Incompleteness of reporting of laboratory-confirmed chlamydial infection by providers affiliated with a managed care organization, 1997-1999.

Abstract

BACKGROUND:

Surveillance for sexually transmitted diseases (STDs) depends on the receipt of positive STD test results from laboratories or reports of STD diagnoses from clinicians to local or state health departments.

GOAL:

The goal of this study was to evaluate incompleteness of reporting of chlamydial infection in a large staff-model managed care organization (MCO) using laboratory data and provider-based reports.

METHODS:

All cases of chlamydial infection in 2 databases, one from the MCO during January 1997 through June 1999 and the other from the state STD registry, were compared by using a standard algorithm alone that included patient's name, sex, and date of specimen collection, and by using the standard algorithm together with the patient's medical record number.

RESULTS:

Of 833 cases of chlamydial infection in the MCO case database, 597 were matched to the cases in the state registry using the standard algorithm alone and 671 were matched using the standard algorithm together with the patient's medical record number. In addition, 89 cases of chlamydial infection in the state registry had been reported from the MCO during the same timeframe but were not matched to cases in the MCO case database by these algorithms. The estimated incompleteness of reporting ranged from 9% to 28% depending on matching algorithms used and the criteria used to define completeness.

CONCLUSION:

Based on this comparison of MCO data with the state STD registry data, the estimated incompleteness of reporting in a MCO depended on matching algorithms used and the criteria used to define completeness. Incompleteness of STD case reporting could be reduced if confidential electronic reporting methods and more complete case characteristic variables were used.

• Authors: Guoyu Tao, Peter Carr, Michael Stiffman, Terese A DeFor
• Journal: Sexually transmitted diseases (Sex Transm Dis) Vol. 31 Issue 3 Pg. 139-42 (Mar 2004) ISSN: 0148-5717 [Print] United States
• PMID: 15076924 (Publication Type: Journal Article)

Topics

• Algorithms
• Chlamydia Infections (epidemiology, prevention & control)
• Disease Notification (statistics & numerical data)
• Humans
• Managed Care Programs
• Minnesota (epidemiology)
• Registries (statistics & numerical data)
• Retrospective Studies