Abstract
Background and Aims
Patients with metabolic (dysfunction)‐associated fatty liver disease (MAFLD) are frequently multimorbid, putting upward pressure on healthcare costs compared to other liver diseases. As Australian data are limited on expenditures in managing MAFLD, we evaluated hospital‐related costs and predictors of costs in patients managed in a dedicated MAFLD clinic.
Methods
We conducted a retrospective review of adults attending a MAFLD clinic in Melbourne, Australia between January 2017 and December 2020. A control cohort of chronic hepatitis B (CHB) patients provided disease context. We analysed direct healthcare utilisation and costs categorised by specialty, hospital setting and fibrosis stage. Multivariate Poisson regression identified independent predictors of increased healthcare utilisation. Multivariate linear regression analysis identified independent predictors of healthcare cost.
Results
A total of 310 MAFLD and 261 CHB patients were followed up over a median 1.93 vs 4.06 years (P < 0.001). Advanced fibrosis/cirrhosis (F3‐4) represented 26% MAFLD patients and 9% CHB patients accounting for 54.9% and 18.2% total expenditure respectively. Inpatient utility was greater in MAFLD compared to CHB (6.1% vs 0.4%, P < 0.001), as was proportion of hospitalisation costs (48.3% vs 0.8%, P < 0.001). Independent predictors of cost in MAFLD were obstructive sleep apnea (P < 0.01), cardiovascular disease (P = 0.04) and F3‐4 (P < 0.001), which also predicted liver‐related outpatient appointments and radiology (P < 0.001 for both).
Conclusions
The greatest healthcare‐related costs for MAFLD clinic patients are incurred through hospitalisation, with F3‐4 predicting a disproportionately high economic burden. Our findings demonstrate the association between metabolic comorbidities and liver disease progression in MAFLD, highlighting a research gap of integrated care provision to optimise resource allocation.
Keywords: MAFLD, health economics, healthcare utilisation, advanced liver disease, hospitalisation
Introduction
Chronic liver disease (CLD) is a growing healthcare challenge in Australia and globally with increasing burden of the metabolic syndrome (MetSyn) and obesity. Metabolic (dysfunction)‐associated fatty liver disease (MAFLD) describes hepatic steatosis in the presence of overweight/obesity, type 2 diabetes mellitus (T2DM) or at least two specified metabolic risk abnormalities. 1 It is considered the hepatic manifestation of the metabolic syndrome (MetSyn) and is frequently associated with comorbidities including T2DM (31%–32%), obesity (60%–80%), hypertension (13%–50%) and major adverse cardiovascular events (8%–28%). 2 , 3
The crude prevalence of MAFLD in Australia is estimated to be between 37% and 47% 4 , 5 and is increasing in parallel with obesity trends. 6 While epidemiological data on MAFLD in Australia continue to evolve, there remains a paucity of economic data. The economic impact of MAFLD is growing, with mortality often driven by extrahepatic sequelae, such as cardiovascular disease (CVD) and malignancy. 7 A modelling study designed to estimate the disease and economic burden of MAFLD performed in the United Kingdom estimated an annual healthcare cost of 2.3 billion and 4.2 billion pounds for lower and higher prevalence scenarios respectively for direct, indirect and wellbeing costs including years of life lost due to disability. 8 Similarly, in those with non‐alcoholic fatty liver disease followed for a median 19.9 years, mean annual healthcare costs were USD 4397 for those with F3‐4 compared to USD 629 for those with F0‐2. 9
The aims of this study were to determine the direct healthcare resource use and healthcare costs of patients with single‐aetiology MAFLD managed in a dedicated, multidisciplinary MAFLD clinic, and to determine predictors of cost.
Methods
Study design
A retrospective review of adult patients who attended a dedicated MAFLD clinic in a single tertiary referral center in Victoria, Australia, was performed and included patients with a clinic appointment between 1 January 2017 and 31 December 2020 and at least 6 months of follow‐up. The end date was determined based on available financial data at the time of data collection for the 2020–2021 financial year.
Patient population
All adult patients (≥18 years old) with a diagnosis of single‐aetiology MAFLD were included. MAFLD was diagnosed in those with radiological features of steatosis along with risk factors of overweight/obesity, T2DM, or two or more of hypertension, dyslipidemia or pre‐diabetes. Notably, C‐reactive protein and homeostatic model assessment of insulin resistance criteria were not included as these were not routinely reported throughout the study duration.
