Evidence Hub

Analysis of hospital management information system satisfaction using the end-user computing satisfaction method: A cross-sectional study

Nindy Shara Meiyana, Tantut Susanto, D. Rokhmah, R. Yunanto, Ira Rahmawati

Jurnal Keperawatan Padjadjaran, 2023

9 citations

Abstract

Background: The completeness of patient information can help improve the patient service process. However, the application of the hospital management information systems (HMIS) is experiencing obstacles that affect user satisfaction. The end-user computing satisfaction (EUCS) method was developed for improvement of HMIS in accordance with the needs of user in the field of medical records.Purpose: To analyze the correlation satisfaction of HMIS and EUCS in hospital setting.Methods: Quantitative descriptive design with a cross-sectional approach was conducted among 105 healthcare providers at Graha Sehat Medika Hospital from June to July 2022. The EUCS questionnaires related to aspects of content, accuracy, format, timeliness, and ease of use were used to measure user satisfaction of HMIS. A Pearson Product Moment was used to analyze the correlation between HMIS and EUCS user satisfaction.Results: There was significant correlation between satisfaction of HMIS and components of EUCS (p= 0.001), including content (r= 0.705), accuracy (r= 0.651), format (r=0.538), timeliness (r= 0.706), and ease of use (r= 0.875). Furthermore, there were differences between ease to use of EUCS method and attending a computer course (10.93±2.66; p= 0.022) and gender (10.74±2.58; p= 0.007) of healthcare providers.Conclusion: The EUCS method is important for improving HMIS satisfaction. Therefore, training and socialization of EUCS should improve to maintain ease of use of computers to increase…

How strong is the evidence?

Evidence Hub reads this as a cross-sectional, done in people. Its evidence level is 4 of 5 (Low · observational). Observational designs can show an association but not prove cause.

How the five levels of evidence work. The level is assigned automatically from the abstract and can be wrong, so check the paper.

Read the paper

Related studies

Go deeper in Evidence Hub

Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.

Open this study Sign up free