Heather J Cole-Lewis1, Arlene M Smaldone2, Patricia R Davidson3, Rita Kukafka4, Jonathan N Tobin5, Andrea Cassells5, Elizabeth D Mynatt6, George Hripcsak4, Lena Mamykina7. 1. Department of Biomedical Informatics, Columbia University, New York, NY, USA; ICF International, Rockville, MD, USA. 2. School of Nursing, Columbia University, USA; Department of Epidemiology and Population Health, Albert Einstein College of Medicine of Yeshiva University, Bronx, NY, USA. 3. College of Health Sciences, Nutrition Department, West Chester University, West Chester, PA, USA; Department of Epidemiology and Population Health, Albert Einstein College of Medicine of Yeshiva University, Bronx, NY, USA. 4. Department of Biomedical Informatics, Columbia University, New York, NY, USA; Department of Epidemiology and Population Health, Albert Einstein College of Medicine of Yeshiva University, Bronx, NY, USA. 5. Clinical Directors Network, NY, USA; Department of Epidemiology and Population Health, Albert Einstein College of Medicine of Yeshiva University, Bronx, NY, USA. 6. Department of Epidemiology and Population Health, Albert Einstein College of Medicine of Yeshiva University, Bronx, NY, USA; Georgia Institute of Technology, Atlanta, GA, USA. 7. Department of Biomedical Informatics, Columbia University, New York, NY, USA; Department of Epidemiology and Population Health, Albert Einstein College of Medicine of Yeshiva University, Bronx, NY, USA. Electronic address: lena.mamykina@dbmi.columbia.edu.
Abstract
OBJECTIVE: To develop an expandable knowledge base of reusable knowledge related to self-management of diabetes that can be used as a foundation for patient-centric decision support tools. MATERIALS AND METHODS: The structure and components of the knowledge base were created in participatory design with academic diabetes educators using knowledge acquisition methods. The knowledge base was validated using scenario-based approach with practicing diabetes educators and individuals with diabetes recruited from Community Health Centers (CHCs) serving economically disadvantaged communities and ethnic minorities in New York. RESULTS: The knowledge base includes eight glycemic control problems, over 150 behaviors known to contribute to these problems coupled with contextual explanations, and over 200 specific action-oriented self-management goals for correcting problematic behaviors, with corresponding motivational messages. The validation of the knowledge base suggested high level of completeness and accuracy, and identified improvements in cultural appropriateness. These were addressed in new iterations of the knowledge base. DISCUSSION: The resulting knowledge base is theoretically grounded, incorporates practical and evidence-based knowledge used by diabetes educators in practice settings, and allows for personally meaningful choices by individuals with diabetes. Participatory design approach helped researchers to capture implicit knowledge of practicing diabetes educators and make it explicit and reusable. CONCLUSION: The knowledge base proposed here is an important step towards development of new generation patient-centric decision support tools for facilitating chronic disease self-management. While this knowledge base specifically targets diabetes, its overall structure and composition can be generalized to other chronic conditions.
OBJECTIVE: To develop an expandable knowledge base of reusable knowledge related to self-management of diabetes that can be used as a foundation for patient-centric decision support tools. MATERIALS AND METHODS: The structure and components of the knowledge base were created in participatory design with academic diabetes educators using knowledge acquisition methods. The knowledge base was validated using scenario-based approach with practicing diabetes educators and individuals with diabetes recruited from Community Health Centers (CHCs) serving economically disadvantaged communities and ethnic minorities in New York. RESULTS: The knowledge base includes eight glycemic control problems, over 150 behaviors known to contribute to these problems coupled with contextual explanations, and over 200 specific action-oriented self-management goals for correcting problematic behaviors, with corresponding motivational messages. The validation of the knowledge base suggested high level of completeness and accuracy, and identified improvements in cultural appropriateness. These were addressed in new iterations of the knowledge base. DISCUSSION: The resulting knowledge base is theoretically grounded, incorporates practical and evidence-based knowledge used by diabetes educators in practice settings, and allows for personally meaningful choices by individuals with diabetes. Participatory design approach helped researchers to capture implicit knowledge of practicing diabetes educators and make it explicit and reusable. CONCLUSION: The knowledge base proposed here is an important step towards development of new generation patient-centric decision support tools for facilitating chronic disease self-management. While this knowledge base specifically targets diabetes, its overall structure and composition can be generalized to other chronic conditions.
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