Patients were referred to the clinic by general practitioners, other specialty units or gastroenterologists. Attendance included consultations with a hepatologist, dietitian and referral to other specialties such as endocrinology where indicated. Patients in the clinic had confirmation of diagnosis, fibrosis stage and institution of contemporary guideline‐based therapy, and/or enrolment into novel clinical trials. Patients were identified by a clinic‐based database curated since the clinic's inception in 2017. Patients were followed up until 30 June 2021, death, loss to follow‐up or referral to an external service for consideration of liver transplantation.
Diagnostic criteria for advanced fibrosis/cirrhosis
Threshold measurements for advanced fibrosis and cirrhosis using vibration‐controlled transient elastography (VCTE) were applied at the time of clinic enrolment, which was prior to implementation of revised MAFLD criteria and reflects real‐time clinical management. Hence, non‐alcoholic fatty liver disease (NAFLD)‐specific criteria for categorisation into advanced fibrosis (liver stiffness measurement (LSM) 9.8 to 12.9 kilopascals (kPa)) and cirrhosis (≥12.91 kPa 10 ) were used. Additional cirrhosis criteria included histopathology, radiologic or clinical features consistent with cirrhosis with/without portal hypertension. Only valid VCTE results per established criteria 11 were recorded. Annual re‐staging of fibrosis was considered according to the availability of new diagnostic data (VCTE and/or histopathology).
Outcomes
The primary outcomes were the direct, tertiary‐level healthcare use and costs of MAFLD. Secondary outcomes included costs according to fibrosis stage (dichotomized as no fibrosis to significant fibrosis (F0‐2) and advanced fibrosis or cirrhosis (F3‐4), defined by the presence of F3‐4 at any time point during follow‐up), hospital setting (inpatient vs outpatient) and specialty unit (see below) and determining predictors of cost in those with MAFLD. To provide a contextual framework regarding resource use and costs related to surveillance and management of a classical liver disease, a control cohort with chronic hepatitis B (CHB), managed in a dedicated viral hepatitis clinic, was used. Those with co‐existent MAFLD were excluded. CHB was selected given this is an archetypal chronic liver condition necessitating tertiary‐level care, with stable guidelines for long‐term surveillance, management and treatment.
Economic evaluation
Healthcare utilisation and costings data were obtained through retrospective search of electronic medical records to identify all direct healthcare costs, in particular inpatient costs, outpatient costs, radiology (including treatment for hepatocellular carcinoma (HCC)) and procedures (e.g. gastroscopy). Only episodes of care pertaining to MAFLD and its established disease associations within the MetSyn, obesity‐related complications or any solid‐organ malignancy (excluding skin cancer) were included. Similarly, only episodes of care pertaining to CHB and its established disease associations (e.g. treatment‐related bone loss or renal disease) were included. Utilisation and costing were further categorised into liver‐related (including dietician review), cancer‐related (including HCC), CVD‐related and surgery‐related. Other costs included those not otherwise categorised but relevant to the liver conditions, such as endocrinology for the management of T2DM in those with MAFLD or nephrology for the management of Fanconi's syndrome in CHB on tenofovir disoproxil fumarate. Extrahepatic utilisation and costs were captured even if the referral to those clinical services were external to the MAFLD clinic. All healthcare costs were standardised according to the 2021 calendar year, according to the Reserve Bank of Australia, 12 to account for inflation over the study period, and presented in Australian dollars (AUD; $). The scope of this study was confined to hospital‐based costs, and therefore those pertaining to outpatient medicines were not included unless relevant to MAFLD/CHB and dispensed by the hospital pharmacy. Granular costings around medication prescription were not available. Inpatient pharmacy costs and medicines supplied on discharge are included in the overall admission costs.
