Summary
Background
Long-term trends in hospitalization burden, healthcare utilization, and costs of chronic liver disease (CLD) in the United States remain poorly characterized. Using statewide hospital discharge data, we quantified trends from 2005 to 2018 and projected future burden through 2035 across demographic subgroups.
Methods
We used average annual percent change (AAPC) to quantify trends in hospitalized patients, hospitalizations, deaths, along with age-standardized rates (ASHPR, ASHR, and ASMR); hospitalizations per patient-year, average length of stay, 30-day readmission, in-hospital mortality; and inflation-adjusted hospital charges (2019 US dollars). Analyses were conducted overall and for hepatitis B virus(HBV), hepatitis C virus(HCV), alcohol-associated liver disease(ALD), and metabolic dysfunction-associated steatotic liver disease (MASLD).
Findings
From 2005 to 2018, hospitalized CLD patients increased from 71,214 to 122,810 (AAPC, 4.37%; 95% CI, 3.87%–4.88%), and deaths from 11,455 to 24,560 (6.02%; 4.20%–7.86%). ASHPR increased from 275.12 to 377.88 per 100,000, and ASMR from 45.53 to 74.77. Hospitalizations and charges increased from 116,482 to 185,268 and $9.63 billion to $18.63 billion, while in-hospital mortality declined (AAPC, −7.02%; 95% CI, −8.72%–5.30%). MASLD- and ALD-related hospitalizations increased, whereas HBV- and HCV-related hospitalizations declined. Men had higher hospitalization and mortality rates, particularly for ALD. Hispanic populations had the fastest-rising burden, driven by MASLD; HBV burden was concentrated among non-Hispanic Asian populations, whereas overall CLD and ALD-related mortality were highest among non-Hispanic White populations.
Interpretation
Findings highlight the need for targeted prevention and screening, early management of metabolic and alcohol-related risk factors, and equitable access to liver care.
Funding
No funding.
Keywords: Chronic liver disease, Metabolic dysfunction-associated steatotic liver disease, Alcohol-associated liver disease, Hospitalization trends, Healthcare utilization, Healthcare costs
Research in context.
Evidence before this study
We searched PubMed for articles published in English from database inception to June 24, 2025, using the terms “chronic liver disease”, “cirrhosis”, “metabolic dysfunction-associated steatotic liver disease”, “non alcoholic fatty liver disease”, “alcohol-associated liver disease”, “hepatitis B”, “hepatitis C”, “hospitalization”, “healthcare utilization”, “healthcare costs”, “mortality”, “trends”, “projections”, “California”, and “United States”. We also screened the reference lists of relevant studies. However, evidence integrating long-term trends in hospitalization burden, healthcare utilization, economic impact, etiologic changes, and sociodemographic disparities was limited, and the future implications for healthcare planning remained uncertain.
Added value of this study
This study extends the existing evidence by integrating long-term changes in CLD-related hospitalization burden, healthcare utilization, economic impact, etiologic patterns, and sociodemographic disparities in a large and diverse population. It provides a more complete understanding of how these factors have evolved together and shows that improvements in inpatient outcomes can coexist with an increasing overall clinical and economic burden. This distinction is important for future healthcare planning and resource allocation.
Implications of all the available evidence
These findings indicate an epidemiologic transition in CLD toward metabolic and alcohol-related etiologies and support integrated prevention strategies targeting metabolic risk factors and alcohol use. The projected increases in healthcare utilization, costs, morbidity, and mortality highlight the need for proactive healthcare planning. The substantial sociodemographic disparities observed suggest that interventions should also prioritize populations experiencing the greatest burden and address structural inequities in access to care. Future research should validate these trends in other populations, assess the effects of emerging therapies and public health interventions, and update the projections as more recent data become available.
Introduction
Chronic liver disease (CLD) is a growing public health challenge worldwide and in the United States, contributing substantially to morbidity, mortality, and healthcare expenditures.1, 2, 3 According to the Global Burden of Disease (GBD) Study, there were an estimated 1.7 billion prevalent cases, 58.4 million incident cases, and 1.4 million deaths attributable to CLD worldwide in 2021.4 Despite advances in prevention and treatment, the overall burden of CLD continues to rise, placing increasing pressure on healthcare systems.
In recent years, the etiologic spectrum of CLD has shifted considerably.5, 6, 7 Metabolic dysfunction-associated steatotic liver disease (MASLD)7,8 and alcohol-related liver disease (ALD)9,10 have emerged as major drivers of liver-related morbidity, while the epidemiology of viral hepatitis has evolved, with declines in hepatitis C virus (HCV) infection following the introduction of direct-acting antiviral (DAA) therapies,11,12 and reductions in hepatitis B virus (HBV) infection associated with the widespread implementation of hepatitis B vaccination.13,14 At the same time, different CLD etiologies are characterized by distinct sociodemographic profiles. For example, HBV infection is more prevalent among immigrants from endemic areas such as the Asia–Pacific region, whereas MASLD is more common in Western populations and is particularly prevalent among Hispanic populations in the United States.15 These shifts may alter the demographic composition of affected populations and reshape patterns of disease burden, healthcare utilization, and costs. Understanding these dynamics is essential for informing equitable healthcare planning and resource allocation.
California, the most populous and ethnically diverse state in the United States, provides a unique setting to examine these evolving trends. However, comprehensive population-based analyses of long-term trends in CLD burden, healthcare utilization, and healthcare costs across the state remain limited. Therefore, using statewide inpatient discharge data from the California Department of Health Care Access and Information (HCAI), we aimed to (1) characterize temporal trends in CLD burden, including hospitalized patients, hospitalizations, and mortality (inpatient and overall), overall and by major etiology; (2) quantify healthcare utilization and inflation-adjusted hospital charges; (3) assess sociodemographic disparities across race and ethnicity, sex, age group, and county-level income quartiles; and (4) project future trends in CLD burden and associated costs.
Methods
Study design and data source
We conducted a retrospective, population-based study using statewide hospital discharge data from the California Department of Health Care Access and Information (HCAI) Patient Discharge Database from 2005 to 2019. The database provides near-complete coverage of inpatient discharges from licensed nonfederal acute care hospitals in California and is widely used for population-based epidemiologic and health services research.16 All conditions were identified using the International Classification of Diseases, Ninth and Tenth Revisions (ICD-9 and ICD-10) and Current Procedural Terminology (CPT) codes (Supplementary Table S1). Data from 2019 were used for descriptive analyses but were excluded from trend analyses and long-term projections because of incomplete reporting and administrative lag, which may lead to underestimation of disease burden. Mortality data were obtained through linkage with the California Department of Public Health Vital Statistics Death Records using unique patient identifiers. The study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline.
Study population and CLD definitions
Adult patients (age ≥ 18 years) hospitalized with CLD were included between 2005 and 2019. CLD was defined based on any-listed diagnosis codes recorded during hospitalization. CLD categories encompassed a comprehensive range of etiologies, including HBV, HCV, ALD, MASLD, autoimmune hepatitis, chronic toxic hepatitis, Wilson disease, hemochromatosis, Budd–Chiari syndrome, and primary biliary cholangitis, as well as advanced disease categories of cirrhosis and hepatocellular carcinoma (HCC) with any etiology. Analyses focused on overall CLD as well as major etiology-specific categories (HBV, HCV, ALD, and MASLD). Because the MASLD nomenclature was introduced in 2023, MASLD cases during the study period were identified using administrative diagnosis codes for non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH). Cardiometabolic risk factors were identified using diagnosis codes and relevant medication records for diabetes, hypertension, dyslipidemia, and overweight/obesity. In etiology-specific analyses, disease categories were not mutually exclusive; patients with multiple CLD-related diagnostic codes were included in each corresponding etiology group to capture the full burden of each condition.
Outcome measures
Outcomes of interest included measures of CLD burden, healthcare utilization, and economic burden. CLD burden was assessed using annual counts of unique hospitalized patients and CLD-related deaths, as well as age-standardized hospitalized patient, hospitalization, and long-term mortality rates (ASHPR, ASHR, and ASMR). Healthcare utilization outcomes included the number of hospitalizations, hospitalizations per patient-year, average length of stay (ALOS), 30-day readmission rate, and in-hospital mortality, reflecting both healthcare resource use and utilization efficiency. Economic outcomes comprised total hospital charges, charges per hospitalization, and charges per patient. All hospital charges were inflation-adjusted to 2019 U.S. dollars using the annual Consumer Price Index for Medical Care (CPIMEDNS).
