The study used the Practical, Robust, Implementation and Sustainability Model (PRISM) with mixed methods to: redesign a diabetes survival skills education (DSSE) program (DM2Go) content and the processes for its inpatient delivery; and to evaluate the feasibility of integrating and implementing high-tech tablet computer-enabled delivery of the DSSE program for hospital inpatients within usual workflow by staff on general medical/surgical units (MSUs) and a behavioral health unit. The four study phases were: I) Interviews and focus groups with stakeholders to identify perceived barriers and facilitators for implementation; II) Redesign of the D2Go program to address usability issues and potential barriers and to optimize perceived facilitators; III) Development of implementation processes and a D2Go toolkit; IV) Conduct of a prospective cohort pilot study on three MSUs and one BHU.

The investigators sought to determine the feasibility of integrating the Diabetes To Go inpatient DSSE program sustainably into ongoing hospital nursing unit processes for diabetes patient education and discharge planning. If successful, preliminary data generated will be used to develop a randomized controlled trial which will further assess program outcomes, including clinical and economic measures and potential for widespread dissemination.

The objectives of the R34 Diabetes To Go Inpatient proposal were to refine the Diabetes To Go program content based on user feedback and experience, as well as to design and develop processes to enhance the feasibility of integrated implementation within usual nursing unit workflow within one hospital belonging to a regional health system. A mixed-methods approach is used to leverage implementation science frameworks and human factors principles to make DSSE and discharge support more accessible, interactive and engaging for patients. The long-term goal of this research is to optimize scalable and sustainable solutions for DSSE delivery and for DM-related discharge support. This personalized approach leverages e-health technologies to pursue the following Specific Aims:

Aim 1: To refine and optimize the Diabetes To Go program content and implementation processes.

This will be achieved by applying user-centered interface design principles, content development in partnership with patients and providers, detailed process mapping for program integration into existing processes and workflow, and integrating mobile and e-health technology to support care transitions. The Practical, Robust, Implementation and Sustainability Model will guide implementation planning and evaluation.

Hypothesis 1. Diabetes To Go: will be optimized for patient and provider usability and integration into nursing unit workflow; will enhance patient self-care knowledge and skills; and will support the discharge transition process.

Aim 2: To conduct iterative rapid-cycle usability testing of the enhanced Diabetes To Go program content and processes and establish a Diabetes To Go program toolkit for widespread implementation.

This will be achieved by a series of intervention-evaluation cycles of field testing, refinement, retesting of the Diabetes To Go program and evaluation through: direct observation; patient, provider and system leadership stakeholder interviews and focus groups; and evaluation of changes in early patient outcomes.

Hypothesis 2. The Diabetes To Go program will be perceived favorably by stakeholders yielding a high-quality toolkit for implementation and delivery of the program for further evaluation and testing.

Preliminary data gathered during this study will be used to design an R18 pragmatic trial in response to PAR 15-157 which will examine outcomes of implementation of the Diabetes To Go program when delivered on hospital nursing units to adult patients with diabetes across multiple hospitals in a regional health system. The model has the potential to cause a paradigm shift in sustainable and generalizable approaches for delivery of patient-centered education and medication adherence and discharge transition support in the hospital.

Inclusion Criteria:

1. Age > 18 yrs (lower limit of age for admission to MWHC adult units. All of the Diabetes To Go content is designed for adult learners)
2. English speaking (Diabetes To Go content is currently only available in English);
3. Diagnosis of diabetes mellitus (ICD9 250.xx/ICD-10-CM E08-E11) documented in the EMR
4. Admitted to one of the inpatient units (non-critical care adult medicine/surgery nursing units, including 1 psychiatry unit) where the study is being conducted
5. Willing and able to participate in the program.

Exclusion criteria:

1. Age < 18 years (MWHC does not admit minors to its Medicine units and Diabetes To Go content has been prepared for adult learners) 2. Pregnancy or anticipated conception within 3 mos (Diabetes To Go content does not address gestational diabetes or diabetes in pregnancy where management and glycemic targets differ considerably from those for non-pregnant adults ); 3. Admission to an intensive-care unit, diabetic ketoacidosis, hyperglycemic hyperosmolar state - conditions in which the acuity level would likely preclude participation in DSME; 4. Patient declines participation in the education program for any reason; and any medical condition or cognitive dysfunction that, in the opinion of unit staff, would preclude participation in the education program.

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All patients with diabetes on the selected units who meet the criteria above are eligible.

Among 596 T2DM patients identified on three medical-surgical units, 415 (70%) were program eligible (mean age 64 years, 57% male, 51% Black).

The criteria for inclusion were intentionally been kept broad to minimize disruption to unit workflow and to increase generalizability of findings. Where appropriate, the justification for each criteria is also presented, e.g. exclusion of minors.

All data collected will be housed and maintained within the MedStar Health system on shared drives equipped with appropriate security measures behind the MedStar Health firewall. Data sharing will be housed within the MedStar Health Research Data Capture (RedCap) file server that provides HIPAA level protection of research data. Analytics on identifiable patient data will be maintained within MedStar Health's research servers.