Overcoming Clinical Inertia: A Randomized Clinical Trial of a Telehealth Remote Monitoring Intervention Using Paired Glucose Testing in Adults With Type 2 Diabetes

Deborah A Greenwood, Shelley A Blozis, Heather M Young, Thomas S Nesbitt, Charlene C Quinn, Deborah A Greenwood, Shelley A Blozis, Heather M Young, Thomas S Nesbitt, Charlene C Quinn

Abstract

Background: Type 2 diabetes mellitus is a worldwide challenge. Practice guidelines promote structured self-monitoring of blood glucose (SMBG) for informing health care providers about glycemic control and providing patient feedback to increase knowledge, self-efficacy, and behavior change. Paired glucose testing—pairs of glucose results obtained before and after a meal or physical activity—is a method of structured SMBG. However, frequent access to glucose data to interpret values and recommend actions is challenging. A complete feedback loop—data collection and interpretation combined with feedback to modify treatment—has been associated with improved outcomes, yet there remains limited integration of SMBG feedback in diabetes management. Incorporating telehealth remote monitoring and asynchronous electronic health record (EHR) feedback from certified diabetes educators (CDEs)—specialists in glucose pattern management—employ the complete feedback loop to improve outcomes.

Objective: The purpose of this study was to evaluate a telehealth remote monitoring intervention using paired glucose testing and asynchronous data analysis in adults with type 2 diabetes. The primary aim was change in glycated hemoglobin (A(1c))—a measure of overall glucose management—between groups after 6 months. The secondary aims were change in self-reported Summary of Diabetes Self-Care Activities (SDSCA), Diabetes Empowerment Scale, and Diabetes Knowledge Test.

Methods: A 2-group randomized clinical trial was conducted comparing usual care to telehealth remote monitoring with paired glucose testing and asynchronous virtual visits. Participants were aged 30-70 years, not using insulin with A1c levels between 7.5% and 10.9% (58-96 mmol/mol). The telehealth remote monitoring tablet computer transmitted glucose data and facilitated a complete feedback loop to educate participants, analyze actionable glucose data, and provide feedback. Data from paired glucose testing were analyzed asynchronously using computer-assisted pattern analysis and were shared with patients via the EHR weekly. CDEs called participants monthly to discuss paired glucose testing trends and treatment changes. Separate mixed-effects models were used to analyze data.

Results: Participants (N=90) were primarily white (64%, 56/87), mean age 58 (SD 11) years, mean body mass index 34.1 (SD 6.7) kg/m2, with diabetes for mean 8.2 (SD 5.4) years, and a mean A(1c) of 8.3% (SD 1.1; 67 mmol/mol). Both groups lowered A(1c) with an estimated average decrease of 0.70 percentage points in usual care group and 1.11 percentage points in the treatment group with a significant difference of 0.41 percentage points at 6 months (SE 0.08, t159=-2.87, P=.005). Change in medication (SE 0.21, t157=-3.37, P=.009) was significantly associated with lower A(1c) level. The treatment group significantly improved on the SDSCA subscales carbohydrate spacing (P=.04), monitoring glucose (P=.001), and foot care (P=.02).

Conclusions: An eHealth model incorporating a complete feedback loop with telehealth remote monitoring and paired glucose testing with asynchronous data analysis significantly improved A(1c) levels compared to usual care.

Trial registration: Clinicaltrials.gov NCT01715649; https://www.clinicaltrials.gov/ct2/show/NCT01715649 (Archived by WebCite at http://www.webcitation.org/6ZinLl8D0).

Keywords: blood glucose self-monitoring; diabetes mellitus, type 2; eHealth; electronic health records; health records, personal; hemoglobin A1c, glycosylated; monitoring, physiologic; patient participation; remote consultation; self-care; telehealth.

Conflict of interest statement

Conflicts of Interest: DAG received research support from the Investigator Initiated Studies program of LifeScan Corporation and Intel-GE Care Innovations. No other conflicts are declared.

Figures

Figure 1
Figure 1
Complete feedback loop for improved outcomes in diabetes management.
Figure 2
Figure 2
CONSORT flowchart of enrollment and participant status.
Figure 3
Figure 3
Sample weekly paired glucose testing data analysis, by software designed for the study, and sample message text for feedback to participants through asynchronous secure messaging via the electronic health record.
Figure 4
Figure 4
Estimated A1C trajectories for the usual care and treatment groups from baseline to 6 months.

