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Identifying Measures of Suboptimal Healthcare Interaction (SOHI) to Develop a Claims-Based Model for Predicting Patients with Inflammatory Bowel Disease at Risk for SOHI

BACKGROUND: Understanding the demographic and clinical characteristics of patients with Inflammatory Bowel Disease (IBD) who are likely to experience poor disease outcomes may allow early interventions that can improve health outcomes. OBJECTIVES: To describe demographic and clinical characteristics...

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Autores principales: Korrer, Stephanie, Naegeli, April N., Etemad, Lida, Johnson, Gabriel, Gottlieb, Klaus T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10188318/
https://www.ncbi.nlm.nih.gov/pubmed/37195414
http://dx.doi.org/10.1007/s40801-023-00369-z
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author Korrer, Stephanie
Naegeli, April N.
Etemad, Lida
Johnson, Gabriel
Gottlieb, Klaus T.
author_facet Korrer, Stephanie
Naegeli, April N.
Etemad, Lida
Johnson, Gabriel
Gottlieb, Klaus T.
author_sort Korrer, Stephanie
collection PubMed
description BACKGROUND: Understanding the demographic and clinical characteristics of patients with Inflammatory Bowel Disease (IBD) who are likely to experience poor disease outcomes may allow early interventions that can improve health outcomes. OBJECTIVES: To describe demographic and clinical characteristics of patients with ulcerative colitis (UC) and Crohn’s disease (CD) with the presence of at least one Suboptimal Healthcare Interaction (SOHI) event, which can inform the development of a model to predict SOHI in members with IBD based on insurance claims, with the goal of offering these patients some additional intervention. METHODS: We identified commercially insured individuals with IBD between 01 January 2019 and 31 December 2019 using Optum Labs’ administrative claims database. The primary cohort was stratified on the presence or absence of ≥ 1 SOHI event (a SOHI-defining data point or characteristic at a specific time point) during the baseline observation period. SOHI was deployed as the basis for the development of a model to predict which individuals with IBD were most likely to continue to have SOHI within a 1-year timeframe (follow-up SOHI) using insurance claims data. All baseline characteristics were analyzed descriptively. Multivariable logistic regression was used to examine the association of follow-up SOHI with baseline characteristics. RESULTS: Of 19,824 individuals, 6872 (34.7%) were found to have follow-up SOHI. Individuals with follow-up SOHI were more likely to have had similar SOHI events in the baseline period than those with non-SOHI. A significantly greater proportion of individuals with SOHI had ≥ 1 claims-based C-reactive protein (CRP) test order and ≥ 1 CRP lab results compared with non-SOHI. Individuals with follow-up SOHI were more likely to incur higher healthcare expenditures and resource utilization as compared with non-SOHI individuals. A few of the most important variables used to predict follow-up SOHI included baseline mesalamine use, count of baseline opioid fills, count of baseline oral corticosteroid fills, baseline extraintestinal manifestations of disease, proxy for baseline SOHI, and index IBD provider specialty. CONCLUSION: Individuals with SOHI are likely to have higher expenditures, higher healthcare resource utilization, uncontrolled disease, and higher CRP lab results as compared with non-SOHI members. Distinguishing SOHI and non-SOHI patients in a dataset could efficiently identify potential cases of poor future IBD outcomes. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40801-023-00369-z.
