268704 Reliability of a visit date selection algorithm: Correctly characterizing follow-up visits and missed opportunities to re-test

Wednesday, October 31, 2012 : 11:30 AM - 11:45 AM

Mary Menz, PHN, BSN , Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco, Bixby Center for Global Reproductive Health, Sacramento, CA
Fran Maguire , Bixby Center for Global Reproductive Health, University of California, San Francisco, Sacramento, CA
Mary Bradsberry , UCSF Bixby Center for Global Reproductive Health, Sacramento, CA
Philip Darney, MD, MSc , Bixby Center for Global Reproductive Health, University of California, San Francisco, San Francisco, CA
Heike Thiel de Bocanegra, PhD, MPH , Assistant Professor and Director, UCSF Family PACT Evaluation, University of California, San Francisco, Sacramento, CA
Background: Administrative claims are the most convenient data available to evaluate the quality of care delivered. However, they may not always include sufficient information about the content of a clinic encounter.

Objective: Demonstrate with onsite chart review the accuracy of a visit selection algorithm to identify visits related to management of sexually transmitted infections (STI).

Methods: We sampled from client claims data at the California Department of Public Health offices. Charts were requested for 809 visits for 389 clients in a sample of females matched to the state chlamydia case registry for 2009. Encounters were then selected with a claims-based algorithm using standardized procedure codes and service dates. We used chart abstraction to determine whether STI episodes were correctly identified.

Results: The algorithm correctly identified 83% of the face-to-face encounters within 7 days of the diagnosis date for chlamydia cases. We found 118 encounter records at an interval appropriate for re-testing after treatment. Based on these records, 55% were seen for an STI-related reason but only 31% of clients were re-tested. The encounters associated with timely re-testing included pelvic exam (60%) and urine pregnancy test procedures (40%). However 50% of the clients with either or both procedures documented were not tested in spite of the convenient specimen opportunity and the indication to collect it.

Conclusions/Implications: Our algorithm correctly identified episodes of chlamydia management. Missed opportunities for re-testing are also identified. The algorithm can be modified to identify episodes of care to evaluate quality of disease management.

Learning Areas:
Conduct evaluation related to programs, research, and other areas of practice
Planning of health education strategies, interventions, and programs

Learning Objectives:
1)List 2 claims-based procedures that can correctly identify face-to-face opportunities for convenient chlamydia re-testing specimen collection. 2)Identify the 3 most common validated reasons clients return after being treated for chlamydia. 3)Describe how a claims-based algorithm can identify missed opportunities for health screening.

Keywords: Health Care Quality, STD Prevention

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I am an RN and PHN and have worked in the areas of program policy and administration for publicly funded health programs for 18 years with a special interest in accurately assessing the quality of care delivered in women's health settings.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.