Subject(s)
Benzoates/therapeutic use , Hydrazines/therapeutic use , Purpura, Thrombocytopenic, Idiopathic/drug therapy , Pyrazoles/therapeutic use , Antibodies, Monoclonal, Murine-Derived/therapeutic use , Blood Transfusion , Combined Modality Therapy , Drug Resistance , Drug Substitution , Gastrointestinal Hemorrhage/etiology , Gastrointestinal Hemorrhage/prevention & control , Gastrointestinal Hemorrhage/therapy , Humans , Immunoglobulins, Intravenous/therapeutic use , Male , Middle Aged , Prednisone/therapeutic use , Purpura, Thrombocytopenic, Idiopathic/complications , Purpura, Thrombocytopenic, Idiopathic/therapy , Receptors, Fc/therapeutic use , Receptors, Thrombopoietin/agonists , Recombinant Fusion Proteins/pharmacology , Recombinant Fusion Proteins/therapeutic use , Rituximab , Scleroderma, Systemic/complications , Thrombopoietin/pharmacology , Thrombopoietin/therapeutic useABSTRACT
Objetivo Aplicacion de un analisis modal de fallos y efectos al proceso de prescripcion, validacion y dispensacion de medicamentos en pacientes hospitalizados. Metodos Un grupo de trabajo analizo los pasos que componian el proceso desde la prescripcion medica hasta la dispensacion, identificandose los mas criticos y estableciendo los modos potenciales de fallo que podrian producir un error. Se analizaron posibles causas, sus efectos potenciales y los sistemas de control existentes para prevenir su aparicion. Se calculo el Hazard Score, seleccionandose los que tenian una puntuacion (..) (AU)
Objective To apply a failure modes and effects analysis to the prescription, validation and dispensing process for hospitalised patients. Methods A work group analysed all of the stages included in the process from prescription to dispensing, identifying the most critical errors and establishing potential failure modes which could produce a mistake. The possible causes, their potential effects, and the existing control systems were analysed to try and stop them from developing. The Hazard Score was calculated, choosing those that were ≥ 8, and a Severity Index = 4 was selected independently of the hazard Score value. Corrective measures and an implementation plan were proposed. Results A flow diagram that describes the whole process was obtained. A risk analysis was conducted of the chosen critical points, indicating: failure mode, cause, effect, severity, probability, Hazard Score, suggested preventative measure and strategy to achieve so. Failure modes chosen: Prescription on the nurse's form; progress or treatment order (paper); Prescription to incorrect patient; Transcription error by nursing staff and pharmacist; Error preparing the trolley. Conclusions By applying a failure modes and effects analysis to the prescription, validation and dispensing process, we have been able to identify critical aspects, the stages in which errors may occur and the causes. It has allowed us to analyse the effects on the safety of the process, and establish measures to prevent or reduce them (AU)
Subject(s)
Humans , Drug Prescriptions , Drug Dispensaries , Drug Evaluation/trends , Inappropriate Prescribing/trends , Good Dispensing Practices , Medication Errors/statistics & numerical data , Risk Management , Safety ManagementABSTRACT
OBJECTIVE: To apply a failure modes and effects analysis to the prescription, validation and dispensing process for hospitalised patients. METHODS: A work group analysed all of the stages included in the process from prescription to dispensing, identifying the most critical errors and establishing potential failure modes which could produce a mistake. The possible causes, their potential effects, and the existing control systems were analysed to try and stop them from developing. The Hazard Score was calculated, choosing those that were ≥ 8, and a Severity Index = 4 was selected independently of the hazard Score value. Corrective measures and an implementation plan were proposed. RESULTS: A flow diagram that describes the whole process was obtained. A risk analysis was conducted of the chosen critical points, indicating: failure mode, cause, effect, severity, probability, Hazard Score, suggested preventative measure and strategy to achieve so. Failure modes chosen: Prescription on the nurse's form; progress or treatment order (paper); Prescription to incorrect patient; Transcription error by nursing staff and pharmacist; Error preparing the trolley. CONCLUSIONS: By applying a failure modes and effects analysis to the prescription, validation and dispensing process, we have been able to identify critical aspects, the stages in which errors may occur and the causes. It has allowed us to analyse the effects on the safety of the process, and establish measures to prevent or reduce them.
