Bynum 1-Year Standard Method for identifying Alzheimer’s Disease and Related Dementias (ADRD) in Medicare Claims data

Here, you will find resources to use the Bynum-Standard 1-Year Algorithm including a README file that accompanies SAS and Stata scripts for the 1-Year Standard Method for identifying Alzheimer’s Disease and Related Dementias (ADRD) in Medicare Claims data. <br> <br>There are seven script files (plus a parameters file for SAS [parm.sas]) for both SAS and Stata. The files are numbered in the order in which they should be run; the five “1” files may be run in any order.<br><br>The full algorithm requires access to a single year of Medicare Claims data for (1) MedPAR, (2) Home Health Agency (HHA) Claims File, (3) Hospice Claims File, (4) Carrier Claims and Line Files, and (5) Hospital Outpatient File (HOF) Claims and Revenue Files. All Medicare Claims files are expected to be in SAS format (.sas7bdat).<br>For each data source, the script will output three files*:<br><br>Diagnosis-level file: Lists individual ADRD diagnoses for each beneficiary for a given visit. This file allows researchers to identify which ICD-9-CM or ICD-10-CM codes are used in the claims data.Service Date-level file: Aggregated from the Diagnosis-level file, this file includes all beneficiaries with an ADRD diagnosis by Service Date (date of a claim with at least one ADRD diagnosis).Beneficiary-level file: Aggregated from the Service Date-level file, this file includes all beneficiaries with at least one* ADRD diagnosis at any point in the year within a specific file<br>* The algorithm combines the Carrier and HOF files at the Service Date-level. The final combined Carrier and HOF Beneficiary-level file includes those with at least two (2) claims that are seven (7) or more days apart.<br>​<br>A final combined file is created by merging all Beneficiary-level files. This file is used to identify beneficiaries with ADRD and can be merged onto other files by the Beneficiary ID (BENE_ID).<br><br><br>With appreciation &amp; acknowledgement to colleagues from a grant funded by the NIA for their involvement in development &amp; validation of the Bynum-Standard 1-Year Algorithm<br>

本资源库提供拜纳姆标准一年期算法（Bynum-Standard 1-Year Algorithm）的使用材料，包含适配该算法的SAS及Stata脚本的说明文档（README文件），该算法用于从医疗保险索赔数据中识别阿尔茨海默病及相关痴呆（Alzheimer’s Disease and Related Dementias, ADRD）。

针对SAS与Stata软件，本资源均包含7个脚本文件（SAS版本额外附带参数文件parm.sas）。所有脚本按运行顺序编号，其中编号带"1"的5个脚本可任意顺序执行。

完整算法需使用单年度的五类医疗保险索赔数据：(1) 医疗保险供应商分析与审核（MedPAR）文件、(2) 家庭健康机构（Home Health Agency, HHA）索赔文件、(3) 临终关怀索赔文件、(4) 经办商索赔及明细文件、(5) 医院门诊（Hospital Outpatient File, HOF）索赔与收入文件。所有医疗保险索赔文件需为SAS格式（.sas7bdat）。

针对每一类数据源，脚本将输出三类文件*：

诊断层面文件：记录每位受保人单次就诊对应的单条阿尔茨海默病及相关痴呆诊断信息，便于研究者识别索赔数据中使用的ICD-9-CM或ICD-10-CM编码。
服务日期层面文件：由诊断层面文件聚合生成，收录所有在某一服务日期（即包含至少一条阿尔茨海默病及相关痴呆诊断的索赔日期）存在对应诊断的受保人信息。
受保人层面文件：由服务日期层面文件聚合生成，收录在对应数据源的年度周期内，任意时间点存在至少一条阿尔茨海默病及相关痴呆诊断的受保人信息。

* 本算法将经办商索赔文件与医院门诊文件在服务日期层面进行合并。最终合并后的经办商与医院门诊受保人层面文件，将收录至少提交过2条间隔7天及以上索赔的受保人信息。

通过合并所有受保人层面文件，可生成最终合并文件。该文件用于识别存在阿尔茨海默病及相关痴呆诊断的受保人，可通过受保人ID（BENE_ID）与其他数据集进行关联匹配。

谨此感谢美国国家老龄化研究所（National Institute on Aging, NIA）资助项目团队的同仁，感谢他们参与拜纳姆标准一年期算法的开发与验证工作。