Statistical analysis
Descriptive statistics were used to summarize annual characteristics of the study population. For presentation purposes, baseline characteristics are shown in 3-year intervals in the main text, with annual estimates provided in the Supplementary Materials. Continuous variables were presented as means with standard deviations (SD), and categorical variables as counts with percentages. Age-standardized rates were calculated using the direct standardization method with the 2000 US Census Standard Population (aged ≥ 18 years) as the reference. Rates were reported per population with Poisson-based 95% confidence intervals (CIs), where applicable. Temporal trend analyses were conducted using annual data from 2005 to 2018. Joinpoint regression models were used to identify significant inflection points and estimate the annual percent change (APC) for each segment and the average annual percent change (AAPC) for the overall study period. For presentation purposes, selected years are shown in the tables. Long-term projections of study outcomes through 2035 were estimated using linear regression models fitted to data from 2005 to 2018. The projections assumed that the historical trends observed during the study period would continue throughout the projection period, and 95% prediction intervals were calculated to reflect the uncertainty of the projected estimates. All analyses were conducted using R version 4.4.2 (R Foundation for Statistical Computing). All statistical tests were 2-sided, and P < 0.05 was considered statistically significant.
Secondary analyses
Secondary analyses were conducted to examine differences across subgroups defined by age (18–44, 45–64, and ≥65 years), sex (female and male), race and ethnicity (non-Hispanic White, non-Hispanic Black, non-Hispanic Asian, Hispanic [all races], and other), and county-level income quartiles (Q1–Q4).
Ethics statement
The study was conducted in accordance with the Declaration of Helsinki (2013) and was approved by the Institutional Review Boards at Stanford University, Stanford, California, USA (IRB No. 13927), and the California Department of Public Health, Sacramento, California, USA (IRB No. 14-10-1748). The requirement for informed consent was waived because the study used deidentified administrative data.
Role of the funding source
The funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report.
Results
Characteristics of the study population
A total of 1,438,836 unique patients hospitalized with CLD were identified from 2005 to 2019 (Table 1). The mean (SD) age increased from 54.86 (13.95) years in 2005–2007 to 57.35 (15.34) years in 2017–2019. The number and proportion of female patients increased from 93,768 (42.3%) to 149,731 (44.5%). Hispanic patients increased from 53,643 (24.2%) to 103,557 (30.8%), whereas non-Hispanic White patients decreased from 119,610 (54.0%) to 157,795 (46.9%). The number and proportion of patients in the lowest income quartile increased from 17,408 (8.0%) to 55,177 (16.4%). The number and proportion covered by Medicare increased from 75,318 (34.0%) to 131,143 (39.0%), and those covered by Medicaid increased from 51,983 (23.5%) to 106,572 (31.7%). Regarding etiology, HCV remained the most common etiology overall, although its number and proportion declined from 103,584 (46.8%) in 2005–2007 to 87,658 (26.1%) in 2017–2019. In contrast, MASLD increased from 31,880 (14.4%) to 74,202 (22.1%). Comorbidity burden increased during the study period. The mean Charlson Comorbidity Index (CCI) increased from 3.22 to 4.04, while obesity increased from 23,718 (10.7%) to 68,377 (20.3%), and chronic kidney disease from 15,736 (7.1%) to 53,642 (16.0%). Detailed characteristics of hospitalized patients with CLD and CLD-related admissions by year are presented in Supplementary Tables S2 and S3.
Table 1.
Demographic and clinical characteristics of patients hospitalized with chronic liver disease.
| Characteristics | Overall (n = 1,438,836) | 2005–2007 (n = 221,498) | 2008–2010 (n = 258,767) | 2011–2013 (n = 296,114) | 2014–2016 (n = 326,159) | 2017–2019 (n = 336,298) |
|---|---|---|---|---|---|---|
| Age group, year | ||||||
| <40 | 113,521 (7.9) | 14,880 (6.7) | 17,998 (7.0) | 21,717 (7.3) | 26,459 (8.1) | 32,467 (9.7) |
| 40-55 | 506,318 (35.2) | 101,556 (45.8) | 104,305 (40.3) | 103,189 (34.8) | 100,956 (31.0) | 96,312 (28.6) |
| 55-65 | 657,140 (45.7) | 82,381 (37.2) | 109,089 (42.2) | 137,956 (46.6) | 161,418 (49.5) | 166,296 (49.4) |
| ≥65 | 161,857 (11.2) | 22,681 (10.2) | 27,375 (10.6) | 33,252 (11.2) | 37,326 (11.4) | 41,223 (12.3) |
| Female | 623,557 (43.3) | 93,768 (42.3) | 111,340 (43.0) | 128,033 (43.2) | 140,685 (43.1) | 149,731 (44.5) |
| Race and ethnicity | ||||||
| Non-Hispanic White | 727,280 (50.5) | 119,610 (54.0) | 136,132 (52.6) | 151,400 (51.1) | 162,343 (49.8) | 157,795 (46.9) |
| Non-Hispanic Black | 137,750 (9.6) | 22,788 (10.3) | 25,685 (9.9) | 28,780 (9.7) | 31,382 (9.6) | 29,115 (8.7) |
| Non-Hispanic Asian | 120,791 (8.4) | 17,865 (8.1) | 21,186 (8.2) | 24,956 (8.4) | 27,601 (8.5) | 29,183 (8.7) |
| Hispanic | 397,881 (27.7) | 53,643 (24.2) | 67,368 (26.0) | 81,016 (27.4) | 92,297 (28.3) | 103,557 (30.8) |
| Others | 55,129 (3.8) | 7592 (3.4) | 8396 (3.2) | 9962 (3.4) | 12,536 (3.8) | 16,643 (4.9) |
| County-level income quartiles | ||||||
| Q1 (lowest) | 225,161 (15.7) | 17,408 (8.0) | 42,663 (16.7) | 53,930 (18.3) | 55,983 (17.2) | 55,177 (16.4) |
| Q2 | 164,254 (11.5) | 38,907 (17.8) | 25,281 (9.9) | 26,320 (8.9) | 32,993 (10.1) | 40,753 (12.1) |
| Q3 | 590,851 (41.3) | 77,225 (35.4) | 92,607 (36.3) | 129,225 (43.9) | 144,521 (44.3) | 147,273 (43.8) |
| Q4 (highest) | 449,637 (31.4) | 84,722 (38.8) | 94,565 (37.1) | 84,962 (28.9) | 92,379 (28.3) | 93,009 (27.7) |
| Insurance type | ||||||
| Medicare | 534,685 (37.2) | 75,318 (34.0) | 90,514 (35.0) | 111,614 (37.7) | 126,096 (38.7) | 131,143 (39.0) |
| Medicaid | 390,151 (27.1) | 51,983 (23.5) | 59,236 (22.9) | 66,492 (22.5) | 105,868 (32.5) | 106,572 (31.7) |
