A Low-Cost Automated Clinical Pathway for Supporting the Clinical Decision Process

Geletaw Sahle Tegenaw, Demisew Amenu, Girum Ketema, Frank Verbeke, Jan Cornelis, Bart Jansen

Research output: Unpublished contribution to conferencePoster


In a constrained environment: (I). Following the paper-based clinical guideline is a traditional practice and the only choice utmost, (II). The service is challenged to deliver accurate and inadequate evidence for decision making, and (III). The service is suboptimal. This research in progress paper addresses to: (I). Introduce an automated clinical pathway, (II). Assist the organization of the care processes (by generating the pathway or plan of care) for simple treatment or referral service, and (II). Deliver optimal care by: (I). Reducing delay, (II). Minimizing cost, and (III). Improving patient outcomes. The chosen context is pregnant patients and breast symptoms at Jimma Health-center, Ethiopia but the solution can be easily generalized to other contexts. A Django framework is employed to design the CDSS_CP (Clinical Decision Support System Clinical Pathway) APP. This system has three main features- (I). Input: collecting the sign and symptoms. Since; the focus is on low resource setting, the CDSS-CP: (A). didn’t promote lengthy inputs rather try to promote inputs based on options, combo box, drop down selection and so on to minimize input error, and (B). try to promote ease of access and comfortable usability from mobile and tablet device, (II). Path Exploration: Based on the input the CDSS-CP try to generate the three possible paths (plan of care) i.e. treatable, referred and consideration path, and (III). Path Visualization: green, yellow and red colored coded visualization is used for treatable, consideration and referred path respectively. This paper presents and discusses the development process of the CDSS-CP system.
Original languageEnglish
Publication statusPublished - 28 Jun 2019


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