Assessing Prevalence of Hypoglycemia in a Medical Transcription Database

Chioma Uzoigwe, Carol Mahler Hamersky, Deborah I Arbit, Wayne Weng, Michael S Radin Novo Nordisk Inc., Plainsboro, NJ, USACorrespondence: Chioma UzoigweNovo Nordisk Inc., 800 Scudders Mill Road, Plainsboro, NJ 08536, USATel +1 609 786 4317Email coms@novonordisk.comPurpose: The prevalence of hypoglyc...

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Autores principales:	Uzoigwe C, Hamersky CM, Arbit DI, Weng W, Radin MS
Formato:	article
Lenguaje:	EN
Publicado:	Dove Medical Press 2020
Materias:	natural language processing type 1 diabetes mellitus type 2 diabetes mellitus Specialties of internal medicine RC581-951
Acceso en línea:	https://doaj.org/article/55f0710e830c4a548bbff52dcc5574fa
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spelling	oai:doaj.org-article:55f0710e830c4a548bbff52dcc5574fa2021-12-02T12:06:42ZAssessing Prevalence of Hypoglycemia in a Medical Transcription Database1178-7007https://doaj.org/article/55f0710e830c4a548bbff52dcc5574fa2020-06-01T00:00:00Zhttps://www.dovepress.com/assessing-prevalence-of-hypoglycemia-in-a-medical-transcription-databa-peer-reviewed-article-DMSOhttps://doaj.org/toc/1178-7007Chioma Uzoigwe, Carol Mahler Hamersky, Deborah I Arbit, Wayne Weng, Michael S Radin Novo Nordisk Inc., Plainsboro, NJ, USACorrespondence: Chioma UzoigweNovo Nordisk Inc., 800 Scudders Mill Road, Plainsboro, NJ 08536, USATel +1 609 786 4317Email coms@novonordisk.comPurpose: The prevalence of hypoglycemia in patients with diabetes mellitus is likely underreported, particularly with regard to non-severe episodes, and representative estimates require more detailed data than claims or typical electronic health record (EHR) databases provide. This study examines the prevalence of hypoglycemia as identified in a medical transcription database.Patients and Methods: The Amplity Insights database contains medical content dictated by providers detailing patient encounters with health care professionals (HCPs) from across the United States. Natural language processing (NLP) was used to identify episodes of hypoglycemia using both symptom-based and non-symptom-based definitions of hypoglycemic events. This study examined records of 41,688 patients with type 1 diabetes mellitus and 317,399 patients with type 2 diabetes mellitus between January 1, 2016, and April 30, 2018.Results: Using a non-symptom-based definition, the prevalence of hypoglycemia was 18% among patients with T1DM and 8% among patients with T2DM. These estimates show the prevalence of hypoglycemia to be 2- to 9-fold higher than the 1% to 4% prevalence estimates suggested by claims database analyses.Conclusion: In this exploration of a medical transcription database, the prevalence of hypoglycemia was considerably higher than what has been reported via retrospective analyses from claims and EHR databases. This analysis suggests that data sources other than claims and EHR may provide a more in-depth look into discrepancies between the mention of hypoglycemia events during a health care visit and documentation of hypoglycemia in patient records.Keywords: natural language processing, type 1 diabetes mellitus, type 2 diabetes mellitusUzoigwe CHamersky CMArbit DIWeng WRadin MSDove Medical Pressarticlenatural language processingtype 1 diabetes mellitustype 2 diabetes mellitusSpecialties of internal medicineRC581-951ENDiabetes, Metabolic Syndrome and Obesity: Targets and Therapy, Vol Volume 13, Pp 2209-2216 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	natural language processing type 1 diabetes mellitus type 2 diabetes mellitus Specialties of internal medicine RC581-951
spellingShingle	natural language processing type 1 diabetes mellitus type 2 diabetes mellitus Specialties of internal medicine RC581-951 Uzoigwe C Hamersky CM Arbit DI Weng W Radin MS Assessing Prevalence of Hypoglycemia in a Medical Transcription Database
description	Chioma Uzoigwe, Carol Mahler Hamersky, Deborah I Arbit, Wayne Weng, Michael S Radin Novo Nordisk Inc., Plainsboro, NJ, USACorrespondence: Chioma UzoigweNovo Nordisk Inc., 800 Scudders Mill Road, Plainsboro, NJ 08536, USATel +1 609 786 4317Email coms@novonordisk.comPurpose: The prevalence of hypoglycemia in patients with diabetes mellitus is likely underreported, particularly with regard to non-severe episodes, and representative estimates require more detailed data than claims or typical electronic health record (EHR) databases provide. This study examines the prevalence of hypoglycemia as identified in a medical transcription database.Patients and Methods: The Amplity Insights database contains medical content dictated by providers detailing patient encounters with health care professionals (HCPs) from across the United States. Natural language processing (NLP) was used to identify episodes of hypoglycemia using both symptom-based and non-symptom-based definitions of hypoglycemic events. This study examined records of 41,688 patients with type 1 diabetes mellitus and 317,399 patients with type 2 diabetes mellitus between January 1, 2016, and April 30, 2018.Results: Using a non-symptom-based definition, the prevalence of hypoglycemia was 18% among patients with T1DM and 8% among patients with T2DM. These estimates show the prevalence of hypoglycemia to be 2- to 9-fold higher than the 1% to 4% prevalence estimates suggested by claims database analyses.Conclusion: In this exploration of a medical transcription database, the prevalence of hypoglycemia was considerably higher than what has been reported via retrospective analyses from claims and EHR databases. This analysis suggests that data sources other than claims and EHR may provide a more in-depth look into discrepancies between the mention of hypoglycemia events during a health care visit and documentation of hypoglycemia in patient records.Keywords: natural language processing, type 1 diabetes mellitus, type 2 diabetes mellitus
format	article
author	Uzoigwe C Hamersky CM Arbit DI Weng W Radin MS
author_facet	Uzoigwe C Hamersky CM Arbit DI Weng W Radin MS
author_sort	Uzoigwe C
title	Assessing Prevalence of Hypoglycemia in a Medical Transcription Database
title_short	Assessing Prevalence of Hypoglycemia in a Medical Transcription Database
title_full	Assessing Prevalence of Hypoglycemia in a Medical Transcription Database
title_fullStr	Assessing Prevalence of Hypoglycemia in a Medical Transcription Database
title_full_unstemmed	Assessing Prevalence of Hypoglycemia in a Medical Transcription Database
title_sort	assessing prevalence of hypoglycemia in a medical transcription database
publisher	Dove Medical Press
publishDate	2020
url	https://doaj.org/article/55f0710e830c4a548bbff52dcc5574fa
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Assessing Prevalence of Hypoglycemia in a Medical Transcription Database

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