title: Randomized trial of a health IT tool to support between-visit-based laboratory monitoring for chronic disease medication prescriptions.
abstract: BACKGROUND
  Lack of timely medication intensification and inadequate medication safety monitoring are two prevalent and potentially modifiable barriers to effective and safe chronic care. Innovative applications of health information technology tools may help support chronic disease management.
  
  
  OBJECTIVE
  To examine the clinical impact of a novel health IT tool designed to facilitate between-visit ordering and tracking of future laboratory testing.
  
  
  METHODS
  Clinical trial randomized at the provider level (n = 44 primary care physicians); patient-level outcomes among 3,655 primary care patients prescribed 5,454 oral medicines for hyperlipidemia, diabetes, and/or hypertension management over a 12-month period.
  
  
  METHODS
  Time from prescription to corresponding follow-up laboratory testing; proportion of follow-up time that patients achieved corresponding risk factor control (A1c, LDL); adverse event laboratory monitoring 4 weeks after medicine prescription.
  
  
  RESULTS
  Patients whose physicians were allocated to the intervention (n = 1,143) had earlier LDL laboratory assessment compared to similar patients (n = 703) of control physicians [adjusted hazard ratio (aHR): 1.15 (1.01-1.32), p = 0.04]. Among patients with elevated LDL (486 intervention, 324 control), there was decreased time to LDL goal in the intervention group [aHR 1.26 (0.99-1.62)]. However, overall there were no significant differences between study arms in time spent at LDL or HbA1c goal. Follow-up safety monitoring (e.g., creatinine, potassium, or transaminases) was relatively infrequent (ranging from 7 % to 29 % at 4 weeks) and not statistically different between arms. Intervention physicians indicated that lack of reimbursement for non-visit-based care was a barrier to use of the tool.
  
  
  CONCLUSIONS
  A health IT tool to support between-visit laboratory monitoring improved the LDL testing interval but not LDL or HbA1c control, and it did not alter safety monitoring. Adoption of innovative tools to support physicians in non-visit-based chronic disease management may be limited by current visit-based financial and productivity incentives.
authors.affiliation: Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA, Richard.W.Grant@KP.org.
authors.forename: Richard W
authors.initials: RW
authors.lastname: Grant
authors.forename: Jeffrey M
authors.initials: JM
authors.lastname: Ashburner
authors.forename: Michael C
authors.initials: MC
authors.lastname: Jernigan
authors.forename: Jaime
authors.initials: J
authors.lastname: Chang
authors.forename: Leila H
authors.initials: LH
authors.lastname: Borowsky
authors.forename: Yuchiao
authors.initials: Y
authors.lastname: Chang
authors.forename: Steven J
authors.initials: SJ
authors.lastname: Atlas
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D002908:Chronic Disease / Q000188:drug therapy*; D016000:Cluster Analysis; D003920:Diabetes Mellitus / Q000097:blood / Q000188:drug therapy; D011307:Drug Prescriptions / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D006949:Hyperlipidemias / Q000097:blood / Q000188:drug therapy; D006973:Hypertension / Q000097:blood / Q000188:drug therapy; D020407:Internet; D007755:Laboratories, Hospital / Q000458:organization & administration*; D008297:Male; D008875:Middle Aged; D008991:Monitoring, Physiologic / Q000295:instrumentation*; D058007:Physicians, Primary Care / Q000706:statistics & numerical data; D011320:Primary Health Care / Q000458:organization & administration*; D016016:Proportional Hazards Models; D058996:Quality Improvement; D013997:Time Factors; D014481:United States