Statistical analyses
Categorical data are presented as frequency and percentages and compared with chi‐squared or Fisher's exact test, where appropriate. Continuous data are presented as a median (interquartile range (IQR)) or mean (± standard deviation (SD)) and compared using Mann–Whitney U test or independent sample t‐test for non‐parametric and parametric data respectively. Univariate and multivariate linear regression models were constructed to determine predictors of healthcare cost, with all variables with a P‐value < 0.10 on univariate analysis carried forward into the multivariate model. Two multivariate models were constructed, with Model 1 considering individual comorbidity items and Model 2 considering Charlson Comorbidity Index (CCI) rather than individual comorbidities (except for obstructive sleep apnoea (OSA), which is not contained within CCI). A Poisson regression model with a cluster variance–covariance matrix was used to determine predictors of healthcare utilisation. Given differences in follow‐up time between MAFLD and CHB, utilisation and cost are presented as rates per follow‐up time. A two‐tailed P‐value < 0.05 is considered statistically significant. All analyses were conducted using IBM Statistical Package for the Social Sciences (SPSS) Statistics, version 28.0.0.0 and StataNow/SE 19.5 (StataCorp), with graphs created using GraphPad Prism version 10.1.1 (GraphPad Software).
Ethics approval was granted by Alfred Health Human Research Ethics Committee (project 284/22).
Results
Baseline demographics
A total of 310 adult patients who attended the MAFLD clinic during the study period were included, with a median follow‐up time of 1.93 years (IQR 1.07–3.24). Six (1.9%) participants died during the study period, of which five were F3‐4 at baseline and 67 (21.1%) were lost to follow‐up with a median loss to follow‐up time of 1.22 years (IQR 0.81–1.81). Baseline characteristics are presented in Table 1. The CHB cohort were significantly younger (mean age 48.5 ± 14.1 years, P < 0.001), fewer were White (28.7%, P < 0.001) and less overweight/obese (54.9%, P < 0.001) and fewer with MetSyn comorbidities (P < 0.001 for all).
Table 1.
Baseline demographic and clinical details of patients with metabolic (dysfunction‐)associated fatty liver disease and chronic hepatitis B
| MAFLD (n = 310) | CHB (n = 261) | P‐value | |
|---|---|---|---|
| Male gender | 157 (50.65) | 141 (54.02) | 0.42 |
| Age, years | 53.13 (±13.75) | 48.48 (±14.12) | <0.001 |
| Ethnicity | <0.001 | ||
| White | 219 (70.65) | 75 (28.74) | |
| South‐East Asian | 19 (6.13) | 161 (61.69) | |
| South Asian | 21 (6.77) | 8 (3.07) | |
| South American | 20 (6.45) | 0 (0) | |
| Middle Eastern | 17 (5.48) | 6 (2.30) | |
| African | 7 (2.26) | 7 (2.68) | |
| Other | 5 (1.61) | 2 (0.77) | |
| Not specified | 2 (0.65) | 2 (0.77) | |
| Body mass index, kg/m2 | 31.5 (28.1–35.3) | 24.1 (21.7–26.3) | <0.001 |
| Overweight/obese | 296/305 (97.05) | 78/142 (54.93) | <0.001 |
| Type 2 diabetes mellitus | 106 (34.19) | 11 (4.21) | <0.001 |
| Hypertension | 117 (37.74) | 28 (10.73) | <0.001 |
| Dyslipidemia | 147 (47.42) | 29 (11.11) | <0.001 |
| Obstructive sleep apnea | 32 (10.32) | 4 (1.53) | <0.001 |
| Polycystic ovarian syndrome | 9 (2.90) | 1 (0.38) | 0.025 |
| Hypothyroidism | 24 (7.74) | 3 (1.15) | <0.001 |
| Prior bariatric surgery | 9 (2.90) | 1 (0.38) | 0.025 |
| Cardiovascular disease | 40 (12.90) | 15 (5.75) | 0.004 |
| Chronic kidney disease | 11 (3.55) | 9 (3.45) | 0.95 |
| Adjusted Charlson Comorbidity Index | 3 (1–4) | 1 (1–3) | <0.001 |
| Valid VCTE, n(%) | 236 (76.13) | 185 (70.88) | 0.16 |
| Liver stiffness measurement, kPa | 6.8 (4.9–10.6) | 5.2 (4.2–6.3) | <0.001 |
| Advanced fibrosis/cirrhosis | 69 (28.05) | 23 (12.11) | <0.001 |
| Decompensated cirrhosis | 0/69 (0) | 1/23 (4.35) | 0.25 |
Note: Categorical data presented as frequency (%), continuous data presented as mean (± standard deviation) or median (interquartile range).
