Applied nursing research : ANR · 2026
Association between the PERROCA patient classification system and nursing workload: A multicentre cross-sectional study.
СтатьяМногоцентровое исследованиеНазвание и аннотация: Перевод пока не подготовлен
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Zaboli Arian, Solazzo Pasquale, Rigger Manuel, Vidi Marta, Ruzzante Davide, Macciocu Chiara, Piva Miriam, Innerhofer Helena, Ziller Marta, Lioni Roland, Turcato Gianni, Siller Marianne
Аннотация
BACKGROUND: Measuring nursing workload is essential for staffing decisions and patient allocation, yet evidence remains limited on whether the PERROCA Patient Classification System reflects actual nursing workload across heterogeneous hospital settings.
PURPOSE: To evaluate the strength and independence of the association between PERROCA Patient Classification System and nursing workload, measured as real-time recorded nursing care time, across different hospital ward settings.
METHODS: We conducted a prospective multicentre cross-sectional study in 12 wards across five hospitals. Adult inpatients present on designated study days were enrolled. Nursing workload was measured as the total time spent on nurse-performed activities over 24 h. Associations were analysed using linear regression, mixed-effects linear regression with ward-level clustering, and logistic regression.
RESULTS: A total of 472 patients were included. Median PERROCA score was 17, and median total daily nursing care time was 155 min. In simple linear regression, each 1-point increase in PERROCA was associated with 12.8 additional minutes of nursing care time. In the mixed model, PERROCA remained independently associated with nursing care time, with 7.45 additional minutes per point increase. High nursing workload occurred in 112 patients (23.7%), and PERROCA was independently associated with this outcome.
CONCLUSIONS: PERROCA was significantly associated with nursing workload and may represent a practical tool for estimating nursing workload across different hospital ward settings.
PURPOSE: To evaluate the strength and independence of the association between PERROCA Patient Classification System and nursing workload, measured as real-time recorded nursing care time, across different hospital ward settings.
METHODS: We conducted a prospective multicentre cross-sectional study in 12 wards across five hospitals. Adult inpatients present on designated study days were enrolled. Nursing workload was measured as the total time spent on nurse-performed activities over 24 h. Associations were analysed using linear regression, mixed-effects linear regression with ward-level clustering, and logistic regression.
RESULTS: A total of 472 patients were included. Median PERROCA score was 17, and median total daily nursing care time was 155 min. In simple linear regression, each 1-point increase in PERROCA was associated with 12.8 additional minutes of nursing care time. In the mixed model, PERROCA remained independently associated with nursing care time, with 7.45 additional minutes per point increase. High nursing workload occurred in 112 patients (23.7%), and PERROCA was independently associated with this outcome.
CONCLUSIONS: PERROCA was significantly associated with nursing workload and may represent a practical tool for estimating nursing workload across different hospital ward settings.