title: A benchmark comparison of deterministic and probabilistic methods for defining manual review datasets in duplicate records reconciliation.
abstract: BACKGROUND
  Clinical databases require accurate entity resolution (ER). One approach is to use algorithms that assign questionable cases to manual review. Few studies have compared the performance of common algorithms for such a task. Furthermore, previous work has been limited by a lack of objective methods for setting algorithm parameters. We compared the performance of common ER algorithms: using algorithmic optimization, rather than manual parameter tuning, and on two-threshold classification (match/manual review/non-match) as well as single-threshold (match/non-match).
  
  
  METHODS
  We manually reviewed 20,000 randomly selected, potential duplicate record-pairs to identify matches (10,000 training set, 10,000 test set). We evaluated the probabilistic expectation maximization, simple deterministic and fuzzy inference engine (FIE) algorithms. We used particle swarm to optimize algorithm parameters for a single and for two thresholds. We ran 10 iterations of optimization using the training set and report averaged performance against the test set.
  
  
  RESULTS
  The overall estimated duplicate rate was 6%. FIE and simple deterministic algorithms allowed a lower manual review set compared to the probabilistic method (FIE 1.9%, simple deterministic 2.5%, probabilistic 3.6%; p<0.001). For a single threshold, the simple deterministic algorithm performed better than the probabilistic method (positive predictive value 0.956 vs 0.887, sensitivity 0.985 vs 0.887, p<0.001). ER with FIE classifies 98.1% of record-pairs correctly (1/10,000 error rate), assigning the remainder to manual review.
  
  
  CONCLUSIONS
  Optimized deterministic algorithms outperform the probabilistic method. There is a strong case for considering optimized deterministic methods for ER.
authors.affiliation: School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas, USA.
authors.forename: Erel
authors.initials: E
authors.lastname: Joffe
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Byrne
authors.forename: Phillip
authors.initials: P
authors.lastname: Reeder
authors.forename: Jorge R
authors.initials: JR
authors.lastname: Herskovic
authors.forename: Craig W
authors.initials: CW
authors.lastname: Johnson
authors.forename: Allison B
authors.initials: AB
authors.lastname: McCoy
authors.forename: Dean F
authors.initials: DF
authors.lastname: Sittig
authors.forename: Elmer V
authors.initials: EV
authors.lastname: Bernstam
mesh_terms: D000465:Algorithms; D019985:Benchmarking; D057286:Electronic Health Records; D017143:Fuzzy Logic; D006801:Humans; D008498:Medical Record Linkage / Q000379:methods; D011336:Probability
keywords: Medical Record Linkage [N04.452.859.564.550]; Medical Records Systems, Computerized [L01.700.508.300.695]