title: Inpatient treatment of diabetic patients in Asia: evidence from India, China, Thailand and Malaysia.
abstract: OBJECTIVE
  The prevalence of Type 2 diabetes mellitus (DM) has grown rapidly, but little is known about the drivers of inpatient spending in low- and middle-income countries. This study aims to compare the clinical presentation and expenditure on hospital admission for inpatients with a primary diagnosis of Type 2 DM in India, China, Thailand and Malaysia.
  
  
  METHODS
  We analysed data on adult, Type 2 DM patients admitted between 2005 and 2008 to five tertiary hospitals in the four countries, reporting expenditures relative to income per capita in 2007.
  
  
  RESULTS
  Hospital admission spending for diabetic inpatients with no complications ranged from 11 to 75% of per-capita income. Spending for patients with complications ranged from 6% to over 300% more than spending for patients without complications treated at the same hospital. Glycated haemoglobin was significantly higher for the uninsured patients, compared with insured patients, in India (8.6 vs. 8.1%), Hangzhou, China (9.0 vs. 8.1%), and Shandong, China (10.9 vs. 9.9%). When the hospital admission expenditures of the insured and uninsured patients were statistically different in India and China, the uninsured always spent less than the insured patients.
  
  
  CONCLUSIONS
  With the rising prevalence of DM, households and health systems in these countries will face greater economic burdens. The returns to investment in preventing diabetic complications appear substantial. Countries with large out-of-pocket financing burdens such as India and China are associated with the widest gaps in resource use between insured and uninsured patients. This probably reflects both overuse by the insured and underuse by the uninsured.
authors.affiliation: Centers for Health Policy and Primary Care and Outcomes Research, Stanford University School of Medicine, Stanford, CA 94305, USA.
authors.forename: J D
authors.initials: JD
authors.lastname: Goldhaber-Fiebert
authors.forename: H
authors.initials: H
authors.lastname: Li
authors.forename: S
authors.initials: S
authors.lastname: Ratanawijitrasin
authors.forename: S
authors.initials: S
authors.lastname: Vidyasagar
authors.forename: X Y
authors.initials: XY
authors.lastname: Wang
authors.forename: S
authors.initials: S
authors.lastname: Aljunid
authors.forename: N
authors.initials: N
authors.lastname: Shah
authors.forename: Z
authors.initials: Z
authors.lastname: Wang
authors.forename: S
authors.initials: S
authors.lastname: Hirunrassamee
authors.forename: K L
authors.initials: KL
authors.lastname: Bairy
authors.forename: J
authors.initials: J
authors.lastname: Wang
authors.forename: S
authors.initials: S
authors.lastname: Saperi
authors.forename: A M
authors.initials: AM
authors.lastname: Nur
authors.forename: K
authors.initials: K
authors.lastname: Eggleston
mesh_terms: D002681:China / Q000453:epidemiology; D017281:Cost of Illness; D003924:Diabetes Mellitus, Type 2 / Q000191:economics* / Q000453:epidemiology; D005260:Female; D017722:Hospital Charges / Q000706:statistics & numerical data*; D006760:Hospitalization / Q000191:economics* / Q000706:statistics & numerical data; D006801:Humans; D007194:India / Q000453:epidemiology; D007902:Length of Stay / Q000191:economics* / Q000706:statistics & numerical data; D008296:Malaysia / Q000453:epidemiology; D008297:Male; D008875:Middle Aged; D015995:Prevalence; D013785:Thailand / Q000453:epidemiology