[The new methods to define the staffing requirements for doctors,nurses and nurses aides: an example of their implementation in an Italian hospital]. / Le nuove metodologie di valutazione del fabbisognodel personale infermieristico, medico e di supporto: un esempio di applicazione.

. The new methods to define the staffing requirements for doctors, nurses and nurses aides: an example of their implementation in an Italian hospital. The Italian government, after the transposition of European Union legislation on working hours, made a declaration of commitment to increase the number of staff of the National Health Service (NHS). The method for assessing the staffing needs innovates the old one that dated back a few decades. AIM: To implement the method proposed by the Ministry of Health to an Italian hospital and assess its impact on staffing and costs. METHODS: The model was implemented on all the wards, multiplying the minutes of care expected in 2016, dividing the result by 60 to obtain the hours of care, and further dividing by the number of yearly hours of work of a nurse (1418). Same was done for nurses aides. The minutes of care were related to mean weight of the Diagnosis Related Groups of the ward and the results obtained compared to the actual staffing of nurses and nurses aides. The costs of the differences were calculated. RESULTS: The implementation of the model produced an excess of 23 nurses and a scarcity of 95 nurses aides compared to the actual staffing, with an increase of the costs of € 1.828.562,00. CONCLUSIONS: The results obtained and the criticisms received so far show the need of major changes. The data from international studies that associate staffing and patients outcomes and the nurse/patient ratio are macro-indicators already available that may orient choices and investments on the health care professions.

Fall prevention: is the STRATIFY tool the right instrument in Italian Hospital inpatient? A retrospective observational study.

BACKGROUND: Although several risk assessment tools are in use, uncertainties on their accuracy in detecting fall risk already exist. Choosing the most accurate tool for hospital inpatient is still a challenge for the organizations. We aimed to retrospectively assess the appropriateness of a fall risk prevention program with the STRATIFY assessment tool in detecting acute-care inpatient fall risk. METHODS: Number of falls and near falls, occurred from January 2014 to March 2015, was collected through the incident reporting web-system implemented in the hospital's intranet. We reported whether the fall risk was assessed with the STRATIFY assessment tool and, if so, which was the judgement. Primary outcome was the proportion of inpatients identified as high risk of fall among inpatients who fell (True Positive Rate), and the proportion of inpatients identified as low-risk that experienced a fall howsoever (False Negative Rate). Characteristics of population and fall events were described among subgroups of low risk and high risk inpatients. RESULTS: We collected 365 incident reports from 40 hospital units, 349 (95.6%) were real falls and 16 (4.4%) were near falls. The fall risk assessment score at patient's admission had been reported in 289 (79%) of the overall incident reports. Thus, 74 (20.3%) fallers were actually not assessed with the STRATIFY, even though the majority of them presented risk recommended to be assessed. The True Positive Rate was 35.6% (n = 101, 95% CI 30% - 41.1%). The False Negative Rate was 64.4% (n = 183, 95% CI 58.9%-70%) of fallers, nevertheless they incurred in a fall. The STRATIFY mean score was 1.3 ± 1.4; the median was 1 (IQQ 0-2). CONCLUSIONS: The prevention program using only the STRATIFY tool was found to be not adequate to screen our inpatients population. The incorrect identification of patients' needs leads to allocate resources to erroneous priorities and to untargeted interventions, decreasing healthcare performance and quality.