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Older adults using cellular telephones for diabetes management: a pilot study.

For many patients with diabetes mellitus, the traditional office visit, characterized by brief face-to-face encounters, is both inadequate and ineffective for long-term diabetes management. The increased time constraints experienced by busy practices limit the ability of health care providers to assess patients' needs and communicate effectively. Furthermore, short visits separated by long intervals do not provide sufficient opportunity for health care providers to motivate individuals and give the feedback necessary to influence behavior. Travel to a health care provider's office also places a substantial burden on many patients with chronic disease. This is especially true for older adult patients with diabetes, many of whom have co-morbid illnesses and disabilities. Although home visits by nurses and doctors can overcome the burden of patient travel, home visits are still relatively costly in resources and time. For these reasons clinicians are looking for technologic solutions that can meaningfully extend contact with patients, empower them to sustain self-care regimens, and thereby improve diabetes care outcomes. Telemedicine and other communication technologies offer a partial solution to some of these challenges. Communication technologies that permit easier contact between the patient and health care team can be used to reinforce diabetes knowledge, prompt self-care behavior, monitor disease, and improve health care access.

Research suggests that education without followup prompting does not result in improved medication adherence (Fulmer et al., 1999). Likewise, diabetes education without post-educational followup does not result in improved self-care behavior in patients newly diagnosed with diabetes (Tu, McDaniel, & Gay, 1993). Consistent with these findings, regular nurse-initiated telephone contact results in better glycemic control than a control group receiving usual diabetes care (Weinberger et al., 1995). When combined with automated calling systems, nurse-initiated followup calls can increase glucose self-monitoring and foot inspections, and reduce symptoms of poor glycemic control (Piette, Weinberger, Kraemer, & McPhee, 2001). In this same study (Piette et al., 2001), patients with glycosylated hemoglobin greater than 8% who received automated and nurse-initiated calls had a significant reduction of the glycosylated hemoglobin values compared to the control group. Furthermore, patients receiving automated and nurse-initiated calls over a 12-month period experienced greater ability to conduct self-care than a control group receiving usual diabetes care (Piette, Weinberger, & McPhee, 2000). Therefore, efforts to develop telephonic prompting systems that improve patient self-care and glycemic control appear promising. For this reason, the authors undertook a pilot study to test the Personal Diabetes Management System (PDMS), which incorporated a Web-based interface into the automated telephone call system. This is a new system developed by Adherence Technologies (Burke, VA).

The goals in this pilot were to evaluate:

1. Older patients' ability to use the PDMS, including the use of a cellular phone to receive the phone calls.

2. The impact of the PDMS on diabetes health behaviors, knowledge, glycosylated hemoglobin, and body mass index (BMI).

3. The effect of the PDMS on provider and patient communication.

At times predetermined by patients and provider, the PDMS prompts patients with interactive recorded human voice messages. These messages include performing self-care activities (for example, check feet, check blood glucose, take medication), calling the provider for medical advice, providing health education, and recording personal health data. These messages can be customized to meet changing individual patient needs. Patients can record data such as glucose levels by entering the values on the telephone keypad. The data are transmitted to the secure Web site and can be reviewed by the health care provider at his/her discretion (see Figure 1 for an example of a typical dialogue).


Study design. Charts from the authors' practice were reviewed to identify patients with Type 2 diabetes over 60 years of age who were independent in self-care and able to use a telephone. Ten patients agreed to participate and were enrolled in the pilot study using a pretest, post-test design. The study was approved by the Johns Hopkins Bayview Institutional Review Board. The participants used the PDMS with Motorola cellular phones and/or home touch-tone phones for 12 weeks. Each participant had an initial interview with the nurse practitioner, who explained the study, obtained consent, set mutual goals for glycemic control, and provided individualized diabetes education. The initial visit included about 1.5 hours face-to-face with the patient and one-half hour of nursing time to program the system for each patient. Participants were also given the American Diabetes Association (ADA) book Diabetes A to Z (ADA, 1997). The nurse practitioner and physician reviewed each patient's medical record for current medications, glucose trends, diabetes complications, and health maintenance before customizing the PDMS messages. Participants completed a diabetes knowledge test and a questionnaire regarding diabetes health behaviors. A glycosylated hemoglobin level and any other laboratory tests pertinent to the patient's routine care were drawn. Weight and height were measured to calculate body mass index (BMI). The nurse practitioner taught each participant how to use the cellular phone to receive messages and record glucose values and weight.

One week after the initial interviews, the nurse practitioner called the participants to determine if they experienced any problems with the PDMS. It took approximately 1 hour per day to review the data and phone patients with feedback and changes regarding their diabetes management. The PDMS was also programmed to prompt the participants to call the nurse practitioner when the patients experienced diabetic symptoms, medication side effects, or any problems with the care plan.

