| Literature DB >> 31542740 |
Lewis E Kazis1, Omid Ameli2,3, James Rothendler2, Brigid Garrity2, Howard Cabral4, Christine McDonough5, Kathleen Carey2, Michael Stein2, Darshak Sanghavi3, David Elton6, Julie Fritz7, Robert Saper8.
Abstract
OBJECTIVE: This study examined the association of initial provider treatment with early and long-term opioid use in a national sample of patients with new-onset low back pain (LBP).Entities:
Keywords: Back pain; Opioid use; PAIN MANAGEMENT; opioid
Year: 2019 PMID: 31542740 PMCID: PMC6756340 DOI: 10.1136/bmjopen-2018-028633
Source DB: PubMed Journal: BMJ Open ISSN: 2044-6055 Impact factor: 2.692
Figure 1Inclusion and exclusion criteria. Initially, 8 797 787 patients with LBP were identified. Patients with an insufficient clean period (LBP within the last 1 year), patients with a diagnosis of LBP that was not in the first position of their diagnosis and LBP in only inpatient settings were excluded, reducing the number of patients to 4 263 713. Patients were excluded if they were not continuously enrolled in their insurance for 24 months before and after the initial LBP visit and if they were aged <18 years, reducing the number of patients to 422 871. Patients with exclusionary conditions, LBP that was not limited to the low back, patients with back procedures in the 12 months prior to the index LBP visit and patients with any opioid use in the 12 months before the index visit were excluded, leaving 216 504 patients in our sample.
Patient characteristics
| Entry-point provider | ||||||||||
| Conservative therapist | Physician | |||||||||
| Total | Chiropractor | Physical therapist | Acupuncture | Primary care | Orthopaedic surgeon | Emergency medicine | MD other | Rehab | Neurosurgeon | |
| Full sample—N (%) | 216 504 (100) | 50 014 (23.1) | 3499 (1.6) | 1839 (0.8) | 114 782 (53.0) | 9335 (4.3) | 8746 (4.0) | 4422 (2.0) | 3246 (1.5) | 578 (0.3) |
| Age, year—mean (SD) | 48.1 (15.9) | 45.7 (14.9) | 47.0 (15.7) | 42.4 (10.6) | 47.7 (15.4) | 50.1 (16.4) | 50.1 (18.3) | 51.3 (15.3) | 46.9 (15.0) | 52.2 (14.8) |
| Sex/gender—N (%) | ||||||||||
| Female | 108 347 (50.1) | 22 808 (45.6) | 1995 (57.1) | 972 (52.9) | 58 182 (50.7) | 4648 (49.8) | 4560 (52.2) | 2282 (51.6) | 1554 (47.9) | 245 (42.4) |
| Male | 107 660 (49.8) | 27 193 (54.4) | >1493 (>42.6)* | >856 (>46.5)* | 56 517 (49.2) | 4674 (50.1) | >4175 (>47.7)* | 2140 (48.4) | >1681 (>51.8)* | 333 (57.6) |
| Race/ethnicity—N (%) | ||||||||||
| Black | 18 907 (8.7) | 2190 (4.4) | 191 (5.5) | 45 (2.4) | 11 755 (10.2) | 802 (8.6) | 1192 (13.6) | 494 (11.2) | 208 (6.4) | 50 (8.7) |
| Hispanic | 20 936 (9.7) | 3766 (7.5) | 263 (7.5) | 224 (12.2) | 12 212 (10.6) | 752 (8.1) | 860 (9.8) | 541 (12.2) | 293 (9.0) | 38 (6.6) |
| Asian | 9344 (4.3) | 1636 (3.3) | 224 (6.4) | 747 (40.6) | 4885 (4.3) | 354 (3.8) | 270 (3.1) | 194 (4.4) | 218 (6.7) | 15 (2.6) |
| White | 159 503 (73.7) | 40 709 (81.4) | 2666 (76.2) | 732 (39.8) | 81 971 (71.4) | 7046 (75.5) | 6115 (69.9) | 3013 (68.1) | 2394 (73.8) | 449 (77.7) |
| Unknown (missing) | 7814 (3.6) | 1713 (3.4) | 155 (4.4) | 91 (4.9) | 3959 (3.4) | 381 (4.1) | 309 (3.5) | 180 (4.1) | 133 (4.1) | 26 (4.5) |
| Insurance—N (%) | ||||||||||
| Commercial | 183 117 (84.7) | 44 520 (89.0) | 3048 (87.1) | 1827 (99.3) | 99 842 (87.0) | 7696 (82.5) | 6236 (71.3) | 3601 (81.4) | 2891 (89.1) | 472 (81.7) |
| Medicare Advantage | 32 937 (15.2) | 5476 (11.0) | >440 (>12.6)* | 12 (0.7) | 14 900 (13.0) | >1628 (>17.4)* | >2499 (>28.6)* | >810 (>18.3)* | >344 (>10.6)* | >95 (>16.4)* |
Age, sex/gender, race/ethnicity and insurance are all statistically significant at p<0.0001.
