Telemedicine application in diabetes blood glucose monitoring: A systematic review
Ming Ying Lisa Chu-Weininger, PhD, Ed S, MBA, MPH, MSLIS, FRIPH; Adol Esquivel, MD, MS; Lasonya Knowles, BBA; Kim Dunn, MD, PhD
Background
Diabetes associated health risks: heart disease, blindness, kidney failure, extremity amputations, & other chronic conditions Estimated diabetes healthcare cost US$91.8 billion in 2002 North American (ADA 2003) Goal: normalizing blood glucose level, adjust medication, & regulate related biological signs. More frequent blood glucose monitoring beneficial to type 1 or type 2 diabetes patients in metabolic control Studies inconsistence in telemedicine effectiveness in improving HbA1c/ other aspects of diabetes mgt. This study reviewed diabetes teleinterventions: blood glucose monitoring, metabolic control, & feedback to patients
Methods
Systematic search of English publications indexed by MeSH terms, publication type, or text word in the NLM‟s PubMed database for the years 1995 to 2006
Search terms: “telemedicine” AND “diabetes”
A total of 105 documents retrieved Document inclusion criteria: Tele-interventions for blood glucose monitoring, medication change advices, feedback to patients, and diabetes selfmanagement. Duplicated records (20), education only, fundus imaging & tele-retinopathy studies were excluded A total of 21 articles were reviewed
Modes of Intervention
Category Examples of Intervention Applications
Internet-based Monitoring
Interactive program incorporating measures within 3 different domains: physical, behavioral and psychosocial. Automated data transfer
Phone, web-phone, applications of Trans-theoretical stages of change model, and Negotiated Telephone Support for behavior change Home unit glucose data entry device, blood glucose data meter and modem for glucose data transmission
Telephone-based Monitoring
Software Assisted Reporting
Internet Based Reporting
Data of glucose levels is electronically transmitted (some automated) to the health care provider via the Internet Wireless network, email, video-mail messages, web & phone Efficient & accurate data reporting & transfer Provider assessment of data & feedback, or education Innovative & cost-effective including elderly diabetics (Bond 2006)
Telephone Reporting
Nurse initiated, or voice-interactive 24-hour access
Results: HbA1c reduction ≥ .085 to .078 in 6 months, & .095 to .082 in 3 months (Thompson et al. 1999, Whitlock et al. 2000) 3-fold reduction (204 patients) in occurrence of diabetes related crises (hypo- or hyper- glycaemia) (Albisser 1996) Glycated hemoglobin fell 1.0-1.3% (active youth in system) compared to no improvements (inactive controls) (Adkins et al.
2006)
Trans-theoretical stages of change model (TTM) effective in proactive phone-based step-treatment (Gambling & Long 2006)
“Negotiated Telephone Support”: principles of problem solving & social learning theory significant improvement in self-efficacy & barriers to insulin use adherence
(Howells et al. 2002)
Software Assisted Reporting
Inconsistent glucometer & modem reliability in data transmission.
