Fig 1.
Chronic liver disease was based on yes responses to the following questions: “Has a doctor or other health professional ever told you that you had any kind of chronic, or long-term liver condition?” or “During the past 12 months, have you been told by a doctor or other health professional that you had any kind of liver condition?”.
Fig 2.
Analytic model for latent class analysis.
Identification of unique risk groups (latent classes) was based on the pattern and probability of responses to the 13 questions about different healthcare barriers. The association between different risk groups and recurrent acute care use was then assessed by adjusting for covariates.
Table 1.
Sociodemographic and health characteristics of the total sample and by risk group (N = 5,062).
Table 2.
Model selection using fit and diagnostic statistics.
Fig 3.
Prevalence of healthcare barriers in the four group latent class model (N = 5,062).
Source: National Health Interview Survey, 2011–2017. Weighted prevalence is reported for each risk group (latent class) on the y-axis. Specific barriers are included on the x-axis. The largest group, minimal barriers (light solid line), included a sample of 3,953 (weighted 3,703,788) adults with chronic liver disease who had the lowest frequency of healthcare barriers. The second largest group, unaffordability (dark solid line), included 540 (weighted 506,347) adults who reported frequent challenges affording healthcare. The third largest group, care delays (dotted line), consisted of 328 (weighted 307,013) adults who reported having delays in care due to organizational barriers within the healthcare system. The fourth group, inability to establish care (dash line), included 240 (weighted 225,296) adults who reported having frequent barriers at entry to healthcare.
Table 3.
Prevalence of health care barriers in the total sample and by risk group (N = 5,062).
Table 4.
Association of Sociodemographic and health characteristics and risk group membership (n = 4,646).
Fig 4.
Adjusted probability of recurrent acute care use by risk group.
Source: National Health Interview Survey, 2011–2017. Abbreviations: aOR, adjusted odds ratio. All estimates are from a weighted sample. Probabilities of recurrent acute care use (y-axis) are obtained from a logistic regression model (n = 4,645) that adjusted for sex, age, race or ethnicity, number of comorbidities, fair or poor health, functional limitation due to health, employment, poverty, and insurance. Adjusted probabilities of recurrent acute care use are reported for each risk group (x-axis). Compared to the reference group (minimal barriers), the aOR were as follows: group 2 (affordability) aOR, 1.48; 95% CI, 1.11–1.97; P = 0.007; group 3 (care delays) aOR, 1.50; 95% CI, 1.07–2.11; P = 0.019); group 4 (inability to establish care) aOR 1.85; 95% CI, 1.23–2.79; P = 0.003.
Fig 5.
Adjusted probability of recurrent acute care use by risk group and insurance.
Source: National Health Interview Survey, 2011–2017. Abbreviations: aOR, adjusted odds ratio. All estimates are from a weighted sample. Probabilities of recurrent acute care use (y-axis) are obtained from a logistic regression model (n = 4,645) that adjusted for sex, age, race or ethnicity, number of comorbidities, fair or poor health, functional limitation due to health, employment, poverty, and insurance. Adjusted probabilities of recurrent acute care use are reported for each risk group (x-axis) and by insurance type. Compared to the reference group (minimal barriers), the aOR were as follows: group 2 (affordability) aOR, 1.48; 95% CI, 1.11–1.97; P = 0.007; group 3 (care delays) aOR, 1.50; 95% CI, 1.07–2.11; P = 0.019); group 4 (inability to establish care) aOR 1.85; 95% CI, 1.23–2.79; P = 0.003.
Table 5.
Odds ratios and predicted probabilities of recurrent acute care use by risk group.