*Cell suppressed due to small N’s with unknown sex/gender or insurance in the corresponding column. Two additional initial type of providers—other non-MD (eg, physician assistants, advance practice nurses) and radiologist—were included in the analyses but not reported in this table. Outcomes with a sample size <11 are not shown due to small sample size. There were a small number of individuals with unknown sex/gender and insurance type, and if we provided exact n’s, readers may be able to infer the unknown n’s which would be problematic since we cannot disclose n<11 for purposes of confidentiality of the data. For example, in table 1 under male PT, >1493 means that there was an unknown sex/gender row or column with n<11. Therefore, the number of male PT first individuals is between 1493 and 1504.
PT, physical therapy.
Odds of early and long-term opioid use by initial provider
| Early use, OR (95% CI) | Long-term, OR (95% CI) | ||
| Initial provider | PT (n=3499) | 0.15 (0.13 to 0.17) | 0.27 (0.15 to 0.48) |
| DC (n=50 014) | 0.10 (0.09 to 0.10) | 0.22 (0.18 to 0.26) | |
| Acupuncture (n=1839) | 0.09 (0.07 to 0.12) | 0.07 (0.01 to 0.48) | |
| Ortho (n=9335) | 0.63 (0.60 to 0.67) | 1.10 (0.92 to 1.30) | |
| Emerg Med (n=8746) | 2.66 (2.54 to 2.78) | 0.92 (0.77 to 1.10) | |
| Neurosgn (n=578) | 0.58 (0.47 to 0.71) | 1.50 (0.88 to 2.58) | |
| MD other (n=4422) | 0.50 (0.46 to 0.54) | 2.03 (1.70 to 2.41) | |
| Rehab (n=3246) | 0.54 (0.49 to 0.59) | 1.78 (1.40 to 2.26) | |
| Age (years) | 45–64 vs 18–44 | 1.07 (1.05 to 1.10) | 1.32 (1.19 to 1.46) |
| 65–74 vs 18–44 | 0.89 (0.82 to 0.97) | 0.79 (0.54 to 1.15) | |
| 75+ vs 18–44 | 0.80 (0.72 to 0.89) | 0.67 (0.45 to 1.00) | |
| Sex/gender | Female vs male | 0.83 (0.81 to 0.85) | 0.82 (0.76 to 0.89) |
| Race | Asian vs white | 0.49 (0.46 to 0.52) | 0.29 (0.20 to 0.42) |
| Black vs white | 0.90 (0.87 to 0.94) | 0.87 (0.76 to 0.99) | |
| Hispanic vs white | 0.79 (0.76 to 0.82) | 0.69 (0.59 to 0.81) | |
| Unknown vs white | 0.84 (0.79 to 0.89) | 0.65 (0.51 to 0.83) | |
| Region | Midwest vs Northeast | 0.78 (0.75 to 0.81) | 0.74 (0.64 to 0.87) |
| South vs Northeast | 1.11 (1.08 to 1.14) | 1.22 (1.11 to 1.34) | |
| West vs Northeast | 1.01 (0.97 to 1.04) | 1.17 (1.02 to 1.34) | |
| Insurance type | Medicare <65 years vs commercial insurance | 0.98 (0.89 to 1.08) | 3.77 (3.19 to 4.46) |
| Medicare ≥65 years vs commercial insurance | 0.98 (0.89 to 1.08) | 2.24 (1.54 to 3.26) | |
| Comorbidities | Anxiety | 1.05 (1.01 to 1.09) | 1.46 (1.30 to 1.63) |
| Bipolar disorder | 1.11 (1.01 to 1.21) | 1.41 (1.13 to 1.76) | |
| Depression | 1.11 (1.07 to 1.15) | 1.55 (1.39 to 1.73) | |
| Dementia | 0.80 (0.70 to 0.92) | 0.99 (0.73 to 1.36) | |
| ADHD | 0.87 (0.80 to 0.95) | 1.00 (0.75 to 1.32) | |
| Alcohol use disorder | 1.08 (0.98 to 1.20) | 1.28 (0.98 to 1.66) | |
| Substance use disorder | 1.06 (0.93 to 1.22) | 2.34 (1.76 to 3.10) | |
| Fibromyalgia/chronic pain/fatigue | 0.96 (0.92 to 1.01) | 1.92 (1.71 to 2.16) | |
| PTSD | 0.84 (0.69 to 1.03) | 1.16 (0.77 to 1.77) | |
| Psychotic disorder | 0.86 (0.74 to 0.99) | 0.76 (0.55 to 1.05) | |
| Elixhauser physical | 1.07 (1.06 to 1.08) | 1.24 (1.21 to 1.27) |
The following variables were all included in the regression: age, sex/gender, race/ethnicity, insurance, Elixhauser, which included physical comorbidities and mental health comorbidities. PCP is the reference group (n=114 782); adjusted for race/ethnicity, sex/gender, region and insurance type. Two additional initial providers—other non-MD (eg, physician assistants, advance practice nurses) and radiologist—were included in the analyses but not reported in this table.
*P<0.01.
ADHD, attention deficit hyperactivity disorder; DC, chiropractor; Emerg Med, emergency medicine physician; MD other, other physician; Neurosgn, neurosurgeon; Ortho, orthopaedic surgeon; PCP, primary care physician; PT, physical therapy; PTSD, post-traumatic stress disorder; Rehab, rehab physician.