Comparison of risk adjustment methods in patients with liver disease using electronic medical record data

Developing and validating a Chinese multimorbidity-weighted index for middle-aged and older community-dwelling individuals

OBJECTIVE

To develop and validate an index to quantify the multimorbidity burden in Chinese middle-aged and older community-dwelling individuals.

METHODS

We included 20,035 individuals aged 45 and older from the China Health and Retirement Longitudinal Study (CHARLS) and 19,297 individuals aged 65 and older from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). Health outcomes of physical functioning (PF), basic and instrumental activities of daily living (ADL and IADL) and mortality were obtained. Based on self-reported disease status, we calculated five commonly used western multimorbidity indexes for CHARLS baseline participants. The one that predicted the health outcomes the best was selected and then modified through a linear mixed model using the repeated individual data in CHARLS. The performance of the modified index was internally and externally evaluated with CHARLS and CLHLS data.

RESULTS

The multimorbidity-weighted index (MWI) performed the best among the five indexes. In the modified Chinese multimorbidity-weighted index (CMWI), the weights of the diseases varied greatly (range 0.2-5.1). The top three diseases with the highest impact were stroke, memory-related diseases and cancer, corresponding to weights of 5.1, 4.3 and 3.4, respectively. Compared with the MWI, the CMWI showed better model fits for PF and IADL with larger R2 and smaller Akaike information criterion, and comparable prediction performances for ADL, IADL and mortality (e.g. the same predictive accuracy of 0.80 for ADL disability).

CONCLUSION

The CMWI is an adequate index to quantify the multimorbidity burden for Chinese middle-aged and older community-dwelling individuals. It can be directly computed via disease status examined in regular community health check-ups to facilitate health management.

Predictive scoring systems for in-hospital mortality due to acutely decompensated liver cirrhosis in Indonesia

Background

Acutely decompensated liver cirrhosis is associated with high medical costs and negatively affects productivity and quality of life. Data on factors associated with in-hospital mortality due to acutely decompensated liver cirrhosis in Indonesia are scarce. This study aims to identify predictors of in-hospital mortality and develop predictive scoring systems for clinical application in acutely decompensated liver cirrhosis patients.

Methods

This was a retrospective cohort study using a hospital database of acutely decompensated liver cirrhosis data at Cipto Mangunkusumo National General Hospital, Jakarta (2016–2019). Bivariate and multivariate logistic regression analyses were performed to identify the predictors of in-hospital mortality. Two scoring systems were developed based on the identified predictors.

Results

A total of 241 patients were analysed; patients were predominantly male (74.3%), had hepatitis B (38.6%), and had Child–Pugh class B or C cirrhosis (40% and 38%, respectively). Gastrointestinal bleeding was observed in 171 patients (70.9%), and 29 patients (12.03%) died during hospitalization. The independent predictors of in-hospital mortality were age (adjusted OR: 1.09 [1.03–1.14]; p = 0.001), bacterial infection (adjusted OR: 6.25 [2.31–16.92]; p < 0.001), total bilirubin level (adjusted OR: 3.01 [1.85–4.89]; p < 0.001) and creatinine level (adjusted OR: 2.70 [1.20–6.05]; p = 0.016). The logistic and additive scoring systems, which were developed based on the identified predictors, had AUROC values of 0.899 and 0.868, respectively.

Conclusion

The in-hospital mortality rate of acutely decompensated liver cirrhosis in Indonesia is high. We have developed two predictive scoring systems for in-hospital mortality in acutely decompensated liver cirrhosis patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12876-021-01972-6.

Prevalence and Patterns of Opioid Use Before and After Liver Transplantation

BACKGROUND

Opioid use in liver transplantation is poorly understood and has potential associated morbidity.

METHODS

Using a national data set of employer-based insurance claims, we identified 1257 adults who underwent liver transplantation between December 2009 and February 2015. We categorized patients based on their duration of opioid fills over the year before and after transplant admission as opioid-naive/no fills, chronic opioid use (≥120 d supply), and intermittent use (all other use). We calculated risk-adjusted prevalence of peritransplant opioid fills, assessed changes in opioid use after transplant, and identified correlates of persistent or increased opioid use posttransplant.

