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Table 3 Logistic regression evaluating the relationship between formulary decision support and preferred medication tier (n = 14660) *

From: Effect of electronic prescribing with formulary decision support on medication tier, copayments, and adherence

PCP or Claim characteristic Odds ratio 95% CIs P value
Medication class – inhaled steroid 4.1 3.4-5.0 <0.0001
E-prescribing with formulary decision support (FDS) usage  
Low users (<30% of time) 0.9 0.8-1.1 0.35
High users (>30% of time) 0.8 0.6-1.1 0.16
Time periods  
Non-interruptive FDS time period 1.1 0.9-1.3 0.42
Interruptive and Non-interruptive FDS time period 1.0 0.9-1.1 0.59
Interactions  
Low users during time period with Non-interruptive FDS only 0.9 0.6-1.5 0.74
Low users during time period with Interruptive and Non-interruptive FDS 0.8 0.6-1.1 0.13
High users during time period with Non-interruptive FDS only 0.9 0.4-2.3 0.83
High users during time period with Interruptive and Non-interruptive FDS 1.9 1.0-3.4 0.04
  1. *Variables without association, and therefore not used as predictors in this model, are: date dispensed, PCP prescribing volume with this insurer, patients’ average pharmaceutical claims per month, and patient race and income (as estimated from zip code data).
  2. The referent categories were as follows: angiotensin receptor blocker medication class, non-users, and claims from the time period prior to e-prescribing activation.
  3. As noted in the text, this odds ratio remained in the range of 1.6-2.0 in five other models where we: (1) excluded pediatricians completely, (2) controlled for physician specialty, (3) controlled for practice size, (4) restricted to ARB only, and (5) restricted to IS only.