Predictors for Emergency Admission Among Homeless Metastatic Cancer Patients and Association of Social Determinants of Health with Negative Health Outcomes
Simple Summary
Abstract
1. Introduction
2. Methods
2.1. Study Design and Data Source
2.2. Study Population
2.3. Study Measurements
2.4. Statistical Analysis
2.4.1. Prediction Models and Risk Factor Analysis
2.4.2. Association with Outcomes
3. Results
3.1. Prediction Model and Risk Factors
3.2. PC Cohort and Homelessness
3.3. PC Cohort and PrbLA
3.4. BC Cohort and Homelessness
3.5. BC Cohort and PrbLA
3.6. LC Cohorts and Homelessness
3.7. LC Cohorts and PrbLA
3.8. CLOP Cohorts and Homelessness
3.9. Factors Associated with Risk of Homelessness and PrbLA and the Outcome of Anxiety and Depression and LOS Among PC, LC, BC, and CLOP Cancer Patients
4. Discussion
- While certain homeless individuals may seek treatment in hospitals either ambulatory or in-hospital admission care, others become ensnared in a detrimental cycle of homelessness and hospitalization [68,69]; nevertheless, this may not apply to cancer patients. However, the period preceding homelessness is associated with an increased likelihood of hospitalization [70]. Research shows that medical emergencies and SDOHs are associated with emergency admissions [70,71]. Furthermore, among cancer patients, this might be exacerbated by SDOHs and predictive factors such as transferred in or not from another facility, elective admission or not, deficiency anemia, alcohol dependence, weekend admission or not, and blood loss anemia. Additional research is needed to identify the outcome of infectious complications and healthcare-associated complications in this cohort that additionally impact the burden of illness among cancer patients.
- There is insufficient study on integrating data on homelessness with hospitalized or ambulatory care systems for cancer patients. Research on the financial demands and healthcare consumption patterns of cancer patients is limited, and the existing studies often concentrate on certain demographics or service categories. The current study indicates that patients utilized Medicaid or Medicare services more frequently before and after their enrollment in shelters, motels, relative housing, or their own residences, following recent housing insecurity that likely contributed to homelessness. Upon analyzing Medicaid, Medicare, and income-based housing status, it was found that residency in neighborhoods containing shelters, motels, relative housing, or personal housing—regardless of employment status—was frequently mandated.
- A deeper comprehension of the correlation between homelessness in cancer patients and healthcare systems should guide future initiatives. The use of hospitals during periods of homelessness may reveal the potential role of health systems in preventing or alleviating homelessness, the effects of housing instability on health and healthcare utilization, and the distinct implications of homelessness on healthcare consumption compared to standard hospitalization. This study addresses a significant information deficit by examining the temporal patterns of hospitalizations and emergency department visits related to individuals experiencing and getting out of homelessness.
- Homeless individuals frequently incur elevated healthcare expenses due to restricted access to primary care, increased dependence on emergency services, and heightened hospitalization rates for preventable conditions, resulting in substantial financial burdens for taxpayers and healthcare systems. Factors contributing to elevated healthcare expenditures encompass restricted access to primary care, resulting in several homeless individuals lacking health insurance, a primary care physician, or consistent healthcare access, which culminates in deferred treatment and exacerbated health issues. This elucidates the augmented utilization of emergency departments, resulting in recurrent visits and elevated expenses per patient.Homeless individuals exhibit a higher propensity for hospitalization, frequently for ailments that may be addressed in more economical environments, hence exacerbating overall healthcare expenditures related to mental health and substance addiction. Housing instability can aggravate health issues and result in increased healthcare consumption. A 2006 study revealed that the mean annual expenditure for a recurrent emergency department client facing homelessness was USD 64,000. Hospital expenses for homeless patients, both in total and per hospitalization, can be markedly greater than those for housed patients [72].Individuals experiencing housing instability are more prone to possess Medicaid coverage or lack insurance altogether, resulting in their care expenses frequently being borne by state programs and hospitals. In addition to direct healthcare expenses, homelessness incurs secondary economic consequences, including diminished productivity and heightened expenditures related to incarceration.
