Table 1.
Study Population Characteristics of Patients with ADRD by Urban/Rural
| Variable | Urban (%) | Rural (%) | P value |
|---|---|---|---|
| Preventable ED Visit Status | < .001 | ||
| Not Preventable | 154,598 (94.79) | 31,707 (92.14) | |
| Preventable | 8,492 (5.21) | 2,705 (7.86) | |
| Race | < .001 | ||
| Non-Hispanic White | 123,930 (75.99) | 28,649 (83.25) | |
| Non-Hispanic Black | 22,499 (13.80) | 4,093 (11.89) | |
| Hispanic | 13,389 (8.21) | 914 (2.66) | |
| Non-Hispanic Asian/Pacific Islander | 1,206 (0.74) | 52 (0.15) | |
| Non-Hispanic Native American | 754 (0.46) | 596 (1.73) | |
| Non-Hispanic Other | 1,312 (0.80) | 108 (0.31) | |
| Gender | .855 | ||
| Male | 58,317 (35.76) | 12,287 (35.71) | |
| Female | 104,773 (64.24) | 22,125 (64.29) | |
| Age group | < .001 | ||
| 30–49 years old | 1,420 (0.87) | 297 (0.86) | |
| 50–64 years old | 7,971 (4.89) | 1,737 (5.05) | |
| 65–74 years old | 22,186 (13.60) | 5,429 (15.78) | |
| 75+ years old | 131,513 (80.64) | 26,949 (78.31) | |
| Income Quartile by ZIP Code | < .001 | ||
| 0–25th percentile | 48,609 (29.81) | 21,406 (62.21) | |
| 26th–50th percentile | 46,882 (28.75) | 9,843 (28.60) | |
| 51th–75th percentile | 37,965 (23.28) | 2,977 (8.65) | |
| 76th–100th percentile | 29,634 (18.17) | 186 (0.54) | |
| Disposition Location | < .001 | ||
| Routine | 122,892 (75.35) | 23,152 (67.28) | |
| Transfer to Short-term Hospital | 5,110 (3.13) | 3,751 (10.90) | |
| Transfer to SNF/ICF/Other | 28,999 (17.78) | 6,681 (19.41) | |
| Home Health Care | 4,912 (3.01) | 702 (2.04) | |
| Against Medical Advice | 1,177 (0.72) | 126 (0.37) | |
| Primary Payer | < .001 | ||
| Medicare | 141,044 (86.48) | 29,926 (86.96) | |
| Medicaid | 3,737 (2.29) | 748 (2.17) | |
| Other | 18,309 (11.23) | 3,738 (10.86) | |
| Elixhauser Comorbidities | < .001 | ||
| ≤2 | 112,591 (69.04) | 22,711 (66.00) | |
| >2 | 50,499 (30.96) | 11,701 (34.00) | |
| Time Index | < .001 | ||
| Q1–Q3 | 122,881 (75.35) | 26,238 (76.25) | |
| Q4 | 40,209 (24.65) | 8,174 (23.75) | |
| County Average Percent African American | 15.37% | 12.01% | < .001 |
| County MD’s per 1000 Residents | 2.63 | 2.63 | .530 |
| County Hospitals Beds per 1000 Residents | 2.80 | 2.37 | < .001 |
| County Health Professional Shortage Area | < .001 | ||
| Not/Part of County HPSA | 161,066 (98.76) | 29,028 (84.35) | |
| Whole County HPSA | 2,024 (1.24) | 5,384 (15.65) | |
| County Mental Health Professional Shortage Area | < .001 | ||
| Not/Part of County Mental Health HPSA | 128,383 (78.72) | 13,915 (40.44) | |
| Whole County Mental Health HPSA | 34,707 (21.28) | 20,497 (59.56) | |
| County Low Education Status (ages 25–64) | < .001 | ||
| ≥20% High School Graduate | 161,555 (99.06) | 25,577 (74.33) | |
| <20% High School Graduate | 1,535 (0.94) | 8,835 (25.67) | |
| States (% urban/rural patients of state in italics) | < .001 | ||
| Arizona | 21,183 (12.99) | 929 (2.70) | |
| 95.80 | 4.20 | ||
| Florida | 62,429 (38.28) | 2,374 (6.90) | |
| 96.34 | 3.66 | ||
| Kentucky | 8,954 (5.49) | 8,350 (24.26) | |
| 51.75 | 48.25 | ||
| Maryland | 20,228 (12.40) | 896 (2.60) | |
| 95.76 | 4.24 | ||
| North Carolina | 37,237 (22.83) | 15,233 (44.27) | |
| 70.97 | 29.03 | ||
| Vermont | 183 (0.11) | 238 (0.69) | |
| 43.47 | 56.53 | ||
| Wisconsin | 12,876 (7.90) | 6,392 (18.57) | |
| 66.83 | 33.17 | ||
| Overall | 163,090 (82.58) | 34,412 (17.42) | < .001 |
Notes. Dataset: 2015 State Emergency Department Databases (SEDD) from HCUP (Healthcare Cost and Utilization Project) as administered by the Agency for Healthcare Research and Quality (AHRQ). P value is based on the χ2 test. The range for each income quartile is as follows; 0–25th: $1 - $41,999, 26th–50th: $42,000 - $51,999, 51st–75th: $52,000 - $67,999, 76th–100th: $68,000+. There were 204,384 observations before regression and 197,502 after taking out incomplete cases which results in 6,882 missing. Race/ethnicity is missing 1,197, gender is missing 23, insurance is missing 46, zip code income is missing 3,419, and disposition is missing 2,266 (these numbers are not mutually exclusive). The missing values make up only 3.3% of the total sample.