Abbreviations: CHB = chronic hepatitis B; MAFLD = metabolic (dysfunction‐)associated fatty liver disease; VCTE = vibration‐controlled transient elastography.
Liver fibrosis
In MAFLD patients that were adequately able to be staged from baseline to study completion, 12 with F0‐2 fibrosis at baseline progressed to F3‐4 at any timepoint during the follow‐up period with a total 81/310 (26.1%) prevalence of advanced fibrosis/cirrhosis at any timepoint. In contrast, 23/261 (8.8%) CHB patients were F3‐4 at baseline, with no patients progressing from baseline F0‐F2 to F3‐4. In both groups, factors associated with F3‐4 at any timepoint included older age, T2DM, hypertension, chronic kidney disease and a greater adjusted CCI at baseline (Table S1).
Outpatient use
Patients with MAFLD had a small but significantly greater liver clinic appointment rate at 2.49 (IQR 1.85–3.39) versus 2.10 (IQR 1.84–2.59) appointments per year of follow‐up time (P < 0.001) compared to those with CHB. This was driven by the difference in those with F0‐2 fibrosis (2.37 vs 2.08, P < 0.001), with no difference in rate of liver clinic attendance between conditions for those with F3‐4 fibrosis (P = 0.07) (Table 2). A multivariate Poisson regression analysis demonstrated the only independent variable associated with total number of liver outpatient clinic appointments was the presence of F3‐4 fibrosis at any point during follow‐up time (incidence rate ratio (IRR) 1.28, 95% confidence interval (CI) 1.17–1.39, P < 0.001) (Table 3).
Table 2.
Outpatient clinic and radiology use in those with metabolic (dysfunction‐)associated fatty liver disease and chronic hepatitis B
| MAFLD (n = 310) | CHB (n = 261) | P‐value | |
|---|---|---|---|
| Liver outpatient clinic rate |
2.49 (1.85–3.39) |
2.10 (1.84–2.59) |
<0.001 |
| Liver outpatient clinic rate in F0‐2 |
2.37 (1.80–3.17) |
2.08 (1.83–2.54) |
0.005 |
| Liver outpatient clinic rate F3‐4 |
2.89 (2.12–3.79) |
2.51 (1.98–2.82) |
0.07 |
| Liver radiology rate |
0.96 (0.54–1.56) |
1.62 (0.93–1.98) |
<0.001 |
| Liver radiology rate F0‐2 |
0.81 (0.46–1.25) |
1.60 (0.90–1.95) |
<0.001 |
| Liver radiology rate F3‐4 |
1.63 (1.08–2.37) |
2.06 (1.62–2.41) |
0.15 |
Note: Rate presented as number of clinic episodes per year of follow up time.
Abbreviations: CHB = chronic hepatitis B; F0‐2 = no fibrosis to significant fibrosis (throughout follow up); F3‐4 = advanced fibrosis/cirrhosis (at any time point during follow up); MAFLD = metabolic (dysfunction‐)associated fatty liver disease.
Table 3.
Poisson multivariate regression analysis investigating factors influencing total number of liver outpatient clinic appointments
| Variable | Incidence rate ratio | 95% confidence interval | P‐value |
|---|---|---|---|
| MAFLD (vs CHB) | 1.03 | 0.96–1.10 | 0.37 |
| Age | 1.00 | 0.99–1.01 | 0.98 |
| Female gender | 1.01 | 0.96–1.07 | 0.63 |
| Asian ethnicity | 0.98 | 0.92–1.04 | 0.54 |
| Adjusted Charlson Comorbidity Index | 1.02 | 0.99–1.04 | 0.20 |
| F3‐4 (anytime during follow‐up) | 1.28 | 1.17–1.39 | <0.001 |
Abbreviations: CHB = chronic hepatitis B; MAFLD = metabolic (dysfunction‐)associated fatty liver disease.
CHB patients had a significantly greater liver‐related radiology clinic rate per year of follow‐up time for both the overall cohort (1.96 vs 0.92, P < 0.001) and for those with F0‐2 fibrosis (1.60 vs 0.81, P < 0.001), with no difference in the F3‐4 fibrosis subgroup compared to those with MAFLD (Table 2). In contrast to liver clinic appointments, factors independently associated with total liver‐related radiology usage included CHB, age, Asian ethnicity and presence of F3‐4 fibrosis at any time (Table 4).
