Comorbidities And Reducing InEquitieS (CARES): Feasibility of self-monitoring and community health worker support in management of comorbidities among Black breast and prostate cancer patients.

Background: Black individuals with cancer have a higher prevalence of comorbidities and a worse cancer prognosis than other racial groups in the US. As part of a quality improvement project, we aimed to demonstrate feasibility of self-monitoring and community health worker (CHW) support among managing comorbidities for Black individuals with breast or prostate cancer.

Methods: In a single arm, pre-post study, we enrolled patients with diabetes and/or hypertension who identified as Black and were diagnosed with 1) stage 0-IV breast cancer, or 2) prostate cancer and on long-term androgen-deprivation therapy.

The critical elements of digital health in diabetes and cardiometabolic care.

Digital innovations provide novel opportunities to individualize a person's care to best match their lifestyle needs and circumstances and to support them as they live their daily lives with diabetes. These innovations also serve to provide actionable data and insights for the care team giving them a "Webb telescope-like" view into their individual self-management journey, allowing them to see what cannot be seen during infrequent and limited office visits, thereby facilitating collaboration and communication to optimize the care plan on a timely basis. Technology advances are enabling diabetes care to transition from episodic, synchronous, primarily in-person care to include synchronous virtual care options and to continuous, on-demand, data-informed, asynchronous digital care better matching the demands of living with a relentless 24/7 chronic condition.

A New Taxonomy for Technology-Enabled Diabetes Self-Management Interventions: Results of an Umbrella Review.

Background: A 2017 umbrella review defined the technology-enabled self-management (TES) feedback loop associated with a significant reduction in A1C. The purpose of this 2021 review was to develop a taxonomy of intervention attributes in technology-enabled interventions; review recent, high-quality systematic reviews and meta-analyses to determine if the TES framework was described and if elements contribute to improved diabetes outcomes; and to identify gaps in the literature.

Methods: We identified key technology attributes needed to describe the active ingredients of TES interventions.

Engagement and Outcomes Associated with Contextual Annotation Features of a Digital Health Solution.

Background: Digital health solutions targeting diabetes self-care are popular and promising, but important questions remain about how these tools can most effectively help patients. Consistent with evidence of the salutary effects of note-taking in education, features that enable annotation of structured data entry might enhance the meaningfulness of the interaction, thereby promoting persistent use and benefits of a digital health solution.

Method: To examine the potential benefits of note-taking, we explored how patients with type 2 diabetes used annotation features of a digital health solution and assessed the relationship between annotation and persistence in engagement as well as improvements in glycated hemoglobin (A1C).

A Framework for Optimizing Technology-Enabled Diabetes and Cardiometabolic Care and Education: The Role of the Diabetes Care and Education Specialist.

Purpose: The purpose of this article is to present a framework for optimizing technology-enabled diabetes and cardiometabolic care and education using a standardized approach. This approach leverages the expertise of the diabetes care and education specialist, the multiplicity of technologies, and integration with the care team. Technology can offer increased opportunity to improve health outcomes while also offering conveniences for people with diabetes and cardiometabolic conditions.

A Systematic Review of Reviews Evaluating Technology-Enabled Diabetes Self-Management Education and Support.

Background: Since the introduction of mobile phones, technology has been increasingly used to enable diabetes self-management education and support. This timely systematic review summarizes how currently available technology impacts outcomes for people living with diabetes.

Methods: A systematic review of high quality review articles and meta analyses focused on utilizing technology in diabetes self-management education and support services was conducted.

Evidence-Based mHealth Chronic Disease Mobile App Intervention Design: Development of a Framework.

Background: Mobile technology offers new capabilities that can help to drive important aspects of chronic disease management at both an individual and population level, including the ability to deliver real-time interventions that can be connected to a health care team. A framework that supports both development and evaluation is needed to understand the aspects of mHealth that work for specific diseases, populations, and in the achievement of specific outcomes in real-world settings. This framework should incorporate design structure and process, which are important to translate clinical and behavioral evidence, user interface, experience design and technical capabilities into scalable, replicable, and evidence-based mobile health (mHealth) solutions to drive outcomes.

Hypoglycemia prediction using machine learning models for patients with type 2 diabetes.

Minimizing the occurrence of hypoglycemia in patients with type 2 diabetes is a challenging task since these patients typically check only 1 to 2 self-monitored blood glucose (SMBG) readings per day. We trained a probabilistic model using machine learning algorithms and SMBG values from real patients. Hypoglycemia was defined as a SMBG value < 70 mg/dL.

Integration of a mobile-integrated therapy with electronic health records: lessons learned.

Background: Responses to the chronic disease epidemic have predominantly been standardized in their approach to date. Barriers to better health outcomes remain, and effective management requires patient-specific data and disease state knowledge be presented in methods that foster clinical decision-making and patient self-management. Mobile technology provides a new platform for data collection and patient-provider communication.

