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Table 2 Prevalence of medical debt outcomes and associations between guarantor characteristics and medical debt outcomes, 2015 CarePayment sample

From: Demographic and service-use profiles of individuals using the CarePayment program for hospital-related medical debt: results from a nationwide survey of guarantors

Medical Debt Outcome Descriptive Results Results of Logistic Regression Modelsa
Percent of Respondents Household Income
(Comparison: $80,000 or more)b
Amount of debt
(Comparison: Less than $2,000)b
Service Usageb
  Less than $20,000 $20,000–39,999 $40,000–59,999 $60,000–79,999 $2,000–3,999 $4,000–7,999 $8,000–9,999 $10,000 or more First-time CP User (Y) Other medical debt (Y)
Because of medical bills, in the last two years…
Unable to pay for necessities (food, heat, rent) 14.4 8.0** 4.8* 4.4* x x x x 2.4* x 2.5*
Used up all your savings 38.5 2.4* 2.3* 2.5* 2.0* x x x 4.4** 1.6* 2.8**
Taken out a mortgage or loan 9.6 x x x x x x x 4.3** x 2.3*
Taken on credit card debt 30.9 x x x x x x x 2.02* x 4.2**
Thought about filing for bankruptcy 8.9 x x 3.2* x x x 3.4* x x 3.2*
Had to declare bankruptcy 2.8 x x x x x x x x x x
Received a lower credit rating 20.9 3.1* 2.0* x x x x x x x 3.0**
Delayed education or career plans 9.6 3.5* x x 3.4* x x x 3.8* 2.1* 2.9*
Because of cost, in the past 12 months…  
Did not fill a prescription 28.9 x x x x x x x 2.1* x 3.2**
Skipped a medical test, treatment or follow-up recommended by a doctor 32.9 x x x x x x x x 1.6* 3.4**
Skipped doses of a prescription medicine or cut pills 24.6 x 2.3* x x x x x 2.1* x 3.1**
Had a medical problem but did not go to a doctor/clinic 30.3 x 1.8* 2.6** x x x x x x 2.9**
Did not see a specialist when you/your doctor thought you needed one 24.0 x x x x x 1.8* x 2.2* x 2.1**
Delayed or skipped preventive care screening 24.6 x x x x x x x 2.1* 1.8* 2.7**
In the past 12 months…
Problems paying/unable to pay medical bills 59.5 3.2** 2.5** 2.5** x x x x x x 2.8**
Had to change way of life significantly in order to pay medical bills 38.7 4.9** 4.4** 2.6* 2.7* x x x 8.7** x 2.4**
Contacted by a collection agency about owing money for medical bills 19.9 x x x x x x x x 1.5* 3.1**
  1. aEach row represents one logistic regression model with outcome variable representing the odds of the respondent reporting the negative outcome listed in the first column
  2. bCells present Odds Ratios from the full model for significant co-variates only
  3. *p < 0.05; **p < .001; x: p > 0.05