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spelling pubmed-101883182023-05-19 Identifying Measures of Suboptimal Healthcare Interaction (SOHI) to Develop a Claims-Based Model for Predicting Patients with Inflammatory Bowel Disease at Risk for SOHI Korrer, Stephanie Naegeli, April N. Etemad, Lida Johnson, Gabriel Gottlieb, Klaus T. Drugs Real World Outcomes Original Research Article BACKGROUND: Understanding the demographic and clinical characteristics of patients with Inflammatory Bowel Disease (IBD) who are likely to experience poor disease outcomes may allow early interventions that can improve health outcomes. OBJECTIVES: To describe demographic and clinical characteristics of patients with ulcerative colitis (UC) and Crohn’s disease (CD) with the presence of at least one Suboptimal Healthcare Interaction (SOHI) event, which can inform the development of a model to predict SOHI in members with IBD based on insurance claims, with the goal of offering these patients some additional intervention. METHODS: We identified commercially insured individuals with IBD between 01 January 2019 and 31 December 2019 using Optum Labs’ administrative claims database. The primary cohort was stratified on the presence or absence of ≥ 1 SOHI event (a SOHI-defining data point or characteristic at a specific time point) during the baseline observation period. SOHI was deployed as the basis for the development of a model to predict which individuals with IBD were most likely to continue to have SOHI within a 1-year timeframe (follow-up SOHI) using insurance claims data. All baseline characteristics were analyzed descriptively. Multivariable logistic regression was used to examine the association of follow-up SOHI with baseline characteristics. RESULTS: Of 19,824 individuals, 6872 (34.7%) were found to have follow-up SOHI. Individuals with follow-up SOHI were more likely to have had similar SOHI events in the baseline period than those with non-SOHI. A significantly greater proportion of individuals with SOHI had ≥ 1 claims-based C-reactive protein (CRP) test order and ≥ 1 CRP lab results compared with non-SOHI. Individuals with follow-up SOHI were more likely to incur higher healthcare expenditures and resource utilization as compared with non-SOHI individuals. A few of the most important variables used to predict follow-up SOHI included baseline mesalamine use, count of baseline opioid fills, count of baseline oral corticosteroid fills, baseline extraintestinal manifestations of disease, proxy for baseline SOHI, and index IBD provider specialty. CONCLUSION: Individuals with SOHI are likely to have higher expenditures, higher healthcare resource utilization, uncontrolled disease, and higher CRP lab results as compared with non-SOHI members. Distinguishing SOHI and non-SOHI patients in a dataset could efficiently identify potential cases of poor future IBD outcomes. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40801-023-00369-z. Springer International Publishing 2023-05-17 /pmc/articles/PMC10188318/ /pubmed/37195414 http://dx.doi.org/10.1007/s40801-023-00369-z Text en © The Author(s) 2023 https://creativecommons.org/licenses/by-nc/4.0/Open Access This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Original Research Article
Korrer, Stephanie
Naegeli, April N.
Etemad, Lida
Johnson, Gabriel
Gottlieb, Klaus T.
Identifying Measures of Suboptimal Healthcare Interaction (SOHI) to Develop a Claims-Based Model for Predicting Patients with Inflammatory Bowel Disease at Risk for SOHI
title Identifying Measures of Suboptimal Healthcare Interaction (SOHI) to Develop a Claims-Based Model for Predicting Patients with Inflammatory Bowel Disease at Risk for SOHI
title_full Identifying Measures of Suboptimal Healthcare Interaction (SOHI) to Develop a Claims-Based Model for Predicting Patients with Inflammatory Bowel Disease at Risk for SOHI
title_fullStr Identifying Measures of Suboptimal Healthcare Interaction (SOHI) to Develop a Claims-Based Model for Predicting Patients with Inflammatory Bowel Disease at Risk for SOHI
title_full_unstemmed Identifying Measures of Suboptimal Healthcare Interaction (SOHI) to Develop a Claims-Based Model for Predicting Patients with Inflammatory Bowel Disease at Risk for SOHI
title_short Identifying Measures of Suboptimal Healthcare Interaction (SOHI) to Develop a Claims-Based Model for Predicting Patients with Inflammatory Bowel Disease at Risk for SOHI
title_sort identifying measures of suboptimal healthcare interaction (sohi) to develop a claims-based model for predicting patients with inflammatory bowel disease at risk for sohi
topic Original Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10188318/
https://www.ncbi.nlm.nih.gov/pubmed/37195414
http://dx.doi.org/10.1007/s40801-023-00369-z
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