The nurse practitioner reviewed the data daily over the 12-week study. At the exit interview with the nurse practitioner, the participants repeated the earlier questionnaires. They also completed an additional questionnaire regarding PDMS usability and answered five open-ended questions. Glycosylated hemoglobin, weight, and height were again measured.

Instruments and data analysis. The instrument to measure diabetes knowledge was the 14-item General Diabetes Knowledge Test developed by the Michigan Diabetes Research and Training Center (Davis, Hess, & Harrison, 1987). Topics on this multiple-choice test include diet, glucose monitoring, foot care, and symptoms of diabetes complications. The test is reliable with a Cronbach's coefficient alpha > 0.70 for various settings and populations (Fitzgerald et al., 1998). Validity was determined by studying two different groups. For both samples, patients with prior diabetes education or more years of formal education scored higher on the test as would be expected (Fitzgerald et al., 1998).

The Diabetes Health Behavior Questions were developed by the authors to elicit information regarding participation in physical activity, glucose monitoring, medication adherence, foot care, and hypoglycemic and hyperglycemic symptoms. These behaviors were chosen based on ADA Standards of Care (ADA, 2000) for diabetes management.

The first seven items of the PDMS Study Usability Questionnaire were designed to assess participant satisfaction with the system (see Table 1). The last three items were designed to assess the impact of the system on diabetes management and communication with the health care providers. Items were rated on a Likert scale of 1 to 5, with 5 being the best. The data were analyzed using SPSS 10.0 to calculate frequencies and descriptive statistics.


Demographics. Seven participants completed the study; three did not complete the study due to acute illness and hospitalization. Two participants lived alone in a continuing care retirement community (CCRC), one lived with her son, and four lived with spouses. One of the couples resided in a CCRC as well. The mean age of the seven participants was 78.43 (SD=9.91) years. There were three men and four women. Six participants had some college or higher level of education. Four participants took nine or more medications daily. Three participants were managed with insulin, while the others were treated with oral diabetic agents. Only one of the seven participants used a cellular telephone routinely prior to the pilot study. For the study, three participants used the cellular phone, two used their home phones, and two reported using both.

Usability of the PDMS. Results of the post-PDMS Study Usability Questions are displayed in Table 1. Convenience and ease of use of the home phone was rated 4.17 (SD=1.60) and 4.33 (SD=1.63) respectively, while convenience and ease of use of the cellular phone was rated 3.71 (1.70) and 2.57 (1.40) respectively. Participants' comments regarding cell phone use included lack of familiarity with this type of phone, difficulty manipulating the buttons, and faint signal reception in some locations.

Diabetes health behaviors. Frequencies of diabetes health behaviors are presented in Table 2. Before the intervention, three of the seven participants never engaged in at least 20 minutes of sustained physical activity on a daily basis. After the intervention all participants reported engaging in sustained physical activity at least 1 to 2 times a week, and three reported daily participation in sustained activity.

Diabetes knowledge test scores, glycosylated hemoglobin, body mass index. Diabetes knowledge test scores, glycosylated hemoglobin, and BMI are found in Table 3. Three of the seven participants had increased diabetes knowledge test scores, four had decreased glycosylated hemoglobin, and four had decreased BMI.

Summary of Participants' Comments

* All participants reported general satisfaction with the system. They believed it would be especially useful for older patients, those living alone, and those with memory problems or problems taking their medications and managing their diabetes.

* All participants reported an increased awareness of the impact of diet, activity, and medication on glucose and diabetes management.

* Despite scheduling the calls at mutually agreed upon times, the calls were occasionally received at inconvenient times. The participants appreciated the feature of the PDMS that accommodates for such situations.

* Some participants suggested shorter messages and less-frequent calls. These participants found the educational messages and timely individualized provider recommendations based on glucose values to be more useful than prompts and medication reminders.

* Some participants would have liked an interactive conversation with the voice on the phone.


In this pilot study, the PDMS was tested with seven older patients with diabetes in order to learn more about the human-device interaction and determine its feasibility for prompting behavior and improving health-related outcomes. These participants generally reported satisfaction with the system, and valued the prompts and educational messages to reinforce their self-care behaviors and diabetes knowledge. The system gave these older adults added confidence to continue to manage their diabetes. In one case, detailed medication adjustments were made during the study to improve the patient's glycemic control. In another case, a patient who had resisted recording glucose levels on paper entered them into the PDMS on a regular basis.

