Effectiveness of technology-assisted case management in low income adults with type 2 diabetes (TACM-DM): study protocol for a randomized controlled trial

Leonard E Egede, Joni L Strom, Jyotika Fernandes, Rebecca G Knapp, Adebola Rojugbokan, Leonard E Egede, Joni L Strom, Jyotika Fernandes, Rebecca G Knapp, Adebola Rojugbokan

Abstract

Background: An estimated 1 in 3 American adults will have diabetes by the year 2050. Nationally, South Carolina ranks 10th in cases of diagnosed diabetes compared to other states. In adults, type 2 diabetes (T2DM) accounts for approximately 90-95% of all diagnosed cases of diabetes. Clinically, provider and health system factors account for < 10% of the variance in major diabetes outcomes including hemoglobin A1c (HbA1c), lipid control, and resource use. Use of telemonitoring systems offer new opportunities to support patients with T2DM while waiting to be seen by their health care providers at actual office visits. A variety of interventions testing the efficacy of telemedicine interventions have been conducted, but the outcomes have yielded equivocal results, emphasizing the shortage of controlled, randomized trials in this area. This study provides a unique opportunity to address this gap in the literature by optimizing two strategies that have been shown to improve glycemic control, while simultaneously implementing clinical outcomes measures, using a sufficient sample size, and offering health care delivery to rural, underserved and low income communities with T2DM who are seen at Federally Qualified Health Centers (FQHCs) in coastal South Carolina.

Methods: We describe a four-year prospective, randomized clinical trial, which will test the effectiveness of technology-assisted case management in low income rural adults with T2DM. Two-hundred (200) male and female participants, 18 years of age or older and with an HbA1c ≥ 8%, will be randomized into one of two groups: (1) an intervention arm employing the innovative FORA system coupled with nurse case management or (2) a usual care group. Participants will be followed for 6-months to ascertain the effect of the interventions on glycemic control. Our primary hypothesis is that among indigent, rural adult patients with T2DM treated in FQHC's, participants randomized to the technology-assisted case management intervention will have significantly greater reduction in HbA1c at 6 months of follow-up compared to usual care.

Discussion: Results from this study will provide important insight into the effectiveness of technology-assisted case management intervention (TACM) for optimizing diabetes care in indigent, rural adult patients with T2DM treated in FQHC's.

Trial registration: National Institutes of Health Clinical Trials Registry (http://ClinicalTrials.gov identifier# NCT01373489.

Figures

Figure 1
Figure 1
The FORA Telehealth System.
Figure 2
Figure 2
The FOR A 2-in-1 Blood Glucose and Blood Pressure Machine (FORA D15g).
Figure 3
Figure 3
Operation Instructions for the FORA Telephone/Ethernet Gateway.
Figure 4
Figure 4
Description of Study Design and Study Flow.

