Data Visualization in Diabetes Self-Management: Empowering Patients with Actionable Insights

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@article{1706463,
      author = {Precious Ejiba, Emmanuella Unuode, Odera Ohazurike, Frank Okpara},
      title = {Data Visualization in Diabetes Self-Management: Empowering Patients with Actionable Insights},
      journal = {Iconic Research And Engineering Journals},
      year = {2024},
      volume = {8},
      number = {5},
      pages = {10-19},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1706463.pdf},
      abstract = {Effective blood glucose monitoring and interpretation are crucial in diabetes management, helping patients maintain glycaemic control and mitigate risks of complications. This study explores the role of data visualization in empowering diabetic patients to manage their condition by transforming raw blood sugar data into actionable insights. The Diabetes Data Visualizer app was developed to assist patients in visualizing blood glucose trends and generating personalized recommendations. The app utilized simple line charts and bar charts to highlight blood sugar trends over time and compare morning vs. evening blood sugar levels, respectively. Key insights such as trends, peak levels, and fluctuations were derived, with recommendations provided based on average blood sugar levels and general trends. In a case study, the app analysed the blood glucose data of a diabetic patient over a 7-day period, and insights showed that the patient?s blood sugar levels fluctuated within the normal range (70?140 mg/dL) and exhibited a general downward trend. While the app provided useful insights, several limitations were noted, including its thresholds, which may differ from standard clinical guidelines, and the need for additional features, such as generating recommendations from morning vs. evening comparisons. Future improvements aim to expand the app?s capabilities by hosting it online and integrating more advanced analytics, including machine learning. These refinements could enhance the app?s potential in helping patients and healthcare providers better manage diabetes.},
      keywords = {Diabetes, Data visualisation, Self-management, Patient empowerment, Blood Sugar Monitoring, SMA (Simple Moving Average), Trend Analysis},
      month = {November},
  }