The PDMS is flexible. Frequency and types of messages can be adjusted by the nurse to accommodate individual patient needs. Frequent reminders may be helpful for newly diagnosed patients or those with uncontrolled diabetes. Experienced patients such as these participants may find periodic messages to assess symptoms and reinforce self-care behaviors via the patient's home phone to be a feasible method to supplement office diabetes management.

The PDMS prompted patients to contact their providers for questions, and participants reported that this was satisfying. Participants also appreciated the positive feedback from the automated script when glucose or weights were within their set goals. Personal telephone calls from the nurse practitioner, based on the PDMS data, with individualized advice to adjust medications, diet, or activity in response to recorded blood glucose levels were helpful. Some patients wanted to have an interactive conversation with the voice. In fact, some systems under development will be able to provide such an automated voice response message system (Friedman, Stollerman, Mahoney, & Rozenblyum, 1997; Letzt & Durso, 2001) in the future.

The participants reported varied prior experience with cellular phones. This posed little problem for the study participants because the PDMS could be used with either the home phone or the provided cellular phone. Some participants had intermittent problems with phone reception, especially in their homes. Manipulating the small keys and hearing the messages did not preclude the use of the cellular phone for these older adults, although this factor appeared to result in entry of some incorrect values for glucose readings and weights. The mobility of the cellular phone added little value for this group of patients.

These participants followed prescriptions for foot care, medication administration, and glucose monitoring prior to the study; however, three participants reported not engaging in physical activity before the study. The improvement in daily physical activity reported by this small group after the intervention is of interest. A telecommunications intervention that prompts and reinforces this aspect of diabetes management may prove to be valuable if this behavior can be sustained. The brevity of this study, small number of patients, self-reported data, and lack of a control group limit the conclusions that can be drawn about the contribution of the PDMS to improved self-care behaviors, diabetes knowledge, glycosylated hemoglobin, and BMI. However, the reported and observed trends were very positive and warrant further study of such methods that reinforce self-care behaviors, including physical activity in patients with diabetes.


Web-based telecommunications systems coordinated by nurses promise to provide an important link to enhance patient and provider communication and improve diabetes self-care behaviors and management. The reported ease of use of the PDMS on the home telephone and trends in improved glycemic control, increased exercise, and improved diabetes knowledge are encouraging. Further studies are needed with larger patient populations over longer periods of time to assess the ideal frequency and duration of prompts and the impact on long-term outcomes such as diabetes-related complications, hospitalizations, and cost of care.
Table 1.
PDMS Study Usability Questions (n=7)
(1-5 scale, with 5 the best)

                                                  Mean (SD)

Convenience of cellular phone                     3.71 (1.7)
Convenience of home phone                         4.17 (1.60)
Quality of voice on phone                         4.71 (0.76)
Your ability to understand messages               4.71 (0.76)
Ease of cell phone use                            2.57 (1.40)
Ease of home phone use                            4.33 (1.63)
Ease of recording glucose, weight, and exercise   3.86 (1.46)
Value in management of diabetes                   4.28 (0.95)
Aid to communication with health provider         4.28 (1.50)

Table 2.
Diabetes Health Behaviors Before and After PDMS (n=7)


                Frequency            % (n)

Activity          Never              42.9% (3)
                1-2 x week           14.3% (1)
                3-4 x week           14.3% (1)
                5-6 x week           28.6% (2)
                 Everyday               0

Monitor           Never              28.6% (2)
glucose         4-6 x week           14.3% (1)
                 Once/day            28.6% (2)
                More than once/day   28.6% (1)

Miss              Never                85% (6)
medications     1-2 x month             0
                1-3 x week           14.3% (7)

Check feet        Daily               100% (7)

Symptoms of       Never              42.9% (3)
hypoglycemia    1-2 x month          57.1% (4)
                1-3 x week              0

Symptoms of       Never              57.1% (4)
hyperglycemia   1-2 x month          14.3% (1)
                1-3 x week              0
                 Everyday            28.6% (2)


                Frequency            % (n)

Activity          Never                 0
                1-2 x week           14.3% (1)
                3-4 x week           28.6% (2)
                5-6 x week           14.3% (1)
                 Everyday            42.9% (3)

Monitor           Never              14.3% (1)
glucose         4-6 x week           14.3% (1)
                 Once/day            28.6% (1)
                More than once/day   42.9% (3)

Miss              Never                85% (6)
medications     1-2 x month          14.3% (1)
                1-3 x week              0

Check feet        Daily               100% (7)

Symptoms of       Never              14.3% (1)
hypoglycemia    1-2 x month          71.4% (2)
                1-3 x week           14.3% (1)

Symptoms of       Never              42.9% (3)
hyperglycemia   1-2 x month          28.6% (2)
                1-3 x week           14.3% (1)
                 Everyday            14.3% (1)