Table 4.
Poisson multivariate regression analysis investigating factors influencing total number of liver outpatient radiology appointments
| Variable | Incidence rate ratio | 95% confidence interval | P‐value |
|---|---|---|---|
| MAFLD (vs CHB) | 0.69 | 0.62–0.77 | <0.001 |
| Age | 1.09 | 1.06–1.13 | <0.001 |
| Female gender | 0.95 | 0.87–1.04 | 0.30 |
| Asian ethnicity | 1.13 | 1.02–1.25 | 0.023 |
| Adjusted Charlson Comorbidity Index | 1.00 | 0.96–1.05 | 0.84 |
| F3‐4 (anytime during follow‐up) | 1.46 | 1.29–1.64 | <0.001 |
Abbreviations: CHB = chronic hepatitis B; MAFLD = metabolic (dysfunction‐)associated fatty liver disease.
Other outpatient utility incurred by MAFLD but not CHB patients included attendance at specialty clinics for CVD (n = 99), oncology (n = 105) and surgery (n = 48), including related radiology for CVD (n = 42) and oncology (n = 37). Other specialty units related to the management of underlying liver disease included 577 visits in the 310 MAFLD patients and 36 visits in the 261 CHB patients.
Inpatient use
There were significantly greater admissions in MAFLD patients at 19/310 (6.13%) versus 1/261 (0.38%), P < 0.001. The inpatient admissions incurred by MAFLD patients were for surgery‐ (n = 8), liver‐ (n = 6), CVD‐ (n = 4), oncology‐ (n = 3) and other (n = 2) related reasons, with the greatest total bed days (n = 102) attributed to surgical admissions, followed by CVD admissions (n = 85) and liver admissions (n = 81). In contrast, the single CHB patient was admitted for a liver‐related admission with a 4‐day length of stay.
Costs
Absolute total tertiary cost of care for the 310 MAFLD patients during the study period was $1 186 448.87, compared to $1 049 725.98 for the 261 CHB patients. Distribution of total costs categorised by setting (outpatient, inpatient and radiology) are demonstrated in Figure 1 and Table 5 with the greatest proportion of cost burden in MAFLD patients attributed to inpatient costs (48.34%) and outpatient costs in CHB patients (82.40%). MAFLD patients had greater liver clinic attendance rate per year of follow‐up time overall and for F0‐2 fibrosis. CHB patients had greater use of liver‐related radiology overall and for F0‐2 fibrosis (Table S3). Cost per stream was almost all liver‐related in CHB patients (98.79% of total cost) compared to distribution among liver (43.51%), CVD (12.76%), oncologic (11.48%), surgical (16.45%) and other (15.79%) streams in MAFLD (Fig. 1). Factors independently associated with overall cost in the MAFLD cohort were presence of obstructive sleep apnea, CVD and F3‐4 (Table 6). Cost distribution across fibrosis stages differed between cohorts with 54.90% of total MAFLD costs incurred by the 81/310 patients with F3‐4 compared to only 18.24% of costs in the CHB cohort attributed to those with F3‐4 fibrosis (Table S2). In both MAFLD and CHB cohorts, the inpatient cost was significantly higher than outpatient costs (including radiology) for F3‐4 versus F0‐2, while there was only a significant difference in cost according to stream (liver‐related vs extrahepatic cost) for CHB dichotomized between F0‐2 and F3‐4, though the difference was marginal.
Figure 1.
Cost distribution according to setting and stream for those with metabolic (dysfunction‐)associated fatty liver disease (MAFLD) and chronic hepatitis B (CHB).
Table 5.
Cost distribution according to setting and stream for those with metabolic (dysfunction‐)associated fatty liver disease and chronic hepatitis B
| MAFLD (n = 310) | CHB (n = 261) | P‐value | |
|---|---|---|---|
| Setting | <0.001 | ||
| Outpatient |
451 015.72 (38.01) |
865 011.02 (82.40) |
|
| Inpatient |
573 561.68 (48.34) |
7939.19 (0.76) |
|
| Radiology |
161 871.47 (13.64) |
176 775.77 (16.84) |
|
| Stream | <0.001 | ||
| Liver |
516 211.72 (43.51) |
1 036 994.50 (98.79) |
|
| Cardiovascular disease |
151 431.72 (12.76) |
0 (0) |
|
| Surgery |
195 220.61 (16.45) |
0 (0) |
|
| Oncology |
136 223.21 (11.48) |
0 (0) |
|
| Other |
187 361.61 (15.79) |
12 731.48 (1.21) |
Abbreviations: CHB = chronic hepatitis B; MAFLD = metabolic (dysfunction‐)associated fatty liver disease.
