scholarly journals Patient Input for Design of a Decision Support Smartphone Application for Type 1 Diabetes

2019 ◽  
Vol 14 (6) ◽  
pp. 1081-1087
Author(s):  
Leah M. Wilson ◽  
Nichole Tyler ◽  
Peter G. Jacobs ◽  
Virginia Gabo ◽  
Brian Senf ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Decision Support ◽  
Decision Support Tool ◽  
Smartphone Application ◽  
Valuable Insight ◽  
Support Tool ◽  
Health Community ◽  
Continuous Glucose Monitors ◽  
Survey Responses

Background: Decision support smartphone applications integrated with continuous glucose monitors may improve glycemic control in type 1 diabetes (T1D). We conducted a survey to understand trends and needs of potential users to inform the design of decision support technology. Methods: A 70-question survey was distributed October 2017 through May 2018 to adults aged 18-80 with T1D from a specialty clinic and T1D Exchange online health community ( myglu.org ). The survey responses were used to evaluate potential features of a diabetes decision support tool by Likert scale and open responses. Results: There were 1542 responses (mean age 46.1 years [SD 15.2], mean duration of diabetes 26.5 years [SD 15.8]). The majority (84.2%) have never used an app to manage diabetes; however, a large majority (77.8%) expressed interest in using a decision support app. The ability to predict and avoid hypoglycemia was the most important feature identified by a majority of the respondents, with 91% of respondents indicating the highest level of interest in these features. The task that respondents find most difficult was management of glucose during exercise (only 47% of participants were confident in glucose management during exercise). The respondents also highly desired features that help manage glucose during exercise (85% of respondents were interested). The responses identified integration and interoperability with peripheral devices/apps and customization of alerts as important. Responses from participants were generally consistent across stratified categories. Conclusions: These results provide valuable insight into patient needs in decision support applications for management of T1D.

Outsourcing glucose management to AI

2020 ◽  
Vol 12 (564) ◽  
pp. eabe8120
Author(s):  
James Ankrum
Keyword(s):  
Type 1 Diabetes ◽  
Decision Support ◽  
Insulin Therapy ◽  
Intensive Insulin Therapy ◽  
Decision Support Tool ◽  
Support Tool ◽  
Glucose Management

An automated decision support tool could expand access to intensive insulin therapy for patients with type 1 diabetes.

Factors Affecting Type One Diabetes Self-Management According to Youth and Parents (Preprint)

2020 ◽  
Author(s):  
Janet Panoch ◽  
Lisa Yazel ◽  
Courtney Moore ◽  
Sarah Wiehe ◽  
Tamara Hannon
Keyword(s):  
Type 1 Diabetes ◽  
Decision Support ◽  
Decision Support Tool ◽  
Self Management ◽  
Adult Care ◽  
Patient Centered ◽  
Diabetes Clinic ◽  
Human Centered Design ◽  
Support Tool

BACKGROUND Adolescents with type 1 diabetes differ from their parents and physicians about what they need from healthcare. Therefore, it is important to implement patient-centered diabetes care for adolescents. OBJECTIVE This study used human-centered design to reveal diabetes self-management challenges faced by youth with type 1 diabetes and their parents. This was a pre-study design phase of a larger study to develop a patient-centered automated decision support tool for diabetes clinic. METHODS Data were collected from youth and parents in two settings 1) a diabetes summer camp to capture challenges faced by youth and parents, 2) youth and parents participating in human-centered design sessions to further explore challenges. RESULTS Fifty-six people completed the camp worksheet, identifying 15 unique themes. The sessions further verified three problematic themes each for youth and parents. Youth generated 23 questions and parents identified 33 questions for potential use for the decision support tool development. CONCLUSIONS Including patient and parent self-management needs is vital. Providers should understand the psychosocial factors associated with barriers to self-management. The incorporation of patient and parent questions, ideas, and subsequent patient-provider communication in the support tool may improve trust in the provider and youth self-efficacy as they navigate the transition to independent adult care. CLINICALTRIAL Trial Registration: ClinicalTrials.gov NCT03084900

Patient Input for Design of a Type 1 Diabetes (T1D) Decision Support Smartphone Application

Diabetes ◽  
2018 ◽  
Vol 67 (Supplement 1) ◽  
pp. 991-P ◽  
Author(s):  
LEAH M. WILSON ◽  
VIRGINIA GABO ◽  
NICHOLE S. TYLER ◽  
RAVI REDDY ◽  
PETER G. JACOBS ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Decision Support ◽  
Smartphone Application

Abstract P305: Assessing the Feasibility of Implementing a Clinical Decision Support Tool in the Office-Based Setting: Experiences From the American College of Cardiology's Improving Continuous Cardiac Care (IC3) Pilot Program

