TABLE 1.
Sociodemographic and Zip Code Characteristics for All Prescriptions Written to 1 Community Pharmacy Chain in Greater Cincinnati Between October 1, 2016, and April 1, 2017, Including a Bivariate Assessment of Whether Those Prescriptions Were Filled Within 30 Days
| Characteristic | All Prescriptions Written (n = 213 719) | Prescriptions Filled Within 30 d (n = 187 665) | Prescriptions Not Filled Within 30 d (n = 26 054) | Pa |
|---|---|---|---|---|
| Across entire sample, n (%) | 213 719 (100) | 187 665 (87.8) | 26 054 (12.2) | — |
| Age, y, median (IQR) | 9.0 (4.0–14.0) | 8.0 (4.0–14.0) | 10.0 (5.0–14.0) | <.0001 |
| Sex, n (%) | <.0001 | |||
| Female | 105 660 (49.4) | 93 133 (88.1) | 12 527 (11.9) | |
| Male | 108 059 (50.6) | 94 532 (87.5) | 13 527 (12.5) | |
| Payment mechanism, n (%) | <.0001 | |||
| Private | 107 999 (50.5) | 98 906 (91.6) | 9093 (8.4) | |
| Public | 83 983 (39.3) | 74 932 (89.2) | 9051 (10.8) | |
| Discount card | 2051 (1.0) | 1829 (89.2) | 222 (10.8) | |
| Unknown | 19 686 (9.2) | — | — | |
| Medication class, n (%) | <.0001 | |||
| Antiepileptic | 3248 (1.5) | 2781 (85.6) | 467 (14.4) | |
| Analgesic and/or antipyretic | 18 651 (8.7) | 16 062 (86.1) | 2589 (13.9) | |
| Asthma and/or allergy | 40 244 (18.8) | 33 094 (82.2) | 7150 (17.8) | |
| Contraceptive | 2058 (1.0) | 1693 (82.3) | 365 (17.7) | |
| Dermatology | 10 989 (5.1) | 8519 (77.5) | 2470 (22.5) | |
| Endocrine | 2793 (1.3) | 2282 (81.7) | 511 (18.3) | |
| Gastrointestinal | 10 017 (4.7) | 8363 (83.5) | 1654 (16.5) | |
| Antihypertensive and/or nephrology | 1823 (1.0) | 1517 (83.2) | 306 (16.8) | |
| Mental health | 19 818 (9.3) | 16 750 (84.5) | 3068 (15.5) | |
| Nutritional | 3472 (1.6) | 2455 (70.7) | 1017 (29.3) | |
| Oral anti-infective | 77 936 (36.5) | 74 680 (95.8) | 3256 (4.2) | |
| Topical anti-infective | 18 050 (8.5) | 15 768 (87.4) | 2282 (12.6) | |
| Other | 4620 (2.2) | 3701 (80.1) | 919 (19.9) | |
| Quintiles of zip code percentage below federal poverty level,b n (%) | <.0001 | |||
| Low | 45 804 (22.1) | 40 989 (89.5) | 4815 (10.5) | |
| Low-medium | 42 519 (20.6) | 38 103 (89.6) | 4416 (10.4) | |
| Medium | 37 195 (18.0) | 33 071 (88.9) | 4124 (11.1) | |
| Medium-high | 52 445 (25.4) | 45 743 (87.2) | 6702 (12.8) | |
| High | 28 922 (14.0) | 23 796 (82.3) | 5216 (17.7) | |
| Quintiles of zip code percentage of households without access to a vehicle,c n (%) | <.0001 | |||
| Low | 35 869 (17.3) | 32 203 (89.8) | 3666 (10.2) | |
| Low-medium | 48 956 (23.7) | 43 754 (89.4) | 5202 (10.6) | |
| Medium | 39 359 (19.0) | 34 831 (88.5) | 4528 (11.5) | |
| Medium-high | 54 014 (27.1) | 49 281 (88.0) | 6733 (12.0) | |
| High | 26 687 (12.9) | 21 633 (81.1) | 5054 (18.9) |
When numbers do not add up to the total prescription count, it is a result of missing data. IQR, interquartile range; —, not applicable.
For P values, we compared nonfilled prescriptions with filled prescriptions. Categorical variables were assessed by using the χ2 test and the Mantel-Haenszel χ2 test of trend; continuous variables were assessed by using the Wilcoxon rank test.
Zip code poverty cut-points were as follows: low (1.6%–6.8%), low-medium (7.1%–10.4%), medium (10.4%–14.3%), medium-high (14.9%–20.5%), and high (20.7%–61.0%).
Zip code vehicle access cut-points were as follows: low (0.4%–3.0%), low-medium (3.1%–4.5%), medium (4.5%–6.0%), medium-high (6.1%–11.8%), and high (12.8%–43.5%).