5. Conclusions
6. Limitations
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Metastatic Cancer Patients Reported with Homelessness | |
---|---|
n | 2635 |
AGE (mean (SD)) | 56.83 (9.94) |
Sex (%) | |
Female | 695 (26.4) |
RACE (%) | |
White | 1560.0 (60.5) |
Black | 665.0 (25.8) |
Hispanic | 165.0 (6.4) |
Asian and others | 190.0 (7.4) |
Median household income (based on current year) | |
0–25th percentile | 945.0 (46.2) |
26th to 50th percentile | 400.0 (19.6) |
51st to 75th percentile | 380.0 (18.6) |
76th to 100th percentile | 320.0 (15.6) |
Expected primary payer (%) | |
Medicare | 745.0 (28.3) |
Medicaid | 1495.0 (56.7) |
Private insurance | 150.0 (5.7) |
Self-pay, no charge, and other | 245.0 (9.3) |
Patient Location: NCHS Urban–Rural Code (%) | |
“Central” counties of metro areas of ≥1 million population | 1000.0 (46.3) |
“Fringe” counties of metro areas of ≥1 million population | 400.0 (18.5) |
Counties in metro areas of 250,000–999,999 population. | 515.0 (23.8) |
Counties in metro areas of 50,000–249,999 population. | 110.0 (5.1) |
Micropolitan counties and non-metropolitan or micropolitan counties | 135.0 (6.3) |
Indicator of a transfer out of the hospital | |
Transferred in | 330.0 (12.6) |
Elective admission (%) | 510.0 (52.3) |
Weekend admission (%) | 645.0 (24.5) |
Emergency admission (%) | 2040.0 (77.4) |
Weighted Elixhauser score (mean (SD)) | 22.25 (8.47) |
Prostate Cancer Patients Without Homelessness (Weighted) | Prostate Cancer Patients with Homelessness (Weighted) | p-Value | Prostate Cancer Patients Without PrbLA (Weighted) | Prostate Cancer Patients with PrbLA (Weighted) | p-Value | |
---|---|---|---|---|---|---|
n | 208,985 | 425 | 209,055 | 355 | ||
AGE (mean [SD]) | 71.5 (10.81) | 64.6 (8.55) | <0.001 | 71.5 (10.81) | 76.1 (10.20) | <0.001 |
Age groups (%) | <0.001 | 0.07 | ||||
45–54 | 10,110 (5.1) | 35 (8.9) | ||||
55–64 | 44,790 (22.5) | 170 (43.0) | 44,900 (22.6) | 60 (17.1) | ||
>65 | 143,919 (72.4) | 190 (48.1) | 143,820 (72.3) | 290 (82.9) | ||
RACE (%) | <0.001 | 0.56 | ||||
White | 140,409 (69.8) | 205 (50.0) | 140,375 (69.7) | 240 (69.6) | ||
Black | 35,530 (17.7) | 160 (39.0) | 35,615 (17.7) | 75 (21.7) | ||
Hispanic | 14,250 (7.1) | 20 (4.9) | 14,260 (7.1) | |||
Other | 11,000 (5.5) | 25 (6.1) | 11,005 (5.5) | 20 (5.8) | ||
Expected primary payer (%) | <0.001 | 0.003 | ||||
Medicare | 13,7394 (65.8) | 245 (57.6) | 137,334 (65.8) | 305 (85.9) | ||
Medicaid | 9305 (4.5) | 125 (29.4) | 9415 (4.5) | 15 (4.2) | ||
Private insurance | 54,095 (25.9) | 30 (7.1) | 54,100 (25.9) | 25 (7.0) | ||
Self-pay, no charge, and other | 7855 (3.8) | 25 (5.9) | 7870 (3.8) | |||
Median household income (based on current year) | <0.001 | 0.28 | ||||
0–25th percentile | 52,215 (25.4) | 190 (58.5) | 52,290 (25.4) | 115 (32.9) | ||
26th to 50th percentile | 51,980 (25.3) | 65 (20.0) | 51,945 (25.3) | 100 (28.6) | ||
51st to 75th percentile | 50,665 (24.6) | 45 (13.8) | 50,630 (24.6) | 80 (22.9) | ||
76th to 100th percentile | 50,730 (24.7) | 25 (7.7) | 50,700 (24.7) | 55 (15.7) | ||