Table 6.
Univariate and multivariate linear regression analysis to predict total direct healthcare‐related cost amongst patients with metabolic dysfunction‐associated fatty liver disease
| Variable | Univariate | Multivariate model 1 | Multivariate model 2 | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Beta coefficient | 95% confidence interval | P‐value | Beta coefficient | 95% confidence interval | P‐value | Beta Coefficient | 95% confidence interval | P‐value | |
| Age, years | 97.64 | 15.74–179.55 | 0.020 | 3.13 | −77.40‐83.66 | 0.94 | −21.35 | −130.69‐87.99 | 0.70 |
| Female gender | 2353.73 | 99.70–4607.75 | 0.041 | 811.90 | −1334.37‐2958.16 | 0.46 | −65.01 | −2176.14‐2046.12 | 0.95 |
| Follow up duration, years | 1338.25 | 446.12–2230.38 | 0.003 | 436.70 | −367.21‐1240.61 | 0.29 | 525.40 | −290.35‐1341.15 | 0.21 |
| BMI, kg/m2 | 414.10 | 235.63–592.57 | <0.001 | 130.36 | −45.23‐305.95 | 0.15 | 148.48 | −29.54‐326.51 | 0.10 |
| Type 2 diabetes mellitus | 1845.93 | −536.99‐4228.85 | 0.13 | ||||||
| Hypertension | 1295.43 | −1040.72‐3631.58 | 0.28 | ||||||
| Dyslipidemia | 512.22 | −1759.31‐2783.75 | 0.66 | ||||||
| Obstructive sleep apnea | 9201.87 | 5618.25–12 785.48 | <0.001 | 4881.17 | 1417.02–8345.32 | 0.006 | 4556.88 | 1067.86–8045.91 | 0.011 |
| Cardiovascular disease | 4102.49 | 749.37–7455.62 | 0.017 | 3461.23 | 229.84–6692.62 | 0.036 | |||
| Chronic kidney disease | 7541.03 | 1466.52–13 615.53 | 0.015 | 5333.60 | −131.72‐10 798.91 | 0.056 | |||
| Adjusted Charlson Comorbidity Index | 1134.80 | 595.01–1674.58 | <0.001 | 700.40 | −72.95‐1473.75 | 0.08 | |||
| F3‐4 anytime | 6176.82 | 3886.11–8467.53 | <0.001 | 4021.71 | 1710.33–6333.08 | 0.001 | 3428.64 | 934.17–5923.12 | 0.007 |
Discussion
Patients attending a dedicated MAFLD clinic in a single tertiary referral center in Australia incurred significant hospital costs, primarily driven by hospitalisation attributed to both liver and non‐liver admission reasons. There was a marked difference in the proportion of costs due to hospitalisation between those with MAFLD and CHB, reflecting the magnitude of inpatient cost burden in those with MAFLD and highlighting a key area of concern for the healthcare system as we witness a growth in MAFLD prevalence.
The burden of disease associated with MAFLD is multifaceted, reflecting the multiple body systems affected by sequelae of MAFLD and/or MetSyn. 13 This is demonstrated in our study by the distribution of resource use across specialty areas and is greatly contrasted with the primarily liver‐related use incurred by CHB patients. Another contributing factor includes the availability of antiviral medications reducing development of complications including cirrhosis and hepatocellular carcinoma. 14 This is exemplified by the fact that no patients with CHB in our study progressed from F0‐2 to F3‐4, compared to 12/241 (5%) in the MAFLD cohort.
