Table 3.
Change in risk-adjusted probability of antipsychotic and mood stabilizer treatment among long-stay nursing home residents in the U.S. with depression or bipolar disorder from the first quarter of 2011 to final quarter of 2014 (N = 139,071).
| Variable | Antipsychotics | Mood stabilizers | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| 2011Q1 | 2014Q4 | 2011Q1 | 2014Q4 | P-valuea | ||||||
| Adjusted predicted probability | 95%CI | Adjusted predicted probability | 95%CI | P-valuea | Adjusted predicted probability | 95%CI | Adjusted predicted probability | 95%CI | ||
| Overall | 0.081 | (0.079–0.082) | 0.087 | (0.085–0.088) | <0.001 | 0.193 | (0.190–0.196) | 0.251 | (0.248–0.253) | <0.001 |
| Age | ||||||||||
| <75 (ref) | 0.107 | (0.104–0.110) | 0.115 | (0.112–0.117) | <0.001 | 0.229 | (0.225–0.233) | 0.295 | (0.291–0.299) | <0.001 |
| 75–84 | 0.064 | (0.062–0.067) | 0.070 | (0.068–0.072) | -- | 0.169 | (0.165–0.173) | 0.230 | (0.226–0.234) | -- |
| 85+ | 0.054 | (0.051–0.057) | 0.058 | (0.056–0.060) | -- | 0.151 | (0.147–0.156) | 0.186 | (0.182–0.190) | --b |
| Sex | ||||||||||
| Female (ref) | 0.076 | (0.074–0.078) | 0.082 | (0.080–0.084) | <0.001 | 0.195 | (0.192–0.199) | 0.256 | (0.253–0.259) | <0.001 |
| Male | 0.094 | (0.090–0.097) | 0.100 | (0.097–0.103) | -- | 0.187 | (0.182–0.192) | 0.238 | (0.234–0.243) | -- |
| Race/ethnicity | ||||||||||
| White (ref) | 0.082 | (0.080–0.084) | 0.089 | (0.087–0.091) | <0.001 | 0.195 | (0.192–0.198) | 0.253 | (0.250–0.256) | <0.001 |
| Black | 0.070 | (0.064–0.076) | 0.074 | (0.070–0.079) | -- | 0.182 | (0.173–0.191) | 0.246 | (0.238–0.254) | -- |
| Hispanic | 0.085 | (0.077–0.095) | 0.078 | (0.072–0.085) | --b | 0.176 | (0.165–0.189) | 0.232 | (0.221–0.243) | -- |
| Others | 0.076 | (0.066–0.088) | 0.077 | (0.068–0.087) | -- | 0.187 | (0.170–0.206) | 0.225 | (0.210–0.240) | -- |
Adjusted predicted probabilities determined from logistic regression models adjusted for age, gender, race, census division, the Elixhauser conditions, as well as additional clinical diagnoses (delirium, Parkinson’s disease, post-traumatic stress disorder, personality disorder, other anxiety disorders). For each characteristic-specific sub-cohort, the adjusted predicted probabilities were obtained using additional interaction terms of time (as a continuous variable) by the specific sub-cohort factor variables. For example, for sex sub-cohorts, the models for antipsychotic use and mood stabilizer use each included time by sex indicator of male × time, with female as the referent category.
P-value reflects significance test for time effect in the main model for the overall cohort and referent categories (e.g., p<0.001 for residents <75 [reference] means that the probability of antipsychotic use by persons with depression or bipolar disorder changed [increased] with time).
p<0.001 (or c p<0.01) for a significant characteristic-by-time effect that differs from the referent sub-group category (e.g., in the case of age, the effect of time on likelihood of antipsychotic treatment was no different than those 75–84 or 85+ than for those <75 [reference]).