We therefore planned to use the automated NLP algorithm to identify some screens with documented medical use and, if the algorithm’s sensitivity was below 90%, use NLP-assisted manual review to resolve notes for the remaining screens.
How to replace a physiotherapist: artificial intelligence and the redistribution of expertise
Published in Physiotherapy Theory and Practice, 2022
Michael Rowe, David A. Nicholls, James Shaw
The development of computers that can use natural language processing (NLP) to imitate human interaction means that soon it may not be possible to know whether one is speaking to a person or a machine. In the clinical context, NLP is being used to generate structured, annotated text from unstructured clinical records that enable the automation of clinical workflows at volumes and speeds that human beings are incapable of achieving (Cai et al., 2016; Jackson et al., 2017). In addition, NLP may soon be used to transcribe and summarize conversations between clinicians and patients that will then only need to be approved by the care provider (Kreimeyer et al., 2017). The recording of clinician-patient conversations will also enable the conversion of unstructured human conversation into semantic data, allowing the automated capture of symptoms, medications, and other clinically relevant information directly into the EHR, lowering the risk of data capturing errors and reducing clinician burnout (Kroth et al., 2019). This will also facilitate new forms of clinical research by identifying patterns and relationships across large databases of patient records, which are too numerous and complex for human beings to recognize. As conversational user interfaces become ubiquitous in our devices and virtual personal assistants (VPAs) it will become increasingly difficult to know when our interactions are being mediated by software (Levy, 2016), opening up a wide range of ethical and legal concerns that are nowhere more pressing than in healthcare systems.