| Private | 374,805 (26.1) | 63,465 (28.7) | 72,236 (27.9) | 75,255 (25.4) | 79,125 (24.3) | 84,724 (25.2) |
| Self-pay | 58,761 (4.1) | 13,317 (6.0) | 16,392 (6.3) | 17,236 (5.8) | 6186 (1.9) | 5630 (1.7) |
| Others | 80,217 (5.6) | 17,381 (7.8) | 20,348 (7.9) | 25,486 (8.6) | 8852 (2.7) | 8150 (2.4) |
| Rural hospital | 51,001 (3.7) | 7730 (3.8) | 9060 (3.8) | 11,320 (4.1) | 11,694 (3.7) | 11,197 (3.4) |
| Etiology of CLD | ||||||
| HBV | 107,313 (7.5) | 21,820 (9.9) | 21,800 (8.4) | 21,983 (7.4) | 20,502 (6.3) | 21,208 (6.3) |
| HCV | 539,898 (37.5) | 103,584 (46.8) | 113,527 (43.9) | 120,296 (40.6) | 114,833 (35.2) | 87,658 (26.1) |
| ALD | 324,112 (22.5) | 54,319 (24.5) | 59,402 (23.0) | 64,409 (21.8) | 71,322 (21.9) | 74,660 (22.2) |
| MASLD | 291,580 (20.3) | 31,880 (14.4) | 47,618 (18.4) | 64,937 (21.9) | 72,943 (22.4) | 74,202 (22.1) |
| Liver severity | ||||||
| No cirrhosis | 962,963 (66.9) | 141,166 (63.7) | 166,893 (64.5) | 191,011 (64.5) | 220,180 (67.5) | 243,713 (72.5) |
| Compensated cirrhosis | 215,555 (15.0) | 42,049 (19.0) | 38,746 (15.0) | 43,209 (14.6) | 46,120 (14.1) | 45,431 (13.5) |
| Decompensated cirrhosis | 260,318 (18.1) | 38,283 (17.3) | 53,128 (20.5) | 61,894 (20.9) | 59,859 (18.4) | 47,154 (14.0) |
| Liver transplant | 29,350 (2.0) | 4885 (2.2) | 5593 (2.2) | 5885 (2.0) | 6260 (1.9) | 6727 (2.0) |
| HCC | 51,434 (3.6) | 7861 (3.5) | 9592 (3.7) | 11,013 (3.7) | 11,401 (3.5) | 11,567 (3.4) |
| Comorbidities | ||||||
| CCI (mean (SD)) | 3.68 (2.85) | 3.22 (2.71) | 3.45 (2.80) | 3.61 (2.84) | 3.89 (2.92) | 4.04 (2.87) |
| Obesity | 244,698 (17.0) | 23,718 (10.7) | 37,612 (14.5) | 52,130 (17.6) | 62,861 (19.3) | 68,377 (20.3) |
| Diabetes | 346,781 (24.1) | 50,956 (23.0) | 63,136 (24.4) | 74,238 (25.1) | 82,868 (25.4) | 75,583 (22.5) |
| CVD | 60,227 (4.2) | 8529 (3.9) | 10,805 (4.2) | 13,363 (4.5) | 14,733 (4.5) | 12,797 (3.8) |
| CKD | 203,284 (14.1) | 15,736 (7.1) | 34,546 (13.4) | 46,303 (15.6) | 53,057 (16.3) | 53,642 (16.0) |
| Non-liver cancer | 132,096 (9.2) | 20,868 (9.4) | 25,420 (9.8) | 30,380 (10.3) | 29,991 (9.2) | 25,437 (7.6) |
Data are presented as number (percentage) unless otherwise indicated. Continuous variables are presented as mean (SD). Income quartiles were defined according to county-level median household income (Q1 indicates lowest income and Q4 highest income). CCI was calculated using validated ICD-9 and ICD-10 coding algorithms.
Abbreviations: ALD, alcohol-associated liver disease; CCI, Charlson Comorbidity Index; CKD, chronic kidney disease; CLD, chronic liver disease; CVD, cardiovascular disease; HBV, hepatitis B virus; HCC, hepatocellular carcinoma; HCV, hepatitis C virus; MASLD, metabolic dysfunction–associated steatotic liver disease.
Trends in CLD burden and etiology-specific patterns
Between 2005 and 2018, the overall burden of CLD increased substantially (Table 2, Fig. 1). Annual hospitalized patients increased from 71,214 to 122,810 (AAPC, 4.37%; 95% CI, 3.87 to 4.88), while the ASHPR increased from 275.12 to 377.88 per 100,000 population (AAPC, 2.44%; 95% CI, 1.92 to 2.96). The ASHR also increased from 449.91 to 566.77 per 100,000 population (AAPC, 1.87%; 95% CI, 1.37 to 2.36). Mortality increased more rapidly than hospitalization burden: annual CLD-related deaths rose from 11,455 to 24,560 (AAPC, 6.02%; 95% CI, 4.20 to 7.86), and the ASMR increased from 45.53 to 74.77 per 100,000 population (AAPC, 3.03%; 95% CI, 1.50 to 4.58). Joinpoint analysis showed particularly rapid growth in ASMR during 2005–2009 (APC, 11.40%; 95% CI, 5.95 to 17.13), followed by a relatively stable trend thereafter (Table 2).
Table 2.
Trends in the number of hospitalized patients, deaths, and age-standardized hospitalized patient, hospitalization, and mortality rates of chronic liver disease in California, 2005–2018.
| CLD, total and by etiology | Metrics | 2005 | 2008 | 2011 | 2014 | 2018 | Average APC (95% CI) 2005–2018 | P value | Trend segment |
||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Year | APC (95% CI) | P value | |||||||||
| CA Pop., M | 26.42 | 27.28 | 28.42 | 29.61 | 30.57 | 1.18 (1.09–1.27) | <0.001 | 2005–2015 | 1.32 (1.27–1.37) | <0.001 | |
| 2015–2018 | 0.70 (0.35–1.05) | <0.001 | |||||||||
| All CLD | No. of patients | 71,214 | 82,490 | 95,902 | 104,654 | 122,810 | 4.37 (3.87–4.88) | <0.001 | 2005–2011 | 5.09 (4.38–5.82) | <0.001 |
| 2011–2018 | 3.76 (3.05–4.48) | <0.001 | |||||||||
| No. of deaths | 11,455 | 17,044 | 20,528 | 20,073 | 24,560 | 6.02 (4.20–7.86) | <0.001 | 2005–2009 | 13.61 (8.17–19.32) | <0.001 | |
| 2009–2018 | 2.80 (1.57–4.05) | <0.001 | |||||||||
| ASHPR, per 100,000 | 275.12 | 302.17 | 329.98 | 338.71 | 377.88 | 2.44 (1.92–2.96) | <0.001 | 2005–2010 | 3.07 (2.13–4.02) | <0.001 | |
| 2010–2018 | 2.05 (1.45–2.66) | <0.001 | |||||||||
| ASHR, per 100,000 | 449.91 | 488.46 | 535.30 | 537.04 | 566.77 | 1.87 (1.37–2.36) | <0.001 | 2005–2011 | 2.95 (2.09–3.82) | <0.001 | |
| 2011–2018 | 0.94 (0.40–1.49) | 0.001 | |||||||||
| ASMR, per 100,000 | 45.53 | 63.91 | 71.92 | 65.39 | 74.77 | 3.03 (1.50–4.58) | <0.001 | 2005–2008 | 11.40 (5.95–17.13) | <0.001 | |
| 2008–2018 | 0.64 (−0.59 to 1.89) | 0.310 | |||||||||
| HBV | No. of patients | 8456 | 7923 | 8027 | 7718 | 7534 | −0.83 (−1.83 to 0.18) | 0.108 | 2005–2006 | −5.15 (−14.81 to 5.61) | 0.335 |
| 2006–2018 | −0.46 (−1.09 to 0.17) | 0.155 | |||||||||
| No. of deaths | 1177 | 1671 | 1921 | 1855 | 2084 | 3.70 (2.16–5.26) | <0.001 | 2005–2009 | 10.73 (6.84–14.76) | <0.001 | |
| 2009–2018 | 0.72 (−0.74 to 2.20) | 0.335 | |||||||||
| ASHPR, per 100,000 | 32.41 | 29.08 | 27.90 | 25.36 | 23.21 | −2.20 (−4.02 to −0.36) | 0.020 | 2005–2016 | −2.53 (−3.19 to −1.86) | <0.001 | |
| 2016–2018 | −0.40 (−11.28 to 11.81) | 0.945 | |||||||||
| ASHR, per 100,000 | 43.31 | 38.44 | 37.79 | 34.34 | 31.65 | −2.38 (−3.47 to −1.28) | <0.001 | 2005–2006 | −6.82 (−17.26 to 4.95) | 0.244 | |
| 2006–2018 | −2.00 (−2.68 to −1.31) | <0.001 | |||||||||
| ASMR, per 100,000 | 4.63 | 6.20 | 6.67 | 6.00 | 6.25 | 1.57 (0.09–3.07) | 0.037 | 2005–2009 | 8.57 (4.82–12.45) | <0.001 | |
| 2009–2018 | −1.39 (−2.79 to 0.03) | 0.056 | |||||||||
