Cluster-randomized trial of a mobile phone personalized behavioral intervention for blood glucose control

Charlene C Quinn, Michelle D Shardell, Michael L Terrin, Erik A Barr, Shoshana H Ballew, Ann L Gruber-Baldini, Charlene C Quinn, Michelle D Shardell, Michael L Terrin, Erik A Barr, Shoshana H Ballew, Ann L Gruber-Baldini

Abstract

Objective: To test whether adding mobile application coaching and patient/provider web portals to community primary care compared with standard diabetes management would reduce glycated hemoglobin levels in patients with type 2 diabetes.

Research design and methods: A cluster-randomized clinical trial, the Mobile Diabetes Intervention Study, randomly assigned 26 primary care practices to one of three stepped treatment groups or a control group (usual care). A total of 163 patients were enrolled and included in analysis. The primary outcome was change in glycated hemoglobin levels over a 1-year treatment period. Secondary outcomes were changes in patient-reported diabetes symptoms, diabetes distress, depression, and other clinical (blood pressure) and laboratory (lipid) values. Maximal treatment was a mobile- and web-based self-management patient coaching system and provider decision support. Patients received automated, real-time educational and behavioral messaging in response to individually analyzed blood glucose values, diabetes medications, and lifestyle behaviors communicated by mobile phone. Providers received quarterly reports summarizing patient's glycemic control, diabetes medication management, lifestyle behaviors, and evidence-based treatment options.

Results: The mean declines in glycated hemoglobin were 1.9% in the maximal treatment group and 0.7% in the usual care group, a difference of 1.2% (P = 0.001) [corrected] over 12 months. Appreciable differences were not observed between groups for patient-reported diabetes distress, depression, diabetes symptoms, or blood pressure and lipid levels (all P > 0.05).

Conclusions: The combination of behavioral mobile coaching with blood glucose data, lifestyle behaviors, and patient self-management data individually analyzed and presented with evidence-based guidelines to providers substantially reduced glycated hemoglobin levels over 1 year.

Figures

Figure 1
Figure 1
Flowchart of enrollment and patient status (n = 163).
Figure 2
Figure 2
Primary study outcome and baseline A1C stratified analyses.

References

    1. Huang ES, Basu A, O’Grady M, Capretta JC. Projecting the future diabetes population size and related costs for the U.S. Diabetes Care 2009;32:2225–2229
    1. Cowie CC, Rust KF, Ford ES, et al. . Full accounting of diabetes and pre-diabetes in the U.S. population in 1988-1994 and 2005-2006. Diabetes Care 2009;32:287–294
    1. Gaede PH, Jepsen PV, Larsen JN, Jensen GV, Parving HH, Pedersen OB. The Steno-2 study. Intensive multifactorial intervention reduces the occurrence of cardiovascular disease in patients with type 2 diabetes. Ugeskr Laeger 2003;165:2658–2661
    1. Solomon CG. Reducing cardiovascular risk in type 2 diabetes. N Engl J Med 2003;348:457–459
    1. Knowler WC, Barrett-Connor E, Fowler SE, et al. . Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med 2002;346:393–403
    1. Cleland JG, Ekman I. Enlisting the help of the largest health care workforce: patients. JAMA 2010;304:1383–1384
    1. American Diabetes Association. Standards of medical care in diabetes: 2008. Diabetes Care 2008;31(Suppl. 1):S12–S54
    1. American Diabetes Association. Standards of medical care in diabetes: 2009. Diabetes Care 2009;32(Suppl. 1):S13–S61
    1. Saaddine JB, Cadwell B, Gregg EW, et al. . Improvements in diabetes processes of care and intermediate outcomes: United States, 1988–2002. Ann Intern Med 2006;144:465–474
    1. Peyrot M, Rubin RR, Lauritzen T, Snoek FJ, Matthews DR, Skovlund SE. Psychosocial problems and barriers to improved diabetes management: results of the Cross-National Diabetes Attitudes, Wishes and Needs (DAWN) Study. Diabet Med 2005;22:1379–1385
    1. Renders CM, Valk GD, Griffin S, Wagner EH, Eijk JT, Assendelft WJ. Interventions to improve the management of diabetes mellitus in primary care, outpatient and community settings. Cochrane Database Syst Rev 2001:CD001481.
    1. Griffin S, Kinmonth AL. Diabetes care: the effectiveness of systems for routine surveillance for people with diabetes. Cochrane Database Syst Rev 2000:CD000541.
    1. Quinn CC, Gruber-Baldini AL, Shardell M, et al. . Mobile diabetes intervention study: testing a personalized treatment/behavioral communication intervention for blood glucose control. Contemp Clin Trials 2009;30:334–346
    1. Quinn CC, Clough SS, Minor JM, Lender D, Okafor MC, Gruber-Baldini A. WellDoc mobile diabetes management randomized controlled trial: change in clinical and behavioral outcomes and patient and physician satisfaction. Diabetes Technol Ther 2008;10:160–168
    1. Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med 2001;16:606–613
    1. Whitty P, Steen N, Eccles M, et al. . A new self-completion outcome measure for diabetes: is it responsive to change? Qual Life Res 1997;6:407–413
    1. McColl E, Steen IN, Meadows KA, et al. . Developing outcome measures for ambulatory care: an application to asthma and diabetes. Soc Sci Med 1995;41:1339–1348
    1. Polonsky WH, Fisher L, Earles J, et al. . Assessing psychosocial distress in diabetes: development of the diabetes distress scale. Diabetes Care 2005;28:626–631
    1. Fisher L, Glasgow RE, Mullan JT, Skaff MM, Polonsky WH. Development of a brief diabetes distress screening instrument. Ann Fam Med 2008;6:246–252
    1. Shea S, Weinstock RS, Starren J, et al. . 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;13:40–51
    1. Hayes RJ, Bennett S. Simple sample size calculation for cluster-randomized trials. Int J Epidemiol 1999;28:319–326
    1. Robins J, Rotnitzky A, Zhao L. Analysis of semiparametric regression models for repeated outcomes under the presence of missing data. J Am Stat Assoc 1995;90:106–121
    1. Gerstein HC, Miller ME, Byington RP, et al. . Effects of intensive glucose lowering in type 2 diabetes. N Engl J Med 2008;358:2545–2559
    1. Duke SA, Colagiuri S, Colagiuri R. Individual patient education for people with type 2 diabetes mellitus. Cochrane Database Syst Rev 2009:CD005268.
    1. Verbeke G, Lesaffre E. Repeated Measurements. Wiley: New York, 2007

Source: PubMed

3
購読する