References

    1. Centers for Disease Control and Prevention. Press Release: older, more diverse population and longer lifespans contribute to increase. Atlanta, GA: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention; 2010. Accessible from: .
    1. Centers for Disease Control and Prevention. National diabetes fact sheet: general information and national estimates on diabetes in the United States, 2007. Atlanta, GA: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention; 2008.
    1. SC DHEC; South Carolina Diabetes Prevention and Control Program and Diabetes Initiative of South Carolina; Medical University of South Carolina; Diabetes Center. Burden of diabetes in South Carolina, 2009 Edition [Report] Columbia, SC: Department of Health and Environmental Control; 2009. Accessible from: .
    1. National Institute of Diabetes and Digestive and Kidney Diseases. National Diabetes Statistics fact sheet: general information and national estimates on diabetes in the United States, 2005. Bethesda, MD: U.S. Department of Health and Human Services, National Institutes of Health; 2008.
    1. Montani S, Bellazzi R, Quaglini S, D'Annunzio Z. Meta analysis of the effect of the use of the computer based systems on the metabolic control of diabetes mellitus patients. Diabetes Technology Ther. 2001;3:347–356. doi: 10.1089/15209150152607123.
    1. Farmer A, Gibson O, Hayton P, Bryden K, Dudley C, Neil A, Tarassenko L. A real-time, mobile phone-based telemedicine system to support young adults with type 1 diabetes. Inform Prim Care. 2005;13(3):171–7.
    1. Costa BM, Fitzgerald KJ, Jones KM, Dunning Am T. Effectiveness of IT-based diabetes management interventions: a review of the literature. BMC Fam Pract. 2009;10:72. doi: 10.1186/1471-2296-10-72. Review.
    1. Bellazzi R, Arcelloni M, Bensa G, Blankenfeld H, Brugués E, Carson E, Cobelli C, Cramp D, D'Annunzio G, De Cata P, De Leiva A, Deutsch T, Fratino P, Gazzaruso C, Garcìa A, Gergely T, Gómez E, Harvey F, Ferrari P, Hernando E, Boulos MK, Larizza C, Ludekke H, Maran A, Nucci G, Pennati C, Ramat S, Roudsari A, Rigla M, Stefanelli M. Design, methods, and evaluation directions of a multi-access service for the management of diabetes mellitus patients. Diabetes Technol Ther. 2003;5(4):621–9. doi: 10.1089/152091503322250640.
    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. Diabetes Technol Ther. 2008;10(3):160–8. doi: 10.1089/dia.2008.0283.
    1. Cherry JC, Moffatt TP, Rodriguez C, Dryden K. Diabetes disease management program for an indigent population empowered by telemedicine technology. Diabetes Technol Ther. 2002;4(6):783–91. doi: 10.1089/152091502321118801.
    1. Farmer A, Gibson OJ, Tarassenko L, Neil A. A systematic review of telemedicine Interventions to support blood glucose self-monitoring in diabetes. Diabet Med. 2005;22(10):1372–8. doi: 10.1111/j.1464-5491.2005.01627.x. PMID: 16176199.
    1. McMahon GT, Gomes HE, Hickson Hohne S, Hu TM, Levine BA, Conlin PR. Web-based care management in patients with poorly controlled diabetes. Diabetes Care. 2005;28(7):1624–9. doi: 10.2337/diacare.28.7.1624.
    1. Stone RA, Rao RH, Sevick MA, Cheng C, Hough LJ, Macpherson DS, Franko CM, Anglin RA, Obrosky DS, Derubertis FR. Active care management supported by home telemonitoring in veterans with type 2 diabetes: the DiaTel randomized controlled trial. Diabetes Care. 2010;33(3):478–84. doi: 10.2337/dc09-1012. Epub 2009 Dec 15.
    1. Garg SK, Bookout TR, McFann KK, Kelly WC, Beatson C, Ellis SL, Gutin RS, Gottlieb PA. Improved glycemic control in intensively treated adult subjects with type 1 diabetes using insulin guidance software. Diabetes Technol Ther. 2008;10(5):369–75. doi: 10.1089/dia.2007.0303.
    1. Earle KA, Istepanian RS, Zitouni K, Sungoor A, Tang B. Mobile telemonitoring for achieving tighter targets of blood pressure control in patients with complicated diabetes: a pilot study. Diabetes Technol Ther. 2010;12(7):575–9. doi: 10.1089/dia.2009.0090.
    1. Shea S, Weinstock RS, Teresi JA, Palmas W, Starren J, Cimino JJ, Lai AM, Field L, Morin PC, Goland R, Izquierdo RE, Ebner S, Silver S, Petkova E, Kong J, Eimicke JP. 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. Epub Apr 23. PMID: 19390093.
    1. Sutherland D, Hayter M. Structured review: evaluating the effectiveness of nurse case managersin improving health outcomes in three major chronic diseases. J Clin Nurs. 2009;18(21):2978–92. doi: 10.1111/j.1365-2702.2009.02900.x. Epub 2009 Sep 11. Review. PMID: 19747197.
    1. Aubert RE, Herman WH, Waters J, Moore W, Sutton D, Peterson BL, Bailey CM, Koplan JP. Nurse case management to improve glycemic control in diabetic patients in a health maintenance organization. A randomized, controlled trial. Ann Intern Med. 1998;129(8):605–12. PMID: 9786807.
    1. Piette JD, Weinberger M, Kraemer FB, McPhee SJ. Impact of automated calls with nurse follow-up on diabetes treatment outcomes in a Department of Veterans Affairs Health Care System: a randomized controlled trial. Diabetes Care. 2001;24(2):202–8. doi: 10.2337/diacare.24.2.202. PMID: 11213866.
