ISSN : 2093-5986(Print)
ISSN : 2288-0666(Online)
The Korean Society of Health Service Management
Vol.15 No.3 pp.143-155

지역사회 제2형 당뇨병 환자 대상 IT-기반 자가관리서비스의 효과

김 수정1, 한 진아2, 이 순영2, 김 영택3
1동서대학교 보건행정학과
2아주대학교 예방의학교실
3충남대학교병원 공공보건의료사업실

The Impact of IT-based Self-management Service for Type 2 Diabetes Mellitus Patients in a Community

Soojeong Kim1, Jin A Han2, Soon Young Lee2, Young Taek Kim3
1Department of Health Administration, Division of Health Science, Dongseo University
2Department of Preventive Medicine and Public Health, Ajou University of Medicine
3Public Health Medical Service Office, Chungnam National University Hospital



This study evaluates wireless IT-based self-management services for type 2 diabetes mellitus (T2DM) patients.


Patients diagnosed with diabetes mellitus (DM) and undergoing treatment at a local healthcare institution, and those who participated in community hypertension and diabetes registration and management services and capable of using the internet or a smartphone were enrolled in the study. About 320 patients who had completed a questionnaire and provided anthropometric data and baseline blood tests at the end of the 12-month study period were assessed.


In the IT group, a significant improvement was observed in fasting blood sugar (FBS) awareness and self-monitoring blood glucose (SMBG) levels at both baseline and end of the 12-month period. Knowledge scores improved in the human support and IT service groups, and FBS and hemoglobin A1c (HbA1c) decreased significantly in all the groups. In the change in the HbA1c control rate at baseline and 12 months in the three groups, the difference in the IT service group was 13.8% (p=0.0035).


Adding IT-based services to the existing management services for DM patients may help in controlling FBS and HbA1c levels by enhancing blood glucose measurement and management.

    Ⅰ. Introduction

    The prevalence of diabetes mellitus (DM) in Korean adults aged 30 years or older is consistently increasing, from 12.5% in men and 10.4% in women in 2005 to 15.8% in men and 13.0% in women in 2016[1] This poses a socioeconomic and healthcare burden, with 2.704 million patients receiving care at an annual healthcare costs of 20.434 trillion KRW in 2016[2]. A relatively simple test can detect DM, and it can be effectively prevented through continuous drug therapy and management of risk factors through lifestyle adjustment[3]. However, as of 2016, blood glucose was controlled only in 32.9% DM patients, with 26.8% receiving treatment[1], indicating limitations in DM management with the existing treatment-centered disease management services.

    Self-management focused on prevention, such as self-blood glucose measurement and practice of healthy behaviors are important factors gaining traction in DM management. Thus, services that support self-management of chronic diseases must be administered within communities in association with relevant organizations. Moreover, DM is among the prioritized disease management projects for both the government and communities, as it contributes substantially toward lowering medical costs in the long term by reducing complications and mortality[4-6]. Globally, disease management is actively intervened through patient education and counseling in communities or primary care institutions, and the outcomes have been extensively documented in the literature[7-14]. In Korea, some communities have implemented a community-based prevention and management service through hypertension and diabetes registration and education centers, and they are expanding the features and scale of the program[5,6]. However, well-designed community-based studies that examined the impact of chronic disease management education and counseling programs are lacking.

    Easy access and popularization of the internet has recently drawn attention to IT-based blood glucose management and self-management services, and their outcomes have also been verified [7,8,15,16]. Thus, this study has assessed the impact of a community- and IT-based self-management service to help T2DM patients, who need information on DM management and adopting a healthy lifestyle effectively, aimed at continuously maintaining their target blood glucose efficiently.