Patient Location: NCHS Urban–Rural Code (%) | <0.001 | 0.31 | ||||
“Central” counties of metro areas of ≥1 million population | 61,895 (29.7) | 185 (53.6) | 61,975 (29.8) | 105 (29.6) | ||
“Fringe” counties of metro areas of ≥1 million population | 53,240 (25.6) | 65 (18.8) | 53,250 (25.6) | 55 (15.5) | ||
Counties in metro areas of 250,000–999,999 population. | 40,360 (19.4) | 60 (17.4) | 40,325 (19.4) | 95 (26.8) | ||
Counties in metro areas of 50,000–249,999 population | 19,265 (9.2) | 25 (7.2) | 19,250 (9.2) | 40 (11.3) | ||
Micropolitan counties and non-metropolitan or micropolitan counties | 33,565 (16.1) | 33,515 (16.1) | 60 (16.9) | |||
Admission type (%) | <0.001 | <0.001 | ||||
Elective | 83,355 (40.0) | 55 (12.9) | 83,375 (40.0) | 35 (9.9) | ||
Indicator of a transfer out of the hospital | 0.01 | <0.001 | ||||
Transferred out | 39,385 (18.9) | 125 (29.8) | 39,380 (18.9) | 130 (36.6) | ||
Weighted Elixhauser score mean (SD)) | 14.38 (10.93) | 13.62 (10.54) | 0.513 | 14.37 (10.93) | 17.8 (11.15) | 0.006 |
Length of stay (geometric mean) | 2.5 days | 4.7 days | <0.001 | 2.5 days | 4.1 days | <0.001 |
Total charge (geometric mean) | USD 41,476 | USD 46,340 | 0.7 | USD 41,476 | USD 31,652 | 0.02 |
In-hospital mortality (%) | 6895 (3.3) | 6885 (3.3) | 15 (4.2) | 0.66 | ||
Anxiety (%) | 14,345 (6.9) | 100 (23.5) | <0.001 | 14,390 (6.9) | 55 (15.5) | 0.005 |
Depression (%) | 16,550.0 (7.9) | 95.0 (22.4) | <0.001 | 16,585 (7.9) | 60 (16.9) | 0.003 |
Anxiety and depression (%) | 25,885.0 (12.4) | 155.0 (36.5) | <0.001 | 25,940 (12.4) | 100 (28.2) | <0.001 |
Emergency admission (%) | 102,535 (49.1) | 310.0 (72.9) | <0.001 | 102,625 (49.1) | 220 (62.0) | 0.05 |
Opioid abuse (%) | 1320.0 (0.6) | 20.0 (4.7) | <0.001 | |||
Opioid long-term use (%) | 2385.0 (1.1) | 15.0 (3.5) | 0.04 | 3905 (1.9) | 20 (5.6) | 0.01 |
aOR (95% CI) | Coefficient and 95% CIs (Back Transformed from Log Transformation) | ||
---|---|---|---|
Anxiety and Depression | LOS | ||
PCa homelessness status Non-homelessness Homelessness | Reference 5.14 (3.17–8.35) | Reference 1.96 (1.03–3.74) | |
Age | 0.99 (0.98–0.99) | 1.04 (1.00–1.01) | |
RACE (%) | |||
White | Reference | Reference | |
Black | 0.57 (0.51–0.63) | 1.22 (1.14–1.30) | |
Hispanic | 0.62 (0.54–0.72) | 1.07 (0.97–1.18) | |
Asian and Native American and other | 0.65 (0.53–0.79) | 1.06 (0.95–1.18) | |
Expected primary payer | |||
Medicare | Reference | Reference | |
Medicaid | 0.99 (0.85–1.15) | 1.23 (1.09–1.39) | |
Private insurance | 0.64 (0.58–0.70) | 0.87 (0.82–0.92) | |
Self-pay and no charge and other | 0.81 (0.68–0.98) | 0.76 (0.64–0.89) | |
Patient Location: NCHS Urban–Rural Code | |||
Central counties of metro areas of ≥1 million population | Reference | Reference | |
“Fringe” counties of metro areas of ≥1 million population | 0.94 (0.86–1.03) | 0.97 (0.97–1.12) | |
Counties in metro areas of 250,000–999,999 population. | 0.94 (0.85–1.04) | 0.96 (0.98–1.13) | |
Counties in metro areas of 50,000–249,999 population. | 0.89 (0.79–1.02) | 0.73 (0.98–1.16) | |
