How Continuous Glucose Monitoring Reports Inform Clinical Decision-Making for Older Adults With Type 2 Diabetes: Mapping Clinical Workflow to Situation Awareness.

BACKGROUND

Older adults with type 2 diabetes experience high risk of hypoglycemia, yet clinicians often lack actionable glucose data to guide individualized treatment decisions. This study examined how standardized continuous glucose monitoring (CGM) reports inform clinicians' decision-making using Endsley's situation awareness (SA) framework.

METHODS

We conducted semi-structured interviews. Thirty clinicians reviewed three simulated older adult type 2 diabetes cases before and after reviewing CGM reports. Data saturation was achieved, consistent with qualitative research standards. Using an SA informed framework, we analyzed the proportion of clinicians referencing specific data elements and describing changes in diagnostic reasoning and treatment decisions.

RESULTS

After CGM data review, clinicians frequently revised assessments and plans. Most clinicians (90%) incorporated time-in-range metrics, while 93% identified previously unrecognized hypoglycemia or nocturnal patterns. Continuous glucose monitoring data led 86% of clinicians to modify their original treatment plan, including deprescribing high-risk agents (eg, sulfonylureas), adjusting insulin timing or dosing, or initiating safer alternatives (eg, SGLT-2 inhibitors, GLP-1 receptor agonists). Clinicians also identified multiple barriers to treatment implementation, including cost, medication access, housing instability, and limited food security.

CONCLUSIONS

Continuous glucose monitoring data-compared with A1C alone-provided meaningful, actionable information that improved individualized treatment decisions for older adults with type 2 diabetes. Continuous glucose monitoring data enhanced clinicians' perception, comprehension, and projection across the SA continuum, fostering more confident diagnostic reasoning and safer treatment strategies. These findings inform the design of SA-based clinical decision-support tools to better integrate CGM data, address contextual barriers, and optimize management of older adults with type 2 diabetes.