H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA, USA (RH, YZ, NS).
Department of Pediatrics, School of Medicine, Emory University, Atlanta, GA, USA (AF).
Med Decis Making. 2018 Jan;38(1):107-119. doi: 10.1177/0272989X17731753. Epub 2017 Oct 13.
This study introduces a framework for analyzing and visualizing health care utilization for millions of children, with a focus on pediatric asthma, one of the major chronic respiratory conditions.
The data source is the 2005 to 2012 Medicaid Analytic Extract claims for 10 Southeast states. The study population consists of Medicaid-enrolled children with persistent asthma. We translate multiyear, individual-level medical claims into sequences of discrete utilization events, which are modeled using Markov renewal processes and model-based clustering. Network analysis is used to visualize utilization profiles. The method is general, allowing the study of other chronic conditions.
The study population consists of 1.5 million children with persistent asthma. All states have profiles with high probability of asthma controller medication, as large as 60.6% to 90.2% of the state study population. The probability of consecutive asthma controller prescriptions ranges between 0.75 and 0.95. All states have utilization profiles with uncontrolled asthma with 4.5% to 22.9% of the state study population. The probability for controller medication is larger than for short-term medication after a physician visit but not after an emergency department (ED) visit or hospitalization. Transitions from ED or hospitalization generally have a lower probability into physician office (between 0.11 and 0.38) than into ED or hospitalization (between 0.20 and 0.59).
In most profiles, children who take asthma controller medication do so regularly. Follow-up physician office visits after an ED encounter or hospitalization are observed at a low rate across all states. Finally, all states have a proportion of children who have uncontrolled asthma, meaning they do not take controller medication while they have severe outcomes.
本研究介绍了一个用于分析和可视化数百万儿童医疗保健利用情况的框架,重点关注儿科哮喘,这是一种主要的慢性呼吸道疾病。
数据来源是 2005 年至 2012 年 Medicaid Analytic Extract 的 10 个东南部州的索赔数据。研究人群包括有持续性哮喘的 Medicaid 参保儿童。我们将多年的个人医疗索赔数据转化为离散利用事件序列,这些事件序列使用马尔可夫更新过程和基于模型的聚类进行建模。网络分析用于可视化利用情况。该方法具有通用性,可用于研究其他慢性疾病。
研究人群包括 150 万患有持续性哮喘的儿童。所有州的哮喘控制器药物的使用概率都很高,高达 60.6%至 90.2%的州研究人群。连续使用哮喘控制器处方的概率在 0.75 到 0.95 之间。所有州都有未控制哮喘的利用情况,占州研究人群的 4.5%至 22.9%。在医生就诊后,使用控制器药物的概率大于短期药物,但在急诊室 (ED) 就诊或住院后则不然。从 ED 或住院过渡到医生办公室的概率通常较低(在 0.11 到 0.38 之间),而从 ED 或住院过渡到 ED 或住院的概率则较高(在 0.20 到 0.59 之间)。
在大多数情况下,服用哮喘控制器药物的儿童会定期服用。所有州的 ED 就诊或住院后,后续的医生就诊率都很低。最后,所有州都有一部分儿童患有未控制的哮喘,这意味着他们在出现严重后果时不服用控制器药物。