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Ranked severe maternal morbidity index for population-level surveillance at delivery hospitalization based on hospital discharge data

BACKGROUND: Severe maternal morbidity (SMM) is broadly defined as an unexpected and potentially life-threatening event associated with labor and delivery. The Centers for Disease Control and Prevention (CDC) produced 21 different indicators based on International Classification of Diseases, 9th Revi...

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Autores principales: Kuklina, Elena V., Ewing, Alexander C., Satten, Glen A., Callaghan, William M., Goodman, David A., Ferre, Cynthia D., Ko, Jean Y., Womack, Lindsay S., Galang, Romeo R., Kroelinger, Charlan D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10635479/
https://www.ncbi.nlm.nih.gov/pubmed/37943788
http://dx.doi.org/10.1371/journal.pone.0294140
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author Kuklina, Elena V.
Ewing, Alexander C.
Satten, Glen A.
Callaghan, William M.
Goodman, David A.
Ferre, Cynthia D.
Ko, Jean Y.
Womack, Lindsay S.
Galang, Romeo R.
Kroelinger, Charlan D.
author_facet Kuklina, Elena V.
Ewing, Alexander C.
Satten, Glen A.
Callaghan, William M.
Goodman, David A.
Ferre, Cynthia D.
Ko, Jean Y.
Womack, Lindsay S.
Galang, Romeo R.
Kroelinger, Charlan D.
author_sort Kuklina, Elena V.
collection PubMed
description BACKGROUND: Severe maternal morbidity (SMM) is broadly defined as an unexpected and potentially life-threatening event associated with labor and delivery. The Centers for Disease Control and Prevention (CDC) produced 21 different indicators based on International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) hospital diagnostic and procedure codes to identify cases of SMM. OBJECTIVES: To examine existing SMM indicators and determine which indicators identified the most in-hospital mortality at delivery hospitalization. METHODS: Data from the 1993–2015 and 2017–2019 Healthcare Cost and Utilization Project’s National Inpatient Sample were used to report SMM indicator-specific prevalences, in-hospital mortality rates, and population attributable fractions (PAF) of mortality. We hierarchically ranked indicators by their overall PAF of in-hospital mortality. Predictive modeling determined if SMM prevalence remained comparable after transition to ICD-10-CM coding. RESULTS: The study population consisted of 18,198,934 hospitalizations representing 87,864,173 US delivery hospitalizations. The 15 top ranked indicators identified 80% of in-hospital mortality; the proportion identified by the remaining indicators was negligible (2%). The top 15 indicators were: restoration of cardiac rhythm; cardiac arrest; mechanical ventilation; tracheostomy; amniotic fluid embolism; aneurysm; acute respiratory distress syndrome; acute myocardial infarction; shock; thromboembolism, pulmonary embolism; cerebrovascular disorders; sepsis; both DIC and blood transfusion; acute renal failure; and hysterectomy. The overall prevalence of the top 15 ranked SMM indicators (~22,000 SMM cases per year) was comparable after transition to ICD-10-CM coding. CONCLUSIONS: We determined the 15 indicators that identified the most in-hospital mortality at delivery hospitalization in the US. Continued testing of SMM indicators can improve measurement and surveillance of the most severe maternal complications at the population level.
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spelling pubmed-106354792023-11-10 Ranked severe maternal morbidity index for population-level surveillance at delivery hospitalization based on hospital discharge data Kuklina, Elena V. Ewing, Alexander C. Satten, Glen A. Callaghan, William M. Goodman, David A. Ferre, Cynthia D. Ko, Jean Y. Womack, Lindsay S. Galang, Romeo R. Kroelinger, Charlan D. PLoS One Research Article BACKGROUND: Severe maternal morbidity (SMM) is broadly defined as an unexpected and potentially life-threatening event associated with labor and delivery. The Centers for Disease Control and Prevention (CDC) produced 21 different indicators based on International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) hospital diagnostic and procedure codes to identify cases of SMM. OBJECTIVES: To examine existing SMM indicators and determine which indicators identified the most in-hospital mortality at delivery hospitalization. METHODS: Data from the 1993–2015 and 2017–2019 Healthcare Cost and Utilization Project’s National Inpatient Sample were used to report SMM indicator-specific prevalences, in-hospital mortality rates, and population attributable fractions (PAF) of mortality. We hierarchically ranked indicators by their overall PAF of in-hospital mortality. Predictive modeling determined if SMM prevalence remained comparable after transition to ICD-10-CM coding. RESULTS: The study population consisted of 18,198,934 hospitalizations representing 87,864,173 US delivery hospitalizations. The 15 top ranked indicators identified 80% of in-hospital mortality; the proportion identified by the remaining indicators was negligible (2%). The top 15 indicators were: restoration of cardiac rhythm; cardiac arrest; mechanical ventilation; tracheostomy; amniotic fluid embolism; aneurysm; acute respiratory distress syndrome; acute myocardial infarction; shock; thromboembolism, pulmonary embolism; cerebrovascular disorders; sepsis; both DIC and blood transfusion; acute renal failure; and hysterectomy. The overall prevalence of the top 15 ranked SMM indicators (~22,000 SMM cases per year) was comparable after transition to ICD-10-CM coding. CONCLUSIONS: We determined the 15 indicators that identified the most in-hospital mortality at delivery hospitalization in the US. Continued testing of SMM indicators can improve measurement and surveillance of the most severe maternal complications at the population level. Public Library of Science 2023-11-09 /pmc/articles/PMC10635479/ /pubmed/37943788 http://dx.doi.org/10.1371/journal.pone.0294140 Text en https://creativecommons.org/publicdomain/zero/1.0/This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication.
spellingShingle Research Article
Kuklina, Elena V.
Ewing, Alexander C.
Satten, Glen A.
Callaghan, William M.
Goodman, David A.
Ferre, Cynthia D.
Ko, Jean Y.
Womack, Lindsay S.
Galang, Romeo R.
Kroelinger, Charlan D.
Ranked severe maternal morbidity index for population-level surveillance at delivery hospitalization based on hospital discharge data
title Ranked severe maternal morbidity index for population-level surveillance at delivery hospitalization based on hospital discharge data
title_full Ranked severe maternal morbidity index for population-level surveillance at delivery hospitalization based on hospital discharge data
title_fullStr Ranked severe maternal morbidity index for population-level surveillance at delivery hospitalization based on hospital discharge data
title_full_unstemmed Ranked severe maternal morbidity index for population-level surveillance at delivery hospitalization based on hospital discharge data
title_short Ranked severe maternal morbidity index for population-level surveillance at delivery hospitalization based on hospital discharge data
title_sort ranked severe maternal morbidity index for population-level surveillance at delivery hospitalization based on hospital discharge data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10635479/
https://www.ncbi.nlm.nih.gov/pubmed/37943788
http://dx.doi.org/10.1371/journal.pone.0294140
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