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Current clinical guidelines allow already for some degree of personalized treatment for people with type 2 diabetes (T2D). Factors such as age and comorbidity as well as patient preferences and goals should be taken into account when prescribing glucose-regulating and cardiovascular medication treatment.
Recent cross-sectional research indicates that this personalised approach is not yet common practice, and that undertreatment occurs in younger patients (<50 years) and overtreatment occurs in older patients (>70 years). This apparent lack of implementing personalized treatment needs further study in order to develop support strategies for both healthcare providers and patients to adopt more personalised treatment decision making. Since the majority of people with type 2 diabetes treatment are managed in primary care, this project will focus on the general practice setting where both general practitioners and practice support staff are responsible for routine diabetes care.
Questions may include:
Develop patient-oriented strategies and tools to support personalized decision making for people with type 2 diabetes.
This project includes the essential steps for developing a new practice-oriented intervention strategy before it can be implemented in practice: (1) describe the current situation and its determinants, (2) develop a toolbox to support healthcare professionals and patients in making personalized decisions, (3) evaluate the feasibility and potential effects of implementing the toolbox in general practice.
For part 1: cohort studies making use of existing data from the GIANTT cohort.
For part 2: literature/interview/survey studies focusing on healthcare providers and patients in primary care.
For part 3: pilot studies in general practice
This project will give insight in the current status and needs for implementing patient-oriented personalized treatment decision making in diabetes care, and provide a toolbox to support this implementation process in clinical practice.
Important links can be made within the Drug Regulation Domain and the Drug Application Domain. This may lead to expanding the patient-level factors that will be studied; developing tools together that can be used for assessing patient preferences; developing algorithms together that can be used to support healthcare professionals in making personalized decisions.
This is a research project of PROMINENT