References

    1. Centers for Disease Control and Prevention . National Diabetes Statistics Report: Estimates of Diabetes and Its Burden in the United States, 2014. Atlanta, GA: US Department of Health and Human Services; 2014. [2015-07-03]. .
    1. American Diabetes Association Standards of medical care in diabetes-2015 abridged for primary care providers. Clin Diabetes. 2015 Apr;33(2):97–111. doi: 10.2337/diaclin.33.2.97.
    1. Khunti Kamlesh, Wolden Michael L, Thorsted Brian Larsen, Andersen Marc, Davies Melanie J. Clinical inertia in people with type 2 diabetes: a retrospective cohort study of more than 80,000 people. Diabetes Care. 2013 Nov;36(11):3411–7. doi: 10.2337/dc13-0331.
    1. Ziemer David C, Miller Christopher D, Rhee Mary K, Doyle Joyce P, Watkins Clyde, Cook Curtiss B, Gallina Daniel L, El-Kebbi Imad M, Barnes Catherine S, Dunbar Virginia G, Branch William T, Phillips Lawrence S. Clinical inertia contributes to poor diabetes control in a primary care setting. Diabetes Educ. 2005;31(4):564–71. doi: 10.1177/0145721705279050.
    1. Burke Sandra D, Sherr Dawn, Lipman Ruth D. Partnering with diabetes educators to improve patient outcomes. Diabetes Metab Syndr Obes. 2014;7:45–53. doi: 10.2147/DMSO.S40036.
    1. Polonsky William H, Fisher Lawrence, Schikman Charles H, Hinnen Deborah A, Parkin Christopher G, Jelsovsky Zhihong, Axel-Schweitzer Matthias, Petersen Bettina, Wagner Robin S. A structured self-monitoring of blood glucose approach in type 2 diabetes encourages more frequent, intensive, and effective physician interventions: results from the STeP study. Diabetes Technol Ther. 2011 Aug;13(8):797–802. doi: 10.1089/dia.2011.0073.
    1. Durán Alejandra, Martín Patricia, Runkle Isabelle, Pérez Natalia, Abad Rosario, Fernández Mercedes, Del Valle Laura, Sanz Maria Fuencisla, Calle-Pascual Alfonso Luis. Benefits of self-monitoring blood glucose in the management of new-onset Type 2 diabetes mellitus: the St Carlos Study, a prospective randomized clinic-based interventional study with parallel groups. J Diabetes. 2010 Sep;2(3):203–11. doi: 10.1111/j.1753-0407.2010.00081.x.
    1. Bonomo Katia, De Salve Alessandro, Fiora Elisa, Mularoni Elena, Massucco Paola, Poy Paolo, Pomero Alice, Cavalot Franco, Anfossi Giovanni, Trovati Mariella. Evaluation of a simple policy for pre- and post-prandial blood glucose self-monitoring in people with type 2 diabetes not on insulin. Diabetes Res Clin Pract. 2010 Feb;87(2):246–51. doi: 10.1016/j.diabres.2009.10.021.
    1. Funnell Martha M, Brown Tammy L, Childs Belinda P, Haas Linda B, Hosey Gwen M, Jensen Brian, Maryniuk Melinda, Peyrot Mark, Piette John D, Reader Diane, Siminerio Linda M, Weinger Katie, Weiss Michael A. National standards for diabetes self-management education. Diabetes Care. 2012 Jan;35 Suppl 1:S101–8. doi: 10.2337/dc12-s101.
    1. International Diabetes Federation. 2009. [2015-07-03]. Self-monitoring of blood glucose in non-insulin-treated type 2 diabetes .
    1. Stetson B, Schlundt D, Peyrot M, Ciechanowski P, Austin MM, Young-Hyman D, McKoy J, Hall M, Dorsey R, Fitzner K, Quintana M, Narva A, Urbanski P, Homko C, Sherr D. Monitoring in diabetes self-management: issues and recommendations for improvement. Popul Health Manag. 2011 Aug;14(4):189–97. doi: 10.1089/pop.2010.0030.
    1. Parkin Christopher G, Hinnen Deborah, Campbell R Keith, Geil Patricia, Tetrick David L, Polonsky William H. Effective use of paired testing in type 2 diabetes: practical applications in clinical practice. Diabetes Educ. 2009;35(6):915–27. doi: 10.1177/0145721709347601.