    Ⅱ. Methods

    1. Study design

    In this community-based health intervention study, 25 healthcare institutions in “A” city participating in the hypertension and diabetes registration and management project were selected. The participating healthcare institutions provided a patient list to the research team, and all the lists were combined and the patients were randomized into control, human support, and IT service groups. We avoided intervening contamination by excluding the possibility of meeting each other during the process of recruiting subjects. After signing an informed consent form, the patients participated in a human support(counseling) and IT service intervention for a 12-month period, and blood tests were performed to examine changes in their fasting blood sugar(FBS) and HbA1c levels. The control group was not given an additional intervention, while the human support group received individual counseling services. The IT service group was given only an IT service. Educated and trained investigators and nurses provided all the surveys and counseling, respectively.

    2. Interventions

    1) Information technology services

    The objective of information technology (IT) services is to improve patients' self-blood glucose management by helping them to self-measure and self-monitor their blood glucose levels. Patients were given a blood glucose self-monitoring device and wireless gateway that recommends patients to measure blood glucose once a day before breakfast and send the blood glucose measurement to the patient's cell phone immediately after measurement as a reminder. If the blood glucose level was 300 mg/dL (milligrams per deciliter) or higher or 60 mg/dL or lower, a warning message was sent. Patients could monitor their blood glucose levels online or by using a cell phone application, and they could access information on the web. Patients' doctors checked and used self-blood glucose measurements of patients under their care. The gateway, a wireless communication device, was supported by H company. The blood glucose meter was provided free of charge by Company C, and K telecom company developed a homepage and supported it for free and also supported communication costs.

    2) Human support

    The individual counseling service aimed to motivate patients for self-blood glucose management. A trained nurse provided phone counseling once every three months, during which the nurse informed patients about the importance of the HbA1c test and regular blood glucose management and complication tests, and encouraged adherence to medication, exercise, and a healthy diet. Further, a newsletter containing useful information about DM, including disease management, exercise, and diet, was distributed once every three months. Human support was a public service involving the personnel of the 'A city' Human Center for Hypertension and Diabetes Education, which is linked to a public health center responsible for monitoring local primary healthcare.

    3. Study participants

    The study participants were patients aged between 3064 years and diagnosed with T2DM. They were receiving treatment at a local healthcare institution and were enrolled to participate in a hypertension and diabetes registration and management service. Additional inclusion criteria comprised patients capable of using the internet or smartphone on their own or with assistance from their family, and those capable of taking a survey, anthropometry, and blood tests at baseline and at the end of the study. Individuals with serious complications related to diabetes, liver disease, or renal disease, pregnant women or those planning a pregnancy within one year, individuals with mental disorders, cognitive impairment, cancer, intractable disease, drug abusers, and individuals on steroids were excluded from the study. The target sample size was computed according to the equation shown below, with the difference in HbA1c among the three independent groups set to 0.5%. The conditions for sample size calculation were set to =0.05, power 80%, HbA1c difference of 0.5% detection, and SD=1.5. Per group, the figures for number of patients was computed at 98, and considering potential withdrawals, the target sample size was 420, with 140 for each group.

    N = ( Z α + Z β ) × 2 × σ 2 d 2

    Totally, 422 patients were enrolled through 24 participating healthcare institutions for three months from May 2012 to September 2012. Of them, 320 who completed the survey and blood tests at baseline and at the end of the study were included in the final analysis.

    4. Data collection

    A baseline survey and follow-up survey were performed. On the day patients visited the hospital, an interviewer administered a 1:1 interview survey using a computer-assisted personal interviewing (CAPI) system on On the same day, the healthcare institution recorded patients' blood pressure, and took anthropometric measurements including height, weight, waist circumference, and entered the results on the website. For the blood test, nurses at the respective institution, collected patients' blood samples and sent them to the designated clinical laboratories, and these laboratories sent the results back to the respective healthcare institutions. Once the participating healthcare institutions sent these results to the hypertension and diabetes registration and education center in A city, the researcher checked them and entered them on the website. Blood glucose measurements taken by the patients at home were noted in their blood glucose meter and were automatically recorded and accumulated on the web service database (DB) using a wireless gateway through a 3G wireless network.

    5. Questionnaire items and study variables

    The questionnaire items included general characteristics (gender, age, education, occupation, history of chronic diseases, duration of DM diagnosis, diabetes complications), health behaviors (smoking, drinking, exercise, and healthy diet), awareness (fasting blood sugar, HbA1c), characteristics of DM management (SMBG), adherence to medication, and eye and kidney tests for screening diabetes complications during the past year, and knowledge of DM and self-efficacy.

