ABSTRACT
Introducción y objetivo La herramienta Appropriateness Evaluation Protocol (AEP) analiza las estancias e ingresos hospitalarios inadecuados. El objetivo de este estudio fue adaptar el cuestionario AEP para analizar la adecuación de los ingresos y las estancias hospitalarias en nuestra realidad asistencial. Método Se desarrolló un estudio utilizando el método Delphi en el que participaron 15 expertos en gestión clínica y en asistencia hospitalaria. Los ítems del formulario inicial se conformaron a partir de la herramienta AEP tal y como fue definida en su primera versión. En la primera ronda los participantes aportaron nuevos ítems que consideraron relevantes en nuestra realidad actual. En las rondas 2 y 3 evaluaron 80 ítems según su relevancia mediante la utilización de una escala Likert del 1 al 4 (máxima utilidad). De acuerdo al diseño de nuestro estudio los ítems del AEP se consideraron adecuados si la media de la puntuación una vez evaluados por los expertos, era igual o superior a 3. Resultados Los participantes definieron un total de 19 nuevos ítems. Finalmente 47 ítems obtuvieron una puntuación media igual o superior a 3. El cuestionario resultante modificado consta de 17 ítems en «causas de admisiones adecuadas», 5 en «causas de admisiones inadecuadas», 15 en «causas de estancias adecuadas» y 10 en «causas de estancias inadecuadas». Conclusiones La identificación de ítems prioritarios para determinar la adecuación de los ingresos y las estancias prolongadas en nuestro medio y según la opinión de los expertos, podría definir un futuro instrumento para su utilización en nuestro entorno (AU)
Introduction and aim The Appropriateness Evaluation Protocol (AEP) tool analyzes inappropriate hospital stays and admissions. This study aimed to adapt the AEP questionnaire in order to analyze the appropriateness of hospital admissions and stays in our healthcare reality. Methods A study was conducted using the Delphi method in which 15 experts in clinical management and hospital care participated. The initial questionnaire items were taken from the first version of the AEP. In the first round, the participants contributed new items that they considered relevant in our current reality. In rounds 2 and 3, they evaluated 80 items according to their relevance using a Likert scale from 1 to 4 (maximum usefulness). Pursuant to the study's design, AEP items were considered adequate if the mean score according to the experts evaluation was greater than or equal to 3. Results The participants defined a total of 19 new items. In the end, 47 items earned a mean score greater than or equal to 3. The resulting modified questionnaire include 17 items in Reasons for Appropriate Admissions, 5 in Reasons for Inappropriate Admissions, 15 in Reasons for Appropriate Hospital Stays, and 10 in Reasons for Inappropriate Hospital Stays. Conclusions The identification according to expert opinion of priority items to determine the appropriateness of admissions and extended stays could be used in the future to help create an instrument to be used in our setting (AU)
Subject(s)
Humans , Strategic Planning , Length of Stay , Patient Admission/standards , Delphi Technique , Surveys and QuestionnairesABSTRACT
INTRODUCTION AND AIM: The Appropriateness Evaluation Protocol (AEP) tool analyzes inappropriate hospital stays and admissions. This study aimed to adapt the AEP questionnaire in order to analyse the appropriateness of hospital admissions and stays in our healthcare reality. METHODS: A study was conducted using the Delphi method in which 15 experts in clinical management and hospital care participated. The initial questionnaire items were taken from the first version of the AEP. In the first round, the participants contributed new items that they considered relevant in our current reality. In rounds 2 and 3, they evaluated 80 items according to their relevance using a Likert scale from 1 to 4 (maximum usefulness). Pursuant to the study's design, AEP items were considered adequate if the mean score according to the experts' evaluation was greater than or equal to 3. RESULTS: The participants defined a total of 19 new items. In the end, 47 items earned a mean score greater than or equal to 3. The resulting modified questionnaire include 17 items in "Reasons for Appropriate Admissions," 5 in "Reasons for Inappropriate Admissions," 15 in "Reasons for Appropriate Hospital Stays," and 10 in "Reasons for Inappropriate Hospital Stays." CONCLUSIONS: The identification according to expert opinion of priority items to determine the appropriateness of admissions and extended stays could be used in the future to help create an instrument to be used in our setting.