    1. Polonsky William H, Fisher Lawrence, Schikman Charles H, Hinnen Deborah A, Parkin Christopher G, Jelsovsky Zhihong, Petersen Bettina, Schweitzer Matthias, Wagner Robin S. Structured self-monitoring of blood glucose significantly reduces A1C levels in poorly controlled, noninsulin-treated type 2 diabetes: results from the Structured Testing Program study. Diabetes Care. 2011 Feb;34(2):262–7. doi: 10.2337/dc10-1732.
    1. Klonoff DC, Blonde L, Cembrowski G, Chacra AR, Charpentier G, Colagiuri S, Dailey G, Gabbay RA, Heinemann L, Kerr D, Nicolucci A, Polonsky W, Schnell O, Vigersky R, Yale J, Coalition for Clinical Research-Self-Monitoring of Blood Glucose Scientific Board Consensus report: the current role of self-monitoring of blood glucose in non-insulin-treated type 2 diabetes. J Diabetes Sci Technol. 2011 Nov;5(6):1529–48.
    1. Malanda UL, Welschen LM, Riphagen I, Dekker JM, Nijpels G, Bot SD. Self-monitoring of blood glucose in patients with type 2 diabetes mellitus who are not using insulin. Cochrane Database Syst Rev. 2012;1:CD005060. doi: 10.1002/14651858.CD005060.pub3.
    1. Franciosi M, Lucisano G, Pellegrini F, Cantarello A, Consoli A, Cucco L, Ghidelli R, Sartore G, Sciangula L, Nicolucci A. ROSES: role of self-monitoring of blood glucose and intensive education in patients with Type 2 diabetes not receiving insulin. A pilot randomized clinical trial. Diabet Med. 2011 Jul;28(7):789–96. doi: 10.1111/j.1464-5491.2011.03268.x.
    1. Bosi Emanuele, Scavini Marina, Ceriello Antonio, Cucinotta Domenico, Tiengo Antonio, Marino Raffaele, Bonizzoni Erminio, Giorgino Francesco. Intensive structured self-monitoring of blood glucose and glycemic control in noninsulin-treated type 2 diabetes: the PRISMA randomized trial. Diabetes Care. 2013 Oct;36(10):2887–94. doi: 10.2337/dc13-0092.
    1. Schnell Oliver, Alawi Hasan, Battelino Tadej, Ceriello Antonio, Diem Peter, Felton Anne, Grzeszczak Wladyslaw, Harno Kari, Kempler Peter, Satman Ilhan, Vergès Bruno. Addressing schemes of self-monitoring of blood glucose in type 2 diabetes: a European perspective and expert recommendation. Diabetes Technol Ther. 2011 Sep;13(9):959–65. doi: 10.1089/dia.2011.0028.
    1. Jimison Holly, Gorman Paul, Woods Susan, Nygren Peggy, Walker Miranda, Norris Susan, Hersh William. Barriers and drivers of health information technology use for the elderly, chronically ill, and underserved. Evid Rep Technol Assess (Full Rep) 2008 Nov;(175):1–1422.
    1. Ceriello Antonio, Barkai László, Christiansen Jens Sandahl, Czupryniak Leszek, Gomis Ramon, Harno Kari, Kulzer Bernhard, Ludvigsson Johnny, Némethyová Zuzana, Owens David, Schnell Oliver, Tankova Tsvetalina, Taskinen Marja-Riitta, Vergès Bruno, Weitgasser Raimund, Wens Johan. Diabetes as a case study of chronic disease management with a personalized approach: the role of a structured feedback loop. Diabetes Res Clin Pract. 2012 Oct;98(1):5–10. doi: 10.1016/j.diabres.2012.07.005.
    1. Boren Suzanne Austin, Puchbauer Aaron M, Williams Faustine. Computerized prompting and feedback of diabetes care: a review of the literature. J Diabetes Sci Technol. 2009 Jul;3(4):944–50.
    1. Greenwood DA, Young HM, Quinn CC. Telehealth remote monitoring systematic review: structured self-monitoring of blood glucose and impact on A1C. J Diabetes Sci Technol. 2014 Feb 21;8(2):378–389. doi: 10.1177/1932296813519311.
