Table 2.
Predictors of using portal features and predictors of high use versus low use of clinical features.
| Variables in equation | Users vs nonusersa (N=263) | High use vs low use of clinical featuresb (N=263) | |||||||
|
|
Adjusted odds ratioc | 95% CI | Adjusted odds ratio | 95% CI | |||||
| Gender | |||||||||
|
|
Female | 1.00 |
|
1.00 |
|
||||
|
|
Not female | 0.89 | 0.47-1.68 | 0.840 | 0.42-1.69 | ||||
| Age (years) | |||||||||
|
|
18-23 | 1.00 |
|
1.00 |
|
||||
|
|
24-29 | 1.43 | 0.67-3.03 | 0.63 | 0.31-1.28 | ||||
| Ethnicity | |||||||||
|
|
Not Hispanic | 1.00 |
|
1.00 |
|
||||
|
|
Hispanic | 1.13 | 0.40-3.20 | 2.97 | 1.03-8.52 | ||||
| Race | |||||||||
|
|
White | 1.00 |
|
1.00 |
|
||||
|
|
Black | 0.97 | 0.37-2.55 | 2.09 | 0.678-6.42 | ||||
|
|
Asian | 0.75 | 0.30-1.92 | 4.28 | 1.08-16.89 | ||||
|
|
Other | 0.61 | 0.21-1.79 | 2.52 | 0.630-10.05 | ||||
| University type | |||||||||
|
|
Public | 1.00 |
|
1.00 |
|
||||
|
|
Not public | 0.625 | 0.327-2.84 | 1.65 | 0.808-3.36 | ||||
| Health insurance type | |||||||||
|
|
Private insurance | 1.00 |
|
1.00 |
|
||||
|
|
Not private | 1.20 | 0.51-2.87 | 1.03 | 0.44-2.42 | ||||
| Health condition | |||||||||
|
|
Yes | 1.00 |
|
1.00 |
|
||||
|
|
No | 1.08 | 0.55-2.10 | 1.37 | 0.70-2.67 | ||||
| Total health care encounters past 6 months | 1.23 | 1.05-1.44 | 1.16 | 1.01-1.34 | |||||
| eHealth literacy score | 0.99 | 0.96-1.02 | 0.97 | 0.94-1.00 | |||||
| Patient engagement score | 1.08 | 1.04-1.13 | 1.10 | 1.05-1.15 | |||||
aFor this table, nonusers were defined as those who reported not using any of the 8 portal features and users were defined as those who reported using at least one of the 8 portal features.
bHigh users were defined as those who used 3 or more clinical portal features and low users were those who used less than 3 clinical portal features.
cResults from multivariable logistic regression models including all variables shown; significant relationships are italicized.