Mobile diabetes intervention study: testing a personalized treatment/behavioral communication intervention for blood glucose control.

Background: National data find glycemic control is within target (A1c<7.0%) for 37% of patients with diabetes, and only 7% meet recommended glycemic, lipid, and blood pressure goals.

Objectives: To compare active interventions and usual care for glucose control in a randomized clinical trial (RCT) among persons with diabetes cared for by primary care physicians (PCPs) over the course of 1 year.

Where is the patient in diabetes performance measures? The case for including patient-centered and self-management measures.

Objective: Health policies are important determinants of clinician and patient behavior, and an important policy issue is what items are included in healthcare quality and performance measures. There is consensus that patient-centered care and self-management support are essential evidence-based components of good diabetes care. However, most major diabetes performance measures such as the National Committee for Quality Assurance (NCQA)/American Diabetes Association (ADA) Provider Recognition Program indexes have not included self-management or psychosocial items.

Computerized learning technologies for diabetes: a systematic review.

Background: The objective of this study was to evaluate computerized learning technology interventions that can empower patients in the self-management of diabetes and support diabetes education over a distance.

Methods: We searched Medline (1966-2006), CINAHL (1982-2006), and the Cochrane Central Register of Controlled Trials (first quarter 2007) databases. We also reviewed reference lists from included studies to identify additional studies.

Using the American Association of Diabetes Educators Outcomes System to identify patient behavior change goals and diabetes educator responses.

Purpose: The purpose of this article is to ascertain patients' self-identified and mutually identified or agreed on (working with diabetes educators) behavior change goals and examine the diabetes educators' response to these goals during the provision of diabetes self-management education.

Methods: The American Association of Diabetes Educators Outcome System was integrated into Web-based, touch-screen, and telephonic systems within 8 sites within the Pittsburgh Regional Initiative for Diabetes Education network. Data from patients and their diabetes educators were obtained from the Diabetes Self-management Assessment Report Tool (D-SMART) and Diabetes Educator Tool (D-ET).

The Diabetes Self-management Assessment Report Tool (D-SMART): process evaluation and patient satisfaction.

Purpose: The purpose of this article is to present the results of the process evaluation and patient experience in completing the Diabetes Self-management Assessment Report Tool (D-SMART), an instrument within the AADE Outcome System to assist diabetes educators to assess, facilitate, and track behavior change in the provision of diabetes self-management education (DSME).

Methods: The D-SMART was integrated into computer and telephonic systems at 5 sites within the Pittsburgh Regional Initiative for Diabetes Education (PRIDE) network. Data were obtained from 290 patients with diabetes using the system at these programs via paper-and-pencil questionnaires following baseline D-SMART assessments and electronic system measurement of system performance.

Development of the American Association of Diabetes Educators' Diabetes Self-management Assessment Report Tool.

Purpose: The purpose of this article is to describe the development and testing of a new tool for collecting patient information for diabetes self-management education (DSME): the Diabetes Self-management Assessment Report Tool (D-SMART). The D-SMART was designed through expert panel consensus based on a hybrid conceptual framework and is intended to serve multiple functions at the level of the patient, the program, and the field.

Methods: The D-SMART has completed 3 rounds of pilot testing and is currently undergoing a fourth round, with each round resulting in revisions to the original instrument.

Evolution of the American Association of Diabetes Educators' diabetes education outcomes project.

Purpose: This is the initial article in a series that describes a multiyear project of a professional membership organization to define, standardize, collect, and report the outcomes of diabetes self-management education. The purpose of this article is to describe and summarize the contributions of each phase of the project: determining a conceptual framework, developing and testing measurement instruments, defining outcome standards for diabetes self-management education, and implementing a technology approach to capturing the outcomes.

Methods: Association archives, project participants, presentation slides, and published articles provide the historical information that is presented in this article.

Toward describing practice: the AADE National Diabetes Education Practice Survey: diabetes education in the United States--who, what, where, and how.

This article describes the first comprehensive survey of diabetes self-management education programs and practice in the United States. The American Association of Diabetes Educators (AADE), through environmental scanning of members and the external health care environment, identified significant changes in the practice of diabetes education in 2004. In an effort to more completely understand the current state of practice, the association administered the National Diabetes Education Practice Survey (NPS) to the membership in 2005 and 2006.

Tools, technologies, and informatics: supporting glycemic control.

Objective: To overcome the challenges involved in the adoption and implementation of standards of glycemic control in the inpatient setting.

Methods: Three major barriers to effective glycemic control are examined, and solutions are discussed.

Results: The diabetes care process occurs at several levels of the hospital system, including the community level.