Acceptability of Sharing Behavioral Risk and Glucose Data Between Patients and Clinicians – A Pilot Study

Join us as this presenter discusses this poster live on Tuessday, August 11, 2020 | Track C at 5:15 PM Mountain

PRESENTER
AMY HUEBSCHMANN
Associate Professor, Clinician-Investigator, Division of General Internal Medicine, University of Colorado Center for Women’s Health Research
BACKGROUND
Medically complex patients with uncontrolled type 2 diabetes face diabetes self-management challenges, including managing blood glucose levels and lifestyle behaviors. Technology packages have improved clinical outcomes by allowing patients to share data with clinic teams on home glucose (Glooko©) and behavioral health risk data (My Own Health Report, MOHR). However, adoption of Glooko and MOHR remains low in primary care. In a pilot study to inform implementation efforts, we evaluated the acceptability of Glooko/MOHR among key stakeholders: patients and clinicians.
POPULATION
We recruited eligible patients with uncontrolled type 2 diabetes mellitus (Hemoglobin A1c >8%) and their treating clinicians from three academic primary care clinics.
METHODS
Participants provided acceptability ratings after a demonstration of the process of sharing Glooko/MOHR data between patients and clinicians. We considered ratings of ≥ 70% in each of the 7 Technology Acceptance Model (TAM) domains as acceptable. All quantitative data are reported as mean ± SD. We considered survey ratings of 70-80% and >80% as moderately and highly acceptable, respectively.
RESULTS
Patients enrolled (n=12) were adults (age = 65.7 ± 12.8 years), 33% non-white, 58% female, and 50% reported use of internet to manage health issues. Clinicians (n=11) had 13.2 ± 9.9 years of practice experience. Patient acceptability for Glooko data sharing: Intention to use (91.5±12%), Perceived usefulness (89.5±8.1%) and Social influence (83±0%). No unacceptable ratings. Patient acceptability for MOHR data sharing: Perceived usefulness (85.5±8.1%), Self-efficacy (83.5±12%) and Social influence (83±0%). One TAM domain was rated as unacceptable: Resistance to change (58.5±12%), including 33% of patients agreeing that s/he did not want MOHR to change how s/he managed diabetes. Clinician (n=11) acceptability of sharing Glooko and MOHR data: Highest ratings were for Perceived usefulness (88.1 ± 4.2%), Facilitators (84.2 ± 8.6%) and Intention to use (82 ± 15.6%). The Subjective Norms/Others’ support was unacceptably rated (50.2 ± 16%), including anticipation of low perceived support among patients (27%), colleagues (55%), and health managers (55%).
CONCLUSIONS
Medically complex patients with diabetes and their clinicians expressed intention to use technology to share glucose and behavioral risk data between visits. However, to reach the promise of using remote technology and patient-reported data to address health challenges, clinics will need to identify and address factors leading to clinicians’ perceptions of limited support from others to use remote data monitoring, particularly patients, and also better discern why some patients are resistant to using MOHR as part of their diabetes management.
POSTER

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Posted in Planning Methods & Frameworks, Poster Session.

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