Micropolitan counties and non-metropolitan or micropolitan counties | 0.85 (0.76–0.94) | 0.71 (0.88–1.05) | |
Elixhauser comorbidity score | 0.99 (0.99–1.00) | 1.07 (1.04–1.05) | |
Median household income | |||
0–25th percentile | Reference | Reference | |
26th to 50th percentile | 0.97 (0.89–1.07) | 0.93 (0.68–1.28) | |
51st to 75th percentile | 0.98 (0.89–1.08) | 1.15 (0.83–1.58) | |
76th to 100th percentile | 0.95 (0.86–1.06) | 0.85 (0.59–1.24) | |
Indicator of a transfer out of the hospital Not transferred out | Reference | ||
Transferred out | 2.20 (2.07–2.34) |
Breast Cancer Patients Without Homelessness (Weighted) | Breast Cancer Patients with Homelessness (Weighted) | p-Value | Breast Cancer Patients Without PrbLA (Weighted) | Breast Cancer Patients with PrbLA (Weighted) | p-Value | |
---|---|---|---|---|---|---|
n | 116,760 | 320 | 116,855 | 225 | ||
AGE (mean [SD]) | 61.9 (14.19) | 54.7 (11.42) | <0.001 | 61.8 (14.19) | 70.8 (10.16) | <0.001 |
Age groups (%) | 0.008 | 0.008 | ||||
45–54 | 21,475.0 (22.3) | 90.0 (40.0) | 21,550.0 (22.4) | 15.0 (7.0) | ||
55–64 | 26,995.0 (28.0) | 70.0 (31.1) | 27,020.0 (28.1) | 45.0 (20.9) | ||
>65 | 47,790.0 (49.6) | 65.0 (28.9) | 47,700.0 (49.5) | 155.0 (72.1) | ||
RACE (%) | 0.07 | |||||
White | 74,400 (65.5) | 170.0 (53.1) | 74,401.0(65.5) | 165.0 (76.7) | ||
Black | 19,630.0 (17.3) | 95.0 (29.7) | 19,690.0 (17.3) | 35.0 (16.3) | ||
Hispanic | 10,280.0 (9.1) | 20.0 (6.2) | 10,295.0 (9.1) | |||
Other | 9260.0 (8.2) | 35.0 (10.9) | 9285.0 (8.2) | 10.0 (4.7) | ||
Expected primary payer (%) | ||||||
Medicare | 52,950.0 (45.4) | 110.0 (34.9) | 52,895.0 (45.3) | 165.0 (73.3) | ||
Medicaid | 15,620.0 (13.4) | 170.0 (54.0) | 15,770.0 (13.5) | 20.0 (8.9) | ||
Private insurance | 43,685.0 (37.5) | 43,655.0 (37.4) | 40.0 (17.8) | |||
Self-pay, no charge, and other | 4350.0 (3.7) | 25.0 (7.9) | 4375.0 (3.7) | |||
Median household income (based on current year) | <0.001 | 0.44 | ||||
0–25th percentile | 29,230.0 (25.4) | 130.0 (52.0) | 29,310.0 (25.5) | 50.0 (22.7) | ||
26th to 50th percentile | 27,325.0 (23.7) | 50.0 (20.0) | 27,340.0 (23.8) | 35.0 (15.9) | ||
51st to 75th percentile | 28,225.0 (24.5) | 50.0 (20.0) | 28,220.0 (24.5) | 55.0 (25.0) | ||
76th to 100th percentile | 30,275.0 (26.3) | 20.0 (8.0) | 30,215.0 (26.3) | 80.0 (36.4) | ||
Patient Location: NCHS Urban–Rural Code (%) | 0.36 | |||||
“Central” counties of metro areas of ≥1 million population | 38,900.0 (33.4) | 105.0 (41.2) | 38,945.0 (33.4) | 60.0 (26.7) | ||
“Fringe” counties of metro areas of ≥1 million population | 31,770.0 (27.3) | 80.0 (31.4) | 31,805.0 (27.3) | 45.0 (20.0) | ||
Counties in metro areas of 250,000–999,999 population. | 21,715.0 (18.6) | 55.0 (21.6) | 21,725.0 (18.6) | 45.0 (20.0) | ||
Counties in metro areas of 50,000–249,999 population | 8545.0 (7.3) | 8520.0 (7.3) | 25.0 (11.1) | |||
Micropolitan counties and non-metropolitan or micropolitan counties | 15,539.9 (13.3) | 15.0 (5.9) | 15,504.9 (13.3) | 50.0 (22.2) | ||
