Hospital costs of intracranial haemorrhage in patients with acute pulmonary embolism : possible implications for emerging therapies

Abstract

Pulmonary embolism (PE) is a potentially life-threatening event,[1] with increasing incidence over the past decades.[2] [3] Treatment of acute PE is currently undergoing profound change, and novel reperfusion treatment modalities rapidly entering the market need to show, among others, whether they can reduce the complications associated with systemic fibrinolysis and thus justify their elevated costs.[4] [5] [6] In this regard, intracranial haemorrhage (ICH) is in the focus of interest,[7] [8] [9] since it is associated with a high early case fatality and seriously impacts the patients' well-being and quality of life over the long term. We therefore examined the impact of ICH on reimbursed hospital costs (reflecting the payer's perspective) in patients with acute PE, and dissected the main cost drivers. Data from all patients hospitalized in Germany (with the exception of a very small minority admitted to military hospitals and psychiatric centres) with a main diagnosis of PE (ICD-10 code I26) during the period 2016–2020 (source: RDC of the Federal Statistical Office and the Statistical Offices of the Federal States, DRG Statistics 2016–2020; own calculations) were analyzed as previously described.[3] [10] [11] We stratified patients by the occurrence of ICH, identified by at least one of the following ICD-10 codes: I60, I61, I62, G95.10, S06.33, S06.5, S06.6. We analyzed all procedure codes related to the treatment of ICH, including surgical, endoscopic, or interventional drainage of intracranial haematomas (5-012.0, 5-012.2, 5-013.1, 5-013.4, 5-014.1, 5-022.0, 5-022.00, 5-022.01, 5-022.02, 5-022.0x, 5-022.20, 5-022.y, 5-033.2, 5-034.1, 5-034.4, 5-038.0, 8-020.d, and/or 8-151.1). Finally, we included multidisciplinary treatment in specialized facilities, coded as 8-981 or 8-98b.[12] [13] The statistical software SPSS® for Windows, Version 20.0 (Armonk, NY: IBM Corp) was used for data analysis.