    1. Schnell Oliver, Alawi Hasan, Battelino Tadej, Ceriello Antonio, Diem Peter, Felton Anne-Marie, Grzeszczak Wladyslaw, Harno Kari, Kempler Peter, Satman Ilhan, Vergès Bruno. Self-monitoring of blood glucose in type 2 diabetes: recent studies. J Diabetes Sci Technol. 2013;7(2):478–88.
    1. Darkins Adam, Ryan Patricia, Kobb Rita, Foster Linda, Edmonson Ellen, Wakefield Bonnie, Lancaster Anne E. Care Coordination/Home Telehealth: the systematic implementation of health informatics, home telehealth, and disease management to support the care of veteran patients with chronic conditions. Telemed J E Health. 2008 Dec;14(10):1118–26. doi: 10.1089/tmj.2008.0021.
    1. Shea Steven, Weinstock Ruth S, Starren Justin, Teresi Jeanne, Palmas Walter, Field Lesley, Morin Philip, Goland Robin, Izquierdo Roberto E, Wolff L Thomas, Ashraf Mohammed, Hilliman Charlyn, Silver Stephanie, Meyer Suzanne, Holmes Douglas, Petkova Eva, Capps Linnea, Lantigua Rafael A. A randomized trial comparing telemedicine case management with usual care in older, ethnically diverse, medically underserved patients with diabetes mellitus. J Am Med Inform Assoc. 2006;13(1):40–51. doi: 10.1197/jamia.M1917.
    1. Fitzgerald J T, Funnell M M, Hess G E, Barr P A, Anderson R M, Hiss R G, Davis W K. The reliability and validity of a brief diabetes knowledge test. Diabetes Care. 1998 May;21(5):706–10.
    1. Toobert D J, Hampson S E, Glasgow R E. The summary of diabetes self-care activities measure: results from 7 studies and a revised scale. Diabetes Care. 2000 Jul;23(7):943–50.
    1. Anderson Robert M, Fitzgerald James T, Gruppen Larry D, Funnell Martha M, Oh Mary S. The Diabetes Empowerment Scale-Short Form (DES-SF) Diabetes Care. 2003 May;26(5):1641–2.
    1. Inzucchi Silvio E, Bergenstal Richard M, Buse John B, Diamant Michaela, Ferrannini Ele, Nauck Michael, Peters Anne L, Tsapas Apostolos, Wender Richard, Matthews David R. Management of hyperglycemia in type 2 diabetes, 2015: a patient-centered approach: update to a position statement of the American Diabetes Association and the European Association for the Study of Diabetes. Diabetes Care. 2015 Jan;38(1):140–9. doi: 10.2337/dc14-2441.
    1. Marcolino Milena Soriano, Maia Junia Xavier, Alkmim Maria Beatriz Moreira. Boersma Eric, Ribeiro Antonio Luiz. Telemedicine application in the care of diabetes patients: systematic review and meta-analysis. PLoS One. 2013 Nov;8(11):e79246. doi: 10.1371/journal.pone.0079246.
    1. Wakefield Bonnie J, Holman John E, Ray Annette, Scherubel Melody, Adams Margaret R, Hillis Stephen L, Rosenthal Gary E. Effectiveness of home telehealth in comorbid diabetes and hypertension: a randomized, controlled trial. Telemed J E Health. 2011 May;17(4):254–61. doi: 10.1089/tmj.2010.0176.
    1. Quinn Charlene C, Shardell Michelle D, Terrin Michael L, Barr Erik A, Ballew Shoshana H, Gruber-Baldini Ann L. Cluster-randomized trial of a mobile phone personalized behavioral intervention for blood glucose control. Diabetes Care. 2011 Sep;34(9):1934–42. doi: 10.2337/dc11-0366.
    1. Tang Paul C, Overhage J Marc, Chan Albert Solomon, Brown Nancy L, Aghighi Bahar, Entwistle Martin P, Hui Siu Lui, Hyde Shauna M, Klieman Linda H, Mitchell Charlotte J, Perkins Anthony J, Qureshi Lubna S, Waltimyer Tanya A, Winters Leigha J, Young Charles Y. Online disease management of diabetes: engaging and motivating patients online with enhanced resources-diabetes (EMPOWER-D), a randomized controlled trial. J Am Med Inform Assoc. 2013 May 1;20(3):526–34. doi: 10.1136/amiajnl-2012-001263.
