Article Text
Abstract
Objectives: The clinical diagnosis of pelvic inflammatory disease (PID) is subjective. Our aim was to determine if the pattern of diagnosis of PID among experienced clinicians varied compared with the diagnosis of genital warts.
Methods: We conducted a retrospective study of 325 PID diagnoses made by experienced clinicians at Melbourne Sexual Health Centre, Australia (2002–2006), where doctors saw 21 785 unselected female patients in a walk-in service. We compared the proportion of female patients diagnosed as having PID and genital warts between doctors and then compared doctors above (high diagnosing) and below (low diagnosing) the mean rate of PID diagnosis.
Results: There were significant and clinically important differences in the proportion of women diagnosed with having PID (0–5.7%) across 23 doctors investigated. Estimated standard deviation in the frequency of PID diagnosis (logit scale) was 1.26 (95% CI 0.81 to 1.95)—approximately four times greater than for warts. Patients seen by high (n = 4673) and low (n = 16 787) diagnosing doctors had similar epidemiological risk profiles suggesting true distribution of PID cases across doctors was similar (p>0.13). Women diagnosed with having PID by high diagnosing doctors compared with low diagnosing doctors were younger (odds ratio 1.7; 95% CI 1.1 to 2.8, p = 0.013) but otherwise had similar epidemiological and clinical features.
Conclusions: Differences in diagnostic rates for PID between doctors are substantial and may be because of PID cases being missed by some doctors.
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Footnotes
Funding: C S Bradshaw holds a National Medical & Research Council Research Scholarship. No external sources of funding were used to support this project.
Competing interests: None.
Ethics approval: This was a clinical quality assurance audit and under Australian guidelines did not require formal ethics approval.
Contributors: All authors contributed to the design and planning of this study. AD was responsible for the chart reviews. AD, MYC and CKF were responsible for the database analysis. JH and LG oversaw the statistical analysis. All authors contributed to the writing, editing and approval of the manuscript.
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