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Table 2 Associations between alert acceptance and clinician characteristics and workload

From: Effects of workload, work complexity, and repeated alerts on alert fatigue in a clinical decision support system

Predictor

Median value of continuous predictors

Acceptance rates (yes vs. no or above vs. below median)

Bivariate models

Multivariable model

   

IRR (95% CI)

P

IRR (95% CI)

p

 For best practice advisories (BPAs)

  Clinician characteristics

   Nurse practitioner (vs physician)

--

22.7% vs 21.0%

1.08 (0.74, 1.57)

.69

0.79 (0.57-1.10)

.16

   Attested for meaningful use (vs not attested)

--

22.9% vs 19.3%

1.19 (0.94, 1.51)

.15

1.06 (0.88-1.28)

.50

   Female (vs male)

--

23.0% vs 18.4%

1.25 (0.98, 1.59)

.07

1.06 (0.88-1.27)

.54

  Markers of workload

   Patients per year

790

20.7% vs 21.7%

1.002 (0.98, 1.02)c

.85

---f

 

   Encounters per year

1357

21.8% vs 20.6%

0.999 (0.99, 1.01)d

.92

1.01 (1.00-1.02)

.21

  Markers of complexity

   BPAs received per encounter

3.2

15.8% vs 26.7%

0.65 (0.55, 0.77)a

<.001

0.70 (0.60-0.82)

<.001

   Drug alerts received per encounter

0.7

22.7% vs 19.8%

1.17 (0.80, 1.72)a

.41

1.91 (1.39-2.64)

<.001

   Average ADG comorbidity count of patients

0.3

18.9% vs 23.5%

0.27 (0.10, 0.71)b

.008

0.49 (0.23-1.03)

.06

   Percent of BPAs that are within-patient repeats

26.2

17.0% vs 25.4%

0.90 (0.87, 0.94)e

<.001

0.90 (0.86-0.95)

<.001

 For drug alerts (DDI and DAI)

  Clinician characteristics

   Nurse practitioner (vs physician)

--

0.9% vs 0.2%

3.97 (1.64, 9.62)

.002

4.56 (1.72-12.06)

.002

   Attested for meaningful use (vs not attested)

--

0.3% vs 0.3%

0.92 (0.40, 2.11)

.85

0.96 (0.49-1.88)

.91

   Female (vs male)

--

0.4% vs 0.2%

1.72 (0.82, 3.60)

.15

0.85 (0.37-1.95)

.71

  Markers of workload

   Patients per year

790

0.3% vs 0.3%

0.99 (0.94, 1.04)c

.60

-----f

 

   Encounters per year

1357

0.3% vs 0.4%

0.98 (0.96, 1.01)d

.12

1.00 (0.97-1.04)

.82

  Markers of complexity

   BPAs received per encounter

3.2

0.3% vs 0.3%

1.10 (0.78, 1.56)a

.59

1.49 (1.03-2.17)

.04

   Drug alerts received per encounter

0.7

0.2% vs 0.4%

0.69 (0.29, 1.67)a

.42

1.39 (0.44-4.39)

.57

   Average ADG comorbidity count of patients

0.3

0.3% vs 0.4%

0.15 (0.03, 0.80)b

.03

0.37 (0.05-2.74)

.33

   Percent of alerts that are within-patient repeats

31.8

0.3% vs 0.4%

0.87 (0.76, 0.998)e

.046

0.84 (0.68-1.03)

.09

   Order sets used per encounter

1.1

0.3% vs 0.3%

1.20 (0.44, 3.23)a

.72

1.68 (0.76-3.71)

.20

   Labs ordered per encounter

0.9

0.3% vs 0.3%

0.89 (0.43, 1.83)a

.75

0.80 (0.41-1.56)

.51

  1. a. IRR computed per 1 additional unit
  2. b. IRR computed per 1 additional ADG
  3. c. IRR computed per 100 additional patients
  4. d. IRR computed per 100 additional encounters per year
  5. e. IRR computed per 5 percentage point increment
  6. f. Patients per year omitted from multivariable model to avoid collinearity with encounters per year
  7. NOTE: An IRR (incident rate ratio) is the ratio of 2 rates and is interpreted similarly to a relative risk or odds ratio. For example, the adjusted IRR of 4.56 above indicates that nurse practitioners are more than 4 times as likely to accept drug alerts as physicians are, in a model that controlled for patient comorbidity and proportion of repeated alerts