title: The effect of electronic medical record system sophistication on preventive healthcare for women.
abstract: OBJECTIVE
  To observe the effect of electronic medical record (EMR) system sophistication on preventive women's healthcare.
  
  
  METHODS
  Providers in the National Ambulatory Medical Care Survey (NAMCS), 2007-8, were included if they had at least one visit by a woman at least 21 years old. Based on 16 questions from NAMCS, the level of a provider's EMR system sophistication was classified as non-existent, minimal, basic, or fully functional. A two-stage residual-inclusion method was used with ordered probit regression to model the level of EMR system sophistication, and outcome-specific Poisson regressions to predict the number of examinations or tests ordered or performed.
  
  
  RESULTS
  Across the providers, 29.23%, 49.34%, 15.97%, and 5.46% had no, minimal, basic, and fully functional EMR systems, respectively. The breast examination rate was 20.27%, 34.96%, 37.21%, and 44.98% for providers without or with minimal, basic, and fully functional EMR systems, respectively. For breast examinations, pelvic examinations, Pap tests, chlamydia tests, cholesterol tests, mammograms, and bone mineral density (BMD) tests, an EMR system increased the number of these tests and examinations. Furthermore, the level of sophistication increased the number of breast examinations and Pap, chlamydia, cholesterol, and BMD tests.
  
  
  CONCLUSIONS
  The use of advanced EMR systems in obstetrics and gynecology was limited. Given the positive results of this study, specialists in women's health should consider investing in more sophisticated systems.
  
  
  CONCLUSIONS
  The presence of an EMR system has a positive impact on preventive women's healthcare; the more functions that the system has, the greater the number of examinations and tests given or prescribed.
authors.affiliation: Innovation, Health Outcomes and Pharmaceutical Economics, College of Pharmacy, University of Cincinnati, Cincinnati, OH 45267-0004, USA. tundianl@mail.uc.edu
authors.forename: Namita L
authors.initials: NL
authors.lastname: Tundia
authors.forename: Christina M L
authors.initials: CM
authors.lastname: Kelton
authors.forename: Teresa M
authors.initials: TM
authors.lastname: Cavanaugh
authors.forename: Jeff J
authors.initials: JJ
authors.lastname: Guo
authors.forename: Dennis J
authors.initials: DJ
authors.lastname: Hanseman
authors.forename: Pamela C
authors.initials: PC
authors.lastname: Heaton
mesh_terms: D000328:Adult; D003658:Decision Making, Computer-Assisted; D005260:Female; D019983:Guideline Adherence; D019538:Health Care Surveys; D006266:Health Education / Q000706:statistics & numerical data; D006801:Humans; D008403:Mass Screening / Q000706:statistics & numerical data; D016347:Medical Records Systems, Computerized; D017063:Outcome Assessment, Health Care; D016012:Poisson Distribution; D011314:Preventive Health Services / Q000706:statistics & numerical data*; D012044:Regression Analysis; D017010:Reminder Systems; D014481:United States; D016387:Women's Health