Blood glucose measured 4.9 time daily average with telephone feedback reduced mean blood glucose (167 to 158 mg/dL, p < .01), SD (81 to 70 mg/dL, p < .001), & hypoglycemia frequency (5.2 to 3.3 in 4 weeks, p = 0.01)(Liesenfeld 2000) Glucometer application among type I diabetic pregnant women: much similar and better glycaemic controls among interventions (3-yr randomized clinical trial, Whitlock 2002) Dietary & blood glucose monitoring with immediate educational feedback: effective in 12 weeks. Majority of the 20 patients found it easy to operate (95%) and useful (63%)
(Tsang et al. 2001)
Sample Results
Author (yr) Findings
Farmer 2005 Bond 2006 DeLeo 2002 Gambling „06 13 papers meta analysis – significantly improved HbA1c levels 62 older adults – 9 months cost effective nursing informatics Web-phone – data retrieval, basic life support, direct non-prof‟l Web-phone – Trans theoretical stages of change
Howells 2002 Adkins 2006 Montori 2004
Negotiated Telephone Support Age 7-18, 3 times/wk tailored (3 months) .09 -> .079, .10 -> .079 >50 mins., 6 months (7.8% vs 8.2%), inc. dosage change
Carroll 2007 DIRECNET 2007
Integrates glucose monitor to cell phone battery pack Glucometer calibration & relative accuracy: median difference -16 to -20 when greater than 180mg/dl
Conclusion
Telemedicine appeared to be effective for HbA1c levels monitoring among youth and adults Data transmissions: Internet, modem, phone, web & phone, or software assisted all effective at different levels Most programs involved daily blood glucose data selfreporting and immediate feedback by a provider for medication dosage change, and dietary counseling Regular (1-3 time weekly) diabetes nurse educator phone advice significantly improved HbA1c reading Nutritional pattern data tracked adherence of diet plans Educational component involving change theories, problem solving, or social learning theories was helpful
Discussions
• Immediate feedback with an educational component: an effective “formulae” • A couple of negative result or nonresponsive studies: poor program design such as requiring patient traveling, print out and fax of data • Human factor: utilization of the home unit and modem for data transfer, size & ease • Engaging patients fast analysis • Youth: psychosocial • Calibration glucometer
Policy Implication
Telemedicine program effective in diabetes monitoring & reducing diabetes related crisis Intervention program design more essential than technology in program success Change theories may enhance program success Telemedicine has the potential for larger scale community based tele-diabetes intervention Collaboration may involve organizations with interoperable personal health record systems Large scale intervention has the potential of efficiency of scale
Study Limitation
A number of studies were clinical trials Most of the studies reviewed enrolled sample sizes < 50 patients Not necessarily affect study reliability Nevertheless, irregular sample size & varied study designs did not permit comparison of intervention effectiveness that were context specific
References
Adkins JW, Storch EA, Lewin AB, Wiliams L, Silverstein JH, Malasanos T, Gefflen GR. Homebased behavioral health intervention: use of a telehealth model to address poor adherence to type-1 diabetes medical regimens. Journal of Telemedicine and eHealth 2006; 23(3):370-372. Albisser AM, Harris RI, Sakkal S, Parson ID, Chao SC. Diabetes intervention in the information age. Medical Informatics (London) 1996; 21(4):297-316. American Diabetes Association. Economic Costs of Diabetes in the U.S. in 2002. Diabetes Care 2003; 26:917-932. Bond, G. Lessons learned from the implementation of a Web-based nursing intervention. Computer Informatics in Nursing 2006; 24(2):66–74. Howells L, Wilson AC, Skinner TC, Newton R, Morris AD, Greene SA. A randomized control trial of the effect of negotiated telephone support on glycaemic control in young people with type 1 diabetes. Diabetic Medicine 2002; 19(8):643-648. Liesenfeld B, Renner R, Neese M, Hepp KD. Telemedical care reduces hypoglycemias and improves glycemic control in children and adolescents with type 1 diabetes. Technology and Therapeutics 2000; 2(4):561-567. Thompson DM, Kozak SE, Shep S. Insulin adjustment by a diabetes nurse educator improves glucose control in insulin-requiring diabetic patients: a randomized trial. Canadian Medical Association Journal 1999;161(8)959-962. Tsang MW, Mok M, Kam G, Jung M, Tang A, Chan U, Chu CM, Li I, Chan J. Improvement in diabetes control with a monitoring system based on a hand-held, touch-screen electronic diary: Journal of Telemedicine and Telecare 2001; 7:47–50. Whitlock WL, Brown A, Moore K, Pavliscsak H, Dingbaum A, Lacefield D, Buker K, Xenakis S. Telemedicine improved diabetic management. Military Medicine 2000; 165(8):579-584. Wojcicki JM, Ladyzynski P, Krzymien J, Jozwicka E, Blachowicz J, Janczewska E, Czajkowski K, Kanafel W. What we can really expect from telemedicine in intensive diabetes treatment: results from 3-year study on type 1 pregnant diabetic women. Diabetes Technology and Therapeutics 2001; 3(4):581-589. Image from www.fda.gov/diabetes Image from http://www.diabetespilot.com/index.php