McCoy, Rozalina

Background: Gestational diabetes mellitus (GDM) is a common complication of pregnancy that carries lasting risks. For women who have a history of GDM, the risk of developing type 2 diabetes mellitus (T2DM) increases by 50 to 60%. To monitor and prevent the development of T2DM, guidelines suggest screening those with a history of GDM at 6-weeks and 3-years post-delivery. For patients with abnormal lab results at the 6-week mark, it is advised to complete lab work sooner, at the 1-year mark. Data suggests that these guidelines are not being followed globally, and most do not receive adequate screening for T2DM. Methods: A retroactive chart review of 203 women between 18 and 55 years old with a past medical history significant for GDM was conducted to determine if patients with GDM completed screening for T2DM at 6-week, 1-year, and 3-year timestamps post-delivery. Patient demographics (age, race, ethnicity, language), clinical characteristics (body mass index), provider gender, and whether prediabetes or T2DM developed were recorded. Patients who did not complete the required follow-up received educational materials via the online portal system, and hemoglobin A1c (HbA1c) screening tests were ordered. Results: Ninety days post-intervention, 38 patients (50%) completed the HbA1c screening test, which exceeded our goal of a 5% improvement. Age and BMI 1-year postpartum were found to be significant factors in whether a patient completed HbA1c screening, with 16/18 (89%) completing screening with a healthy BMI 1-year postpartum (18.5 ≤ BMI < 25.0) but only 11/41 (27%) completing screening for patients under 40 years with an unhealthy BMI 1-year postpartum. Of the 38 patients who completed HbA1c screening, 9 (23.7%) had abnormal screening results. Conclusion: Follow-up surveillance for T2DM among women with a history of GDM is poor. Electronic health records can be used to identify and rectify gaps in care. Dissemination of standardized educational materials and electronic order entry for patients improved screening between the handoff from obstetrics to primary care.

Abstract Objective It is difficult to assess self-management behaviors (SMBs) and incorporate them into a personalized self-care plan. We aimed to develop and apply SMB phenotyping algorithms from data collected by diabetes devices and a mobile health (mHealth) application to create patient-specific SMBs reports to guide individualized interventions. Follow-up interventions aimed to understand patient's reasoning behind discovered SMB choices. Methods This study deals with adults on continuous subcutaneous insulin infusion using a continuous glucose monitor (CGM) who self-tracked SMBs with an mHealth application for 1 month. Patient-generated data were quantified and an SMB report was designed and populated for each participant. A diabetes educator used the report to conduct personalized, data-driven educational interventions. Thematic analysis of the intervention was conducted. Results Twenty-two participants recorded 118 alcohol, 251 exercise, 2,661 meal events, and 1,900 photos. A patient-specific SMB report was created from this data and used to conduct the educational intervention. High variability of SMB was observed between patients. There was variability in the percentage of alcohol events accompanied by a blood glucose check, median 79% (38–100% range), and frequency of changing the bolus waveform, median 11 (7–95 range). Interventions confirmed variability of SMBs. Main emerging themes from thematic analysis were: challenges and barriers, motivators, current SMB techniques, and future plans to improve glycemic control. Conclusion The ability to quantify SMBs and understand patients' rationale may help improve diabetes self-care and related outcomes. This study describes our first steps in piloting a patient-specific diabetes educational intervention, as opposed to the current “one size fits all” approach.