Effect of Remote Glucose Monitoring Utilizing Computerized Insulin Dose Adjustment Algorithms: A Pilot Project

Abstract

Introduction Primary care physicians are often challenged to adjust insulin doses. To facilitate this process, we evaluated in a safety net clinic the work flow and glycemic effects of remote glucose monitoring utilizing Federal Drug Administration (FDA) cleared, Conformité Européenne (CE) registered software that contained computerized algorithms for insulin dose adjustments to help clinicians make dosing decisions for insulin-requiring patients. Methods Patients taking insulin for at least 6 months with HbA1 c levels of at least 8.0% measured glucose levels with a meter attached to their smartphones. Readings were automatically transmitted to a secure, Health Insurance Portability and Accountability Act (HIPAA)-approved server. Values were analyzed every 2–3 weeks and reports, including recommendations for insulin dose changes, were sent to a clinic nurse practitioner (NP) who modified or accepted the recommendations. A staff person contacted patients with the new doses determined by the NP. Results Insulin regimens included basal alone ( N = 11), basal/bolus ( N = 14), and self-mixed/split ( N = 3). Baseline HbA1 levels of 10.0% fell to 8.1% at 3 months ( N = 28) and 7.6% at 6 months ( N = 17) without any clinic visits for dose adjustments. There were 268 reports which allowed providers to see 268 other patients during these avoided clinic visits. The NP agreed with 82% of the recommendations. The total doses of insulin increased by 24%. No patient experienced severe hypoglycemia or visited an emergency department for hypoglycemia. Conclusion Remote glucose monitoring utilizing computerized insulin dose adjustment algorithms saved time for both providers and patients while effectively improving glycemia. Funding The Leonard M. Lipman Charitable Trust and Mellitus Health. Electronic supplementary material The online version of this article (10.1007/s13300-019-0565-y) contains supplementary material, which is available to authorized users.

Improved Glycemic Control Through the Use of a Telehomecare Program in Patients with Diabetes Treated with Insulin

“…20 Furthermore, a recent study published by Davidson also reported a pilot project using a remote glucose monitoring utilizing computerized insulin dose adjustment and results showed that the method was safe and effective while saving medical time and face-to-face visit. 21 However, it should be noted that our study reflected a short-term analysis for a 6-month period and that long-term impact on medical visits associated with THC monitoring remains to be explored. Moreover, despite a reduction in medical visits, an additional burden in nursing interventions is expected when implementing a THC system and should be taken into consideration.…”

Effect of Incorporating Computerized Insulin Dose Adjustment Algorithms into a Remote Patient Monitoring Program on HbA1c Levels in Patients with Type 2 Diabetes

“…Time savings were also tracked in a different manner in a previous pre-post remote glucose monitoring study utilizing Insulin Insights ™ in which 28 patients were followed by a nurse practitioner for 3 months and 17 for 6 months and reports also generated every 2-3 weeks. 26 The nurse practitioner took 13.7 hours to evaluate and decide on the insulin dose adjustments recommended in 268 reports. A 15 minute inperson visit for these 268 interactions would have required 67 hours.…”

“…14,24,25 Mellitus Health has developed computerized insulin dose adjustment algorithms (CIDAAs) to help PCCs adjust insulin doses. In a pre-post study 26 , a nurse practitioner utilizing these algorithms lowered HbA1c levels from 10.0% to 7.6% in 6 months in poorly controlled, minority patients who measured their glucose levels remotely. In another pre-post study, 27 a clinical pharmacist utilizing these algorithms lowered HbA1c levels from 11.5% to 8.3% and increased time in range from 29% to 51% after a mean of 3 months in a similar population who used continuous glucose monitoring.…”

Nurse and midwife involvement in task‐sharing and telehealth service delivery models in primary care: A scoping review

“…The feasibility of nurse-led care was explored in 12 studies of task-sharing models (Barton et al, 2013;Chin-Quee et al, 2020;Kompala et al, 2016;McNairy et al, 2017;Mitchell et al, 2016;Parham et al, 2010;Putnis et al, 2023;Shaw et al, 2013;Shumbusho et al, 2009;Walker et al, 2015;Wartko et al, 2023;Zewdu et al, 2022), and 5 discussing telehealth models (Davidson & Davidson, 2019;Delahunty-Pike et al, 2023;Howland et al, 2020;McKissick et al, 2017;Vierhile, 2017).…”

“…This included home, in-clinic or telehealth appointments to measure biometrics, following up medication changes, arranging further laboratory testing and health education.Management of health conditions. Managing health conditions and monitoring patients was a key role of nurses in 51 studies(Ajay et al, 2016;Anger et al, 2020;Bajis et al, 2020;Barton et al, 2013;Barton et al, 2018;Bedelu et al, 2007;Bernhardt, 2023;Billington et al, 2015;Bosworth et al, 2011;Bove, 2010;Carlisle & Warren, 2013;Chang et al, 2007;Ciemins et al, 2013;Clarke et al, 2020;Cohen et al, 2009;Datta et al, 2010;Davidson & Davidson, 2019;Delahunty-Pike et al, 2023;Engel et al, 2016;Fernandez, 2021;Fox & McCorkle, 2018;Gerin et al, 2007;Grimsrud et al, 2014;Grisot et al, 2019;Hoffman et al, 2023;Howland et al, 2020;Hui et al, 2022;Jeong et al, 2018;Jordan et al, 2011;Kaplan-Dobbs et al, 2021;Looman et al, 2015;Mallow et al, 2018;Mammen et al, 2020;Mitchell et al, 2016;Momin et al, 2022;Moriyama et al, 2021;O'Byrne et al, 2021;O'Keefe et al, 2023;…”