Admission type (%) | <0.001 | 0.46 | ||||
Elective | 42,520.0 (36.5) | 25.0 (7.8) | 42,475.0 (36.4) | 70.0 (31.1) | ||
Indicator of a transfer out of the hospital | <0.001 | <0.001 | ||||
Transferred out | 16,385.0 (14.0) | 115.0 (35.9) | 16,430.0 (14.1) | 70.0 (31.1) | ||
Weighted Elixhauser score mean (SD)) | 13.32 (10.20) | 13.67 (9.90) | 0.79 | 13.32 (10.20) | 14.89 (10.21) | 0.27 |
Length of stay (geometric mean) | 2.6 days | 4.1 days | 0.2 | 2.6 days | 4.9 days | <0.001 |
Total charge (geometric mean) | USD 40,622 | USD 48,644 | 0.2 | USD 40,622 | USD 34,636 | 0.18 |
In-hospital mortality (%) | 3770.0 (3.2) | 15.0 (4.7) | 0.5 | 3780.0 (3.2) | ||
Anxiety (%) | 18,505.0 (15.8) | 90.0 (28.1) | 0.009 | 18,555.0 (15.9) | 40.0 (17.8) | 0.74 |
Depression (%) | 16,750.0 (14.3) | 55.0 (17.2) | 0.538 | 16,730.0 (14.3) | 75.0 (33.3) | <0.001 |
Anxiety and depression (%) | 27,815.0 (23.8) | 115.0 (35.9) | 0.04 | 27,845.0 (23.8) | 85.0 (37.8) | 0.03 |
Emergency admission (%) | 58,760 (50.3) | 265.0 (82.8) | <0.001 | 58,899.9 (50.4) | 125.0 (55.6) | 0.54 |
Opioid abuse (%) | 825.0 (0.7) | 25.0 (7.8) | <0.001 | |||
Opioid long-term use (%) | 3000.0 (2.6) | 20.0 (8.9) | 0.008 |
aOR (95% CI) | |
---|---|
Anxiety | |
Breast cancer homelessness status Non-homelessness Homelessness | Reference 2.07 (1.06–4.03) |
Age | 0.97 (0.97–0.98) |
RACE (%) | |
White | Reference |
Black | 0.47 (0.42–0.54) |
Hispanic | 0.56 (0.48–0.66) |
Asian and Native American and other | 0.44 (0.34–0.56) |
Expected primary payer | |
Medicare | Reference |
Medicaid | 0.94 (0.81–1.09) |
Private insurance | 0.76 (0.68–0.85) |
Self-pay and no charge and other | 0.71 (0.57–0.88) |
Patient Location: NCHS Urban–Rural Code | |
Central counties of metro areas of ≥1 million population | Reference |
Fringe” counties of metro areas of ≥1 million population | 1.15 (1.04–1.28) |
Counties in metro areas of 250,000–999,999 population. | 1.10 (0.97–1.25) |
Counties in metro areas of 50,000–249,999 population. | 1.05 (0.89–1.24) |
Micropolitan counties and non-metropolitan or micropolitan counties | 0.99 (0.87–1.14) |
Elixhauser comorbidity score | 0.99 (0.99–1.00) |
Median household income | |
0–25th percentile | Reference |
26th to 50th percentile | 0.93 (0.84–1.04) |
51st to 75th percentile | 0.94 (0.84–1.05) |
76th to 100th percentile | 0.95 (0.85–1.08) |
Lung Cancer Patients Without Homelessness (Weighted) | Lung Cancer Patients with Homelessness (Weighted) | p-Value | Lung Cancer Patients Without PrbLA (Weighted) | Lung Cancer Patients with PrbLA (Weighted) | p-Value | |
---|---|---|---|---|---|---|
n | 401,665 | 1345 | 402,190 | 820 | ||
AGE (mean [SD]) | 69.09 (10.54) | 60.41 (8.27) | <0.001 | 69.06 (10.55) | 72.22 (9.59) | <0.001 |
Age groups (%) | <0.001 | 0.04 | ||||
45–54 | 27,065.0 (7.2) | 255.0 (20.4) | 27,290.0 (7.2) | 30.0 (3.8) | ||
55–64 | 92,695.0 (24.6) | 675.0 (54.0) | 93,220.0 (24.7) | 150.0 (19.2) | ||
>65 | 25,7625.0 (68.3) | 320.0 (25.6) | 257,345.0 (68.1) | 600.0 (76.9) | ||
Sex (%) | <0.001 | 0.005 | ||||