    The patients were divided based on age into < 50 years, 5054 years, 5559 years, and ≥ 60 years by quartile. For educational level, the total number of years of education was divided into ≤ 9 years, 1012 years, ≥ 13 years, and occupation was classified as employed, housewife, and unemployed. Patients with chronic diseases were defined as having one or more of the following diseases: hypertension, hyperlipidemia, myocardial infarction, stroke, and angina. Diabetes complications included diabetic retinopathy, diabetic nephropathy, diabetic neuropathy, stroke, coronary artery disease, and peripheral artery disease. Patients who had performed self-monitoring of blood glucose over the prior two weeks were included in the study.

    Medication adherence was defined as taking the medication prescribed by physicians for seven or more days in the prior week and continuing to take them even when their blood glucose levels were controlled or when they believed that the prescribed drugs were not helpful. Screening for DM complications was defined as undergoing screening for eye and kidney problems to check whether any diabetes-related complication had affected eyes and kidneys during the past one year.

    Smoking, drinking, and exercise rates were defined as having smoked, drunk alcohol, and exercised in the past week, and a healthy diet rate was defined as having followed a healthy diet in the past week. For knowledge on DM, a score ranging from 1 to 5 was used to award one point for a correct answer and 0 points for a wrong answer for the following items: Normal fasting blood glucose level is below 100 mg/dl; visual impairment can result if blood glucose levels continue to rise, “blood glucose increases if a DM patient gets a cold or is overly anxious, ” “It is better for a DM patient to have frequent snacks instead of having three meals,”

    “You must consume sugar immediately if you get cold sweat, heart rate increases, have a sense of hunger, fatigue, hand tremor, or headache after taking diabetes drugs or getting an insulin shot.” Self-efficacy was assessed using three items (“I am confident about what to do when my blood glucose drops below or goes above my target level,” “I can eat a diabetic diet even when preparing or eating food with non-diabetic people,” “I can exercise at least three times a week for more than 30 minutes per session”), where each item is rated on a scale ranging from 1 to 10 (higher score indicates agreement), for a maximum score of 30.

    Positive change was defined as cases in which individuals who had undesirable behaviors at the baseline shifted to desirable behaviors at 12 months and when scores for knowledge and self-efficacy were higher than those at the baseline. Blood glucose was considered controlled when the HbA1c level was <6.5% in patients aged < 65 years and <8.0% in those aged > 65 years [17].

    6. Analysis

    This study has assessed the impact of a community IT-based self-management service intervention for T2DM patients, and the primary parameter for assessment was the HbA1c control rate based on an HbA1c cutoff with age group. Personal information (e.g., name, resident registration number) was converted into participants' identifiers (IDs). The IT service and human support groups were compared for changes in health behaviors, DM management, and HbA1c levels after 12 months of community-based clinical trials from the baseline according to the use of self-management services through counseling using the chi-square test, McNemar's test, paired t-test, and a one-way ANOVA. All the tests were performed using the SAS software (version 9.2; SAS Institute, Cary, NC, USA).

    Ⅲ. Results

    1. Baseline characteristics of participants by group

    Table 1 shows the characteristics of the 320 participants in the baseline survey. Most of the participants were men (n=177, 55.3%). The highest percentage of participants were aged 60 years and above (35.6%), with a mean age of 55.6 years. Regarding educational attainment, 39.3% had 12 years of education, followed by 9 years or less (34.0%), and 13 years or more (26.7%). While 61.8% participants were employed, 30.0% were housewives, and 8.2% were unemployed. The incidence of chronic disease morbidity was 60.6%. The mean duration of DM was 6.5 years, and the diabetes complication rate was 6.3%. There were no significant statistical differences in the general characteristics among the groups, including sex, age, education, and occupation. There were statistically significant differences in the duration of DM diagnosis (p=0.0451) between the human support group and the IT service group due to the post-hoc test (p=0.0445).