| HCV | No. of patients | 35,201 | 38,635 | 41,501 | 41,611 | 33,369 | −0.09 (−0.74 to 0.57) | 0.792 | 2005–2014 | 2.42 (1.77–3.08) | <0.001 |
| 2014–2018 | −5.52 (−6.99 to −4.02) | <0.001 | |||||||||
| No. of deaths | 4665 | 7019 | 8131 | 7585 | 7314 | 1.95 (0.18–3.76) | 0.031 | 2005–2011 | 8.61 (5.96–11.34) | <0.001 | |
| 2011–2018 | −3.43 (−5.80 to −1.01) | 0.006 | |||||||||
| ASHPR, per 100,000 | 133.93 | 138.57 | 138.51 | 130.36 | 97.92 | −2.64 (−3.30 to −1.99) | <0.001 | 2005–2013 | 0.22 (−0.38 to 0.82) | 0.480 | |
| 2013–2018 | −7.05 (−8.40 to −5.68) | <0.001 | |||||||||
| ASHR, per 100,000 | 223.58 | 230.05 | 237.13 | 220.64 | 154.15 | −2.36 (−3.07 to −1.64) | <0.001 | 2005–2014 | 0.61 (−0.10 to 1.33) | 0.094 | |
| 2014–2018 | −8.72 (−10.30 to −7.12) | <0.001 | |||||||||
| ASMR, per 100,000 | 18.02 | 25.45 | 27.56 | 24.04 | 21.96 | 1.08 (−0.79 to 2.98) | 0.260 | 2005–2011 | 7.59 (4.17–11.12) | <0.001 | |
| 2011–2018 | −4.19 (−6.17 to −2.17) | <0.001 | |||||||||
| ALD | No. of patients | 19,426 | 21,411 | 23,271 | 24,662 | 29,662 | 3.43 (2.96–3.90) | <0.001 | 2005–2014 | 2.85 (2.52–3.18) | <0.001 |
| 2014–2018 | 4.74 (3.40–6.11) | <0.001 | |||||||||
| No. of deaths | 4835 | 6702 | 7624 | 7178 | 7916 | 3.99 (2.48–5.53) | <0.001 | 2005–2009 | 11.22 (6.68–15.95) | <0.001 | |
| 2009–2018 | 0.94 (−0.09 to 1.98) | 0.075 | |||||||||
| ASHPR, per 100,000 | 74.83 | 77.80 | 79.42 | 79.28 | 92.10 | 1.67 (1.27–2.08) | <0.001 | 2005–2014 | 0.75 (0.47–1.03) | <0.001 | |
| 2014–2018 | 3.78 (2.61–4.95) | <0.001 | |||||||||
| ASHR, per 100,000 | 123.36 | 127.73 | 131.19 | 130.40 | 149.87 | 1.67 (1.21–2.13) | <0.001 | 2005–2014 | 0.86 (0.41–1.30) | <0.001 | |
| 2014–2018 | 3.53 (2.41–4.66) | <0.001 | |||||||||
| ASMR, per 100,000 | 18.87 | 24.59 | 26.22 | 23.01 | 24.10 | 1.24 (−0.03 to 2.53) | 0.055 | 2005–2008 | 8.94 (4.43–13.64) | <0.001 | |
| 2008–2018 | −0.96 (−1.98 to 0.08) | 0.070 | |||||||||
| MASLD | No. of patients | 10,588 | 15,224 | 21,544 | 26,692 | 30,293 | 8.28 (6.29–10.31) | <0.001 | 2005–2012 | 12.92 (10.00–15.91) | <0.001 |
| 2012–2018 | 3.11 (0.45–5.84) | 0.022 | |||||||||
| No. of deaths | 1695 | 3591 | 5111 | 5896 | 5630 | 7.03 (4.26–9.86) | <0.001 | 2005–2012 | 17.08 (13.70–20.55) | <0.001 | |
| 2012–2018 | −3.62 (−7.89 to 0.85) | 0.111 | |||||||||
| ASHPR, per 100,000 | 42.08 | 57.44 | 76.21 | 88.27 | 95.07 | 6.31 (4.38–8.28) | <0.001 | 2005–2012 | 10.67 (7.85–13.57) | <0.001 | |
| 2012–2018 | 1.45 (−1.14 to 4.10) | 0.277 | |||||||||
| ASHR, per 100,000 | 52.40 | 71.68 | 95.27 | 108.77 | 108.13 | 5.37 (3.13–7.66) | <0.001 | 2005–2012 | 10.73 (7.42–14.14) | <0.001 | |
| 2012–2018 | −0.55 (−3.52 to 2.51) | 0.721 | |||||||||
| ASMR, per 100,000 | 7.07 | 14.04 | 18.42 | 19.53 | 17.08 | 5.64 (2.93–8.42) | <0.001 | 2005–2012 | 15.31 (11.16–19.61) | <0.001 | |
| 2012–2018 | −4.62 (−8.05 to −1.06) | 0.011 | |||||||||
No., number; ASHPR, age-standardized hospitalized patient rate; ASHR, age-standardized hospitalization rate; ASMR, age-standardized mortality rate.
Annual counts represent the number of unique hospitalized patients and deaths.
Age-standardized rates were standardized to the 2000 US population and are expressed per 100,000 populations.
Fig. 1.
Trends in hospitalized patient, hospitalizations, long-term mortality, and in-hospital mortality among patients hospitalized with chronic liver disease, California, 2005–2018. Panels show trends in age-standardized hospitalized patient rate, age-standardized hospitalization rate, age-standardized mortality rate, and in-hospital mortality for overall chronic liver disease and major etiologies (HBV, HCV, ALD, and MASLD). Each colored line represents one disease etiology. Rates are expressed per 100,000 population where applicable. Abbreviations: ALD, alcohol-associated liver disease; ASHPR, age-standardized hospitalized patient rate; ASHR, age-standardized hospitalization rate; ASMR, age-standardized mortality rate; CLD, chronic liver disease; HBV, hepatitis B virus; HCV, hepatitis C virus; MASLD, metabolic dysfunction–associated steatotic liver disease.
The burden of MASLD and ALD demonstrated an increasing trend, while viral hepatitis, in contrast, decreased over the study period. Specifically, HCV-related hospitalizations increased during 2005–2014 (APC, 2.42%; 95% CI, 1.77 to 3.08) and declined during 2014–2018 (APC, −5.52%; 95% CI, −6.99 to −4.02). HBV burden declined overall, with ASHPR (AAPC, −2.20%; 95% CI, −4.02 to −0.36) and ASHR (AAPC, −2.38%; 95% CI, −3.47 to −1.28) decreasing, although ASMR continued to increase (AAPC, 1.57%; 95% CI, 0.09 to 3.07). In contrast, MASLD exhibited the fastest growth, with annual hospitalized patients increasing from 10,588 to 30,293 (AAPC, 8.28%; 95% CI, 6.29 to 10.31) and ASHPR increasing from 42.08 to 95.07 per 100,000 population (AAPC, 6.31%; 95% CI, 4.38 to 8.28). ALD related burden increased steadily from 19,426 to 29,662 hospitalized patients (AAPC, 3.43%; 95% CI, 2.96 to 3.90), with accelerated growth after 2014 (Table 2).
Healthcare utilization and economic burden
Trends in healthcare utilization and costs among patients hospitalized with CLD are shown in Table 3 and Fig. 2. Overall, hospitalizations and associated costs increased during the study period, whereas healthcare utilization efficiency improved. Total CLD-related hospitalizations increased from 116,482 in 2005 to 185,268 in 2018 (AAPC, 3.84%; 95% CI, 3.34%–4.34%), while hospitalizations per patient-year declined from 1.64 to 1.51 (AAPC, −0.52%; 95% CI, −0.64% to −0.40%). ALOS decreased from 7.50 days to 5.54 days (AAPC, −2.17%; 95% CI, −2.52% to −1.81%). However, inflation-adjusted total hospital charges increased from $9.63 billion to $18.63 billion (AAPC, 5.40%; 95% CI, 3.35%–7.49%), with charges per hospitalization increasing from $82,707 to $100,569 (AAPC, 1.59%; 95% CI, 1.08%–2.10%) and charges per patient from $135,280 to $151,715 (AAPC, 1.05%; 95% CI, 0.44%–1.66%). During the same period, 30-day readmission declined from 25.01% to 19.80%, and in-hospital mortality declined from 2.95% to 1.18%.
