Abstract
Abstract
Background
Pelvic floor disorders, specifically pelvic organ prolapse and urinary incontinence, are highly prevalent conditions that exhibit substantial practice variation. This study aims to examine the relationship between clinical practice guidelines and practice variation by integrating professional expectations, guideline recommendations and actual healthcare utilization pattens.
Methods
A mixed-methods approach was used to analyze 90 combinations of diagnoses, treatment procedures and specialties. The methodology included: (1) a systematic analysis of Dutch clinical practice guidelines, (2) mapping medical specialists’ expectations of volume and variation, and (3) measuring practice variation. Using nationwide claims data, practice variation was measured as Coefficients of Variation and Treatment Rate Ratios.
Results
Substantial practice variation persisted especially in diagnostic (Coefficient of variation range: 0.4–2.7, Treatment Rate Ratio range: 5.1–94.7) and surgical procedures (Coefficient of variation range: 0.6–2.9, Treatment Rate Ratio range: 4.0–33.9). Of 90 treatment combinations, 54% lacked guideline recommendations. Overall, no clear pattern emerged between guideline clarity and practice variation across hospitals, but for stress urinary incontinence and urge urinary incontinence, procedures with clear guidelines did show less practice variation. Accuracy of specialists’ predictions was high for patient volumes but low for practice variation.
Conclusions
This study revealed substantial inter-hospital variation in pelvic floor care across Dutch hospitals. While procedure volumes largely matched specialists’ expectations, specialists were less accurate in predicting variation. Clear clinical practice guideline recommendations were associated with less variation for diagnostic and surgical procedures for stress urinary incontinence and urge urinary incontinence but not for pelvic organ prolapse. Linking clinical practice guideline content with specialists’ expectation and nationwide claims data provides a framework to identify potential unwarranted variation and prioritize interventions to improve care quality.