Subject(s)
Drug Prescriptions/statistics & numerical data , Medication Errors/statistics & numerical data , Medication Systems, Hospital/statistics & numerical data , Models, Theoretical , Electronic Prescribing , Forms and Records Control , Hospital Records , Hospitals, General , Humans , Medication Errors/prevention & control , Nursing Records , Nursing Staff, Hospital , Quality Improvement , Risk Assessment , Software Design , SpainABSTRACT
Objetivo Calcular la prevalencia de los errores producidos en diferentes sistemas de dispensación de medicamentos, las etapas en que se producen y los factores contribuyentes. Métodos Estudio observacional prospectivo. Se revisaron las etapas del proceso de dispensación en 5 sistemas de dispensación: stock o botiquín de planta, sistema de distribución de medicamentos en dosis unitaria (SDMDU) sin prescripción electrónica asistida (PEA), SDMDU con PEA, sistema automatizado de dispensación (SAD) sin PEA y SAD con PEA. Se identificaron los errores de dispensación, las etapas en que ocurrieron dichos errores y sus factores contribuyentes. Resultados De 54.169 oportunidades de error, se detectaron 2.181 errores. Tasa de error: stock, 10,7%; SDMDU sin PEA, 3,7%; SDMDU con PEA, 2,2%; SAD sin PEA, 20,7%; SAD con PEA, 2,9%. Etapa más frecuente en la que se produce el error: stock, preparación del pedido; SDMDU sin PEA y con PEA, llenado del carro; SAD sin PEA y con PEA, llenado del SAD. Error más frecuente: stock, SAD sin PEA y con PEA, omisión; SDMDU con PEA, diferente cantidad de medicamento; SDMDU sin PEA, sobra medicamento. Factor contribuyente: stock, SAD sin PEA y con PEA, rotura de stock/desabastecimiento; SDMDU con PEA, personal sin experiencia y sistema de comunicación deficiente entre profesionales; SDMDU sin PEA, sistema de comunicación deficiente entre profesionales. Conclusiones La aplicación de nuevas tecnologías en el proceso de dispensación ha aumentado su seguridad, concretamente la implantación de la PEA ha permitido disminuir los errores en el proceso de dispensación (AU)
Objective Calculate error prevalence occurred in different medication-dispensing systems, the stages of occurrence, and contributing factors. Methodology Prospective observational study. The staging of the dispensing process were reviewed in five dispensing systems: Stock, Unitary-Dose dispensing systems (UDDS) without Computerized Prescription Order Entry (CPOE), CPOE-UDDS, Automated Dispensing Systems (ADS) without CPOE and CPOE-ADS. Dispensing errors were identified, together with the stages of occurrence of such errors and their contributing factors.Results2,181 errors were detected among 54,169 opportunities of error. Error-rate: Stock, 10.7%; no-CPOE-UDDS, 3.7%, CPOE-UDDS, 2.2%, no-CPOE-ADS, 20.7%; CPOE-ADS, 2.9%. Most frequent stage when error occurs: Stock, preparation of order; no-CPOE-UDDS and CPOE-UDDS, filling of the unit dose cart; no-CPOE-ADS and CPOE-ADS, filling of the ADS. Most frequent error: Stock, no-CPOE-ADS and CPOE-ADS, omission; CPOE-UDDS, different amount of drug and no-CPOE-UDDS, extra medication. Contributing factor: Stock, CPOE-ADS and no-CPOE-ADS, stock out/supply problems; CPOE-UDDS, inexperienced personnel and deficient communication system between professionals; no-CPOE-UDDS, deficient communication system between professionals. Conclusions Applying new technologies to the dispensing process has increased its safety, particularly, implementation of CPOE has enabled to reduce dispensing errors (AU)
Subject(s)
Humans , Drug Dispensaries , Pharmacy Service, Hospital/organization & administration , Medication Therapy Management/organization & administration , Culturally Appropriate Technology/methods , Good Dispensing Practices , Medication Errors/statistics & numerical data , Electronic Prescribing , Clinical Pharmacy Information Systems/organization & administrationABSTRACT
