How the reliability and validity of the patient classification system can be ensured in daily nursing work? A follow-up study.

AIMS AND OBJECTIVES: This study aimed to determine the reliability and validity of the RAFAELA patient classification system (PCS) for qualified and efficient nurses. BACKGROUND: The number of patients per nurse or diagnosis-based determination of nursing workload are imprecise measures that do not consider the variation in patients' care needs. Ensuring the reliability and validity of the RAFAELA is important for the efficient allocation of nursing resources. METHODS: In this study, we investigated how the maintenance (parallel classification measurement and professional assessment of optimal nursing care intensity level measurement) of the RAFAELA was done with 9 years of follow-up data. The results were analysed using quantitative methods supplemented with qualitative audit descriptions. The STROBE checklist was used. RESULTS: The RAFAELA was used continuously in 44 units (40%). The length of use of the RAFAELA influenced the success of parallel classification measurements. Six per cent of units passed parallel classification measurement over 75% after 1-3 years' use, 42% after 4-6 years and 83% after 7-9 years. Among the units that used the RAFAELA PCS continuously, only four (9%) passed the professional assessment of optimal nursing care intensity level measurement. CONCLUSIONS: This study shows that ensuring the reliability and validity of the use of the RAFAELA is laborious, requires several years of use and continuous investments in nurses' skills and motivation. RELEVANCE TO CLINICAL PRACTICE: Qualified use of PCS is challenging, and organisations should invest to maintenance, training, support and user motivation. Each patient should be classified comprehensively, and nursing resources should be calculated correctly. In addition, utilisation of the nursing intensity level should be maximised. CLINICAL TRIAL REGISTRATION NUMBER: Kuopio University Hospital organisation permit number 73/2014. PATIENT OR PUBLIC CONTRIBUTION: Information regarding individual patients or nurses was not available to the researchers. All materials are in the form of summary tables.

Hospital mortality and optimality of nursing workload: A study on the predictive validity of the RAFAELA Nursing Intensity and Staffing system.

BACKGROUND: Patient classification systems have been developed to manage workloads by estimating the need for nursing resources through the identification and quantification of individual patients' care needs. There is in use a diverse variety of patient classification systems. Most of them lack validity and reliability testing and evidence of the relationship to nursing outcomes. OBJECTIVE: Predictive validity of the RAFAELA system was tested by examining whether hospital mortality can be predicted by the optimality of nursing workload. METHODS: In this cross-sectional retrospective observational study, monthly mortality statistics and reports of daily registrations from the RAFAELA system were gathered from 34 inpatient units of two acute care hospitals in 2012 and 2013 (n=732). The association of hospital mortality with the chosen predictors (hospital, average daily patient to nurse ratio, average daily nursing workload and average daily workload optimality) was examined by negative binomial regression analyses. RESULTS: Compared to the incidence rate of death in the months of overstaffing when average daily nursing workload was below the optimal level, the incidence rate was nearly fivefold when average daily nursing workload was at the optimal level (IRR 4.79, 95% CI 1.57-14.67, p=0.006) and 13-fold in the months of understaffing when average daily nursing workload was above the optimal level (IRR 12.97, 95% CI 2.86-58.88, p=0.001). CONCLUSIONS: Hospital mortality can be predicted by the RAFAELA system. This study rendered additional confirmation for the predictive validity of this patient classification system. In future, larger studies with a wider variety of nurse sensitive outcomes and multiple risk adjustments are needed. Future research should also focus on other important criteria for an adequate nursing workforce management tool such as simplicity, efficiency and acceptability.