Volume 28, Issue 2 (9-2025)                   jha 2025, 28(2): 109-114 | Back to browse issues page


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Jahanbakhsh M, Moeeni M. A Nudge-driven model of health information system as a choice architecture. jha 2025; 28 (2) :109-114
URL: http://jha.iums.ac.ir/article-1-4734-en.html
1- Health Information Technology Research Center, Isfahan University of Medical Sciences, Isfahan, Iran.
2- Social Determinants of Health Research Center, Isfahan University of Medical Sciences, Isfahan, Iran. , mmoeini1387@gmail.com
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Dear Editor,
Information systems, through integrating human and technical capabilities, can be powerful tools for transforming data into knowledge and wisdom [1]. Given that health information systems, particularly within hospitals in our country, have not yet achieved full effectiveness [2-4], integrating decision support systems (DSSs) can improve efficiency in several ways: 1) diagnostic DSS-integrated health information systems  can improve diagnostic accuracy by offering recommendations based on the fusion of patient data with medical knowledge; 2) therapeutic DSS-integrated health information systems can facilitate low-cost, repetitive, or low-risk interventions, representing a practical application of DSSs in the treatment process; 3) recall and follow-up DSS integrated-health information systems can identify high-risk patients requiring frequent screening or faster follow-ups to address abnormal results or overdue actions [5].
We suggest that DSSs can be optimized by incorporating the principles of ​​choice architecture. Choice architecture is an idea developed by behavioral economists Taylor and Sunstein [6]. Prior to their work, Kahneman [7], a Nobel laureate in behavioral economics, demonstrated that human decision making is limited by bounded rationality, cognitive biases and heuristics. Based on the idea of ​​choice architecture, nudges provide policymakers with non-mandatory strategies to improve individuals' decisions while preserving their freedom of choice. Nudges are small changes in the environment that can be implemented easily and at low cost. Nudges neither prohibit any options nor impose penalties or rewards, yet they influence behavior and promote optimal decisions. In fact, many behaviors and decisions can be modified without coercion, simply through better design and indirect cues [6,8]. For this reason, nudges have been incorporated into electronic prescription systems [8,9]. The authors provide two recommendations:
1) Further studies should focus on developing effective nudge-driven models of health information systems. We recommend that researchers in the field of health information management and technology in Iran to conduct innovative research on the application of choice architecture in the design of health decision-support systems.
2) The choice architecture should be noticed by policymaking of health information management in Iran. Specifically, it is suggested to redesign decision-support systems using nudges mainly digital nudges such as health-related reminders, contextual information, and educational messages. For example, issuing alerts for patients with blood glucose levels above 110  and color-coding their demographic data in red withing electronic health records is a simple yet effective nudge for reminder and follow-ups [9].
By utilizing nudges, decision support systems can more optimally reduce medical errors, improve patients’ behavior and providers’ decisions, strengthening trust among researchers and health policymakers. As a result, such redesigned systems can pave the way for increasing the efficiency of health information systems.

Declarations
Ethical considerations: Not Applicable.
Funding: This research was conducted without any financial support.
Conflicts of interests: The authors declare that there is no conflict of interest.
Authors’ contribution: MJ: Conceptualization, study design, resources, writing–original draft, writing– review & editing, final approval; MM: Conceptualization, study design, resources, writing– review &editing, visualization, final approval.
Consent for publication: Not applicable.
Data availability: Not applicable.
AI deceleration: Not applicable.

 
Type of Study: Letter to Editor | Subject: Health Economics
Received: 2025/10/6 | Accepted: 2025/10/26 | Published: 2025/10/29

References
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