Braden Scale and Norton Scale modified by INSALUD in an acute care hospital: validity and cutoff point.

OBJECTIVE: The objective of this article was to determine the most suitable cutoff point (CP) for the Braden Scale and Norton Modified Scale by INSALUD Scale (Norton-MI) in an acute care hospital. DESIGN: The authors have designed a prospective, descriptive study of patients from their hospital. From December 2008 to March 2009, a nurse collected and recorded adult patient data daily, including the appearance of pressure ulcers. PATIENTS: Adult patients in medical and surgical wards. MAIN OUTCOMES MEASURE: The parameters used in both scales are sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), area under curve (AUC) of receiver operating characteristic (ROC). MAIN RESULTS: In the end, the authors have evaluated a total of 1001 patients and obtained 4486 measurements with both the Norton-MI and the Braden scales. The rates for the recommended CP of the Norton-MI scale (CP 14) are as follows: sensitivity: 67.91% (62.42-73.39), specificity: 78.66% (77.41-79.92), PPV: 18.36%, NPV: 97.20%. Those for Braden (CP 16) are as follows: sensitivity: 65.69% (64.19-75), specificity: 79.62% (78.39-80.85), PPV: 19.43%, NPV: 97.37%. The Norton-MI scale offers an AUC-ROC of 0.828 with a 95% confidence interval of 0.811-0.854, and the Braden Scale presents an AUC-ROC of 0.832 with a 95% confidence interval of 0.807 to 0.849. CONCLUSION: Both scales show good validity data. If the CP is raised: MI-Norton (CP 15): sensitivity: 77.36 (72.43-82.30), specificity 74.27 (72.94-75.61), PPV: 17.52 (15.42-19.62), NPV: 97.89 (97.38-98.41). The Braden scale with a CP of 17 presents sensitivity: 78.38 (73.52-83.24), specificity: 73.44 (72.09-74.79), PPV: 17.25 (15.19-19.31), NPV: 97.96 (97.45-98.47). These CPs improved the predictive capacity of both scales in the authors' hospital environment.

[Impact of the codification of nursing activities on mean diagnosis of weight related group and its effects on hospital financing]. / Impacto de la codificación de información de enfermería en el peso medio de los grupos relacionados con el diagnóstico y su repercusión en la facturación de un hospital.

OBJECTIVE: To assess the impact of codification of nursing activities and procedures on a hospital's weighting and finance. METHODS: Codification was performed in two inpatient settings using discharge data. Nurses' procedures and patient conditions falling within nurses' responsibilities were codified. New mean weights for diagnosisrelated groups (DRGs) and hospital complexity units (HCU) were calculated, as were their effects on finance. RESULTS: In January and February, 2006, the mean weighting in the medical admission unit increased by 0.0655, representing 7.2727 more HCU and a rise in the monthly budget of 13,092.25euro. On January of 2006, the mean weighting in the surgical admission unit increased by 0.0747 representing 10.8315 HCU and an increase in the monthly budget of 19,498.76euro. CONCLUSIONS: Codification of nursing activities has improved the case mix and has had a positive effect on the hospital's finance.

[Hospital falls, improvement strategy for reducing their incidence]. / Las caídas hospitalarias, estrategia de mejora para disminuir su incidencia.

TARGET: To evaluate the evolution of falls with the implemented measures to improve the attention of patients at risk and to reduce the number of falls. To know the characteristics of patients who have suffered fall-related injuries. METHOD: All the falls registered between 2008 and 2013 have been analyzed to determine the evolution of these and to describe the implemented measures through the electronic clinical history at University Hospital of Fuenlabrada. The incidence of falls in hospitalized patients has been estimated and the evolution with the chi square test has been studied. The frequencies of the characteristics of patients who fall has been presented: age, length of stay, performed activity, patient companion, mobility level, state of consciousness. RESULTS: 445 registered falls happened. 2009 is the year with the highest number of falls, 86 patients fell of a total of 15,819 discharged patients (0.55%). The statistic drops until 2013, where 55 patients fell out of 15,052 discharged patients (0.37%). This difference was not statistically significant. CONCLUSION: The deployment of an assessment about fall risk at admission has helped to identify individualized risk factors. Furthermore, the awareness and alerts to the nursing staff have helped to consider fall prevention as a rutinary procedure, hence appropriate measures can be implemented on the most vulnerable patients.