Table 3.
Trends in healthcare utilization and hospital costs among patients hospitalized with chronic liver disease in California, 2005–2018.
| CLD, total and by etiology | Metrics | 2005 | 2008 | 2011 | 2014 | 2018 | Average APC (95% CI) 2005–2018 | P value | Trend segment |
||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Year | APC (95% CI) | P value | |||||||||
| All | No. of hospitalizations | 116,482 | 133,747 | 156,311 | 166,873 | 185,268 | 3.84 (3.34–4.34) | <0.001 | 2005–2011 | 5.19 (4.48–5.91) | <0.001 |
| 2011–2018 | 2.69 (2.00–3.39) | <0.001 | |||||||||
| Hosp./Pt-year | 1.64 | 1.62 | 1.63 | 1.59 | 1.51 | −0.52 (−0.64 to −0.40) | <0.001 | 2005–2013 | −0.05 (−0.19 to 0.08) | 0.441 | |
| 2013–2018 | −1.26 (−1.47 to −1.06) | <0.001 | |||||||||
| ALOS, days | 7.50 | 7.02 | 6.50 | 6.05 | 5.54 | −2.17 (−2.52 to −1.81) | <0.001 | 2005–2010 | −2.63 (−3.27 to −1.99) | <0.001 | |
| 2010–2018 | −1.88 (−2.29 to −1.46) | <0.001 | |||||||||
| Total charges, $M | 9633.86 | 11176.88 | 13737.74 | 14396.55 | 18632.17 | 5.40 (3.35–7.49) | <0.001 | 2005–2016 | 4.93 (4.18–5.68) | <0.001 | |
| 2016–2018 | 8.01 (−4.32 to 21.93) | 0.213 | |||||||||
| Charges/Hosp, $ | 82,707 | 83,567 | 87,887 | 86,273 | 100,569 | 1.59 (1.08–2.10) | <0.001 | 2005–2016 | 0.79 (0.43–1.15) | <0.001 | |
| 2016–2018 | 6.13 (3.39–8.96) | <0.001 | |||||||||
| Charges/Pt, $ | 135,280 | 135,494 | 143,248 | 137,563 | 151,715 | 1.05 (0.44–1.66) | 0.001 | 2005–2016 | 0.50 (0.08–0.93) | 0.021 | |
| 2016–2018 | 4.09 (0.86–7.42) | 0.013 | |||||||||
| 30-day readmission, % | 25.01 | 24.25 | 24.05 | 22.60 | 19.80 | −1.67 (−1.91 to −1.42) | <0.001 | 2005–2012 | −0.62 (−0.89 to −0.34) | <0.001 | |
| 2012–2018 | −2.87 (−3.29 to −2.46) | <0.001 | |||||||||
| In-hospital mortality, % | 2.95 | 1.71 | 1.34 | 1.10 | 1.18 | −7.02 (−8.72 to −5.30) | <0.001 | 2005–2010 | −14.85 (−18.18 to −11.38) | <0.001 | |
| 2010–2018 | −1.77 (−3.36 to −0.16) | 0.032 | |||||||||
| HBV | No. of hospitalizations | 11,278 | 10,479 | 10,871 | 10,511 | 10,309 | −0.61 (−1.64 to 0.43) | 0.252 | 2005–2006 | −5.90 (−15.75 to 5.10) | 0.281 |
| 2006–2018 | −0.15 (−0.80 to 0.50) | 0.647 | |||||||||
| Hosp./Pt-year | 1.33 | 1.32 | 1.35 | 1.36 | 1.37 | 0.27 (0.06–0.49) | 0.012 | 2005–2010 | 0.45 (0.07–0.84) | 0.022 | |
| 2010–2018 | 0.16 (−0.09 to 0.41) | 0.199 | |||||||||
| ALOS, days | 7.42 | 7.22 | 6.87 | 7.17 | 6.45 | −1.06 (−2.16 to 0.05) | 0.061 | 2005–2015 | −0.80 (−1.39 to −0.20) | 0.008 | |
| 2015–2018 | −1.95 (−6.18 to 2.48) | 0.383 | |||||||||
| Total charges, $M | 904.61 | 889.31 | 1060.03 | 1103.65 | 1295.75 | 3.58 (1.90–5.29) | <0.001 | 2005–2016 | 2.39 (1.22–3.58) | <0.001 | |
| 2016–2018 | 10.37 (1.32–20.22) | 0.024 | |||||||||
| Charges/Hosp, $ | 80,210 | 84,866 | 97,510 | 104,999 | 125,691 | 3.76 (2.57–4.97) | <0.001 | 2005–2015 | 2.63 (2.00–3.26) | <0.001 | |
| 2015–2018 | 7.63 (2.82–12.66) | 0.002 | |||||||||
| Charges/Pt, $ | 106,978 | 112,244 | 132,058 | 142,996 | 171,987 | 4.01 (2.75–5.28) | <0.001 | 2005–2015 | 2.96 (2.29–3.63) | <0.001 | |
| 2015–2018 | 7.58 (2.53–12.88) | 0.003 | |||||||||
| 30-day readmission, % | 15.79 | 15.24 | 16.07 | 17.16 | 17.05 | 0.61 (−0.33 to 1.55) | 0.204 | 2005–2006 | −3.68 (−12.76 to 6.35) | 0.458 | |
| 2006–2018 | 0.97 (0.38–1.57) | 0.001 | |||||||||
| In-hospital mortality, % | 2.86 | 1.94 | 1.75 | 1.62 | 1.86 | −3.31 (−4.87 to −1.72) | <0.001 | 2005–2010 | −9.99 (−12.61 to −7.31) | <0.001 | |
| 2010–2018 | 1.12 (−0.78 to 3.06) | 0.251 | |||||||||
| HCV | No. of hospitalizations | 58,781 | 64,270 | 71,204 | 70,590 | 52,781 | −0.32 (−1.10 to 0.46) | 0.418 | 2005–2014 | 2.87 (2.08–3.66) | <0.001 |
| 2014–2018 | −7.14 (−8.86 to −5.38) | <0.001 | |||||||||
| Hosp./Pt-year | 1.67 | 1.66 | 1.72 | 1.70 | 1.58 | −0.23 (−0.44 to −0.03) | 0.024 | 2005–2014 | 0.43 (0.23–0.63) | <0.001 | |
| 2014–2018 | −1.72 (−2.19 to −1.24) | <0.001 | |||||||||
| ALOS, days | 7.89 | 7.42 | 6.98 | 6.44 | 5.97 | −1.96 (−2.45 to −1.47) | <0.001 | 2005–2010 | −2.47 (−3.53 to −1.39) | <0.001 | |
| 2010–2018 | −1.64 (−2.08 to −1.20) | <0.001 | |||||||||
| Total charges, $M | 4855.23 | 5401.26 | 6256.21 | 6176.98 | 5269.63 | 0.82 (−0.21 to 1.86) | 0.118 | 2005–2012 | 4.42 (3.23–5.62) | <0.001 | |
| 2012–2018 | −3.22 (−4.92 to −1.48) | <0.001 | |||||||||
| Charges/Hosp, $ | 82,599 | 84,040 | 87,863 | 87,505 | 99,839 | 1.65 (1.25–2.06) | <0.001 | 2005–2016 | 0.92 (0.63–1.21) | <0.001 | |
| 2016–2018 | 5.79 (3.59–8.03) | <0.001 | |||||||||
| Charges/Pt, $ | 137,929 | 139,802 | 150,748 | 148,446 | 157,920 | 1.13 (0.51–1.76) | <0.001 | 2005–2011 | 1.51 (0.63–2.40) | 0.001 | |
| 2011–2018 | 0.81 (−0.07 to 1.70) | 0.070 | |||||||||
| 30-day readmission, % | 24.49 | 23.82 | 24.93 | 23.75 | 20.37 | −0.97 (−1.40 to −0.53) | <0.001 | 2005–2013 | 0.43 (−0.08 to 0.95) | 0.100 | |
| 2013–2018 | −3.17 (−3.93 to −2.39) | <0.001 | |||||||||
| In-hospital mortality, % | 2.32 | 1.15 | 0.90 | 0.77 | 0.86 | −7.81 (−9.70 to −5.88) | <0.001 | 2005–2010 | −17.19 (−20.85 to −13.37) | <0.001 | |
| 2010–2018 | −1.42 (−3.21 to 0.42) | 0.129 | |||||||||
| ALD | No. of hospitalizations | 32,060 | 35,218 | 38,497 | 40,557 | 48,267 | 3.40 (2.78–4.02) | <0.001 | 2005–2014 | 2.93 (2.50–3.37) | <0.001 |
| 2014–2018 | 4.46 (2.69–6.25) | <0.001 | |||||||||
