一种使用行政索赔来识别养老院入院情况的方法的验证
Validation of a method for identifying nursing home admissions using administrative claims.
作者信息
Zuckerman Ilene H, Sato Masayo, Hsu Van Doren, Hernandez Jose J
机构信息
Department of Pharmaceutical Health Services Research, University of Maryland School of Pharmacy, Baltimore, Maryland, USA.
出版信息
BMC Health Serv Res. 2007 Dec 10;7:202. doi: 10.1186/1472-6963-7-202.
BACKGROUND
Currently there is no standard algorithm to identify whether a subject is residing in a nursing home from administrative claims. Our objective was to develop and validate an algorithm that identifies nursing home admissions at the resident-month level using the MarketScan Medicare Supplemental and Coordination of Benefit (COB) database.
METHODS
The computer algorithms for identifying nursing home admissions were created by using provider type, place of service, and procedure codes from the 2000 - 2002 MarketScan Medicare COB database. After the algorithms were reviewed and refined, they were compared with a detailed claims review by an expert reviewer. A random sample of 150 subjects from the claims was selected and used for the validity analysis of the algorithms. Contingency table analysis, comparison of mean differences, correlations, and t-test analyses were performed. Percentage agreement, sensitivity, specificity, and Kappa statistics were analyzed.
RESULTS
The computer algorithm showed strong agreement with the expert review (99.9%) for identification of the first month of nursing home residence, with high sensitivity (96.7%), specificity (100%) and a Kappa statistic of 0.97. Weighted Pearson correlation coefficient between the algorithm and the expert review was 0.97 (p < 0.0001).
CONCLUSION
A reliable algorithm indicating evidence of nursing home admission was developed and validated from administrative claims data. Our algorithm can be a useful tool to identify patient transitions from and to nursing homes, as well as to screen and monitor for factors associated with nursing home admission and nursing home discharge.
背景
目前尚无通过行政索赔来确定个体是否居住在养老院的标准算法。我们的目标是开发并验证一种算法，该算法使用市场扫描医疗保险补充和福利协调（COB）数据库，在居民月层面识别养老院入院情况。
方法
利用2000 - 2002年市场扫描医疗保险COB数据库中的提供者类型、服务地点和程序代码创建识别养老院入院情况的计算机算法。在对算法进行审查和完善后，将其与专家评审员进行的详细索赔审查进行比较。从索赔中随机抽取150名受试者作为样本，用于算法的有效性分析。进行列联表分析、均值差异比较、相关性分析和t检验分析。分析百分比一致性、敏感性、特异性和卡方统计量。
结果
计算机算法在识别养老院居住第一个月方面与专家评审显示出高度一致性（99.9%），敏感性高（96.7%），特异性高（100%），卡方统计量为0.97。算法与专家评审之间的加权皮尔逊相关系数为0.97（p < 0.0001）。
结论
从行政索赔数据中开发并验证了一种可靠的算法，可表明养老院入院证据。我们的算法可成为识别患者进出养老院的有用工具，以及筛查和监测与养老院入院和出院相关的因素。
Zotero 插件