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The California automated mortality linkage system (CAMLIS)

Author

Listed:
  • Abellano, M.G.
  • Petersen, G.R.
  • Petitti, D.B.
  • Smith, R.E.

Abstract

The California Automated Mortality Linkage System (CAMLIS), established in 1981 to facilitate the conduct of follow-up studies in the State of California, employs a combination of deterministic and probabilistic linkage decision criteria to perform the death clearance function. The system was evaluated against four traditional death clearance procedures and the performance of each procedure measured in terms of measures of sensitivity and specificity. Only one procedure was associated with a specificity lower than 0.99; for that one, the specificity was 0.93. There was much greater fluctuation in the observed sensitivity of 0.97 versus 0.79 for the Social Security Administration. A comparison against the National Death Index (NDI) produced sensitivities of 0.89 for CAMLIS and 0.94 for the NDI. An assessment of manual search procedures using a file of Japanese names produced a CAMLIS sensitivity measure of 0.92 compared with 0.93 for the manual search. Another manual search procedure using microfiche copies of the state death index produced a CAMLIS sensitivity of 0.97; in this evaluation, the sensitivity of the manual search was defined in 1.0. Another measure of performance of a death clearance procedure is its predictive value in identifying a person who has died; CAMLIS generated predictive values in these evaluations that ranged from 0.93 through 0.99, contrasted with the NDI value of 0.59.

Suggested Citation

  • Abellano, M.G. & Petersen, G.R. & Petitti, D.B. & Smith, R.E., 1984. "The California automated mortality linkage system (CAMLIS)," American Journal of Public Health, American Public Health Association, vol. 74(12), pages 1324-1330.
  • Handle: RePEc:aph:ajpbhl:1984:74:12:1324-1330_8
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    Cited by:

    1. Neugebauer Romain & Chandra Malini & Paredes Antonio & J. Graham David & McCloskey Carolyn & S. Go Alan, 2013. "A Marginal Structural Modeling Approach with Super Learning for a Study on Oral Bisphosphonate Therapy and Atrial Fibrillation," Journal of Causal Inference, De Gruyter, vol. 1(1), pages 21-50, June.
    2. Scheffler, Richard M. & Brown, Timothy T. & Syme, Leonard & Kawachi, Ichiro & Tolstykh, Irina & Iribarren, Carlos, 2008. "Community-level social capital and recurrence of acute coronary syndrome," Social Science & Medicine, Elsevier, vol. 66(7), pages 1603-1613, April.

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