Table 3.
Diabetes Knowledge Test Scores, Glycosylated Hemoglobin,
Body Mass Index (n=7)

           Knowledge        Glycosylated
Subject   Test Score (%)   Hemoglobin (%)   Body Mass Index

          Before   After   Before   After   Before   After

1001        86      86      8.6      7.3      30      32
1002        79     100      7.4      7.0      24      23
1004        57      86      6.7      6.8      33      33
1005        71      71      6.0      6.1      29      28
1007        79     100      8.6      7.6      29      27
1008        79      71      7.8      8.0      28      29
1011        64      57      8.3      5.9      35      33

Figure 1. Sample Dialogue with PDMS

* Hi, this is Johns Hopkins at White Marsh. If you checked your blood sugar, press 1. If not, press 2

* [If yes] Please enter your blood sugar value then press the pound sign.

* The blood sugar value you entered was {number entered}. If this is correct press 1; if not, press 2

* [If correct and in range] Your blood sugar level is within the desired range. Good job!

* [If correct and out of range] Your blood sugar level is {too high/too low}. Please follow your medical instructions for getting it back in the desired range.

Acknowledgment: This study was supported by the Johns Hopkins University Fund for Geriatric Medicine and Nursing. The authors also thank the participants for their time.


American Diabetes Association. (1997). Diabetes A to Z. Alexandria, VA: Author.

American Diabetes Association. (2000). Clinical practice recommendations 2000 standards of medical care for patients with diabetes mellitus. Diabetes Care, 23, S1-S24.

Davis, W.K., Hess, G.E., & Harrison, R.V. (1987). Psychosocial adjustment to and control of diabetes mellitus: Differences by disease type and treatment. Health Psychology, 61(1), 1-14.

Fitzgerald, J.T., Funnell, MM, Hess, G.E., Barr, P.A., Anderson, R.M., Hiss, R.G., et al. (1998). The reliability and validity of brief diabetes knowledge test. Diabetes Care, 21(5), 706-710.

Friedman, R.H., Stollerman, J.E., Mahoney, D.M., & Rozenblyum, L. (1997). The virtual visit: Using telecommunications technology to take care of patients. Journal of the American Medical Informatics Association, 4(6), 413-425.

Fulmer, T.T., Feldman, P.H., Kim, T.S., Carty, B., Beers, M., Molina, M., et al. (1999). An intervention study to enhance medication compliance in community-dwelling elderly individuals. Journal of Gerontological Nursing, 25(8), 6-14.

Letzt, A.M., & Durso, S.C. (2001). Private communications concerning research at Adherence Technologies Corp. on interactive speech recognition systems for diabetes management.

Piette, J.D., Weinberger, M., Kraemer, F.B., & McPhee, S.J. (2001). 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, 24, 202-208.

Piette, J.D., Weinberger, M., & McPhee, S.J. (2000). The effect of automated calls with telephone nurse follow-up on patient-centered outcomes of diabetes care: A randomized, controlled trial. Medical Care, 38(2), 218-230.

Tu, S., McDaniel, G., & Gay, J.T. (1993). Diabetes self-care knowledge, behaviors, metabolic control of older adults--the effect of a posteducational follow-up program. The Diabetes Educator, 19(1), 25-30.

Weinberger, M., Kirkman, MS., Samsa, G.P., Shortliffe, E.A., Landsman, P.B., Cowper, P.A., et al. (1995). A nurse-coordinated intervention for primary care patients with non-insulin-dependent diabetes mellitus: impact on glycemic control and health-related quality of life. Journal of General Internal Medicine, 10, 59-66.

Samuel C. Durso, MD, is an Assistant Professor of Medicine, Johns Hopkins University School of Medicine, Division of Geriatric Medicine and Gerontology, Baltimore, MD.

Inez Wendel, MS, CRNP, is a Geriatric Nurse Practitioner and Clinical Instructor, Johns Hopkins University School of Nursing, Baltimore, MD.

Alan M. Letzt, MS, PE, is President and CEO of Adherence Technologies Corporation, Burke, VA.

Jacob Lefkowitz, BS, is Chief Technology Officer, Adherence Technologies Corporation, Burke, VA.

Dianne F. Kaseman, PhD, RN, is Vice President, Adherence Technologies Corporation, Burke, VA.

Rita Furst Seifert, PhD, is Director of Clinical Research, Adherence Technologies Corporation, Burke, VA.
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Title Annotation:Research for Practice
Author:Durso, Samuel C.; Wendel, Inez; Letzt, Alan M.; Lefkowitz, Jacob; Kaseman, Dianne F.; Seifert, Rita
Publication:MedSurg Nursing
Date:Oct 1, 2003
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