title: A Bayesian Procedure for File Linking to Analyze End-of-Life Medical Costs.
abstract: End-of-life medical expenses are a significant proportion of all health care expenditures. These costs were studied using costs of services from Medicare claims and cause of death (CoD) from death certificates. In the absence of a unique identifier linking the two datasets, common variables identified unique matches for only 33% of deaths. The remaining cases formed cells with multiple cases (32% in cells with an equal number of cases from each file and 35% in cells with an unequal number). We sampled from the joint posterior distribution of model parameters and the permutations that link cases from the two files within each cell. The linking models included the regression of location of death on CoD and other parameters, and the regression of cost measures with a monotone missing data pattern on CoD and other demographic characteristics. Permutations were sampled by enumerating the exact distribution for small cells and by the Metropolis algorithm for large cells. Sparse matrix data structures enabled efficient calculations despite the large dataset (≈1.7 million cases). The procedure generatesmdatasets in which the matches between the two files are imputed. Themdatasets can be analyzed independently and results combined using Rubin's multiple imputation rules. Our approach can be applied in other file linking applications.
authors: Department of Biostatistics, Brown University, Providence, RI 02912.
authors: Roee
authors: R
authors: Gutman
authors: Christopher C
authors: CC
authors: Afendulis
authors: Alan M
authors: AM
authors: Zaslavsky
keywords: Administrative Data; Bayesian Analysis; Missing Data; Record Linkage; Statistical Matching
references: J Health Econ. 2001 Jul;20(4):461-94
references: 11469231
references: N Engl J Med. 1993 Apr 15;328(15):1092-6
references: 8455667
references: Health Aff (Millwood). 2001 Jul-Aug;20(4):188-95
references: 11463076
references: Int Stat Rev. 2010 Apr;78(1):40-64
references: 21743766
references: J Health Econ. 2000 Sep;19(5):679-95
references: 11184799