Clinician Interface Design for Effective Diabetic Data Visualization in Diabetes Care

Abstract

Background Recently, the prevalence of diabetes has increased rapidly and the rate of diabetes in patients has also increased. Active blood glucose management is required for patients to improve healing rates, to shorten hospitalization periods, and to reduce medical costs. However, hospitals now offer an old-fashioned prescription method that relies on experience due to various limitations such as the limitations of the data provided in the clinical interface and ineffective insulin prescription protocols. Thus, many researchers have argued that visualizing and representing patients’ specific data records in the clinical interface would be effective for medical staff. However, the problem is that the clinical interface visualizes results without considering the actual medical environment. In addition, the need to apply and integrate the clinician's workflow into the clinical interface has been raised, but related studies have been very limited. Therefore, this study identifies the needs of the clinician users through collaborative research with university hospital medical staff members, and presents a clinical interface for this. Methods First, four nurses and two clinicians were interviewed in advance to determine the specific needs of the medical staff. Second, a participatory design workshop was conducted for eight clinicians to investigate patient data that should be comprehensively viewed during treatment and an interface that can help for effective insulin prescription. Third, the research team designed and produced a clinical interface prototype based on the workshop results and conducted a test study with three clinicians. Results At the pre-interview, the medical staff's workflow was largely divided into four stages: blood glucose measurement. system upload. blood sugar level check. and prescription decision. Currently, there are many limitations because only limited data can be viewed in the clinician interface used in domestic hospitals. When classifying blood sugar-related data types at the workshop, 24 types of data could be categorized into 5 groups: baseline patient information, baseline medical examinations, prescriptions affecting blood glucose, and anti-hyperglycemic agents prescriptions. We classified them into three levels according to the priority and designed a clinical interface based on the workshop results. Finally we conducted four-repeated assessments on the interface with three doctors who participated in the workshop. The final interface was produced by reflecting the comments in this process. Conclusions The clinical interface designed in this study has limitations that was not measured and analyzed for a long period in the field in terms of work efficiency and satisfaction of the medical staff. The research team plans to develop a clinical interface by continuous joint research with university hospitals. We expect this study to contribute to clinical interface research used in various medical fields. © This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons. org/licenses/bync/3.0/), which permits unrestricted educational and non-commercial use, provided the original work is properly cited.