Female | 196,665.0 (49.0) | 265.0 (19.7) | 196,445.0 (48.8) | 485.0 (59.1) | ||
Depression (%) | 51,775.0 (12.9) | 210.0 (15.6) | 0.22 | 51,840.0 (12.9) | 145.0 (17.7) | 0.07 |
Anxiety (%) | 64,185.0 (16.0) | 265.0 (19.7) | 0.09 | 64,275.0 (16.0) | 175.0 (21.3) | 0.07 |
Anxiety and depression (%) | 93,070.0 (23.2) | 400.0 (29.7) | <0.001 | 0.88 | ||
Emergency admission (%) | 263,760.0 (65.7) | 1030.0 (76.6) | 0.88 | 264,245.0 (65.7) | 545.0 (66.5) | 0.88 |
Opioid abuse (%) | 4955.0 (1.2) | 80.0 (5.9) | <0.001 | 5020.0 (1.2) | 15.0 (1.8) | 0.59 |
Opioid long-term use (%) | 12,450.0 (3.1) | 50.0 (3.7) | 0.56 | 12,470.0 (3.1) | 30.0 (3.7) | 0.68 |
RACE (%) | <0.001 | 0.53 | ||||
White | 303,165.0 (77.6) | 855.0 (65.0) | 303,370.0 (77.5) | 650.0 (82.3) | ||
Black | 48,210.0 (12.3) | 310.0 (23.6) | 48,435.0 (12.4) | 85.0 (10.8) | ||
Hispanic | 17,900.0 (4.6) | 70.0 (5.3) | 17,950.0 (4.6) | 20.0 (2.5) | ||
Other | 21,510.0 (5.5) | 80.0 (6.1) | 21,555.0 (5.5) | 35.0 (4.4) | ||
Expected primary payer (%) | <0.001 | 0.015 | ||||
Medicare | 267,405.0 (66.7) | 425.0 (31.6) | 267,190.0 (66.5) | 640.0 (78.0) | ||
Medicaid | 39,045.0 (9.7) | 760.0 (56.5) | 39,755.0 (9.9) | 50.0 (6.1) | ||
Private insurance | 775,25.0 (19.3) | 60.0 (4.5) | 77,480.0 (19.3) | 105.0 (12.8) | ||
Self-pay, no charge, and other | 17,160.0 (4.3) | 100.0 (7.4) | 17,235.0 (4.3) | 25.0 (3.0) | ||
Median household income (based on current year) | <0.001 | 0.537 | ||||
0–25th percentile | 119,805.1 (30.2) | 530.0 (48.6) | 120,130.1 (30.3) | 205.0 (25.5) | ||
26th to 50th percentile | 108,425.0 (27.4) | 185.0 (17.0) | 108,370.0 (27.3) | 240.0 (29.8) | ||
51st to 75th percentile | 91,905.0 (23.2) | 215.0 (19.7) | 91,910.0 (23.2) | 210.0 (26.1) | ||
76th to 100th percentile | 76,109.9 (19.2) | 160.0 (14.7) | 76,119.9 (19.2) | 150.0 (18.6) | ||
Patient Location: NCHS Urban–Rural Code (%) | <0.001 | 0.472 | ||||
“Central” counties of metro areas of ≥1 million population | 103,600.0 (25.8) | 440.0 (38.8) | 103,805.0 (25.9) | 235.0 (28.7) | ||
“Fringe” counties of metro areas of ≥1 million population | 101,795.0 (25.4) | 240.0 (21.1) | 101,830.0 (25.4) | 205.0 (25.0) | ||
Counties in metro areas of 250,000–999,999 population. | 80,565.0 (20.1) | 320.0 (28.2) | 807,55.0 (20.1) | 130.0 (15.9) | ||
Counties in metro areas of 50,000–249,999 population | 40,145.0 (10.0) | 85.0 (7.5) | 401,10.0 (10.0) | 120.0 (14.6) | ||
Micropolitan counties and non-metropolitan or micropolitan counties | 74,875.0 (18.7) | 50.0 (4.4) | 747,95.0 (18.6) | 130.0 (15.9) | ||
Admission type (%) | <0.001 | 0.15 | ||||
Elective | 75,095.0 (18.7) | 125.0 (9.3) | 75,105.0 (18.7) | 115.0 (14.0) | ||
Indicator of a transfer out of the hospital | <0.001 | 0.04 | ||||
Transferred out | 86,370.0 (21.5) | 475.0 (35.3) | 86,605.0 (21.6) | 240.0 (29.3) | ||
Weighted Elixhauser score mean (SD)) | 19.10 (9.97) | 18.19 (9.79) | 0.14 | 19.10 (9.97) | 18.99 (9.51) | 0.88 |
Length of stay (geometric mean) | 3.8 days | 6.2 days | <0.001 | 3.8 days | 4.4 days | 0.09 |
