title: Dense Annotation of Free-Text Critical Care Discharge Summaries from an Indian Hospital and Associated Performance of a Clinical NLP Annotator.
abstract: Electronic Health Record (EHR) use in India is generally poor, and structured clinical information is mostly lacking. This work is the first attempt aimed at evaluating unstructured text mining for extracting relevant clinical information from Indian clinical records. We annotated a corpus of 250 discharge summaries from an Intensive Care Unit (ICU) in India, with markups for diseases, procedures, and lab parameters, their attributes, as well as key demographic information and administrative variables such as patient outcomes. In this process, we have constructed guidelines for an annotation scheme useful to clinicians in the Indian context. We evaluated the performance of an NLP engine, Cocoa, on a cohort of these Indian clinical records. We have produced an annotated corpus of roughly 90 thousand words, which to our knowledge is the first tagged clinical corpus from India. Cocoa was evaluated on a test corpus of 50 documents. The overlap F-scores across the major categories, namely disease/symptoms, procedures, laboratory parameters and outcomes, are 0.856, 0.834, 0.961 and 0.872 respectively. These results are competitive with results from recent shared tasks based on US records. The annotated corpus and associated results from the Cocoa engine indicate that unstructured text mining is a viable method for cohort analysis in the Indian clinical context, where structured EHR records are largely absent.
authors.affiliation: RelAgent Technologies (P) Limited, IIT Madras Research Park, #14, 1st Floor, Taramani, Chennai, 600113, India. ramanan@relagent.com.
authors.forename: S V
authors.initials: SV
authors.lastname: Ramanan
authors.affiliation: Division of Medical Informatics, St. John's Research Institute, 100 Feet Road, Koramangala, Bangalore, 560034, India. kedar.angirus@gmail.com.
authors.forename: Kedar
authors.identifier: http://orcid.org/0000-0002-2334-5285
authors.initials: K
authors.lastname: Radhakrishna
authors.affiliation: Division of Medical Informatics, St. John's Research Institute, 100 Feet Road, Koramangala, Bangalore, 560034, India.
authors.forename: Abijeet
authors.initials: A
authors.lastname: Waghmare
authors.affiliation: Division of Medical Informatics, St. John's Research Institute, 100 Feet Road, Koramangala, Bangalore, 560034, India.
authors.forename: Tony
authors.initials: T
authors.lastname: Raj
authors.affiliation: RelAgent Technologies (P) Limited, IIT Madras Research Park, #14, 1st Floor, Taramani, Chennai, 600113, India.
authors.forename: Senthil P
authors.initials: SP
authors.lastname: Nathan
authors.affiliation: Division of Medical Informatics, St. John's Research Institute, 100 Feet Road, Koramangala, Bangalore, 560034, India.
authors.forename: Sai Madhukar
authors.initials: SM
authors.lastname: Sreerama
authors.affiliation: Department of Critical Care Medicine, St. John's Medical College, Bangalore, India.
authors.forename: Sriram
authors.initials: S
authors.lastname: Sampath
mesh_terms: D000367:Age Factors; D003422:Critical Care / Q000706:statistics & numerical data*; D057225:Data Mining / Q000379:methods*; D019937:Diagnostic Techniques and Procedures; D057286:Electronic Health Records / Q000706:statistics & numerical data*; D006801:Humans; D007194:India; D009323:Natural Language Processing; D010351:Patient Discharge / Q000706:statistics & numerical data*; D012737:Sex Factors; D012959:Socioeconomic Factors
keywords: Biomedical text extraction; Data mining; Discharge summary; Natural language processing; Text annotation