Table 4.
Association between STOPP/START and healthcare utilization outcomes using negative binomial regression (incident rate ratios (IRR), 95% confidence intervals (CIs))
| M (SD)a | GP visits (n = 2487) Adjusted IRR (95% CI)b |
||
|---|---|---|---|
| Model 1c | Model 2d | ||
| Any STOPPe (n = 909) | 4.98 (4.79) | 1.06 (1.00, 1.13), p = 0.051 | – |
| Number of STOPP PIMS | |||
| 0 STOPP (n = 2082) | 3.83 (3.33) | – | (Referent) |
| 1 STOPP (n = 658) | 4.69 (4.28) | – | 1.05 (1.00, 1.13), p = 0.064 |
| ≥ 2 STOPP (n = 251) | 5.72 (5.87) | – | 1.06 (0.96, 1.17), p = 0.267 |
| Any STARTe (n = 1062) | 2.09 (6.77) | 1.07 (1.01, 1.13), p = 0.018f | – |
| Number of START PPOs | |||
| 0 START (n = 1933) | 3.89 (3.57) | – | (Referent) |
| 1 START (n = 651) | 4.39 (3.49) | – | 1.07 (1.00, 1.15), p = 0.038 |
| ≥ 2 START (n = 407) | 5.19 (5.35) | – | 1.07 (0.99, 1.16), p = 0.097 |
| M (SD)a | ED visit (n = 2500) Adjusted IRR (95% CI)b |
||
|---|---|---|---|
| Model 1c | Model 2d | ||
| Any STOPPe (n = 915) | 0.37 (0.85) | 0.91 (0.74, 1.11), p = 0.335 | – |
| Number of STOPP PIMS | |||
| 0 STOPP (n = 2091) | 0.27 (0.69) | – | (Referent) |
| 1 STOPP (n = 662) | 0.33 (0.81) | – | 0.88 (0.71, 1.10), p = 0.260 |
| ≥ 2 STOPP (n = 253) | 0.46 (0.93) | – | 0.97 (0.72, 1.31), p = 0.847 |
| Any STARTe (n = 1066) | 0.39 (0.80) | 1.23 (1.03, 1.48), p = 0.025 | – |
| Number of START PPOs | |||
| 0 START (n = 1940) | 0.22 (0.70) | – | (Referent) |
| 1 START (n = 653) | 0.36 (0.74) | – | 1.20 (0.97, 1.49), p = 0.089 |
| ≥ 2 START (n = 413) | 0.43 (0.87) | – | 1.28 (1.00, 1.63), p = 0.050 |
| M (SD)a | Outpatient visit (n = 2493) Adjusted IRR (95% CI)b |
||
|---|---|---|---|
| Model 1c | Model 2d | ||
| Any STOPPe (n = 914) | 2.34 (8.50) | 1.09 (0.92, 1.29), p = 0.304 | – |
| Number of STOPP PIMS | |||
| 0 STOPP (n = 2085) | 1.58 (5.30) | – | (Referent) |
| 1 STOPP (n = 660) | 2.21 (6.14) | – | 1.08 (0.90, 1.30), p = 0.381 |
| ≥ 2 STOPP (n = 254) | 2.67 (12.74) | – | 1.11 (0.84, 1.46), p = 0.452 |
| Any STARTe (n = 1062) | 2.09 (6.77) | 1.21 (1.02, 1.42), p = 0.024 | – |
| Number of START PPOs | |||
| 0 START (n = 1937) | 1.66 (6.27) | – | (Referent) |
| 1 START (n = 650) | 2.11 (8.07) | – | 1.26 (1.04, 1.52), p = 0.018 |
| ≥ 2 START (n = 412) | 2.06 (3.93) | – | 1.13 (0.91, 1.41), p = 0.271 |
| M (SD)a | Hospital admission (n = 2501) Adjusted IRR (95% CI)b |
||
|---|---|---|---|
| Model 1c | Model 2d | ||
| Any STOPPe (n = 916) | 0.49 (1.79) | 1.38 (1.08, 1.75), p = 0.009 | – |
| Number of STOPP PIMS | |||
| 0 STOPP (n = 2091) | 0.28 (1.03) | – | (Referent) |
| 1 STOPP (n = 662) | 0.46 (1.92) | – | 1.28 (0.99, 1.66), p = 0.062 |
| ≥ 2 STOPP (n = 254) | 0.59 (1.40) | – | 1.70 (1.17, 2.47), p = 0.006 |
| Any STARTe (n = 1066) | 0.44 (1.55) | 1.24 (0.99, 1.54), p = 0.063 | – |
| Number of START PPOs | |||
| 0 START (n = 1941) | 0.29 (1.16) | – | (Referent) |
| 1 START (n = 653) | 0.40 (1.66) | – | 1.21 (0.93, 1.57), p = 0.158 |
| ≥ 2 START (n = 413) | 0.52 (1.37) | – | 1.28 (0.95, 1.73), p = 0.108 |
aMean and standard deviation of healthcare utilisation variables at Wave 5
bAdjusted for age group, sex, education, employment status, insurance coverage, multimorbidity, polypharmacy, and wave 4 healthcare utilisation
cModel 1: PIP exposure assessed using binary variables for presence or absence of STOPP/START
dModel 2: PIP exposure assessed using categorical variables for presence of 0, 1 and ≥ 2 STOPP/START criteria
eReferent: none
fAssociations with p <0.05 are in bold