2011 ◽  
Vol 4 (suppl_1) ◽  
Author(s):  
Katie Kehoe ◽  
Kristi Mitchell ◽  
Fran Fiocchi ◽  
Mary Anne Elma ◽  
Tracie Breeding ◽  
...  
Keyword(s):  
Decision Support ◽  
Data Collection ◽  
Clinical Decision Support ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Valuable Insight ◽  
Decision Support Tools ◽  
Patient Encounter ◽  
Support Tool ◽  
Support Tools

BACKGROUND: Clinical decision support tools have been used to improve guideline adherence amidst challenges during implementation in the office-based setting. As such, these tools require pilot testing to assess feasibility and ease of use. METHODS: The IC 3 Program, now known as the PINNACLE Registry, is a prospective, practice-based QI program designed to capture and report outpatient performance measures (PM) and provide decision support tools to optimize the quality of care delivered to outpatient cardiac patients. ACC/AHA guidelines and PMs for CAD, atrial fibrillation, heart failure and hypertension were translated into key data elements collected systematically via a paper-based data collection form (DCF). In September 2008, four offices participated in a 2-week pilot to assess the feasibility of implementing the DCF. A self-reported survey was administered, followed by a phone interview with participants. RESULTS: Results of the implementation pilot found that all respondents agreed with the overall layout of the DCF and that the data collected were typical of that routinely collected during a patient encounter. Physicians completed the DCFs more often( 57.1%) than other staff in the office. However, nurses or other staff(80%) were more likely to fax the data into the ACC. DCFs were faxed generally at the end of the week (66.7%). Most practices entered data both during and after the patient encounter (60%). Time for data entry ranged from 10-20 minutes. Roughly, half of the participants found data collection easy and others found it time consuming. One physician suggested making changes in the office work flow for future data collection. CONCLUSION: The pilot of the DCF provided valuable insight regarding the feasibility of collecting and reporting data, as well as the usability of a paper-based DCF in the outpatient setting. Although challenging, implementation of a paper-based decision support tool in practices can be successful. These findings demonstrate that it takes a team effort with clear delineation of roles and responsibilities to insure practice-wide adoption of a systematic QI process for accurately collecting and reporting clinical data.

scholarly journals Effectiveness and scalability of an electronic patient-reported outcome measure and decision support tool for family-centred and participation-focused early intervention: PROSPECT hybrid type 1 trial protocol

BMJ Open ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. e051582
Author(s):  
Vera Kaelin ◽  
Vivian Villegas ◽  
Yi-Fan Chen ◽  
Natalie Murphy ◽  
Elizabeth Papautsky ◽  
...  
Keyword(s):  
Decision Support ◽  
Early Intervention ◽  
Fixed Effects ◽  
Decision Support Tool ◽  
Patient Reported Outcome ◽  
Support Tool ◽  
Hybrid Type ◽  
Generalised Linear Mixed Model ◽  
Patient Reported

IntroductionEarly intervention (EI) endorses family-centred and participation-focused services, but there remain insufficient options for systematically enacting this service approach. The Young Children’s Participation and Environment Measure electronic patient-reported outcome (YC-PEM e-PRO) is an evidence-based measure for caregivers that enables family-centred services in EI. The Parent-Reported Outcomes for Strengthening Partnership within the Early Intervention Care Team (PROSPECT) is a community-based pragmatic trial examining the effectiveness of implementing the YC-PEM e-PRO measure and decision support tool as an option for use within routine EI care, on service quality and child outcomes (aim 1). Following trial completion, we will characterise stakeholder perspectives of facilitators and barriers to its implementation across multiple EI programmes (aim 2).Methods and analysisThis study employs a hybrid type 1 effectiveness-implementation study design. For aim 1, we aim to enrol 223 caregivers of children with or at risk for developmental disabilities or delays aged 0–3 years old that have accessed EI services for three or more months from one EI programme in the Denver Metro catchment of Colorado. Participants will be invited to enrol for 12 months, beginning at the time of their child’s annual evaluation of progress. Participants will be randomised using a cluster-randomised design at the EI service coordinator level. Both groups will complete baseline testing and follow-up assessment at 1, 6 and 12 months. A generalised linear mixed model will be fitted for each outcome of interest, with group, time and their interactions as primary fixed effects, and adjusting for child age and condition severity as secondary fixed effects. For aim 2, we will conduct focus groups with EI stakeholders (families in the intervention group, service coordinators and other service providers in the EI programme, and programme leadership) which will be analysed thematically to explain aim 1 results and identify supports and remaining barriers to its broader implementation in multiple EI programmes.Ethics and disseminationThis study has been approved by the institutional review boards at the University of Illinois at Chicago (2020-0555) and University of Colorado (20-2380). An active dissemination plan will ensure that findings have maximum reach for research and practice.Trial registration numberNCT04562038.

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