Total charge (geometric mean) | USD 42,055 | USD 58,251 | <0.001 | USD 42,055 | USD 41,190 | 0.81 |
In-hospital mortality (%) | 34,960.0 (8.7) | 110.0 (8.2) | 0.76 | 35,030.0 (8.7) | 40.0 (4.9) | 0.07 |
Depression (%) | 51,775.0 (12.9) | 210.0 (15.6) | 0.22 | 51,840.0 (12.9) | 145.0 (17.7) | 0.07 |
Anxiety (%) | 64,185.0 (16.0) | 265.0 (19.7) | 0.09 | 64,275.0 (16.0) | 175.0 (21.3) | 0.07 |
Anxiety and depression (%) | 93,070.0 (23.2) | 400.0 (29.7) | <0.001 | 0.88 | ||
Emergency admission (%) | 263,760.0 (65.7) | 1030.0 (76.6) | 0.88 | 264,245.0 (65.7) | 545.0 (66.5) | 0.88 |
Opioid abuse (%) | 4955.0 (1.2) | 80.0 (5.9) | <0.001 | 5020.0 (1.2) | 15.0 (1.8) | 0.59 |
Opioid long-term use (%) | 12,450.0 (3.1) | 50.0 (3.7) | 0.56 | 12,470.0 (3.1) | 30.0 (3.7) | 0.68 |
aOR (95% CI) | Coefficient and 95% CIs (Back Transformed from Log Transformation) | |
---|---|---|
Anxiety and Depression | LOS | |
Lung cancer homelessness status Non-homelessness Homelessness | Reference 1.38 (1.02–1.85) | Reference 1.84 (1.40–2.42) |
Age | 0.97 (0.97–0.97) | 0.99 (0.99–0.99) |
RACE (%) | ||
White | Reference | Reference |
Black | 0.51 (0.48–0.55) | 1.22 (1.05–1.17) |
Hispanic | 0.66 (0.60–0.72) | 1.07 (0.93–1.09) |
Asian and Native American and other | 0.53 (0.47–0.59) | 1.13 (1.04–1.23) |
Expected primary payer | ||
Medicare | Reference | Reference |
Medicaid | 0.91 (0.85–0.97) | 0.91 (0.85–0.97) |
Private insurance | 0.78 (0.74–0.83) | 0.89 (0.84–0.93) |
Self-pay and no charge and other | 0.65 (0.59–0.72) | 0.67 (0.59–0.75) |
Patient Location: NCHS Urban–Rural Code | ||
Central counties of metro areas of ≥1 million population | Reference | Reference |
Fringe” counties of metro areas of ≥1 million population | 1.03 (0.96–1.09) | 0.97 (0.92–1.02) |
Counties in metro areas of 250,000–999,999 population. | 1.04 (0.96–1.12) | 1.00 (0.95–1.06) |
Counties in metro areas of 50,000–249,999 population. | 1.03 (0.95–1.13) | 1.00 (0.94–1.08) |
Micropolitan counties and non-metropolitan or micropolitan counties | 0.92 (0.85–0.99) | 0.88 (0.83–0.94) |
Elixhauser comorbidity score | 0.98 (0.98–0.99) | 1.02 (1.02–1.03) |
Median household income | ||
0–25th percentile | Reference | Reference |
26th to 50th percentile | 0.99 (0.95–1.05) | 0.95 (0.90–0.99) |
51st to 75th percentile | 1.01 (0.96–1.07) | 0.94 (0.89–0.99) |
76th to 100th percentile | 0.99 (0.93–1.07) | 0.93 (0.87–0.98) |
Indicator of a transfer out of the hospital Non-transferred out | Reference | |
Transferred out | 2.20 (2.07–2.34) |
CLOP Patients Without Homelessness (Weighted) | CLOP Patients with Homelessness (Weighted) | p-Value | |
---|---|---|---|
n | 53,890 | 375 | |
AGE (mean [SD]) | 64.06 (12.22) | 54.85 (8.53) | <0.001 |
Female (%) | 0.001 | ||
15,540.0 (28.8) | 45.0 (12.0) | ||
Age groups (%) | <0.001 | ||
45–54 | 7700.0 (16.1) | 130.0 (41.3) | |
55–64 | 15,970.0 (33.4) | 165.0 (52.4) | |
>65 | 24,105.0 (50.5) | 20.0 (6.3) | |
RACE (%) | 0.09 | ||
White | 38,965.0 (74.9) | 245.0 (67.1) | |
Black | 5500.0 (10.6) | 70.0 (19.2) | |
