title: Clinical informatics to improve quality of care: a population-based system for patients with diabetes mellitus.
abstract: BACKGROUND
  The prevalence of diabetes mellitus is increasing in the USA. However, control of intermediate outcome measures remains substandard. Recently, significant emphasis has been placed on the value of electronic medical records and informatics systems to improve the delivery of health care.
  
  
  OBJECTIVE
  To determine whether a clinical informatics system improves care of patients with diabetes mellitus.
  
  
  METHODS
  In this quality improvement pilot initiative, we identified 48 patients with diabetes mellitus who were due for their annual haemoglobin A1c (HbA1c), low-density lipoprotein (LDL) and microalbumin tests. Through our newly developed clinical informatics initiative, patients were reminded to schedule tests and a physician appointment. Seventy-five patients without reminders served as controls.
  
  
  RESULTS
  A significant improvement in LDL control was achieved in the intervention group (35.4% vs 13.3%; P=0.004). The intervention group had a greater percentage of patients who underwent the three tests, and members of this group also showed greater control of haemoglobin A1c, but these differences were not statistically significant.
  
  
  CONCLUSIONS
  A clinical informatics system, used to deliver proactive, co-ordinated care to a population of patients with diabetes mellitus, can improve process and also quality outcome measures. Larger studies are needed to confirm these early findings.
authors.affiliation: Division of Primary Care Internal Medicine, Mayo Clinic, Rochester, Minnesota 55905, USA. chaudhry.rajeev@mayo.edu
authors.forename: Rajeev
authors.initials: R
authors.lastname: Chaudhry
authors.forename: Sidna M
authors.initials: SM
authors.lastname: Tulledge-Scheitel
authors.forename: Matthew R
authors.initials: MR
authors.lastname: Thomas
authors.forename: Vicki L
authors.initials: VL
authors.lastname: Hunt
authors.forename: Juliette T
authors.initials: JT
authors.lastname: Liesinger
authors.forename: Ahmed S
authors.initials: AS
authors.lastname: Rahman
authors.forename: James M
authors.initials: JM
authors.lastname: Naessens
authors.forename: Lynn A
authors.initials: LA
authors.lastname: Davis
authors.forename: Robert J
authors.initials: RJ
authors.lastname: Stroebel
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000419:Albuminuria / Q000652:urine; D001071:Appointments and Schedules; D008078:Cholesterol, LDL / Q000097:blood; D003920:Diabetes Mellitus / Q000097:blood / Q000628:therapy* / Q000652:urine; D005260:Female; D006442:Glycated Hemoglobin / Q000032:analysis; D006801:Humans; D008297:Male; D008875:Middle Aged; D010865:Pilot Projects; D011314:Preventive Health Services / Q000379:methods; D011320:Primary Health Care / Q000379:methods*; D011785:Quality Assurance, Health Care; D017010:Reminder Systems; D055815:Young Adult
chemical_list: D008078:Cholesterol, LDL; D006442:Glycated Hemoglobin