| Hosp./Pt-Year | 1.65 | 1.64 | 1.65 | 1.64 | 1.63 | −0.05 (−0.30 to 0.21) | 0.728 | 2005–2015 | 0.07 (−0.07 to 0.20) | 0.334 | |
| 2015–2018 | −0.42 (−1.42 to 0.59) | 0.415 | |||||||||
| ALOS, days | 7.55 | 7.16 | 6.67 | 6.23 | 5.81 | −2.02 (−2.50 to −1.54) | <0.001 | 2005–2010 | −2.67 (−3.71 to −1.62) | <0.001 | |
| 2010–2018 | −1.61 (−2.04 to −1.18) | <0.001 | |||||||||
| Total charges, $M | 2642.17 | 3056.47 | 3528.82 | 3585.20 | 4918.25 | 5.19 (3.84–6.57) | <0.001 | 2005–2015 | 4.10 (3.38–4.82) | <0.001 | |
| 2015–2018 | 8.92 (3.48–14.65) | 0.001 | |||||||||
| Charges/Hosp, $ | 82,413 | 86,787 | 91,665 | 88,399 | 101,897 | 1.64 (1.02–2.28) | <0.001 | 2005–2016 | 1.04 (0.60–1.49) | <0.001 | |
| 2016–2018 | 5.01 (1.66–8.46) | 0.003 | |||||||||
| Charges/Pt, $ | 136,012 | 142,752 | 151,640 | 145,373 | 165,810 | 1.60 (0.44–2.77) | 0.007 | 2005–2016 | 1.08 (0.66–1.51) | <0.001 | |
| 2016–2018 | 4.47 (−2.68 to 12.13) | 0.226 | |||||||||
| 30-day readmission, % | 26.35 | 25.39 | 24.97 | 24.22 | 23.28 | −0.92 (−1.30 to −0.54) | <0.001 | 2005–2006 | −3.13 (−7.00 to 0.90) | 0.126 | |
| 2006–2018 | −0.74 (−0.98 to −0.50) | <0.001 | |||||||||
| In-hospital mortality, % | 5.23 | 3.30 | 2.67 | 2.14 | 1.92 | −7.31 (−8.36 to −6.24) | <0.001 | 2005–2007 | −16.86 (−21.67 to −11.75) | <0.001 | |
| 2007–2018 | −5.45 (−6.21 to −4.69) | <0.001 | |||||||||
| MASLD | No. of hospitalizations | 13,113 | 18,925 | 26,918 | 32,907 | 34,528 | 7.38 (5.09–9.72) | <0.001 | 2005–2012 | 13.06 (9.67–16.55) | <0.001 |
| 2012–2018 | 1.13 (−1.90 to 4.25) | 0.470 | |||||||||
| Hosp./Pt-Year | 1.24 | 1.24 | 1.25 | 1.23 | 1.14 | −0.74 (−1.04 to −0.45) | <0.001 | 2005–2013 | 0.13 (−0.23 to 0.48) | 0.483 | |
| 2013–2018 | −2.12 (−2.65 to −1.59) | <0.001 | |||||||||
| ALOS, days | 6.52 | 5.94 | 5.33 | 4.89 | 4.31 | −3.08 (−3.75 to −2.42) | <0.001 | 2005–2009 | −3.40 (−4.97 to −1.80) | <0.001 | |
| 2009–2018 | −2.94 (−3.59 to −2.29) | <0.001 | |||||||||
| Total charges, $M | 1057.30 | 1427.33 | 2083.78 | 2380.83 | 3022.30 | 7.94 (4.42–11.58) | <0.001 | 2005–2012 | 12.19 (7.06–17.57) | <0.001 | |
| 2012–2018 | 3.18 (−1.54 to 8.13) | 0.190 | |||||||||
| Charges/Hosp, $ | 80,630 | 75,421 | 77,412 | 72,350 | 87,532 | 1.18 (−0.11 to 2.48) | 0.074 | 2005–2016 | −0.64 (−1.53 to 0.26) | 0.163 | |
| 2016–2018 | 11.77 (4.53–19.50) | 0.001 | |||||||||
| Charges/Pt, $ | 99,858 | 93,755 | 96,722 | 89,196 | 99,769 | 0.30 (−2.26 to 2.93) | 0.821 | 2005–2016 | −1.12 (−2.05 to −0.18) | 0.020 | |
| 2016–2018 | 8.46 (−7.56 to 27.26) | 0.319 | |||||||||
| 30-day readmission, % | 11.53 | 11.47 | 11.23 | 10.38 | 6.27 | −5.25 (−7.02 to −3.44) | <0.001 | 2005–2013 | −0.35 (−2.52 to 1.87) | 0.755 | |
| 2013–2018 | −12.58 (−15.52 to −9.54) | <0.001 | |||||||||
| In-hospital mortality, % | 3.42 | 2.39 | 1.62 | 1.30 | 0.77 | −11.02 (−14.56 to −7.33) | <0.001 | 2005–2014 | −9.23 (−12.77 to −5.56) | <0.001 | |
| 2014–2018 | −14.91 (−22.79 to −6.22) | 0.001 | |||||||||
No., number; Hosp./Pt-Year, hospitalizations per patient-year; ALOS, average length of stay.
ALOS was calculated as total length of stay divided by total hospitalizations.
Hosp./Pt-Year was calculated as total hospitalizations divided by the number of unique hospitalized patients per year.
Charges were inflation-adjusted to 2019 US dollars; total charges are presented in millions.
Charges/Hosp and Charges/Pt represent charges per hospitalization and per hospitalized patient, respectively.
30-day Readmission was defined as readmission within 30 days after discharge from the index hospitalization; hospitalizations resulting in in-hospital death were excluded from the readmission analysis.
In-hospital Mortality was defined as death occurring during the index hospitalization.
Fig. 2.
Trends in healthcare utilization and economic burden among patients hospitalized with chronic liver disease, California, 2005–2018. Panels display annual estimates of total hospitalizations, hospitalizations per patient-year, average length of stay, total hospital charges (inflation-adjusted to 2019 US dollars), and charges per hospitalization or per patient. Data are shown for overall chronic liver disease and major etiologies (HBV, HCV, ALD, and MASLD). Each colored line represents one disease etiology. Abbreviations: ALD, alcohol-associated liver disease; ALOS, average length of stay; CLD, chronic liver disease; HBV, hepatitis B virus; HCV, hepatitis C virus; MASLD, metabolic dysfunction–associated steatotic liver disease.
Trends also varied across CLD etiologies. Overall, hospitalizations and costs increased most rapidly for MASLD (AAPC, 7.38%; 95% CI, 5.09%–9.72%) and ALD (AAPC, 3.40%; 95% CI, 2.78%–4.02%), whereas HCV-related hospitalizations declined after 2014 (AAPC, −7.14%; 95% CI, −8.86% to −5.38%) and HBV-related hospitalizations decreased modestly during the study period. By 2018, total hospital charges were highest for HCV ($5269.63 M) and ALD ($4918.25 M), followed by MASLD ($3022.30 M) and HBV ($1295.75 M). HBV had the highest charges per hospitalization ($125,691), whereas MASLD showed the fastest growth in total hospital charges (AAPC, 7.94%; 95% CI, 4.42%–11.58%). Similar reductions in ALOS were observed across major etiologies (Table 3).
