Measuring the hidden burden of violence: use of explicit and proxy codes in Minnesota injury hospitalizations, 2004–2014

Abstract Purpose Commonly-used violence surveillance systems are biased towards certain populations due to overreporting or over-scrutinized. Hospital discharge data may offer a more representative view of violence, through use of proxy codes, i.e. diagnosis of injuries correlated with violence. The...

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Autores principales:	N. Jeanie Santaularia, Marizen R. Ramirez, Theresa L. Osypuk, Susan M. Mason
Formato:	article
Lenguaje:	EN
Publicado:	BMC 2021
Materias:	Violent injury Surveillance Hospital data Child abuse Intimate partner violence Elder abuse Medical emergencies. Critical care. Intensive care. First aid RC86-88.9 Public aspects of medicine RA1-1270
Acceso en línea:	https://doaj.org/article/eaeebfabc92c41a98e22caa73254c60c
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spelling	oai:doaj.org-article:eaeebfabc92c41a98e22caa73254c60c2021-11-08T10:59:07ZMeasuring the hidden burden of violence: use of explicit and proxy codes in Minnesota injury hospitalizations, 2004–201410.1186/s40621-021-00354-62197-1714https://doaj.org/article/eaeebfabc92c41a98e22caa73254c60c2021-11-01T00:00:00Zhttps://doi.org/10.1186/s40621-021-00354-6https://doaj.org/toc/2197-1714Abstract Purpose Commonly-used violence surveillance systems are biased towards certain populations due to overreporting or over-scrutinized. Hospital discharge data may offer a more representative view of violence, through use of proxy codes, i.e. diagnosis of injuries correlated with violence. The goals of this paper are to compare the trends in violence in Minnesota, and associations of county-level demographic characteristics with violence rates, measured through explicitly diagnosed violence and proxy codes. It is an exploration of how certain sub-populations are overrepresented in traditional surveillance systems. Methods Using Minnesota hospital discharge data linked with census data from 2004 to 2014, this study examined the distribution and time trends of explicit, proxy, and combined (proxy and explicit) codes for child abuse, intimate partner violence (IPV), and elder abuse. The associations between county-level risk factors (e.g., poverty) and county violence rates were estimated using negative binomial regression models with generalized estimation equations to account for clustering over time. Results The main finding was that the patterns of county-level violence differed depending on whether one used explicit or proxy codes. In particular, explicit codes suggested that child abuse and IPV trends were flat or decreased slightly from 2004 to 2014, while proxy codes suggested the opposite. Elder abuse increased during this timeframe for both explicit and proxy codes, but more dramatically when using proxy codes. In regard to the associations between county level characteristics and each violence subtype, previously identified county-level risk factors were more strongly related to explicitly-identified violence than to proxy-identified violence. Given the larger number of proxy-identified cases as compared with explicit-identified violence cases, the trends and associations of combined codes align more closely with proxy codes, especially for elder abuse and IPV. Conclusions Violence surveillance utilizing hospital discharge data, and particularly proxy codes, may add important information that traditional surveillance misses. Most importantly, explicit and proxy codes indicate different associations with county sociodemographic characteristics. Future research should examine hospital discharge data for violence identification to validate proxy codes that can be utilized to help to identify the hidden burden of violence.N. Jeanie SantaulariaMarizen R. RamirezTheresa L. OsypukSusan M. MasonBMCarticleViolent injurySurveillanceHospital dataChild abuseIntimate partner violenceElder abuseMedical emergencies. Critical care. Intensive care. First aidRC86-88.9Public aspects of medicineRA1-1270ENInjury Epidemiology, Vol 8, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Violent injury Surveillance Hospital data Child abuse Intimate partner violence Elder abuse Medical emergencies. Critical care. Intensive care. First aid RC86-88.9 Public aspects of medicine RA1-1270
spellingShingle	Violent injury Surveillance Hospital data Child abuse Intimate partner violence Elder abuse Medical emergencies. Critical care. Intensive care. First aid RC86-88.9 Public aspects of medicine RA1-1270 N. Jeanie Santaularia Marizen R. Ramirez Theresa L. Osypuk Susan M. Mason Measuring the hidden burden of violence: use of explicit and proxy codes in Minnesota injury hospitalizations, 2004–2014
description	Abstract Purpose Commonly-used violence surveillance systems are biased towards certain populations due to overreporting or over-scrutinized. Hospital discharge data may offer a more representative view of violence, through use of proxy codes, i.e. diagnosis of injuries correlated with violence. The goals of this paper are to compare the trends in violence in Minnesota, and associations of county-level demographic characteristics with violence rates, measured through explicitly diagnosed violence and proxy codes. It is an exploration of how certain sub-populations are overrepresented in traditional surveillance systems. Methods Using Minnesota hospital discharge data linked with census data from 2004 to 2014, this study examined the distribution and time trends of explicit, proxy, and combined (proxy and explicit) codes for child abuse, intimate partner violence (IPV), and elder abuse. The associations between county-level risk factors (e.g., poverty) and county violence rates were estimated using negative binomial regression models with generalized estimation equations to account for clustering over time. Results The main finding was that the patterns of county-level violence differed depending on whether one used explicit or proxy codes. In particular, explicit codes suggested that child abuse and IPV trends were flat or decreased slightly from 2004 to 2014, while proxy codes suggested the opposite. Elder abuse increased during this timeframe for both explicit and proxy codes, but more dramatically when using proxy codes. In regard to the associations between county level characteristics and each violence subtype, previously identified county-level risk factors were more strongly related to explicitly-identified violence than to proxy-identified violence. Given the larger number of proxy-identified cases as compared with explicit-identified violence cases, the trends and associations of combined codes align more closely with proxy codes, especially for elder abuse and IPV. Conclusions Violence surveillance utilizing hospital discharge data, and particularly proxy codes, may add important information that traditional surveillance misses. Most importantly, explicit and proxy codes indicate different associations with county sociodemographic characteristics. Future research should examine hospital discharge data for violence identification to validate proxy codes that can be utilized to help to identify the hidden burden of violence.
format	article
author	N. Jeanie Santaularia Marizen R. Ramirez Theresa L. Osypuk Susan M. Mason
author_facet	N. Jeanie Santaularia Marizen R. Ramirez Theresa L. Osypuk Susan M. Mason
author_sort	N. Jeanie Santaularia
title	Measuring the hidden burden of violence: use of explicit and proxy codes in Minnesota injury hospitalizations, 2004–2014
title_short	Measuring the hidden burden of violence: use of explicit and proxy codes in Minnesota injury hospitalizations, 2004–2014
title_full	Measuring the hidden burden of violence: use of explicit and proxy codes in Minnesota injury hospitalizations, 2004–2014
title_fullStr	Measuring the hidden burden of violence: use of explicit and proxy codes in Minnesota injury hospitalizations, 2004–2014
title_full_unstemmed	Measuring the hidden burden of violence: use of explicit and proxy codes in Minnesota injury hospitalizations, 2004–2014
title_sort	measuring the hidden burden of violence: use of explicit and proxy codes in minnesota injury hospitalizations, 2004–2014
publisher	BMC
publishDate	2021
url	https://doaj.org/article/eaeebfabc92c41a98e22caa73254c60c
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Measuring the hidden burden of violence: use of explicit and proxy codes in Minnesota injury hospitalizations, 2004–2014

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