Elizabeth B Kirkland1, Justin Marsden2, Jingwen Zhang2, Samuel O Schumann3, John Bian2, Patrick Mauldin2, William P Moran3. 1. Division of General Internal Medicine, Department of Medicine, Medical University of South Carolina, 135 Rutledge Ave, MSC 591, Charleston, SC, USA. Electronic address: kirklane@musc.edu. 2. Section of Health Systems Research and Policy, Department of Medicine, Medical University of South Carolina, 135 Rutledge Ave, MSC 591, Charleston, SC, USA. 3. Division of General Internal Medicine, Department of Medicine, Medical University of South Carolina, 135 Rutledge Ave, MSC 591, Charleston, SC, USA.
Abstract
AIMS: We sought to determine whether underserved patients enrolled in a statewide remote patient monitoring (RPM) program for diabetes achieve sustained improvements in hemoglobin A1c at 6 and 12 months and whether those improvements are affected by demographic and clinical variables. METHODS: Demographic and clinical variables were obtained at baseline, 6 months and 12 months. Baseline HbA1c values were compared with those obtained at 6 and 12 months via paired t-tests. A multivariable regression model was developed to identify patient-level variables associated with HbA1c change at 12 months. RESULTS: HbA1c values were obtained for 302 participants at 6 months and 125 participants at 12 months. Compared to baseline, HbA1c values were 1.8% (19 mmol/mol) lower at 6 months (p < 0.01) and 1.3% (14 mmol/mol) lower at 12 months (p < 0.01). Reductions at 12 months were consistent across clinical settings. A regression model for change in HbA1c showed no statistically significant difference for patient age, sex, race, household income, insurance, or clinic type. CONCLUSIONS: Patients enrolled in RPM had improved diabetes control at 6 and 12 months. Neither clinic type nor sociodemographic variables significantly altered the likelihood that patients would benefit from this type of technology. These results suggest the promise of RPM for delivering care to underserved populations.
AIMS: We sought to determine whether underserved patients enrolled in a statewide remote patient monitoring (RPM) program for diabetes achieve sustained improvements in hemoglobin A1c at 6 and 12 months and whether those improvements are affected by demographic and clinical variables. METHODS: Demographic and clinical variables were obtained at baseline, 6 months and 12 months. Baseline HbA1c values were compared with those obtained at 6 and 12 months via paired t-tests. A multivariable regression model was developed to identify patient-level variables associated with HbA1c change at 12 months. RESULTS: HbA1c values were obtained for 302 participants at 6 months and 125 participants at 12 months. Compared to baseline, HbA1c values were 1.8% (19 mmol/mol) lower at 6 months (p < 0.01) and 1.3% (14 mmol/mol) lower at 12 months (p < 0.01). Reductions at 12 months were consistent across clinical settings. A regression model for change in HbA1c showed no statistically significant difference for patient age, sex, race, household income, insurance, or clinic type. CONCLUSIONS: Patients enrolled in RPM had improved diabetes control at 6 and 12 months. Neither clinic type nor sociodemographic variables significantly altered the likelihood that patients would benefit from this type of technology. These results suggest the promise of RPM for delivering care to underserved populations.
Authors: Tzeyu L Michaud; Mohammad Siahpush; Keyonna M King; Athena K Ramos; Regina E Robbins; Robert J Schwab; Martina A Clarke; Dejun Su Journal: Diabetes Res Clin Pract Date: 2019-11-23 Impact factor: 5.602
Authors: Leonard E Egede; Joni S Williams; Delia C Voronca; Rebecca G Knapp; Jyotika K Fernandes Journal: Diabetes Technol Ther Date: 2017-06-05 Impact factor: 6.118
Authors: Jun Yang Lee; Carina Ka Yee Chan; Siew Siang Chua; Chirk Jenn Ng; Thomas Paraidathathu; Kenneth Kwing Chin Lee; Shaun Wen Huey Lee Journal: J Gen Intern Med Date: 2019-09-11 Impact factor: 5.128
Authors: Michelle M Alvarado; Hye-Chung Kum; Karla Gonzalez Coronado; Margaret J Foster; Pearl Ortega; Mark A Lawley Journal: J Med Internet Res Date: 2017-02-13 Impact factor: 5.428
Authors: Brittany L Smalls; Tiarney D Ritchwood; Kinfe G Bishu; Leonard E Egede Journal: Int J Environ Res Public Health Date: 2020-02-04 Impact factor: 3.390
Authors: Elizabeth Kirkland; Samuel O Schumann; Andrew Schreiner; Marc Heincelman; Jingwen Zhang; Justin Marsden; Patrick Mauldin; William P Moran Journal: Telemed J E Health Date: 2021-06-11 Impact factor: 5.033