Cargando…
Patient and hospital characteristics predictive of inferior vena cava filter usage in venous thromboembolism patients: A study from the 2013 to 2014 Nationwide Readmissions Database
To examine the association between patient and hospital characteristics and inferior vena cava filter (IVCF) utilization in patients with venous thromboembolism (VTE). The 2013 to 2014 Nationwide Readmissions Database was used to define a cohort of patients with VTE aged ≥18 after a primary VTE diag...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer Health
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5895325/ https://www.ncbi.nlm.nih.gov/pubmed/29561421 http://dx.doi.org/10.1097/MD.0000000000010149 |
_version_ | 1783313636069998592 |
---|---|
author | Goodin, Amie Chen, Ming Raissi, Driss Han, Qiong Xiao, Hong Brown, Joshua |
author_facet | Goodin, Amie Chen, Ming Raissi, Driss Han, Qiong Xiao, Hong Brown, Joshua |
author_sort | Goodin, Amie |
collection | PubMed |
description | To examine the association between patient and hospital characteristics and inferior vena cava filter (IVCF) utilization in patients with venous thromboembolism (VTE). The 2013 to 2014 Nationwide Readmissions Database was used to define a cohort of patients with VTE aged ≥18 after a primary VTE diagnosis. Comorbidities of interest were classified via diagnosis codes and IVCF placement was identified via procedure code. Chi square analysis tested differences between patient and hospital-level characteristics and whether or not IVCFs were placed. A hierarchical logistic regression model estimated the relationship between patient-level factors (demographics, socioeconomic status, comorbidities), hospital-level factors (bed size, teaching status, urbanity) and whether or not IVCFs were placed. Additional models were specified to examine goodness of fit across methodological alternatives. There were 212,395 VTE hospitalizations, with 12.18% (n = 25,877) receiving IVCF placement. There were significant differences between those who did and did not receive IVCF placement; notably, those receiving IVCFs were older (P < .001), had Medicare insurance more than private (P < .001), longer lengths of stay (P < .001), and were in privately owned hospitals (P < .001). IVCF placement remained significantly associated with patient and hospital-level characteristics following multivariate adjustment via hierarchical logistic regression; notably, age >80 (adjusted Odds Ratio [aOR]: 2.53, 95% confidence interval [CI]: 2.25–2.85), ≥13 comorbid conditions (aOR: 3.85, 95% CI: 3.25–4.27), and privately owned hospitals (aOR: 1.21, 95% CI: 1.08–1.36). Optimal goodness-of-fit was achieved with a combination of random effects and patient-level fixed effects. These findings provide evidence that combinations of patient and hospital-level factors are related to whether patients with VTE receive IVCFs. |
format | Online Article Text |
id | pubmed-5895325 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Wolters Kluwer Health |
record_format | MEDLINE/PubMed |
spelling | pubmed-58953252018-04-18 Patient and hospital characteristics predictive of inferior vena cava filter usage in venous thromboembolism patients: A study from the 2013 to 2014 Nationwide Readmissions Database Goodin, Amie Chen, Ming Raissi, Driss Han, Qiong Xiao, Hong Brown, Joshua Medicine (Baltimore) 3400 To examine the association between patient and hospital characteristics and inferior vena cava filter (IVCF) utilization in patients with venous thromboembolism (VTE). The 2013 to 2014 Nationwide Readmissions Database was used to define a cohort of patients with VTE aged ≥18 after a primary VTE diagnosis. Comorbidities of interest were classified via diagnosis codes and IVCF placement was identified via procedure code. Chi square analysis tested differences between patient and hospital-level characteristics and whether or not IVCFs were placed. A hierarchical logistic regression model estimated the relationship between patient-level factors (demographics, socioeconomic status, comorbidities), hospital-level factors (bed size, teaching status, urbanity) and whether or not IVCFs were placed. Additional models were specified to examine goodness of fit