Subject(s)
Expert Testimony , Hospitalization , Humans , Length of Stay , Delphi Technique , Health Facilities , Patient AdmissionABSTRACT
Objetivo: Determinar si existen diferencias en la prevalencia del uso de fármacos para la osteoporosis entre pacientes diabéticos tipo 2 (DM2) y no diabéticos. Material y método: Estudio de cohortes retrospectivas con datos del Sistema de Información para el Desarrollo de la Investigación en Atención Primaria (SIDIAP), que contiene información clínica anonimizada de más de 5 millones de pacientes de Cataluña. Se seleccionaron todos los pacientes de ≥50 años de edad con diagnóstico de DM2, que fueron apareados con dos sujetos sin diabetes. Se recogió información sobre variables descriptivas, fracturas prevalentes y el uso de fármacos para la osteoporosis agrupados en bifosfonatos (BF), suplementos calcio y vitamina D (CaD), y cualquier fármaco para la osteoporosis (FPO). Mediante regresión logística se calculó la asociación entre la presencia de DM2 y el uso de FPO, ajustando por variables confusoras. Resultados: Se identificaron 166.106 pacientes con DM2 y 332.212 no diabéticos. Los DM2 tenían mayor prevalencia de fractura que los no diabéticos (1,3% vs. 0,3%). El uso de BF en los pacientes con DM2 era del 6,6%, frente al 9,3% en los no diabéticos (p<0,001); de CaD, 9,7% vs. 12,3% (p<0,001); y de FPO, 7,6% vs. 10,7% (p<0,001). Tras ajustar por variables confusoras, los pacientes con DM2 presentaban menor probabilidad de ser tratados con BF (OR=0,67; IC95%: 0,64-0,68), con CaD (OR=0,71; IC95%: 0,70-0,73) o con FPO (OR=0,66; IC95%: 0,64-0,67) que los no diabéticos. Conclusiones: A pesar de presentar una mayor prevalencia de fracturas previas, los pacientes con DM2 tienen más del 30% de probabilidad de no recibir un FPO que los no diabéticos. Esto podría ser debido a una infravaloración del riesgo en estos pacientes (AU)
Objective: Ascertain whether there are differences in the prevalence of osteoporosis drugs in patients with type 2 diabetes (DM2) and non-diabetic patients. Material and methods: Retrospective cohort study with data from the Information System for the Development of Primary Care Research (SIDIAP), which contains anonymous clinical information from more than 5 million patients in Catalonia. All 50-year-old patients diagnosed with DM2, who were matched with two subjects without diabetes, were selected. Information on descriptive variables, prevalent fractures and the use of osteoporosis drugs grouped in bisphosphonates (BF), calcium and vitamin D supplements (CaD), and any osteoporosis drug (OD) were collected. Through logistic regression, the association between the presence of DM2 and the use of OD was calculated, adjusting for confounding variables. Results: A total of 166,106 patients with DM2 and 332,212 non-diabetics. The DM2 group presented a higher prevalence of fracture than did diabetics (1.3% vs 0.3%). The use of BF in patients with DM2 was 6.6%, compared to 9.3% in non-diabetics (p<0.001). Of CaD, 9.7% vs 12.3% (p<0.001) and OD, 7.6% vs 10.7% (p<0.001). After adjusting for variable confounders, the patients with DM2 presented a lower probability of being treated with BF (OR=0.67, 95% CI: 0.64-0.68), with CaD (OR=0.71, 95% CI: 0.70-0.73) or with OD (OR=0.66, 95% CI: 0.64-0.67) than non-diabetics. Conclusions: Despite having a higher prevalence of fractures in patients with DM2, they have more than 30% chance of not having received an OD than non-diabetic patients. This may be attributed to an underestimation of risk in these patients (AU)