    1. Stone Roslyn A, Rao R Harsha, Sevick Mary Ann, Cheng Chunrong, Hough Linda J, Macpherson David S, Franko Carol M, Anglin Rebecca A, Obrosky D Scott, Derubertis Frederick R. Active care management supported by home telemonitoring in veterans with type 2 diabetes: the DiaTel randomized controlled trial. Diabetes Care. 2010 Mar;33(3):478–84. doi: 10.2337/dc09-1012.
    1. Polonsky William H, Jelsovsky Zhihong, Panzera Susanne, Parkin Christopher G, Wagner Robin S. Primary care physicians identify and act upon glycemic abnormalities found in structured, episodic blood glucose monitoring data from non-insulin-treated type 2 diabetes. Diabetes Technol Ther. 2009 May;11(5):283–91. doi: 10.1089/dia.2008.0087.
    1. McMahon Graham T, Gomes Helen E, Hickson Hohne Sara, Hu Tang Ming-Jye, Levine Betty A, Conlin Paul R. Web-based care management in patients with poorly controlled diabetes. Diabetes Care. 2005 Jul;28(7):1624–9.
    1. Kempf Kerstin, Tankova Tsvetalina, Martin Stephan. ROSSO-in-praxi-international: long-term effects of self-monitoring of blood glucose on glucometabolic control in patients with type 2 diabetes mellitus not treated with insulin. Diabetes Technol Ther. 2013 Jan;15(1):89–96. doi: 10.1089/dia.2012.0213.
    1. Arnhold Madlen, Quade Mandy, Kirch Wilhelm. Mobile applications for diabetics: a systematic review and expert-based usability evaluation considering the special requirements of diabetes patients age 50 years or older. J Med Internet Res. 2014;16(4):e104. doi: 10.2196/jmir.2968.
    1. Shea Steven, Weinstock Ruth S, Teresi Jeanne A, Palmas Walter, Starren Justin, Cimino James J, Lai Albert M, Field Lesley, Morin Philip C, Goland Robin, Izquierdo Roberto E, Ebner Susana, Silver Stephanie, Petkova Eva, Kong Jian, Eimicke Joseph P, IDEATel Consortium. A randomized trial comparing telemedicine case management with usual care in older, ethnically diverse, medically underserved patients with diabetes mellitus: 5 year results of the IDEATel study. J Am Med Inform Assoc. 2009;16(4):446–56. doi: 10.1197/jamia.M3157.
    1. Carter Ernest L, Nunlee-Bland Gail, Callender Clive. A patient-centric, provider-assisted diabetes telehealth self-management intervention for urban minorities. Perspect Health Inf Manag. 2011;8:1b.
    1. Stone Roslyn A, Sevick Mary Ann, Rao R Harsha, Macpherson David S, Cheng Chunrong, Kim Sunghee, Hough Linda J, DeRubertis Frederick R. The Diabetes Telemonitoring Study Extension: an exploratory randomized comparison of alternative interventions to maintain glycemic control after withdrawal of diabetes home telemonitoring. J Am Med Inform Assoc. 2012;19(6):973–9. doi: 10.1136/amiajnl-2012-000815.
    1. Weitzman Elissa R, Kelemen Skyler, Quinn Maryanne, Eggleston Emma M, Mandl Kenneth D. Participatory surveillance of hypoglycemia and harms in an online social network. JAMA Intern Med. 2013 Mar 11;173(5):345–51. doi: 10.1001/jamainternmed.2013.2512.
    1. Gee PM, Greenwood DA, Paterniti DA, Ward D, Miller LM. The eHealth Enhanced Chronic Care Model: a theory derivation approach. J Med Internet Res. 2015 Apr;17(4):e86. doi: 10.2196/jmir.4067.
    1. Eysenbach Gunther, Consort- EHEALTHGroup. CONSORT-EHEALTH: improving and standardizing evaluation reports of Web-based and mobile health interventions. J Med Internet Res. 2011;13(4):e126. doi: 10.2196/jmir.1923.

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