Subspecialty clinic model of care
While awaiting a consensus on an effective and sustainable model of care for MAFLD, dedicated multidisciplinary outpatient programmes have demonstrated improvements in biochemistry and metabolic risk factors. 15 , 16 More recent observational studies have shown weight stability or loss and improvement in liver stiffness measurement. 16 , 17 The main goals of this dedicated MAFLD clinic include confirmation of diagnosis of MAFLD, stratification of patients by liver disease severity, initiation of management strategies for metabolic risk factors and considering trials for novel pharmacotherapies. The MAFLD clinic supports these key tasks through dedicated staffing, funding and referrals to relevant disciplines such as endocrinology. Additionally, streamlined data collection allows single site and collaborative research, which is of particular concern for a condition with increasing incidence and with multisystem impacts. Benefits of a sub‐specialty clinic include pooled resources such as dietitians, which is of significance given that more than 90% of our participants met BMI criteria for overweight or obese, a third had T2DM, and 2.8% had prior bariatric surgery. A previous local study on a similar cohort from the same clinic found that MAFLD clinic enrolment was associated with a reduction in markers of liver disease severity, but low rates of sustained weight loss highlight a need to broaden multidisciplinary involvement and use of pharmacotherapy. 16
Resource use
The greatest resource use for MAFLD patients was attributed to hospitalisation, at 48.34% of total costs despite only 6/310 of patients requiring any admission over the follow‐up period. This highlights the disproportionate inpatient costs compared to ambulatory care, particularly those pertaining to ICU admission and emergency procedures. With such high cost attributed to so few admissions and patients, the need to address hospitalisation is paramount. Integrated care (covering at least two health settings) is frequently associated with reducing hospitalisation use in chronic disease, 18 , 19 although evidence is yet to be incorporated into mainstream use. Multidisciplinary, ambulatory programmes with individualised assessments and education reduced annual costs per 100 patients for managing T2DM with multiple complications, from $10 181 to $1710 20 and reduced hospitalisation and re‐admission in patients with chronic obstructive pulmonary disease. 21 Elements of integrated care employed in this clinic include interdisciplinary collaboration and continuity of care. 22 We recognise the greater and almost entirely liver‐related outpatient costs in the CHB cohort, compared to the lower MAFLD outpatient costs distributed across multiple specialties. Confounding factors for this distribution may include the impact of multimorbidity, age, guidelines influencing radiology requests, cost of directed therapy and attendance at appointments. However, this also flags resource allocation as a potential target to address both MetSyn and liver‐related complications. The greater median follow‐up in the CHB cohort was addressed by examining events per year of follow‐up time (Table S3). For those without overt cirrhosis, MAFLD patients had greater clinic attendance likely due to the clinical need for assessment more frequently than the 6‐monthly reviews required for CHB patients. Additionally, the use of liver‐related radiology was greater in CHB groups, likely due to routine HCC surveillance.
The breadth of co‐morbidities and need for multidisciplinary input contributes to healthcare use in our cohort with patients attending clinic appointments for CVD (total clinic n = 99), oncology (n = 105) and surgery (n = 48). Of note, patients required input for advanced weight loss interventions and diabetes complications including limb amputation, highlighting the extra‐hepatic associations of MAFLD. Thus, while the clinic is dedicated to MAFLD, the patients are multimorbid and at risk of life‐threatening systemic complications, which supports the integration of multiple disciplines, including primary care, into this model of chronic disease management.
Progression of fibrosis/liver disease and liver disease events
The baseline characteristics associated with the presence of F3‐4 fibrosis are also associated with the MetSyn, including higher BMI, presence of T2DM and OSA, as well as history of bariatric surgery, 13 reflecting the influence of metabolic risk factors on liver disease in this cohort. Additionally, those with higher grades of fibrosis, including overt cirrhosis, have a higher age‐adjusted CCI reflecting greater multi‐morbidity, as expected.
The greatest proportion of costs incurred by the MAFLD F0‐F2 group was attributed to outpatient costs (63%). Conversely, those in the F3‐4 group incurred the most costs through inpatient admissions (58%) and had a similar spread of cost between clinical services, reflecting the comorbidity burden of these patients. Additionally, the presence of F3‐4 fibrosis is an independent predictor of total direct healthcare costs, which is consistent with global data on the economic impact of CLD. 23 The practical implications of the association between increasing fibrosis/cirrhosis and direct healthcare costs include future planning, allocation of finite resources and distribution of patient care among primary care and hepatology‐specific services. Future planning is essential with rising rates of advanced chronic liver disease and increasing healthcare resource use due to hepatic decompensation and/or hepatocellular carcinoma. A Markov‐based model has forecast an 85% rise in advanced liver disease cases from NAFLD in Australia by 2030, which will place significant stress on the healthcare budget given the findings from this study. 24 Clinics such as this MAFLD clinic are sustainable in their current form through methods including activity‐based funding; however, if the incidence, diagnosis of MAFLD and referrals to clinics continue to rise as anticipated, both the clinical resources and ability to capture data will be limited.