Hispanic | 3360.0 (6.5) | 30.0 (8.2) | |
Other | 4220.0 (8.1) | 20.0 (5.5) | |
Expected primary payer (%) | <0.001 | ||
Medicare | 27,195.0 (50.6) | 85.0 (22.7) | |
Medicaid | 8130.0 (15.1) | 220.0 (58.7) | |
Private insurance | 15,540.0 (28.9) | 25.0 (6.7) | |
Self-pay, no charge, and other | 2930.0 (5.4) | 45.0 (12.0) | |
Median household income (based on current year) | 0.415 | ||
0–25th percentile | 14,990.0 (28.3) | 115.0 (37.7) | |
26th to 50th percentile | 13,965.0 (26.4) | 75.0 (24.6) | |
51st to 75th percentile | 12,725.0 (24.0) | 60.0 (19.7) | |
76th to 100th percentile | 11,255.0 (21.3) | 55.0 (18.0) | |
Patient Location: NCHS Urban–Rural Code (%) | 0.032 | ||
“Central” counties of metro areas of ≥1 million population | 15,485.0 (28.8) | 115.0 (37.1) | |
“Fringe” counties of metro areas of ≥1 million population | 13,835.0 (25.7) | 55.0 (17.7) | |
Counties in metro areas of 250,000–999,999 population. | 10,960.0 (20.4) | 95.0 (30.6) | |
Counties in metro areas of 50,000–249,999 population | 5150.0 (9.6) | 30.0 (9.7) | |
Micropolitan counties and non-metropolitan or micropolitan counties | 8315.0 (15.5) | 15.0 (4.8) | |
Admission type (%) | <0.001 | ||
Elective | 19,600.0 (36.5) | 45.0 (12.0) | |
Indicator of a transfer out of the hospital | 0.002 | ||
Transferred out | 10,335.0 (19.2) | 125.0 (33.3) | |
Weighted Elixhauser score mean (SD) | 15.71 (9.46) | 14.59 (10.76) | 0.370 |
Length of stay (geometric mean) | 3.7 days | 8.01 days | <0.001 |
Total charge (geometric mean) | USD 48,983 | USD 57,449 | 0.2 |
Anxiety (%) | 7380.0 (13.7) | 105.0 (28.0) | <0.001 |
Depression (%) | 6515.0 (12.1) | 80.0 (21.3) | 0.02 |
Anxiety and depression (%) | 11,140.0 (20.7) | 145.0 (38.7) | <0.001 |
Emergency admission (%) | 26,285.0 (48.8) | 245.0 (65.3) | <0.001 |
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Satheeshkumar, P.S.; Sonis, S.T.; Epstein, J.B.; Pili, R. Predictors for Emergency Admission Among Homeless Metastatic Cancer Patients and Association of Social Determinants of Health with Negative Health Outcomes. Cancers 2025, 17, 1121. https://doi.org/10.3390/cancers17071121
Satheeshkumar PS, Sonis ST, Epstein JB, Pili R. Predictors for Emergency Admission Among Homeless Metastatic Cancer Patients and Association of Social Determinants of Health with Negative Health Outcomes. Cancers. 2025; 17(7):1121. https://doi.org/10.3390/cancers17071121
Chicago/Turabian StyleSatheeshkumar, Poolakkad S., Stephen T. Sonis, Joel B. Epstein, and Roberto Pili. 2025. "Predictors for Emergency Admission Among Homeless Metastatic Cancer Patients and Association of Social Determinants of Health with Negative Health Outcomes" Cancers 17, no. 7: 1121. https://doi.org/10.3390/cancers17071121
APA StyleSatheeshkumar, P. S., Sonis, S. T., Epstein, J. B., & Pili, R. (2025). Predictors for Emergency Admission Among Homeless Metastatic Cancer Patients and Association of Social Determinants of Health with Negative Health Outcomes. Cancers, 17(7), 1121. https://doi.org/10.3390/cancers17071121