Sociodemographic disparities in CLD burden and costs
Sociodemographic disparities were evident in CLD burden and economic impact across race and ethnicity, sex, age group, and income quartile (Fig. 3, Fig. 4, Fig. 5, Supplementary Figs. S1–S5, Supplementary Tables S4–S11). Across racial and ethnic groups, non-Hispanic White and Hispanic populations accounted for the largest absolute burden, with non-Hispanic White patients contributing the greatest share of hospitalizations and total charges in 2018, while Hispanic patients showed the most rapid growth over time (Fig. 3, Supplementary Fig. S1, Supplementary Tables S4 and S5). Hispanic patients comprised 53,643 (24.2%) of hospitalized patients in 2005–2007 and 103,557 (30.8%) in 2017–2019, whereas non-Hispanic White patients comprised 119,610 (54.0%) and 157,795 (46.9%), respectively (Table 1). Consistently, Hispanic patients experienced a faster increase in hospitalizations than non-Hispanic White patients (AAPC, 6.11% vs. 3.28%). In contrast, per-patient charges were highest among non-Hispanic Asian ($158,129) and non-Hispanic Black ($156,771) populations. HBV burden remained disproportionately concentrated among non-Hispanic Asian patients, whereas MASLD burden rose most prominently among non-Hispanic White and Hispanic populations (Fig. 3, Supplementary Fig. S1, Supplementary Tables S4 and S5). Sex-based differences were also observed. Male patients consistently had higher ASHPR, ASHR, and ASMR than female patients across overall CLD and most etiologies and also incurred higher total and per-patient costs, indicating a greater overall disease and economic burden among men. However, in-hospital mortality declined over time in both sexes (Supplementary Figs. S2 and S3, Supplementary Tables S6 and S7). Age-specific patterns indicated that CLD burden and economic impact were concentrated among middle-aged and older adults. Patients aged 45–64 years accounted for the largest share of total hospital charges, whereas those aged ≥ 65 years experienced the highest in-hospital mortality, even for etiologies with declining burden such as viral hepatitis (Fig. 4, Supplementary Fig. S4, Supplementary Tables S8 and S9). Income-based disparities were also evident. Although the third income quartile contributed the greatest absolute burden and total charges, the lowest quartile showed the fastest increase over time. The number of hospitalized patients with overall CLD in Q1 increased from 4608 in 2005 to 19,199 in 2018 (AAPC, 14.15%), and the number and proportion of hospitalized patients from this group rose from 17,408 (8.0%) in 2005–2007 to 55,177 (16.4%) in 2017–2019. Despite declines in utilization measures such as hospitalizations per patient-year and ALOS across quartiles, standardized burden increased most rapidly in lower-income groups, indicating widening socioeconomic disparities (Fig. 5, Supplementary Fig. S5, Supplementary Tables S10 and S11).
Fig. 3.
Trends in Chronic Liver Disease Burden by Race and Ethnicity, California, 2005–2018. Rows represent disease categories (all CLD, HBV, HCV, ALD, and MASLD). Columns display ASHPR, ASHR, ASMR, total hospital charges (2019 US dollars), and in-hospital mortality. Colored lines represent race and ethnicity groups (White, Black, Asian, Hispanic, and Other). Rates are expressed per 100,000 population where applicable.
Fig. 4.
Trends in Chronic Liver Disease Burden by Age Group, California, 2005–2018. Rows represent disease categories (all CLD, HBV, HCV, ALD, and MASLD). Columns display age-standardized hospitalized patient rate (ASHPR), age-standardized hospitalization rate (ASHR), age-standardized mortality rate (ASMR), total hospital charges (2019 US dollars), and in-hospital mortality. Colored lines represent age groups (18–44, 45–64, and ≥65 years). Rates are expressed per 100,000 population where applicable.
Fig. 5.
Trends in Chronic Liver Disease Burden by County-Level Income Quartile, California, 2005–2018. Rows represent disease categories (all CLD, HBV, HCV, ALD, and MASLD). Columns display ASHPR, ASHR, ASMR, total hospital charges (2019 US dollars), and in-hospital mortality. Colored lines represent county-level income quartiles (Q1 [lowest] to Q4 [highest]). Rates are expressed per 100,000 population where applicable.
Projections of future CLD burden and costs
Projections suggested that CLD burden and associated healthcare costs will continue to increase through 2035. Overall, annual hospitalized patients were projected to reach 258,236 (95% prediction interval, 236,198–282,331), annual deaths 58,659 (39,916–86,202), and total hospital charges $43.54 billion ($36.64–51.75 billion; Supplementary Tables S12 and S13). Charges per hospitalization and per patient were projected to increase to $119,336 (95% prediction interval, $104,321–$136,512) and $168,618 ($151,122–$188,139), respectively, whereas hospitalizations per patient-year, ALOS, and 30-day readmission were projected to decline to 1.41 (1.34–1.49), 3.89 days (3.66–4.14), and 15.90% (14.31%–17.67%), respectively. Subgroup projections suggested that the increasing burden of CLD will be most pronounced among middle-aged and older adults, particularly those aged 45–64 years. Racial and ethnic disparities are expected to persist, with Hispanic populations projected to experience the fastest growth in CLD-related hospitalizations, largely driven by MASLD. In contrast, HBV-related burden is projected to remain disproportionately concentrated among non-Hispanic Asian populations. Socioeconomic disparities are also expected to continue, with lower-income populations projected to experience higher hospitalization rates and mortality. Detailed projection estimates across subgroups are presented in the Supplementary Tables S4–S11.
Discussion
In this population-based analysis of statewide inpatient discharge data from California, we observed a substantial increase in the burden of CLD-related hospitalizations between 2005 and 2018, reflected by increasing ASHR, ASHPR, and ASMR during the study period. Healthcare utilization efficiency improved, as reflected by reductions in ALOS, hospitalizations per patient-year, in-hospital mortality, and 30-day readmission rates. Despite these improvements, the economic burden associated with CLD increased markedly, with total hospital charges nearly doubling over the study period. These changes were accompanied by marked shifts in CLD etiology and persistent sociodemographic disparities. Projections further suggest that CLD-related hospitalizations, mortality, and healthcare costs will continue to increase through 2035. To our knowledge, this is the first statewide population-based study to comprehensively integrate temporal trends in disease burden, healthcare utilization, economic impact, etiologic transition, sociodemographic disparities, and future projections within a single analysis, thereby providing novel insights into how these dimensions have evolved together over time.
The etiology spectrum of CLD has changed substantially worldwide in recent years.8, 9, 10, 11,17, 18, 19 Consistent with these global trends, our findings demonstrate a marked shift in the etiologic spectrum of hospitalized CLD in California. Among these etiologies, MASLD showed the most striking increase, with an ASHPR AAPC of 6.31% and total hospital charges increasing at an AAPC of 7.94%, making it the fastest-growing and potentially most costly liver disease category in California by 2018. This pattern parallels the growing global burden of MASLD.4 According to the GBD study, MASLD accounted for the majority of CLD cases worldwide in 2021, representing approximately 74.7% of prevalent and 82.7% of incident CLD cases, with ASHPR and ASIR continuing to rise between 1990 and 2021 (AAPC: 0.73% in ASHPR, and 0.73% in ASIR).4 In contrast, HCV-related hospitalizations exhibited a clear inflection point around 2014, with hospitalization rates declining thereafter (AAPC -2.17%) following the introduction of DAA therapies.11,12 ALD showed persistent and accelerating growth in hospitalization rates (AAPC +2.18%) and overall expenditures. These etiologic shifts were accompanied by increasing clinical complexity among hospitalized patients with CLD. The hospitalized CLD population became progressively more medically complex over time, as reflected by rising multimorbidity, including metabolic disorders, chronic kidney disease, and higher CCI scores. These findings are consistent with the well-recognized multisystem nature of MASLD, which is frequently accompanied by metabolic and extrahepatic comorbidities.20,21
Notably, although overall CLD-related mortality increased during the study period, in-hospital mortality declined substantially. This pattern likely reflects improvements in inpatient management of advanced liver disease and its complications, including advances in critical care, endoscopic therapy for variceal bleeding, and improved management of hepatic encephalopathy and infections.7,22, 23, 24 Declines in 30-day readmission and ALOS further support improvements in acute care and post-discharge transitions. Despite these improvements in clinical outcomes, the economic burden of CLD increased substantially. A national analysis reported that healthcare spending for patients with CLD in the United States increased steadily between 1996 and 2016, reaching $32.5 billion in 2016, with more than 65% of expenditures attributable to inpatient or emergency department care.25 Consistent with these findings, our study showed that although ALOS declined (AAPC = −2.17%), both charges per hospitalization and charges per patient-year increased substantially, particularly in recent years (2016–2018; APC = 6.13% for charges per hospitalization and 4.09% for charges per patient). The rise in total hospital charges despite shorter hospital stays suggests increasing treatment intensity and higher per-day costs, likely reflecting more complex comorbidities and the use of advanced therapeutics.24 At the same time, etiologic shifts, particularly the rapid rise of MASLD and ALD, may increase long-term mortality risk and further amplify the future burden on healthcare systems.26 Together, these trends suggest that the growing burden of CLD will continue to challenge healthcare systems and highlight the need for prevention, early detection, and population-level interventions targeting metabolic and alcohol-related risk factors.
