Barrier Factors to the Completion of Diabetes Education in Korean Diabetic Adult Patients: Korea National Health and Nutrition Examination Surveys 2007-2012

Patient-perceived service needs and health care utilization in people with type 2 diabetes: A multicenter cross-sectional study

The aim of this study was to investigate service needs and health care utilization among people with type 2 diabetes, further to identify the relationship between service needs and health care utilization.We used a self-reported questionnaire to collect data regarding demographic and diabetes characteristics, service needs toward self-management and follow-up care, and 4 health care utilizations during past year. Multiple linear regression and binary logistic regression were used to test the impacts of demographic and diabetes characteristics on service needs and health care utilizations, respectively. Spearman rank correlations were used to explore correlation between service needs and health care utilization.We recruited 1796 participants with type 2 diabetes from 20 community health centers across 12 cities of Sichuan Province in China. Needs of self-management and follow-up had significant positive correlations with health care utilization. Participants rated that nutrition was the most needed aspects of self-management (78.5%), and out-patient visit was the most popular type of follow-up (66.8%). Educational level and treatment modality were predictors of self-management needs. Low educational level (elementary school or blow, β = 0.11, P = .008; middle school, β = 0.10, P = .015) and insulin treatment (β = 0.08, P = .007) were positive factors of self-management needs. Younger age (age < 45 years old, β = 0.07, P = .046), being employed (β = 0.14, P < .001), and underdeveloped region (β = 0.16, P < .001) were positive factors of follow-up care needs. Elementary educational level (OR: 0.53; CI: 0.30-0.96) and underdevelopment region (OR: 0.01; CI: 0.01-0.07) were protective factors of general practitioner visit, in contrast, those factors were risk factors of specialist visit (elementary educational level, OR: 1.69; CI: 1.13-2.5; underdevelopment region, OR: 2.93; CI: 2.06-4.16) and emergency room visit (elementary educational level, OR: 2.97; CI: 1.09, 8.08; underdevelopment region, OR: 6.83; CI: 2.37-14.65).The significant positive relationship between service needs and health care utilization demonstrated the role of service needs in influencing health care utilization. When self-management education is provided, age, educational level, employment status, treatment modality, and region should be considered to offer more appropriate education and to improve health care utilization.

Sociodemographic Factors Associated with Participation in Diabetes Education among Community-Dwelling Adults with Diabetes

PURPOSE

This study investigated the sociodemographic factors associated with participation in diabetes self-management education (DSME) among community-dwelling adults with diabetes.

MATERIALS AND METHODS

Data from 23400 people aged ≥30 years who were diagnosed with diabetes from the nationwide 2016 Korea Community Health Survey were analyzed. The relationship between sociodemographic factors and participation in DSME was examined by logistic regression analysis. The study sample was classified according to the type of institution providing DSME: hospitals/medical clinics (HMCs) and/or public health institutions (PHIs).

RESULTS

Of the total sample population with diabetes, 27.2% had attended DSME programs, including 21.9% at HMCs, 4.0% at PHIs, and 1.3% at both types of institutions. As age increased and educational level and monthly household income decreased, the odds ratios (ORs) of participation in DSME decreased in a fully adjusted model. Respondents living in rural areas had lower ORs for attending DSME compared to those living in urban areas [OR, 0.85; 95% confidence interval (CI), 0.80-0.91]. Service/sales workers and mechanical/manual workers had lower ORs for attending DSME (OR, 0.84; 95% CI, 0.71-0.99; and OR, 0.81; 95% CI, 0.69-0.94, respectively) compared to professional/managerial workers. However, in the subgroup of participants receiving education at PHIs, the likelihood of participation in DSME increased as age increased, and respondents living in rural areas had higher ORs compared to those living in urban areas (OR, 1.73; 95% CI, 1.51-1.98).

CONCLUSION

Customized DSME programs targeting socioeconomically vulnerable groups, including residential region and reimbursement of DSME by public insurance, are needed to resolve the inequalities in participation in DSME.