across methodological alternatives. There were 212,395 VTE hospitalizations, with 12.18% (n = 25,877) receiving IVCF placement. There were significant differences between those who did and did not receive IVCF placement; notably, those receiving IVCFs were older (P < .001), had Medicare insurance more than private (P < .001), longer lengths of stay (P < .001), and were in privately owned hospitals (P < .001). IVCF placement remained significantly associated with patient and hospital-level characteristics following multivariate adjustment via hierarchical logistic regression; notably, age >80 (adjusted Odds Ratio [aOR]: 2.53, 95% confidence interval [CI]: 2.25–2.85), ≥13 comorbid conditions (aOR: 3.85, 95% CI: 3.25–4.27), and privately owned hospitals (aOR: 1.21, 95% CI: 1.08–1.36). Optimal goodness-of-fit was achieved with a combination of random effects and patient-level fixed effects. These findings provide evidence that combinations of patient and hospital-level factors are related to whether patients with VTE receive IVCFs. Wolters Kluwer Health 2018-03-23 /pmc/articles/PMC5895325/ /pubmed/29561421 http://dx.doi.org/10.1097/MD.0000000000010149 Text en Copyright © 2018 the Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by-nd/4.0 This is an open access article distributed under the Creative Commons Attribution-NoDerivatives License 4.0, which allows for redistribution, commercial and non-commercial, as long as it is passed along unchanged and in whole, with credit to the author. http://creativecommons.org/licenses/by-nd/4.0 |
spellingShingle | 3400 Goodin, Amie Chen, Ming Raissi, Driss Han, Qiong Xiao, Hong Brown, Joshua Patient and hospital characteristics predictive of inferior vena cava filter usage in venous thromboembolism patients: A study from the 2013 to 2014 Nationwide Readmissions Database |
title | Patient and hospital characteristics predictive of inferior vena cava filter usage in venous thromboembolism patients: A study from the 2013 to 2014 Nationwide Readmissions Database |
title_full | Patient and hospital characteristics predictive of inferior vena cava filter usage in venous thromboembolism patients: A study from the 2013 to 2014 Nationwide Readmissions Database |
title_fullStr | Patient and hospital characteristics predictive of inferior vena cava filter usage in venous thromboembolism patients: A study from the 2013 to 2014 Nationwide Readmissions Database |
title_full_unstemmed | Patient and hospital characteristics predictive of inferior vena cava filter usage in venous thromboembolism patients: A study from the 2013 to 2014 Nationwide Readmissions Database |
title_short | Patient and hospital characteristics predictive of inferior vena cava filter usage in venous thromboembolism patients: A study from the 2013 to 2014 Nationwide Readmissions Database |
title_sort | patient and hospital characteristics predictive of inferior vena cava filter usage in venous thromboembolism patients: a study from the 2013 to 2014 nationwide readmissions database |
topic | 3400 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5895325/ https://www.ncbi.nlm.nih.gov/pubmed/29561421 http://dx.doi.org/10.1097/MD.0000000000010149 |
work_keys_str_mv | AT goodinamie patientandhospitalcharacteristicspredictiveofinferiorvenacavafilterusageinvenousthromboembolismpatientsastudyfromthe2013to2014nationwidereadmissionsdatabase AT chenming patientandhospitalcharacteristicspredictiveofinferiorvenacavafilterusageinvenousthromboembolismpatientsastudyfromthe2013to2014nationwidereadmissionsdatabase AT raissidriss patientandhospitalcharacteristicspredictiveofinferiorvenacavafilterusageinvenousthromboembolismpatientsastudyfromthe2013to2014nationwidereadmissionsdatabase AT hanqiong patientandhospitalcharacteristicspredictiveofinferiorvenacavafilterusageinvenousthromboembolismpatientsastudyfromthe2013to2014nationwidereadmissionsdatabase AT xiaohong patientandhospitalcharacteristicspredictiveofinferiorvenacavafilterusageinvenousthromboembolismpatientsastudyfromthe2013to2014nationwidereadmissionsdatabase AT brownjoshua patientandhospitalcharacteristicspredictiveofinferiorvenacavafilterusageinvenousthromboembolismpatientsastudyfromthe2013to2014nationwidereadmissionsdatabase |