High Throughput Phenotyping for Dimensional Psychopathology in Electronic Health Records

Abstract

This shows that natural language processing can be used to efficiently and transparently score clinical notes in terms of cognitive and psychopathologic domains.

Stratifying risk for dementia onset using large‐scale electronic health record data: A retrospective cohort study

“…We have previously described derivation and validation of a method for estimating neuropsychiatric symptom domains from narrative text . In brief, this method relies on recognizing a prespecified set of terms within a given symptom domain—cognition in this case.…”

“…For example, if there are 20 possible cognition‐related terms and 5 appear in a note, the note would be assigned a score of 5/20 (25%). The scoring approach is implemented as freely available software for inspection and the full list of tokens is available online at https://github.com/thmccoy/CQH-Dimensional-Phenotyper and described in the initial validation publication . Of note, this tool was not developed or trained to predict emergence of dementia in any way, but simply to capture dimensions of neuropsychiatric symptoms reflecting interest in conceptualizing illness as dimensional rather than categorical …”

“…In this analysis, continuous covariates were included directly. In keeping with prior work, we multiplied the cognitive burden score by 10 to simplify communication and reduce the size of model coefficients . To visualize censored data, we plotted Kaplan‐Meier curves by the quartile of the symptom burden score using ggplot2 version 3.1 and tested time‐to‐event differences among these groups using both univariate and stratified analysis with survival, version 2.43 .…”

“…For example, noncoded psychiatric symptoms captured in clinical documentation improve prediction of suicide risk, the subjective valence of notes predict all‐cause mortality, and symptoms or symptom domains predict future utilization . To extend the literature on the use of NLP in the clinical prediction of dementia risk stratification, we applied a recently validated approach to estimating cognitive symptoms in narrative notes from two large academic medical centers with distinct clinical populations . To evaluate the derived cognitive symptom scores, we examined the extent to which the cognitive score was associated with subsequent dementia risk among hospitalized individuals without a prior diagnosis of dementia.…”

Prevalence and Nature of Financial Considerations Documented in Narrative Clinical Records in Intensive Care Units

“…With the availability of machine learning methods to efficiently capture features in narrative clinical notes, it is possible to define concepts that might not otherwise be available for study at scale. 9 These methods have been applied successfully to a range of clinical problems, which are part of a transformative wave of artificial intelligence studies in medicine. However, to our knowledge, they have not yet been applied to understanding the role of financial considerations in health care decisions.…”