Dataset Information

Prototype of an evidence-based tool to aid individualized treatment for type 2 diabetes.

ABSTRACT: Data-driven tools are needed to inform individualized treatment decisions for people with type 2 diabetes (T2D). To show how treatment might be individualized, an interactive outline tool was developed to predict treatment outcomes. Individualized predictions were generated for change in HbA1c and body weight after initiation of newer antidiabetes drugs recommended by current guidelines. These predictions were based on data from randomized controlled trials of glucose-lowering drugs. The data included patient demographics and clinical characteristics (sex, age, body mass index, weight, diabetes duration, HbA1c level, current diabetes treatment and renal function). Predicted outcomes were determined using prespecified statistical models from original trial protocols and estimated coefficients for selected baseline characteristics. This prototype illustrates how evidence-based individualized treatment might be facilitated in the clinic for people with T2D. Further and ongoing development is required to improve the tool's prognostic value, including the addition of disease co-morbidities and patient-orientated outcomes. Patient engagement and data-sharing by sponsors of clinical trials, as well as real-world evidence, are needed to provide reliable predicted outcomes to inform shared patient-physician decision-making.

SUBMITTER: Buse JB

PROVIDER: S-EPMC8251774 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Prototype of an evidence-based tool to aid individualized treatment for type 2 diabetes.

Buse John B JB Holst Ingrid I Knop Filip K FK Kvist Kajsa K Thielke Desirée D Pratley Richard R

Diabetes, obesity & metabolism 20210504 7

Data-driven tools are needed to inform individualized treatment decisions for people with type 2 diabetes (T2D). To show how treatment might be individualized, an interactive outline tool was developed to predict treatment outcomes. Individualized predictions were generated for change in HbA1c and body weight after initiation of newer antidiabetes drugs recommended by current guidelines. These predictions were based on data from randomized controlled trials of glucose-lowering drugs. The data in ...[more]

PMID: 33764641

Similar Datasets

Project description:BackgroundAdolescents with type 1 diabetes mellitus have difficulty achieving optimal glycemic control, partly due to competing priorities that interfere with diabetes self-care. Often, significant diabetes-related family conflict occurs, and adolescents' thoughts and feelings about diabetes management may be disregarded. Patient-centered diabetes outcomes may be better when adolescents feel engaged in the decision-making process.ObjectiveThe objective of our study was to codesign a clinic intervention using shared decision making for addressing diabetes self-care with an adolescent patient and parent advisory board.MethodsThe patient and parent advisory board consisted of 6 adolescents (teens) between the ages 12 and 18 years with type 1 diabetes mellitus and their parents recruited through our institution's Pediatric Diabetes Program. Teens and parents provided informed consent and participated in 1 or both of 2 patient and parent advisory board sessions, lasting 3 to 4 hours each. Session 1 topics were (1) patient-centered outcomes related to quality of life, parent-teen shared diabetes management, and shared family experiences; and (2) implementation and acceptability of a patient-centered diabetes care plan intervention where shared decision making was used. We analyzed audio recordings, notes, and other materials to identify and extract ideas relevant to the development of a patient-centered diabetes management plan. These data were visually coded into similar themes. We used the information to develop a prototype for a diabetes management plan tool that we pilot tested during session 2.ResultsSession 1 identified 6 principal patient-centered quality-of-life measurement domains: stress, fear and worry, mealtime struggles, assumptions and judgments, feeling abnormal, and conflict. We determined 2 objectives to be principally important for a diabetes management plan intervention: (1) focusing the intervention on diabetes distress and conflict resolution strategies, and (2) working toward a verbalized common goal. In session 2, we created the diabetes management plan tool according to these findings and will use it in a clinical trial with the aim of assisting with patient-centered goal setting.ConclusionsPatients with type 1 diabetes mellitus can be effectively engaged and involved in patient-centered research design. Teens with type 1 diabetes mellitus prioritize reducing family conflict and fitting into their social milieu over health outcomes at this time in their lives. It is important to acknowledge this when designing interventions to improve health outcomes in teens with type 1 diabetes mellitus.

Project description:IntroductionMany parents who choose hypospadias repair for their sons experience decisional conflict (DC) and decisional regret (DR). We previously found that parental decision-making about hypospadias surgery is a complex process characterized by cyclic information-seeking to alleviate anxiety and confusion.ObjectiveThe objective of this study was to engage parents of hypospadias patients and pediatric providers in the co-design of a decision aid (DA) prototype to facilitate shared decision-making about hypospadias surgery and address DC and DR.MethodsFrom August 2018 to January 2019, we conducted three co-design workshops with parents of hypospadias patients, pediatric urology and general pediatric providers to discuss their recommendations for a DA prototype. Activities were audio recorded and professionally transcribed. Transcripts and worksheets were analyzed by six coders using qualitative analysis to identify key aspects of a hypospadias DA desired by stakeholders. We conducted a collaborative design and prototyping session to establish key features and requirements, created a content map visualizing this work, and then developed a DA prototype.ResultsParent participants included 6 mothers and 4 fathers: 8 Caucasian, 2 African-American; median age 31 years. Providers included pediatric urology (n = 7) and general pediatric providers (n = 10): median age 47.5 years, 83.3% Caucasian, 58.3% male, 58.3% MD's and 41.7% nurse practitioners. Participants created user-friendly, interactive DA prototypes with "24/7" availability that had three key functions: 1) provide accurate, customizable, educational content, 2) connect parents with each other, and 3) engage them in a decision-making activity. The prototype consisted of five modules (Extended Summary Figure). "Hypospadias Basics" includes epidemiology and a hypospadias severity scale. "Surgery Basics" includes goals, illustrated steps, and pros/cons of surgery. "Testimonials" includes videos of parents and adolescents discussing their experiences. "Help me Decide" includes a decisional conflict scale and a decision-making activity (i.e. values clarification method). "Frequently Asked Questions" covers general hypospadias information, perioperative expectations and a review of postoperative care.DiscussionTo our knowledge, this is the first DA prototype developed for a pediatric urology condition using a human-centered design approach to engage many key stakeholders in the development process. One limitation of this study is the small population sampled, which limits generalizability and means that our findings may not reflect the views of all parents or pediatric providers involved in hypospadias decision-making.ConclusionsWe created a parent-centered hypospadias DA prototype that provides decision support in an online, interactive format. Future directions include further testing with usability experts, providers and parents.

Dataset Information

Prototype of an evidence-based tool to aid individualized treatment for type 2 diabetes.

Publications

Prototype of an evidence-based tool to aid individualized treatment for type 2 diabetes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets