Shen Siyuan, Yang Catherine, Candon Molly, Lorenc Emily, Jang Min, Mandell David
Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, 3535 Market St, 3rd Floor, Philadelphia, PA, 19104, USA.
Department of Health Care Management, Wharton School, University of Pennsylvania, Philadelphia, PA, USA.
Adm Policy Ment Health. 2025 Mar;52(2):277-284. doi: 10.1007/s10488-024-01416-9. Epub 2024 Oct 11.
To identify patterns of medication adherence during the pandemic and factors associated with these patterns among Medicaid-enrolled individuals with schizophrenia who had highly adherent medication use prior to the COVID-19 pandemic. We used Medicaid claims from Philadelphia to identify individuals with schizophrenia ≥ 18 years of age, their demographic characteristics, and health service use. We used group trajectory models to identify adherence trends, and ANOVA to examine associations between adherence groups and demographic characteristics and service use. The sample included 1,622 individuals. A 4-group trajectory model best fit our data. Seventy percent of individuals averaged about 92% adherence throughout the study period; 10% experienced a pronounced decline when the pandemic started (pandemic non-adherers); 11% experienced a sharp decline mid-pandemic (late non-adherers); and 9% experienced a sharp decline at the beginning of the pandemic and returned to higher adherence after a year (disrupted adherers). Adherers were least likely to be diagnosed with a substance use disorder, and had more telehealth visits, mental health outpatient visits, and fewer emergency department visits on average. Late non-adherers were more likely than adherers to have substance use disorders and physical health conditions. Pandemic non-adherers had more co-occurring psychiatric disorders than adherers and had the lowest use of case management. Three in ten previously adherent individuals with schizophrenia became less adherent to antipsychotic medications, either at the onset or later in the pandemic. Our findings point to telehealth and case management as critical strategies for treatment engagement, especially during public health crises, and well as the need to address co-occurring conditions.
为了确定在疫情期间医疗补助参保的精神分裂症患者的用药依从模式，以及这些模式与在2019年冠状病毒病疫情之前用药依从性高的患者中的相关因素。我们使用了来自费城的医疗补助理赔数据来确定年龄≥18岁的精神分裂症患者、他们的人口统计学特征以及医疗服务使用情况。我们使用群体轨迹模型来确定依从性趋势，并使用方差分析来检验依从性组与人口统计学特征及服务使用之间的关联。样本包括1622名个体。一个4组轨迹模型最适合我们的数据。70%的个体在整个研究期间平均依从率约为92%；10%的个体在疫情开始时出现明显下降（疫情期间不依从者）；11%的个体在疫情中期出现急剧下降（后期不依从者）；9%的个体在疫情开始时急剧下降，一年后恢复到较高的依从性（中断依从者）。依从者被诊断为物质使用障碍的可能性最小，平均有更多的远程医疗就诊、心理健康门诊就诊，急诊就诊次数较少。后期不依从者比依从者更有可能患有物质使用障碍和身体健康状况。疫情期间不依从者比依从者有更多共病的精神障碍，且病例管理使用最少。十分之三以前依从的精神分裂症患者在疫情开始时或之后对抗精神病药物的依从性降低。我们的研究结果表明，远程医疗和病例管理是治疗参与的关键策略，尤其是在公共卫生危机期间，同时也表明需要解决共病情况。
