Healthcare resource utilization burden associated with cognitive impairments identified through natural language processing among patients with schizophrenia in the United States.

IF 4.1 Q2 PSYCHIATRY
Jerome Vaccaro, Mona Nili, Pin Xiang, James K Nelson, Cory Pack, Randall Thompson, Joe Vasey, Joseph Parks
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Abstract

While cognitive impairments in schizophrenia are well documented in research, their identification and impact in clinical practice remain less well understood, despite their association with high patient burden and impact on long-term functional outcomes. In this study we aimed to identify documented cognitive impairments using natural language processing (NLP) and to characterize treatment patterns and healthcare resource utilization (HCRU) among patients with schizophrenia. This US retrospective cohort study used electronic health records (EHR) linked to administrative claims data from January 2016 through February 2023. Adult patients (≥18 years) with at least two schizophrenia diagnosis codes were included. Cognitive impairments were identified by NLP. Patient characteristics were assessed in the 12 months preceding the index date (first documented schizophrenia diagnosis). Treatment patterns and HCRU were measured over the 12 months after index date. A total of 79,326 patients were enrolled in the EHR cohort and 19,974 (25.2%) had documented cognitive impairments. Impairments in "Reasoning and Problem Solving" were identified most often (70.4%) followed by "Working Memory" (27.1%) and "Attention and Vigilance" (19.2%). In the EHR cohort, 11,293 patients (14.2%) had linked claims. Patients with documented cognitive impairments had more HCRU including outpatient visits, psychosocial interventions, and all-cause healthcare claims than patients without documented cognitive impairments (all p < 0.001). Patients with cognitive impairments had greater psychiatric pharmacy utilization than those without cognitive impairments. These observational data add to the limited published literature on cognitive impairments in patients with schizophrenia in the US. The low documented identification of cognitive impairments in this study underscores the importance of improving recognition and documentation of this important domain of schizophrenia. The association of cognitive impairments with high healthcare utilization further emphasizes the need for better treatment options for patients with schizophrenia.

Abstract Image

通过自然语言处理在美国精神分裂症患者中识别与认知障碍相关的医疗资源利用负担。
虽然精神分裂症患者的认知障碍在研究中得到了充分的记录,但尽管它们与患者的高负担和对长期功能预后的影响有关,但它们在临床实践中的识别和影响仍不太清楚。在这项研究中,我们旨在利用自然语言处理(NLP)识别记录在案的认知障碍,并表征精神分裂症患者的治疗模式和医疗资源利用(HCRU)。这项美国回顾性队列研究使用了与2016年1月至2023年2月的行政索赔数据相关的电子健康记录(EHR)。纳入至少有两种精神分裂症诊断代码的成年患者(≥18岁)。通过NLP识别认知障碍。在索引日期(首次记录的精神分裂症诊断)之前的12个月内评估患者特征。在索引日期后的12个月内测量治疗模式和HCRU。共有79,326名患者入组EHR队列,其中19,974名(25.2%)有记录的认知障碍。最常见的是“推理及解决问题能力”(70.4%),其次是“工作记忆能力”(27.1%)及“注意力及警觉性能力”(19.2%)。在EHR队列中,11293例患者(14.2%)有相关的索赔。有记录的认知障碍患者比没有记录的认知障碍患者有更多的HCRU,包括门诊就诊、心理社会干预和全因医疗保健索赔
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