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Predicting Risk of 1-Year Hospitalization Among Patients with Pulmonary Arterial Hypertension

Predicting Risk of 1-Year Hospitalization Among Patients with Pulmonary Arterial Hypertension IntroductionUS claims-based analyses emphasize the substantial hospitalization burden of patients with pulmonary arterial hypertension (PAH) and the significant need for improved monitoring and more timely interventions. A claims-based predictive model may be useful to assist healthcare providers and payers in identifying patients with PAH at increased hospitalization risk. To address this aim, we constructed statistical models using baseline patient variables available in administrative healthcare claims to predict patients’ risk for all-cause and PH-related hospitalization within 1 year of initiating ≥ 1 PAH indicated medication.MethodsAdult patients with PAH who newly initiated ≥ 1 PAH indicated medication were selected from the MarketScan Commercial and Medicare Supplemental databases (January 1, 2009–January 31, 2019). Cox regression models were built with a randomly selected training set and evaluated using a validation set of remaining patients. Predictive variables for the models were selected in three steps: clinical knowledge, univariate analysis, and backward stepwise selection.ResultsWithin 1 year of initiating ≥ 1 PAH indicated medication, 1502/3872 (38.8%) had an all-cause hospitalization and 950/3872 (24.5%) had a pulmonary hypertension (PH)-related hospitalization. Predictive risk factors for all-cause hospitalization were Quan–Charlson Comorbidity Index (CCI) score 2–3 [hazard ratio (HR) 1.229; P = 0.038] and ≥ 4 (HR 1.531; P < 0.001), claims-based frailty index (CFI) score > 1 (highest frailty level; HR 1.301; P = 0.018), hemoptysis (HR 1.254; P = 0.016), malaise/fatigue (HR 1.150; P = 0.037), history of PH-related hospitalization (HR 1.171; P = 0.011), non-PH-related ER visit (HR 1.713; P = 0.014), and higher non-PH-related outpatient visit cost (HR 1.069; P < 0.001). Predictive risk factors for PH-related hospitalization were female sex (HR 1.264; P = 0.004), Quan-CCI score ≥ 4 (HR 1.408; P = 0.008), portal hypertension (HR 1.565; P = 0.019), CFI score > 1 (HR 1.522; P = 0.002), dyspnea (HR 1.259; P = 0.023), and history of PH-related hospitalization (HR 1.273; P = 0.002).ConclusionsThe US claims-based predictive models showed acceptable performance to predict 1-year hospitalization among patients with PAH. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Advances in Therapy Springer Journals

Predicting Risk of 1-Year Hospitalization Among Patients with Pulmonary Arterial Hypertension

Advances in Therapy , Volume OnlineFirst – Apr 6, 2023

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References (28)

Publisher
Springer Journals
Copyright
Copyright © The Author(s), under exclusive licence to Springer Healthcare Ltd., part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
ISSN
0741-238X
eISSN
1865-8652
DOI
10.1007/s12325-023-02501-5
Publisher site
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Abstract

IntroductionUS claims-based analyses emphasize the substantial hospitalization burden of patients with pulmonary arterial hypertension (PAH) and the significant need for improved monitoring and more timely interventions. A claims-based predictive model may be useful to assist healthcare providers and payers in identifying patients with PAH at increased hospitalization risk. To address this aim, we constructed statistical models using baseline patient variables available in administrative healthcare claims to predict patients’ risk for all-cause and PH-related hospitalization within 1 year of initiating ≥ 1 PAH indicated medication.MethodsAdult patients with PAH who newly initiated ≥ 1 PAH indicated medication were selected from the MarketScan Commercial and Medicare Supplemental databases (January 1, 2009–January 31, 2019). Cox regression models were built with a randomly selected training set and evaluated using a validation set of remaining patients. Predictive variables for the models were selected in three steps: clinical knowledge, univariate analysis, and backward stepwise selection.ResultsWithin 1 year of initiating ≥ 1 PAH indicated medication, 1502/3872 (38.8%) had an all-cause hospitalization and 950/3872 (24.5%) had a pulmonary hypertension (PH)-related hospitalization. Predictive risk factors for all-cause hospitalization were Quan–Charlson Comorbidity Index (CCI) score 2–3 [hazard ratio (HR) 1.229; P = 0.038] and ≥ 4 (HR 1.531; P < 0.001), claims-based frailty index (CFI) score > 1 (highest frailty level; HR 1.301; P = 0.018), hemoptysis (HR 1.254; P = 0.016), malaise/fatigue (HR 1.150; P = 0.037), history of PH-related hospitalization (HR 1.171; P = 0.011), non-PH-related ER visit (HR 1.713; P = 0.014), and higher non-PH-related outpatient visit cost (HR 1.069; P < 0.001). Predictive risk factors for PH-related hospitalization were female sex (HR 1.264; P = 0.004), Quan-CCI score ≥ 4 (HR 1.408; P = 0.008), portal hypertension (HR 1.565; P = 0.019), CFI score > 1 (HR 1.522; P = 0.002), dyspnea (HR 1.259; P = 0.023), and history of PH-related hospitalization (HR 1.273; P = 0.002).ConclusionsThe US claims-based predictive models showed acceptable performance to predict 1-year hospitalization among patients with PAH.

Journal

Advances in TherapySpringer Journals

Published: Apr 6, 2023

Keywords: Hospitalization; Healthcare resource utilization; Predictive risk factors; Patient characteristics; Pulmonary arterial hypertension

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