Benevides Teal W, Carretta Henry J, Graves Katelyn Y
Department of Occupational Therapy, College of Allied Health Sciences, Augusta University, Augusta, Georgia.
Department of Behavioral Sciences and Social Medicine, College of Medicine, Florida State University, Tallahassee, Florida.
Autism Adulthood. 2019 Sep 1;1(3):210-218. doi: 10.1089/aut.2018.0036. Epub 2019 Sep 11.
Medicare is a public insurer for whom many autistic adults are eligible in the United States, but little is known about autistic beneficiaries who are covered. A challenge in using claim data is identification of autism spectrum disorder (ASD) cases to ensure accurate characterization. Some work suggests that relying on one claim could identify probable ASD, although other works indicate that two claims are necessary for case identification. The purpose of the current study was to describe the sample of Medicare young adult beneficiaries, and determine whether using a 1+ versus 2+ claim case identification resulted in similar interpretation of sample demographic characteristics and primary care utilization patterns in Medicare professional service claims.
We used Medicare Limited Data Sets (2008-2010) claims. After ASD case identification using ICD-9-CM (299.xx), 527 unique beneficiaries in the last claim year of 2010 professional service file were identified as having at least one claim of ASD. Of these, 69% ( = 364) had two or more claims. Proportions and zero-inflated negative binomial regression were used to examine differences in demographic characteristics and primary care utilization and costs for the 1+ and 2+ samples.
Medicare claims contain a sample of autistic adults with expected demographics identified in historic prevalence cohorts. No differences in age, gender, race/ethnicity, Hispanic status, or dual-eligibility months or Adjusted Clinical Groups (ACG) concurrent risk scores were identified between the 1+ and 2+ samples. No difference was found in the overall estimation of primary care use or costs between the 1+ and 2+ samples based on Zellner's seemingly unrelated regression methods.
This study is the first to describe a national sample of Medicare-insured autistic adults. We found that using a 1+ case identification results in a sample that is demographically similar to a 2+ claim sample, and produces similar estimates of utilization as a 2+ claim sample.
医疗保险是美国许多成年自闭症患者符合资格的公共保险机构，但对于参保的自闭症受益人的了解却很少。使用索赔数据时面临的一个挑战是识别自闭症谱系障碍（ASD）病例，以确保准确描述。一些研究表明，依靠一项索赔可以识别可能的ASD，尽管其他研究表明需要两项索赔才能识别病例。本研究的目的是描述医疗保险青年成年受益人的样本，并确定使用一项及以上索赔与两项及以上索赔病例识别方法在医疗保险专业服务索赔中对样本人口统计学特征和初级保健利用模式的解释是否相似。
我们使用了医疗保险有限数据集（2008 - 2010年）的索赔数据。在使用国际疾病分类第九版临床修订本（ICD - 9 - CM，编码为299.xx）进行ASD病例识别后，在2010年专业服务档案的最后索赔年份中，527名独特的受益人被确定至少有一项ASD索赔。其中，69%（n = 364）有两项或更多项索赔记录。使用比例分析和零膨胀负二项回归来检验一项及以上索赔样本与两项及以上索赔样本在人口统计学特征、初级保健利用情况以及费用方面的差异分析。
医疗保险索赔包含了一个自闭症成年人样本，其人口统计学特征与历史患病率队列中预期的相符。一项及以上索赔样本与两项及以上索赔样本在年龄、性别、种族/族裔、西班牙裔身份、双重资格月数或调整临床分组（ACG）并发风险评分方面未发现差异。基于泽尔纳看似不相关回归方法，一项及以上索赔样本与两项及以上索赔样本在初级保健使用或费用的总体估计上未发现差异。
本研究首次描述了全国范围内医疗保险参保的成年自闭症患者样本。我们发现，使用一项索赔病例识别方法得出的样本在人口统计学上与两项及以上索赔样本相似，并产生与两项及以上索赔样本相似的利用估计值。