    1. Stuckey HL, Dellasega C, Graber NJ, Mauger DT, Lendel I, Gabbay RA. Diabetes nurse case management and motivational interviewing for change (DYNAMIC): study design and baseline characteristics in the Chronic Care Model for type 2 diabetes. Contemp Clin Trials. 2009;30(4):366–74. doi: 10.1016/j.cct.2009.03.002. Epub 2009 Mar.
    1. Welch G, Garb J, Zagarins S, Lendel I, Gabbay RA. Nurse diabetes case management interventions and blood glucose control: results of a meta-analysis. Diabetes Res Clin Pract. 2010;88(1):1–6. doi: 10.1016/j.diabres.2009.12.026. Epub 2010 Feb 8. PMID: 20116879.
    1. Curtis J, Lipke S, Effland S, Dickinson B, McCabe A, Russell B, Russell M, Bloomquist P, Wilson C. Effectiveness and safety of medication adjustments by nurse case managers to control hyperglycemia. Diabetes Educ. 2009;35(5):851–6. doi: 10.1177/0145721709343677. Epub 2009 Aug 27. PMID: 19713556.
    1. Gabbay RA, Lendel I, Saleem TM, Shaeffer G, Adelman AM, Mauger DT, Collins M, Polomano RC. Nurse case management improves blood pressure, emotional distress and diabetes complication screening. Diabetes Res Clin Pract. 2006;71(1):28–35. doi: 10.1016/j.diabres.2005.05.002. Epub 2005 Jul 12. PMID: 16019102.
    1. Gary TL, Batts-Turner M, Yeh HC, Hill-Briggs F, Bone LR, Wang NY, Levine DM, Powe NR, Saudek CD, Hill MN, McGuire M, Brancati FL. The effects of a nurse case manager and a community health worker team on diabetic control, emergency department visits, and hospitalizations among urban African Americans with type 2 diabetes mellitus: a randomized controlled trial. Arch Intern Med. 2009;169(19):1788–94. doi: 10.1001/archinternmed.2009.338. PubMed PMID: 19858437.
    1. FORA 2-in-1 BP + BG meter: FORA D15g TeleHealth System and Gateway: FORA GW9014A. FORA Care, Inc. Newbury Park, California; 2008. Accessible from: .
    1. Altman DG, Schulz KF, Moher D. et al.The revised CONSORT statement for reporting randomized trials: explanation and elaboration. Ann Intern Med. 2001;134(8):663–694.
    1. Hedeker D, Gibbons RD. Longitudinal Data Analysis. New York: Wiley; 2006.
    1. Baron RM, Kenny DA. The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol. 1986;51(6):1173–1182.
    1. Holmbeck GN. Toward terminological, conceptual, and statistical clarity in the study of mediators and moderators: examples from the child-clinical and pediatric psychology literatures. Journal of Consulting and Clinical Psychology. 1997;65(4):599–610.
    1. MacKinnon DP, Fairchild AJ, Fritz MS. Mediation analysis. Annu Rev Psychol. 2007;58:593. doi: 10.1146/annurev.psych.58.110405.085542.
    1. Ware JE, Kosinski M, Keller SD. A 12-Item Short-Form Health Survey: Construction of scales and preliminary tests of reliability and validity. Medical Care. 1996;34:220–233. doi: 10.1097/00005650-199603000-00003.
    1. Garcia AA, Villagomez ET, Brown SA, Kouzekanani K, Hanis CL. The Starr County Diabetes Education Study: development of the Spanish-language diabetes knowledge questionnaire. Diabetes Care. 2001;24(1):16–21. doi: 10.2337/diacare.24.1.16.
    1. Egede LE, Ellis C. Development and psychometric properties of the 12-item diabetes fatalism scale. J Gen Intern Med. 2010;25(1):61–6. doi: 10.1007/s11606-009-1168-5. Epub 2009 Nov 12. PMID: 19908102.
    1. Wallston KA, Rothman RL, Cherrington A. Psychometric properties of the Perceived Diabetes Self-Management Scale (PDSMS) J Behav Med. pp. 395–401. Epub 2007 May 24. PMID: 17522972.
    1. Toobert DJ, Hampson SE, Glasgow RE. The summary of diabetes self-care activities measure: results from 7 studies and a revised scale. Diabetes Care. 2000;23(7):943–950. doi: 10.2337/diacare.23.7.943.
    1. Krousel-Wood M, Islam T, Webber LS, Re RN, Morisky DE, Muntner P. New Medication Adherence Scale Versus Primary Fill Rates in Seniors with Hypertension. Am J Manag Care. 2009;12(1):59–66.
    1. National Center for Health Statistics (2004) Survey Questionnaire, National Health Interview Survey. National Center for Health Statistics, Hyattsville, Maryland; 2002. . Accessed February 2, 2007.
    1. Sherbourne CD, Stewart AL. The MOS Social Support Survey. Social Science and Medicine. 1991;32:705–14. doi: 10.1016/0277-9536(91)90150-B.
    1. Baker DW, Williams MV, Parker RM, Gazmararian JA, Nurss J. Development of a brief test to measure functional health literacy. Patient Educ Couns. 1999;38(1):33–42. doi: 10.1016/S0738-3991(98)00116-5.
    1. Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001;6:606–613.
    1. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40:373–383. doi: 10.1016/0021-9681(87)90171-8.
    1. Borkovec TC, Nau SD. Credibility of analogue therapy rationales. J Behav Ther Exp Psychiat. 1972;3:257–60. doi: 10.1016/0005-7916(72)90045-6.

Source: PubMed

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