Table 8.
Average effects of switching to PCPs with higher primary care spending per patient.
| Utilization outcome | Utilization outcome | ||
|---|---|---|---|
| Primary care $ | $76.37*** (2.806) | # Primary care office visits | 1.062*** (0.0843) |
| All physician $ | $114.8*** (3.957) | # All office visits | 1.242*** (0.0942) |
| Pharmaceutical drug $ | $85.00*** (24.80) | # Diagnoses | 1.049*** (0.0671) |
| Outpatient $ | $171.9*** (30.26) | # Chronic conditions | 0.217*** (0.0138) |
| Inpatient $ | $241.3*** (59.13) | # ED visits | 0.0166** (0.00508) |
| Post-acute care $ | $38.55 (26.00) | # Avoidable hospitalizations | 0.00219 (0.00119) |
| Total $ | $665.7*** (101.2) | Prob. of flu vaccination | 0.0221*** (0.00331) |
| Prob. of diabetes care | 0.0226*** (0.00234) |
Notes: This table shows how switching to a PCP with $100 higher primary care spending per patient correlates with othertypes of health care utilization. We use the difference-in-differences specification in Eq. (3) to estimate these cross-outcome associations. Each cell is an estimate for θ from Eq. (3) for a different utilization outcome y. We include years −4 to −1 in the pre-event period, and we include years 2–6 in the post-event period. We control for patient fixed effects, time-varying patient characteristics, a post-event time indicator, and calendar year fixed effects. The standard errors are clustered at the HRR-level.
p<0.001
p<0.01
p<0.05.