Literature DB >> 14603097

Predictive value of clinical diagnostic codes for the CDC case definition of pelvic inflammatory disease (PID): implications for surveillance.

Sylvie Ratelle1, Deborah Yokoe, Christina Blejan, Michael Whelan, Yuren Tang, Richard Platt, Ralph Blair, Guoyu Tao, Kathleen Irwin.   

Abstract

BACKGROUND: Reporting of pelvic inflammatory disease (PID) from private providers could be incomplete because of time and staff constraints, lack of knowledge of reporting requirements and of case definitions. Reporting burden can be alleviated with the use of administrative data. GOAL: The goal of this study was to determine the validity of clinical diagnostic codes assigned in electronic medical records (EMR) for identifying PID and their use in enhancing surveillance. STUDY
DESIGN: A random sample of 296 records with a PID International Classification of Diseases, 9th Revision (ICD-9), code (614.9) were reviewed to assess for the presence of the Centers for Disease Control and Prevention (CDC) criteria for the case definition of PID. We used the records meeting the CDC clinical case definition criteria as the reference standard to determine the sensitivity, specificity, and predictive values of various data elements.
RESULTS: Used alone, the positive predictive value (PPV) of ICD-9 code 614.9 for a CDC case definition of PID was 18.1%. The PPV increased to 100% and 56% when the ICD-9 code visit was associated with a positive test for Neisseria gonorrhoeae (GC) and Chlamydia trachomatis (CT), respectively.
CONCLUSION: In this multispecialty group practice, a positive test for GC and CT coupled with ICD-9 code 614.9 could be used to enhance reporting of cases of PID.

Entities:  

Mesh:

Year:  2003        PMID: 14603097     DOI: 10.1097/01.OLQ.0000087945.08303.38

Source DB:  PubMed          Journal:  Sex Transm Dis        ISSN: 0148-5717            Impact factor:   2.830


  9 in total

1.  Gonorrhea Update.

Authors:  Margaret C. Bash
Journal:  Curr Infect Dis Rep       Date:  2004-04       Impact factor: 3.725

2.  Under-reporting of pelvic inflammatory disease in Hawaii: a comparison of state surveillance and hospitalization data.

Authors:  Misty Pacheco; Tetine Sentell; Alan R Katz
Journal:  J Community Health       Date:  2014-04

3.  Assessing the Accuracy of Physician Self-disclosed PID Reporting: A Comparison of Data from a Physician Survey and Actual PID Case Reports from a State Surveillance System.

Authors:  Misty Y Pacheco; Alan R Katz
Journal:  Hawaii J Med Public Health       Date:  2018-10

4.  Management of first-episode pelvic inflammatory disease in primary care: results from a large UK primary care database.

Authors:  Amanda Nicholson; Greta Rait; Tarita Murray-Thomas; Gwenda Hughes; Catherine H Mercer; Jackie Cassell
Journal:  Br J Gen Pract       Date:  2010-10       Impact factor: 5.386

5.  Detection of pelvic inflammatory disease: development of an automated case-finding algorithm using administrative data.

Authors:  Catherine L Satterwhite; Onchee Yu; Marsha A Raebel; Stuart Berman; Penelope P Howards; Hillard Weinstock; David Kleinbaum; Delia Scholes
Journal:  Infect Dis Obstet Gynecol       Date:  2011-11-14

6.  Heterogeneity in risk of pelvic inflammatory diseases after chlamydia infection: a population-based study in Manitoba, Canada.

Authors:  Bethan Davies; Helen Ward; Stella Leung; Katy M E Turner; Geoff P Garnett; James F Blanchard; B Nancy Yu
Journal:  J Infect Dis       Date:  2014-12-01       Impact factor: 5.226

7.  Reliability of administrative data to identify sexually transmitted infections for population health: a systematic review.

Authors:  Brian E Dixon; Saurabh Rahurkar; Yenling Ho; Janet N Arno
Journal:  BMJ Health Care Inform       Date:  2019-08

8.  Validation of International Classification of Diseases, Tenth Revision, Clinical Modification Codes for Identifying Cases of Chlamydia and Gonorrhea.

Authors:  Yenling Andrew Ho; Saurabh Rahurkar; Guoyu Tao; Chirag G Patel; Janet N Arno; Jane Wang; Andrea A Broyles; Brian E Dixon
Journal:  Sex Transm Dis       Date:  2021-05-01       Impact factor: 3.868

9.  Billing code algorithms to identify cases of peripheral artery disease from administrative data.

Authors:  Jin Fan; Adelaide M Arruda-Olson; Cynthia L Leibson; Carin Smith; Guanghui Liu; Kent R Bailey; Iftikhar J Kullo
Journal:  J Am Med Inform Assoc       Date:  2013-10-28       Impact factor: 4.497

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.