    <Table 1>

    Participant characteristics by group at the baseline


    2. Changes of categorical variables at baseline and 12 months in all three groups

    Table 2 shows the differences in health behaviors and DM-related characteristics between baseline and 12 months in all three groups. After analyzing health behavioral changes and DM-related variables at baseline and 12 months in all three groups, smoking rate, exercise rate, and healthy diet rate remained unchanged in these groups. In the human support group, there were significant improvements in drinking rate (46.6% at baseline 36.4% at 12 months), FBS awareness (69.7% at baseline 82.0% at 12 months), and screening for diabetes complications (46.1% at baseline 67.4% at 12 months). In the IT service group, there was a significant improvement in FBS awareness (70.2% at baseline 97.0% at 12 months) and the rate of SMBG (48.9% at baseline, 87.8% at 12 months). Medication adherence was lower in the control and human support groups, but there was improvement in the IT service group.

    <Table 2>

    Changes of categorical variables at baseline and 12 months in all three groups


    3. Changes of continuous variables at baseline and 12 months in all three groups

    Table 3 shows the differences in knowledge, self-efficacy, body mass index (BMI), FBS, and HbA1c between baseline and 12 months in all three groups. Knowledge scores improved in the human support and IT service groups, and FBS and HbA1c decreased significantly in all three groups. Indeed, in the human support group and IT service group, there were significant improvements in knowledge score (3.8±1.1 at baseline and 4.1±1.1at 12 months in human support group; 3.8±1.1 at baseline and 4.2±1.1at 12 months in IT service group), self-efficacy (20.2±5.7 at baseline and 21.4±6.2 at 12 months in the human support group; 19.6±6.4 at baseline and 20.8±7.0 at 12 months in the IT service group); however, there were no significant changes observed in the control group.

    <Table 3>

    Changes in continuous variables at baseline and 12 months in all three groups


    4. HbA1c control rate by group

    Figure 1 shows HbA1c control rates at baseline and at 12 months in each group. In the control group, HbA1c control rate increased by 6% during the 12-month period, whereas in the human support group, the control rate increased by 11.2% over 12 months. The IT service group had the highest increase in HbA1c control rate during the same periods. The difference in the IT service group was 13.8% (37.4% at baseline, 51.2% at 12 months), which was statistically significant (p=0.0035).

    <Figure 1>

    HbA1c control rate at baseline and 12 months by group


    Ⅳ. Discussion

    This study has assessed the impact of an IT-based self-management service intervention in communities with T2DM patients to help these patients maintain and manage their target blood glucose levels efficiently and continuously. To this end, for the first time in Korea, an IT-based SMBG registration and management service was provided to DM patients in communities. The IT-based SMBG registration and management service provides T2DM patients latest information and practices related to self-management of DM, including blood glucose management, to maintain and manage their target blood glucose levels efficiently and continuously based on a close collaboration between primary care institutions and local hypertension and diabetes registration and management centers in communities with DM patients[18]. Through this IT-based service, our aim is that patients must receive clinical treatment regularly by sending them alerts about their treatment schedules and missed appointments, ensure physicians support patients to improve disease treatment and management rates, and educate and motivate DM patients to undertake self-management by developing and applying an evidence-based, validated educational program that helps patients to perform SMBG and practice healthy behaviors, and provide counseling.

    Globally, active research efforts are being made to examine the impact of community-based or primary care institution-based self-management support serviceseducation and counselingfor managing DM and monitoring blood glucose levels [7-17]. Korea's hypertension and diabetes registration and education center was founded in Daegu Metropolitan City in 2007 by benchmarking the chronic care model (CCM)[19] and the WHO's new project on Innovative Care for Chronic Conditions [20] to establish a disease management system based on primary care in local communities in collaboration with private health institutions. Further, some si and gun began to implement a community-based comprehensive prevention and management service based on registration for hypertension and diabetes and educational centers since 2012[5,6]; however, the outcome of such efforts have not yet been appropriately assessed. In an era of wide access to the internet, interest is growing in research on IT-based blood glucose management or self-management services, and the impact of such services on self-management have been validated[7,8,15]. In 2011, a study in Korea assessed the impact of an IT-based self-blood glucose management and registration service in a community over a one-year period [16]. However, the study could not compare the impact of the IT-based self-management service with that of a control as it had used a one-group pretest-posttest design without a control group. Therefore, the significance of this study is that it was a randomized controlled trial (RCT)[21,22] that assessed the impact of an IT-based chronic disease management service in communities that had been developed using the CCM.

