Validation of Claims Data for Absorbing Pads as a Measure for Urinary Incontinence after Radical Prostatectomy, a National Cross-Sectional Analysis.
Diederik J H BaasJan ReitsmaLieke van GerwenJaron VleghaarJolanda M L G GehlenCathelijne M P Ziedses des PlantesJean Paul A van BastenRoderick C N van den BerghH Max BruinsEelco R P ColletteRobert J HoekstraBen C KnipscheerPim J van LeeuwenDaphne Luijendijk-de BruinJoep G H van RoermundJ P Michiel SedelaarTommy G W SpeelSaskia P StompsCarl J WijburgRob P W F WijnIgle Jan de JongDiederik M SomfordPublished in: Cancers (2023)
The use of healthcare insurance claims data for urinary incontinence (UI) pads has the potential to serve as an objective measure for assessing post-radical prostatectomy UI rates, but its validity for this purpose has not been established. The aim of this study is to correlate claims data with Patient Reported Outcome Measures (PROMs) for UI pad use. Patients who underwent RP in the Netherlands between September 2019 and February 2020 were included. Incontinence was defined as the daily use of ≥1 pad(s). Claims data for UI pads at 12-15 months after RP were extracted from a nationwide healthcare insurance database in the Netherlands. Participating hospitals provided PROMS data. In total, 1624 patients underwent RP. Corresponding data of 845 patients was provided by nine participating hospitals, of which 416 patients were matched with complete PROMs data. Claims data and PROMs showed 31% and 45% post-RP UI (≥1 pads). UI according to claims data compared with PROMs had a sensitivity of 62%, specificity of 96%, PPV of 92%, NPV of 75% and accuracy of 81%. The agreement between both methods was moderate (κ = 0.60). Claims data for pads moderately align with PROMs in assessing post-prostatectomy urinary incontinence and could be considered as a conservative quality indicator.
Keyphrases
- patient reported outcomes
- electronic health record
- healthcare
- urinary incontinence
- end stage renal disease
- radical prostatectomy
- prostate cancer
- big data
- ejection fraction
- patient reported
- chronic kidney disease
- cross sectional
- prognostic factors
- peritoneal dialysis
- emergency department
- machine learning
- risk assessment
- climate change
- deep learning
- minimally invasive
- social media
- robot assisted
- benign prostatic hyperplasia
- clinical evaluation