CLD has long been characterized by pronounced disparities across sociodemographic groups.1,27 In this study, similar patterns were observed in hospitalized CLD across age, sex, race and ethnicity, and income groups. Age-specific analyses showed that individuals aged 45–64 years carried the highest burden of CLD-related hospitalizations, whereas mortality rates were greatest among those older than 65 years, reflecting the combined effects of disease progression and comorbidity accumulation in aging populations. Notably, MASLD-related hospitalization rates increased across all age groups, including younger adults, suggesting a concerning shift toward earlier onset metabolic liver disease. Clear sex-based differences were also observed, with men experiencing consistently higher hospitalization and mortality rates across most CLD etiologies, particularly for alcohol-associated liver disease, likely reflecting differences in behavioral risk factors and metabolic profiles. Marked racial and ethnic disparities were also evident. Hispanic populations experienced the most rapid increases in CLD burden, largely driven by the rise of MASLD. The high prevalence of the PNPLA3 I148M variant among Hispanic populations may also contribute to their increased susceptibility to MASLD and its progression to cirrhosis and HCC, potentially explaining the disproportionately high burden of MASLD in this population.28 HBV-related hospitalizations remained disproportionately concentrated among non-Hispanic Asian populations, while ALD and overall CLD mortality remained highest among the non-Hispanic White populations. These findings are consistent with global patterns reported by the GBD studies, which showed that the high-income region had the lowest age-standardized death rate in 2017 (10.1 deaths per 100,000 population),29 and CLD burden disproportionately affected countries with a low sociodemographic index.4,29 Consistent with these findings, our study also observed higher hospitalization rates and mortality among lower-income populations. These findings underscore the influence of structural determinants of health, differences in risk factor distribution, and access to care. Taken together, these findings suggest that the evolving epidemiology of CLD is shaped not only by shifts in disease etiology but also by persistent demographic and socioeconomic inequalities, emphasizing the need for targeted prevention strategies and equitable healthcare delivery across high-risk populations.
The findings of this study have important implications for healthcare planning and policy. First, the observed increases and projected future trends in CLD-related hospitalizations and costs suggest that liver disease will impose a growing burden on healthcare system in the coming decades. These findings underscore the need for proactive healthcare planning, including expanded screening, improved management of metabolic risk factors, and increased access to specialty liver care.23,24 Second, the shift toward MASLD and ALD highlights the need for preventive strategies targeting metabolic risk factors, alcohol use disorder, and early disease detection in primary care settings.24,30 Meanwhile, continued progress toward hepatitis C elimination remains essential, particularly through expanded screening and equitable access to DAA therapy. Third, improvements in inpatient outcomes emphasize the importance of strengthening post-discharge care, including coordinated hepatology follow-up, medication access, nutritional support, and addiction services. Finally, the marked sociodemographic disparities identified in this analysis underscore the need for equity-oriented prevention strategies and healthcare delivery.
We acknowledge several limitations to this study. First, the analysis relied on administrative data and diagnosis codes (e.g., ICD-10), which may be subject to misclassification, limited sensitivity, and changes in coding practices and disease recognition over time, although HCAI is an established database rigorously maintained by the State of California. Because the MASLD nomenclature was introduced after the study period, MASLD was identified using administrative codes for NAFLD and NASH, and the cardiometabolic criteria for its clinical diagnosis could not be verified. Second, CLD was identified using ICD diagnosis codes recorded in any diagnosis position rather than being restricted to the primary diagnosis to capture the overall healthcare burden associated with CLD. Consequently, this approach may overestimate the hospitalization burden directly attributable to CLD. In addition, the ASHPR represents unique patients hospitalized with CLD rather than population-level CLD prevalence. An increase in ASHPR may therefore reflect not only a true rise in disease prevalence but also a greater propensity for hospitalization, improved access to care, changes in comorbidity-coding practices, and increased disease detection or awareness. Conversely, the low reported awareness of HCV, HBV, and MASLD in US population-based studies, approximately 50%, 15%, and 5%, respectively, may have resulted in underascertainment of these conditions.31,32 Third, the study captured hospitalizations rather than all individuals with CLD and therefore reflects the burden of clinically significant disease requiring inpatient care. Fourth, hospital charges were used as a proxy for healthcare costs and may not fully reflect actual expenditures or reimbursements. In addition, the HCAI database does not include procedure-specific cost information; therefore, the contribution of individual components of inpatient care, such as liver transplantation, to the overall economic burden could not be evaluated. Fifth, the projections were based on single-slope linear models that may not capture the joinpoints, recent plateaus or reversals, and divergent etiology-specific trajectories observed during the study period. In addition, changes in disease epidemiology, clinical practice, healthcare policy, and therapeutic advances, including incretin-based therapies (e.g., GLP-1 receptor agonists), emerging metabolic therapies such as FGF21 analogs, and advances in antiviral treatment and viral hepatitis elimination programs, may substantially alter future disease trajectories. Hospital charges may not reflect actual healthcare costs, and adjustment using the Consumer Price Index may not fully account for chargemaster inflation. Although 95% prediction intervals were provided to reflect statistical uncertainty, the projections should be interpreted as exploratory trend-based estimates that assume the observed trends will continue rather than as precise forecasts. Finally, generalizability beyond California may be limited, although California’s scale and demographic diversity make it an informative sentinel population.
In conclusion, CLD-related hospitalizations and associated healthcare costs increased substantially over the past decade and are projected to continue rising in the coming years. Although improvements in inpatient management may have led to reductions in in-hospital mortality and more efficient use of healthcare resources, with reduced hospital length of stay and lower readmission rates, the overall clinical and economic burden of CLD continued to increase disproportionately. These findings highlight a widening gap between improving inpatient outcomes and the rapidly increasing burden of liver disease overall. Future efforts should prioritize prevention and early detection of liver disease, strengthen post-discharge care, and address persistent disparities across age, sex, race and ethnicity, and socioeconomic status.
Contributors
HF and MHN conceived and designed the study, acquired, analyzed, and interpreted the data. HF performed the statistical analysis and drafted the manuscript. RC and MHN provided administrative and material support for the database. XM, XS, JW, TY, RC, and MHN critically revised the manuscript for important intellectual content. MHN supervised the study. HF and MHN accessed and verified the underlying data. All authors had access to the data, reviewed and approved the final manuscript, and accept responsibility for the decision to submit it for publication. MHN takes responsibility for the integrity of the data and the accuracy of the data analysis.
Data sharing statement
The data used in this study are not publicly available from the authors because of data-use restrictions. Eligible researchers may apply directly to the California Department of Health Care Access and Information for access.
Declaration of interests
MHN received research grants via Stanford University from Pfizer, Astra Zeneca, Glycotest, GSK, Delfi, Innogen, Exact Science, CurveBio, Gilead, Genomics, Aligos, National Institute of Health, Roche and personal fees from consulting/advisory board from GSK. All other authors have no competing interest to declare.
Acknowledgements
The authors have no additional acknowledgments to declare.
Footnotes
Supplementary data related to this article can be found at https://doi.org/10.1016/j.lana.2026.101653.
Appendix A. Supplementary data
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