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  • Title: Identifying diabetes mellitus or heart disease among health maintenance organization members: sensitivity, specificity, predictive value, and cost of survey and database methods.
    Author: O'Connor PJ, Rush WA, Pronk NP, Cherney LM.
    Journal: Am J Manag Care; 1998 Mar; 4(3):335-42. PubMed ID: 10178496.
    Abstract:
    We conducted a study of the sensitivity, specificity, positive predictive value, and cost of two methods of identifying diagnosed diabetes mellitus or heart disease among members of a health maintenance organization (HMO). Among 3186 adult HMO members who were attending one primary care clinic, 2326 were reached for a telephone survey (efficiency = 0.73). Among these members, 1991 answered standardized questions to ascertain whether they had diabetes or heart disease (corrected response rate = 0.85). Linkage was then made to computerized diagnostic databases. By means of both a database method and a survey method, the 1976 members with complete data for analysis were classified as having or not having diabetes or heart disease. When results with the two methods disagreed, charts were reviewed to confirm the presence or absence of diabetes or heart disease. Diabetes was identified among 4.7% of adult members, and heart disease was identified among 3.7%. Identification of diabetes differed between the database method and the survey method (sensitivity 0.91 vs 0.98, specificity 0.99 vs 0.99, positive predictive value 0.94 vs 0.83). Identification of heart attach history was similar for the database method and the survey method (sensitivity 0.89 vs 0.95, specificity 0.99 vs 0.99, positive predictive value 0.79 vs 0.81). The cost of obtaining data was $13.50 per member for the survey method and $0.30 per member for the database method. Database methods or survey methods of identifying selected chronic diseases among HMO members may be acceptable for various purposes, but database identification methods appear to be less expensive and provide information on a higher proportion of HMO members than do survey methods. Accurate identification of chronic diseases among patients supports clinic-level measures for clinical improvement, research, and accountability.
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