With limited clinic capacity and growing incidence of MAFLD identified in primary care, a question remains regarding the most appropriate setting for ongoing care of patients with F0‐2. Those with advanced fibrosis or cirrhosis, particularly those with clinically significant portal hypertension, are best managed in a specialty hepatology service. Although there is a referral pathway, care is often fragmented between primary and hospital‐based ambulatory care. There is, however, a move to protocolised risk stratification, typically using simple non‐invasive measures of fibrosis such as Fibrosis‐4 Index in conjunction with VCTE in a two‐step algorithm, to support management of MAFLD with no or minimal fibrosis in the primary care setting. 25 , 26 Implementation of protocolised discharge back to a general practitioner following fibrosis assessment will reduce hepatology specialist clinic demand.
Limitations
This is the first study to assess the healthcare use and direct healthcare costs of MAFLD and its associated comorbidities in Australia and was able to provide granular data on where costs lie between clinical services and setting. Limitations include this study being from a single, non‐liver transplant centre and modest sample size. In addition, we were unable to access community‐related costs such as general practitioner appointments, community allied health, external pathology, radiology, procedures, medication cost (relevant to weight management, complications of the metabolic syndrome and antiviral medication use), specialist review or hospitalisation external to the service. We also acknowledge selection bias in referral of patients to this clinic. Costs were derived through categorisation into disease‐related groups, which was undertaken by clinicians trained in using the specific data‐collection tool. The exact costing methods used may have limited generalisability to other health services; however, the findings highlight healthcare resource use by this growing and often multimorbid population. Furthermore, while we employed a comparator group with chronic liver disease within the same institution, it should be recognised that CHB has demographics and associated comorbidities which are inherently disparate to those of MAFLD, which will influence the differences established in healthcare use and cost.
Conclusion
A sub‐specialty clinic for patients with MAFLD demonstrates high direct healthcare‐related costs, primarily incurred by hospitalisations and primarily in those with advanced fibrosis/cirrhosis. This raises significant clinical and economic concerns regarding the rising incidence of MAFLD and complications associated with advanced chronic liver disease. Future challenges to consider include the role for primary and tertiary care preventive approaches to reduce hospitalisations and the factors contributing to the progression of hepatic fibrosis.
Ethics statement
Ethics approval was granted by Alfred Health Human Research Ethics Committee (project 284/22), including a waiver for patient consent.
Disclosure
No material from other sources was reproduced, and references to other work have been cited in the reference list.
Supporting information
Table S1. Baseline demographics according to fibrosis stage in those with metabolic (dysfunction‐)associated fatty liver disease and chronic hepatitis B.
Table S2. Cost distribution according to fibrosis stage in those with metabolic (dysfunction‐)associated fatty liver disease and chronic hepatitis B.
Table S3. Differences in rate of liver clinic attendance by year of follow up time.
Acknowledgements
Laura Morphett, Performance Analysis and Costing unit, Alfred Health. William Chang, Performance Analysis and Costing unit, Alfred Health. John Cho, Performance Analysis and Costing unit, Alfred Health. Open access publishing facilitated by Monash University, as part of the Wiley ‐ Monash University agreement via the Council of Australasian University Librarians
Authors N. N. and K. V. are co‐first authors for this study.
Funding: None.
Conflict of interest: None.
Contributor Information
Natalie Ngu, Email: natalie.ngu@monash.edu.
Karl Vaz, Email: k.vaz@alfred.org.au.
Data availability statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Table S1. Baseline demographics according to fibrosis stage in those with metabolic (dysfunction‐)associated fatty liver disease and chronic hepatitis B.
Table S2. Cost distribution according to fibrosis stage in those with metabolic (dysfunction‐)associated fatty liver disease and chronic hepatitis B.
Table S3. Differences in rate of liver clinic attendance by year of follow up time.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.