Literature DB >> 31949893

Predicting healthcare professionals' intention to use poison information system in a Malaysian public hospital.

Yulita Hanum P Iskandar1, Gogilavani Subramaniam1, Mohamed Isa Abd Majid2, Adilah Mohamed Ariff2, Gururajaprasad Kaggal Lakshmana Rao3.   

Abstract

PURPOSE: The main objective of this paper is to determine the predicting factors that influence the intention to use Poison Information System (PIS) among healthcare professionals.
METHODS: A quantitative approach was applied, using a five-point Likert scale questionnaire, adapted from previous studies. Data were collected from 167 healthcare professionals working for Malaysian Public Hospitals in Penang. Smart Partial Least Square (PLS) version 3.2.7 were used to analyse the proposed relationships.
RESULTS: The results indicated that attitude and computer anxiety had a significant positive relation to the intention to use PIS among healthcare professionals wherein computer knowledge was found to have had a significant relationship with attitude and computer habit. Apart from that, technical support and training had a positive relationship with perceived ease of use. Surprisingly, computer habit, perceived usefulness, perceived ease of use, compatibility and facilitating condition did not significantly influence intention to use PIS.
CONCLUSION: The results of this study provided useful insights for healthcare agencies to understand the underlying elements that could improve the poison information management. The results proved that attitude and computer anxiety were critical factors among healthcare professionals managing poisoning cases in a highly stressful and unpredictable work environment. These factors must, therefore, be considered before implementing PIS in managing poisoning cases. The study also provided an understanding of how to improve system development by utilising the end user's expectation on the implementation of the system. © Springer Nature Switzerland AG 2020.

Entities:  

Keywords:  Healthcare; Intention to use; Poison information system (PIS); Technology acceptance model (TAM)

Year:  2020        PMID: 31949893      PMCID: PMC6942115          DOI: 10.1007/s13755-019-0094-0

Source DB:  PubMed          Journal:  Health Inf Sci Syst        ISSN: 2047-2501


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