Open AccessUniversal coverage but unmet need: National and regional estimates of attrition across the diabetes care continuum in Thailand
Author(s) -
Lily Yan,
Piya Hanvoravongchai,
Wichai Aekplakorn,
Suwat Chariyalertsak,
Pattapong Kessomboon,
Sawitri Assanangkornchai,
Surasak Taneepanichskul,
Nareemarn Neelapaichit,
Andrew Stokes
Publication year - 2020
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0226286
Subject(s) - medicine , diabetes mellitus , logistic regression , attrition , national health and nutrition examination survey , health care , young adult , demography , national health interview survey , cross sectional study , gerontology , environmental health , family medicine , population , endocrinology , dentistry , sociology , economic growth , economics , pathology
Background Diabetes is a growing challenge in Thailand. Data to assess health system response to diabetes is scarce. We assessed what factors influence diabetes care cascade retention, under universal health coverage. Methods We conducted a cross-sectional analysis of the 2014 Thai National Health Examination Survey. Diabetes was defined as fasting plasma glucose ≥126mg/dL or on treatment. National and regional care cascades were constructed across screening, diagnosis, treatment, and control. Unmet need was defined as the total loss across cascade levels. Logistic regression was used to examine the demographic and healthcare factors associated with cascade attrition. Findings We included 15,663 individuals. Among Thai adults aged 20+ with diabetes, 67.0% (95% CI 60.9% to 73.1%) were screened, 34.0% (95% CI 30.6% to 37.2%) were diagnosed, 33.3% (95% CI 29.9% to 36.7%) were treated, and 26.0% (95% CI 22.9% to 29.1%) were controlled. Total unmet need was 74.0% (95% CI 70.9% to 77.1%), with regional variation ranging from 58.4% (95% CI 45.0% to 71.8%) in South to 78.0% (95% CI 73.0% to 83.0%) in Northeast. Multivariable models indicated older age (OR 1.76), males (OR 0.65), and a higher density of medical staff (OR 2.40) and health centers (OR 1.58) were significantly associated with being diagnosed among people with diabetes. Older age (OR 1.80) and higher geographical density of medical staff (OR 1.82) and health centers (OR 1.56) were significantly associated with being controlled. Conclusions Substantial attrition in the diabetes care continuum was observed at diabetes screening and diagnosis, related to both individual and health system factors. Even with universal health insurance, Thailand still needs effective behavioral and structural interventions, especially in primary health care settings, to address unmet need in diabetes care for its population.