    This study has attempted to assess the impact of an IT-based self-management service for T2DM patients in communities. For the first time in Korea, we established an IT-based system for automatic online monitoring of patients' SMBG data using a wireless gateway and 3G wireless network. First, the outcome of the IT service intervention was evaluated by assessing the impact of an IT-based self-management service intervention provided for one year on blood glucose awareness, DM management, health behaviors, DM knowledge, and self-efficacy in T2DM patients and comparing the effect size between the control and intervention groups. A community-based IT service intervention with an education program about disease, nutrition, exercise, as well as motivational counseling was effective in blood glucose regulation and DM management. During the course of the study, patients over 55 years of age experienced digital literacy problems, such as difficulty in monitoring their own blood sugar levels on the homepage, replacing the gateway, and changing the battery; however, this was immediately resolved by the technical support team of H company and K Telecom company.

    For DM patients, it is highly crucial that they are aware of their blood glucose levels through regular and frequent monitoring. It is well established that awareness of blood glucose levels and periodic and frequent monitoring are effective in controlling DM[23]. In this study, the SMBG rate of the IT service group in the prior two weeks had increased significantly from 48.9% at baseline to 87.8% at the end of the 12-monthperiod. Thus far, the impact of self-management support services have been reported by comparing HbA1c levels, which is a key parameter representing blood glucose regulation. Many studies have reported that blood glucose regulation was significantly enhanced in the intervention group based on the result that the intervention group had a greater reduction in HbA1c levels from the baseline level compared to that in the control group[7,911, 24, 25]. However, other studies reported that interventions did not have significant outcomes[12,13]. In a 30-month long-term follow-up study, HbA1c changes were measured in the control and intervention groups at baseline, 15 months, and 30 months. The control group showed changes of 7.5±1.3, 7.4±1.3, and 7.4±1.3, whereas the intervention group showed changes of 7.7±1.5, 6.9±1.1, and 6.7±0.9. It was also reported that HbA1c was maintained at a more stable level for 30 months in the intervention group (p=0.022)[24]. In this relatively short follow-up study, the change in HbA1c at baseline and 12 months decreased from 7.8±1.6 to 7.4±1.3 in the control group and decreased from 7.8±1.6 to 7.3±1.4 in the IT service group. It is necessary to verify the effectiveness of IT services through long-term follow-up. In this study, we also compared the continuous control rates and control rates among the study groups based on HbA1c levels at baseline and at 12 months. An increase in the rate of accommodation was observed at 12 months compared to the baseline across all groups. In the IT service group, the HbA1c control rate increased significantly by 13.8%, which is statistically significant. These results may provide additional evidence to support previous studies. This study is meaningful in that it validates a service model that can monitor and manage blood glucose levels in diabetic patients in a community setting.

    Ⅴ. Conclusion

    This study proposes an effective and efficient prevention and management measure for patients with high cardiovascular risk scores. Adding IT-based services to the existing management services for DM patients in communities may help in controlling FBS and HbA1c by encouraging self-management, such as blood glucose measurement. Communities must develop an appropriate system that combines human support and IT services to improve self-management abilities in DM patients. Indeed, this study presents evidence for structured counseling and education protocols for patients, and administrative and financial support to strengthen collaboration between the community members, patients, and physicians.


    HbA1c control rate at baseline and 12 months by group


    Participant characteristics by group at the baseline
    Changes of categorical variables at baseline and 12 months in all three groups
    Changes in continuous variables at baseline and 12 months in all three groups


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