Objectives: To find out the level of satisfaction of patients seen in the Emergency room of the of San Juan de Dios Hospital, Aljarafe; to identify the determining factors and to define the areas that need improvement and reinforcement in order to improve the quality of care.

Material And Methods: A telephone survey was carried out between July and September, 2008, containing 44 questions, 2 with a closed response, 3 with yes/no answers and the remaining questions scored based on a Likert type scale of 1 (most negative answer) to 5 (most positive answer). Observations were also recorded.

Results: Overall satisfaction was 84.7%: 82% would recommend this Emergency room, and 59.6% considered it better than others. The aspects to be emphasised are: respect (97.6%), cleanliness (97.1%) and intimacy (94.6%). Following these were: the doctor's disposition to listen (93.1%); the preparation of the professionals (from 92.3% for the administration professionals to 88.6% for auxiliary nurses); kindness (from 91.8% for doctors to 89.9% for nurses); and the ease of getting orientated (90%). The information given was evaluated positively by 70.3%, and 87% acknowledged understanding this information. However, 52.4% of patients were satisfied with the information given during triage related to the stay in the emergency room, and, 22.3% as regards the probable waiting period. The satisfaction with the waiting between triage and first medical consultation was higher in the one-two-triage patients and was lower in the four-triage ones; in the waiting between first medical consultation and the discharge, the one-triage patients were more satisfied than the rest. Nevertheless, there were no statistically significant differences with satisfaction with the waiting until the triage.

Conclusions: The percentages of satisfaction was greater than 80% in 23 of the 34 items, with certain aspects having a satisfaction rate over 90%: respect, cleanliness, the doctor's predisposition to listen, qualification and kindness of the personnel. On the contrary, others items were scored under a rate of 70%: information at triage, attention to pain, waiting periods for triage-doctor's first visit and subsequent visit for discharge, and personnel identification.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.cali.2010.11.008DOI Listing

Publication Analysis

Top Keywords

emergency room
16
room san
8
san juan
8
juan dios
8
patients satisfied
8
satisfaction waiting
8
medical consultation
8
satisfaction
6
waiting
5
[patient satisfaction
4

Similar Publications

A mixed-methods observational study of strategies for success in implementation science: overcoming emergency departments hurdles.

BMC Health Serv Res

January 2025

Emergency Medicine, Vanderbilt University Medical Center and, Veterans Affairs Tennessee Valley Healthcare System, Geriatric Research, Education and Clinical Center (GRECC), Nashville, TN, USA.

Background: Heart failure is a major public health concern, affecting 6.7 million Americans. An estimated 16% of emergency department (ED) patients with acute heart failure (AHF) are discharged home.

View Article and Find Full Text PDF

Sepsis is a critical, life-threatening condition that demands precise prediction to mitigate adverse outcomes. The heterogeneity of sepsis leads to variable prognoses, making early and accurate identification increasingly difficult. Despite ongoing advancements, no single gold standard has emerged for sepsis prediction.

View Article and Find Full Text PDF

Background: Studies suggest that less than 4% of patients with pulmonary embolisms (PEs) are managed in the outpatient setting. Strong evidence and multiple guidelines support the use of the Pulmonary Embolism Severity Index (PESI) for the identification of acute PE patients appropriate for outpatient management. However, calculating the PESI score can be inconvenient in a busy emergency department (ED).

View Article and Find Full Text PDF

Background: Prediction models have demonstrated a range of applications across medicine, including using electronic health record (EHR) data to identify hospital readmission and mortality risk. Large language models (LLMs) can transform unstructured EHR text into structured features, which can then be integrated into statistical prediction models, ensuring that the results are both clinically meaningful and interpretable.

Objective: This study aims to compare the classification decisions made by clinical experts with those generated by a state-of-the-art LLM, using terms extracted from a large EHR data set of individuals with mental health disorders seen in emergency departments (EDs).

View Article and Find Full Text PDF

Background: Pneumococcal conjugate vaccines (PCVs) introduced in childhood national immunization programs lowered vaccine-type invasive pneumococcal disease (IPD), but replacement with non-vaccine-types persisted throughout the PCV10/13 follow-up period. We assessed PCV10/13 impact on pneumococcal meningitis incidence globally.

Methods: The number of cases with serotyped pneumococci detected in cerebrospinal fluid and population denominators were obtained from surveillance sites globally.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!