JMIR Publications

JMIR Medical Informatics

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Currently submitted to: JMIR Medical Informatics

Date Submitted: Sep 6, 2017
Open Peer Review Period: Sep 8, 2017 - Nov 3, 2017 (Under Review)

NOTE: This is an unreviewed Preprint

Peer-Review Me

Understanding barriers to physicians adopting clinical decision support systems: A Systematic Review

  • Saif Khairat; 
  • Ali Al Sanousi; 
  • David Marc

ABSTRACT

Background:

The purpose of this paper was to conduct an analytical review and task analysis of CDSS re-search, and to develop a new framework for CDSS design in order to achieve user acceptance.

Objective:

This paper tackles a critical issue modern healthcare systems namely, the adoption of Health Informatics Technologies (HIT). The paper provides a comprehensive literature review of the current status quo of Clinical Decision Support Systems adoption, the barriers to adoption from users stand point, and proposes novel solutions to current gaps in order to the enhancement of healthcare delivery and execution.

Methods:

A literature review of CDSS papers was conducted with a focus on user acceptance. In order to gain a greater understanding of the problems associated with CDSS, we conducted a task analysis to identify and describe the goals, user input, system output, knowledge requirements, and constraints from two different perspectives.

Results:

Based on the literature review, findings are characterized by whether user acceptance was favorable and unfavorable for clinical guidelines, reminders, and diagnostic CDSS. We propose two models: 1) the User Acceptance and System Adaptation Design (UASAD) model which includes optimizing CDSS design based on user needs/expectations and 2) the Input-Process-Output-Engage (IPOE) model which reveals to users the processes the govern CDSS outputs.

Conclusions:

CDSS have the capacity to decrease medical errors and improve patient outcomes. However, current CDSS designs do not consistently show such improvements. We hypothesized that the incorporation of the proposed models will improve user acceptance to support beneficial impacts of CDSS adoption. Ultimately, if a user does not accept technology this not only poses a threat to the use of the technology but can also pose a threat to the health and wellbeing of patients.


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