OBJECTIVE: Calculate error prevalence occurred in different medication-dispensing systems, the stages of occurrence, and contributing factors. METHODOLOGY: Prospective observational study. The staging of the dispensing process were reviewed in five dispensing systems: Stock, Unitary-Dose dispensing systems (UDDS) without Computerized Prescription Order Entry (CPOE), CPOE-UDDS, Automated Dispensing Systems (ADS) without CPOE and CPOE-ADS. Dispensing errors were identified, together with the stages of occurrence of such errors and their contributing factors. RESULTS: 2,181 errors were detected among 54,169 opportunities of error. Error-rate: Stock, 10.7%; no-CPOE-UDDS, 3.7%, CPOE-UDDS, 2.2%, no-CPOE-ADS, 20.7%; CPOE-ADS, 2.9%. Most frequent stage when error occurs: Stock, preparation of order; no-CPOE-UDDS and CPOE-UDDS, filling of the unit dose cart; no-CPOE-ADS and CPOE-ADS, filling of the ADS. Most frequent error: Stock, no-CPOE-ADS and CPOE-ADS, omission; CPOE-UDDS, different amount of drug and no-CPOE-UDDS, extra medication. Contributing factor: Stock, CPOE-ADS and no-CPOE-ADS, stock out/supply problems; CPOE-UDDS, inexperienced personnel and deficient communication system between professionals; no-CPOE-UDDS, deficient communication system between professionals. CONCLUSIONS: Applying new technologies to the dispensing process has increased its safety, particularly, implementation of CPOE has enabled to reduce dispensing errors.
Subject(s)
Medication Errors , Medication Systems, Hospital/trends , Automation , Clinical Pharmacy Information Systems/statistics & numerical data , Clinical Pharmacy Information Systems/trends , Electronic Prescribing/statistics & numerical data , Hospitals, General , Hospitals, University , Humans , Medical Order Entry Systems/statistics & numerical data , Medical Order Entry Systems/trends , Medication Errors/classification , Medication Errors/prevention & control , Medication Errors/statistics & numerical data , Medication Systems, Hospital/statistics & numerical data , Prospective Studies , Robotics , SpainABSTRACT
No disponible
No disponible
Subject(s)
Humans , Male , Female , Good Dispensing Practices , Drugs from the Specialized Component of Pharmaceutical Care , Medication Systems/standards , Medication Systems , Drug Administration Schedule , Prospective Studies , Medication Therapy Management/statistics & numerical data , Medication Therapy Management/standards , Medication Therapy Management/trends , 28599ABSTRACT
A probable case of hypersensitivity reaction to Total Parenteral Nutrition (TPN) in a 55 years old patient diagnosed with gastric adenocarcinoma is presented. Onset of TPN infusion coincides with the time of the onset of a disseminated pruritic cutaneous eruption that repeats after a second exposure to nutrition. The likely causes of this hypersensitivity reaction are analyzed.
Subject(s)
Hypersensitivity/etiology , Parenteral Nutrition, Total/adverse effects , Parenteral Nutrition/adverse effects , Pruritus/etiology , Algorithms , Humans , Male , Middle AgedABSTRACT
Se presenta un caso probable de reacción de hipersensibilidad a Nutrición Parenteral Total (NPT) en un paciente de 55 años diagnosticado de adenocarcinoma gástrico. El inicio de la infusión de la NPT coincide en el tiempo con la aparición de una erupción cutánea pruriginosa diseminada que se repite tras una segunda exposición a la nutrición. Se analizan las causas probables de esta reacción de hipersensibilidad (AU)
A probable case of hypersensitivity reaction to Total Parenteral Nutrition (TPN) in a 55 years old patient diagnosed with gastric adenocarcinoma is presented. Onset of TPN infusion coincides with the time of the onset of a disseminated pruritic cutaneous eruption that repeats after a second exposure to nutrition. The likely causes of this hypersensitivity reaction are analyzed (AU)
