Latent Profiles of Self-Reported Patient Privacy Protection Practices Among Hospital Healthcare Workers: Implications for Patient Safety and Interprofessional Education

Background/Objectives: This study aimed to identify latent profiles of self-reported patient privacy protection practices among hospital healthcare workers and to explore factors associated with profile membership. Methods: In a secondary analysis of survey data from 213 staff at a national hospital, 11 practice items retained through Rasch-based screening were analyzed with latent profile analysis. Model selection used information criteria and a bootstrap likelihood ratio test; robustness was examined with alternative models, resampling, and sensitivity analyses. Associated factors were evaluated with classification error-corrected three-step multinomial logistic regression. Results: Three profiles were identified, Low-practice (16.4%), Moderate-practice (29.1%), and High-practice (54.5%), differing mainly in overall level. The Low-practice profile reported particularly low practice on items about discussing patient information with unrelated staff, minimum-necessary disclosure, and account sharing. The High-practice profile was stable across resamples, whereas the boundary between the lower profiles was not, and comparisons with continuous factor models did not establish discrete types. Respondents aged 50 years or older were more likely than those under 40 to belong to the Moderate-practice rather than the High-practice profile (odds ratio = 2.89; 95% confidence interval, 1.25–6.70), but the 95% interval from a full-procedure bootstrap, which accounts for profile-estimation uncertainty, included 1 (0.42–14.39), so this association is exploratory. Occupation was not associated with profile membership. Conclusions: Self-reported privacy practices varied mainly in overall level, and apparent differences between privacy- and security-related behaviors may partly reflect item wording. Healthcare organizations may consider behavior-specific, interprofessional training and workflow supports rather than defining at-risk groups by demographic or occupational factors; their effectiveness should be evaluated in intervention studies.