ABSTRACT
OBJETIVO: Evaluar la evolución de las caídas con las medidas implementadas para mejorar la atención de los pacientes de riesgo y disminuir el número de caídas. Conocer las características de los pacientes que las han sufrido. MÉTODO: Se ha hecho un análisis de todas las caídas registradas entre 2008-2013 para determinar la evolución de estas y describir las medidas implantadas a partir de la historia clínica electrónica en el Hospital Universitario de Fuenlabrada. Se ha estimado la incidencia de caídas en pacientes hospitalizados y se ha estudiado la evolución con el test de chi cuadrado. Se presentan las frecuencias de las características de los pacientes que sufren caídas en cuanto a edad, estancia, actividad que realizaban, acompañante, nivel de movilidad, estado de conciencia. RESULTADOS: Se produjeron 445 caídas registradas en total. El 2009 es el año en el que se produjeron más caídas con 86 caídas en 15.819 pacientes dados de alta (0,55%) descendiendo hasta el 2013 a 55 caídas en los 15.052 pacientes dados de alta (0,37%). Esta diferencia no resultó estadísticamente significativa. CONCLUSIÓN: La implantación de la valoración al ingreso sobre el riesgo de caídas ha servido para identificar los factores de riesgo de forma individualizada, así como el recordatorio y alertas ayudan al personal de enfermería a considerar la prevención de las caídas como un acto rutinario y que se tomen medidas en los pacientes más vulnerables
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. CONCLUSIONS: 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
Subject(s)
Humans , Accidental Falls/statistics & numerical data , Hospitalization/statistics & numerical data , Risk Management/organization & administration , Evaluation of Results of Preventive Actions , Hospital StatisticsABSTRACT
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.
Subject(s)
Accidental Falls/prevention & control , Hospitalization , Humans , Incidence , Nursing Staff , Risk FactorsABSTRACT
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.
Subject(s)
Pressure Ulcer/diagnosis , Aged , Aged, 80 and over , Female , Hospitals , Humans , Male , Middle Aged , Predictive Value of Tests , Prospective Studies , Reproducibility of Results , Risk Assessment , SpainABSTRACT
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.
Subject(s)
Diagnosis-Related Groups , Nursing Service, Hospital/economics , Nursing Service, Hospital/statistics & numerical data , Costs and Cost Analysis , HumansABSTRACT
Objetivo: Evaluar el impacto de la codificación de los procedimientos y las complicaciones que maneja la enfermería en la complejidad y la financiación de un hospital.Métodos: Se generó la codificación en dos unidades de hospitalización a partir del informe de alta. Se revisaron y codificaron los procedimientos y complicaciones en que actúa enfermería, calculando los nuevos pesos medios de los grupos relacionados con el diagnóstico (GRD), las unidades de complejidad hospitalaria (UCH) y su repercusión en la financiación hospitalaria.Resultados: La unidad de hospitalización médica, en enero y febrero de 2006, incrementó un 0,0655 el peso medio, lo que supuso 7,2727 UCH más, y aumentó la facturación en 13.092,25¿. La unidad de hospitalización quirúrgica, en enero de 2006, incrementó un 0,0747 el peso medio, lo que supuso 10,8315 UCH y aumentó la facturación en 19.498,76¿.Conclusiones: La codificación de los procedimientos y de las complicaciones en que interviene enfermería aporta mayor complejidad al hospital y repercute al alza en la financiación del hospital(AU)
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 13,092.25¿. 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 19,498.76¿.Conclusions: Codification of nursing activities has improved the case mix and has had a positive effect on the hospital's finance(AU)
