title: Using EMR data to evaluate a   physician-developed lifestyle   plan for obese patients in primary care.
abstract: OBJECTIVE
  To use primary care electronic medical records (EMRs) to evaluate the effects of a lifestyle intervention delivered to obese patients compared with obese patients who did not receive the intervention.
  
  
  METHODS
  Retrospective cohort analysis using EMR data derived from the Canadian Primary Care Sentinel Surveillance Network.
  
  
  METHODS
  A primary care clinic in rural Alberta.
  
  
  METHODS
  Obese adult patients with at least 1 weight measurement in the time periods before and after the intervention, grouped by patients who received the intervention (n = 68) and those who did not (n = 365).
  
  
  METHODS
  Physician-developed lifestyle plan to address obesity through a variety of health-promoting recommendations.
  
  
  METHODS
  Mean change from before the intervention for weight, blood pressure, glycated hemoglobin A1c level, and body mass index measurements, compared between the control and intervention groups.
  
  
  RESULTS
  Negligible weight change was observed in both groups, with the exception of older male patients (65 years and older) receiving the intervention, who lost significantly more weight than older men in the control group (a difference in mean reduction of 3.02 kg in favour of the intervention; P = .008). No overall group differences were seen in the secondary health outcomes, except for reductions in systolic and diastolic blood pressures in the intervention group (P = .002 and P = .04, respectively). Only the difference in systolic blood pressure remained significant after adjusting for covariates (P = .01).
  
  
  CONCLUSIONS
  Providing real-time feedback about clinical interventions is possible using EMR data. Although the lifestyle intervention was associated with significant weight loss for a specific group of patients only, with the use of EMR data the cohort can be followed over time and additional health outcomes can be monitored. There is potential for individual physicians and practices to assess and improve clinical processes and interventions in a rigorous, timely, and manageable way.
authors.forename: Stephanie
authors.initials: S
authors.lastname: Garies
authors.forename: Antony
authors.initials: A
authors.lastname: Irving
authors.forename: Tyler
authors.initials: T
authors.lastname: Williamson
authors.forename: Neil
authors.initials: N
authors.lastname: Drummond
mesh_terms: D000328:Adult; D000368:Aged; D000416:Alberta; D001794:Blood Pressure; D015992:Body Mass Index; D057286:Electronic Health Records / Q000706:statistics & numerical data*; D005260:Female; D006442:Glycated Hemoglobin / Q000032:analysis; D006293:Health Promotion / Q000379:methods*; D006801:Humans; D008019:Life Style; D008297:Male; D008875:Middle Aged; D009765:Obesity / Q000097:blood / Q000628:therapy*; D011320:Primary Health Care / Q000379:methods*; D015397:Program Evaluation / Q000379:methods*; D012189:Retrospective Studies; D012424:Rural Population; D015431:Weight Loss
chemical_list: D006442:Glycated Hemoglobin; C517652:hemoglobin A1c protein, human