RESULTS

Overall, 45% of patients filled ≥1 opioid prescription in the year before transplant (35% intermittent use, 10% chronic). Posttransplant, 61% of patients filled an opioid prescription 0-2 months after discharge, and 21% filled an opioid between 10-12 months after discharge. Among previously opioid-naive patients, 4% developed chronic use posttransplant. Among patients with pretransplant opioid use, 84% remained intermittent or increased to chronic use, and 73% of chronic users remained chronic users after transplant. Pretransplant opioid use (risk factor) and hepatobiliary malignancy (protective) were the only factors independently associated with risk of persistent or increased posttransplant opioid use.

CONCLUSIONS

Prescription opioid use is common before and after liver transplant, with intermittent and chronic use largely persisting, and a small development of new chronic use posttransplant. To minimize the morbidity of long-term opioid use, it is critical to improve pain management and optimize opioid use before and after liver transplant.

Extra-hepatic comorbidity burden significantly increases 90-day mortality in patients with cirrhosis and high model for endstage liver disease

BACKGROUND

We examined how extra-hepatic comorbidity burden impacts mortality in patients with cirrhosis referred for liver transplantation (LT).

METHODS

Adults with cirrhosis evaluated for their first LT in 2012 were followed through their clinical course with last follow up in 2019. Extra-hepatic comorbidity burden was measured using the Charlson Comorbidity Index (CCI). The endpoints were 90-day transplant free survival (Cox-Proportional Hazard regression), and overall mortality (competing risk analysis).

RESULTS

The study included 340 patients, mean age 56 ± 11, 63% male and MELD-Na 17.2 ± 6.6. The CCI was 0 (no comorbidities) in 44%, 1-2 in 44% and > 2 (highest decile) in 12%, with no differences based on gender but higher CCI in patients with fatty and cryptogenic liver disease. Thirty-three (10%) of 332 patients not receiving LT within 90 days died. Beyond MELD-Na, the CCI was independently associated with 90-day mortality (hazard ratio (HR), 1.32 (95% confidence interval (CI) 1.02-1.72). Ninety-day mortality was specifically increased with higher CCI category and MELD ≥18 (12% (CCI = 0), 22% (CCI = 1-2) and 33% (CCI > 2), (p = 0.002)) but not MELD-Na ≤17. At last follow-up, 69 patients were alive, 100 underwent LT and 171 died without LT. CCI was associated with increased overall mortality in the competing risk analysis (Sub-HR 1.24, 95%CI 1.1-1.4).

CONCLUSIONS

Extra-hepatic comorbidity burden significantly impacts short-term mortality in patients with cirrhosis and high MELD-Na. This has implications in determining urgency of LT and mortality models in cirrhosis and LT waitlisting, especially with an ageing population with increasing prevalence of fatty liver disease.

Comorbidities and Outcome of Alcoholic and Non-Alcoholic Liver Cirrhosis in Taiwan: A Population-Based Study

The prognosis of different etiologies of liver cirrhosis (LC) is not well understood. Previous studies performed on alcoholic LC-dominated cohorts have demonstrated a few conflicting results. We aimed to compare the outcome and the effect of comorbidities on survival between alcoholic and non-alcoholic LC in a viral hepatitis-dominated LC cohort. We identified newly diagnosed alcoholic and non-alcoholic LC patients, aged ≥40 years old, between 2006 and 2011, by using the Longitudinal Health Insurance Database. The hazard ratios (HRs) were calculated using the Cox proportional hazards model and the Kaplan–Meier method. A total of 472 alcoholic LC and 4313 non-alcoholic LC patients were identified in our study cohort. We found that alcoholic LC patients were predominantly male (94.7% of alcoholic LC and 62.6% of non-alcoholic LC patients were male) and younger (78.8% of alcoholic LC and 37.4% of non-alcoholic LC patients were less than 60 years old) compared with non-alcoholic LC patients. Non-alcoholic LC patients had a higher rate of concomitant comorbidities than alcoholic LC patients (79.6% vs. 68.6%, p < 0.001). LC patients with chronic kidney disease demonstrated the highest adjusted HRs of 2.762 in alcoholic LC and 1.751 in non-alcoholic LC (all p < 0.001). In contrast, LC patients with hypertension and hyperlipidemia had a decreased risk of mortality. The six-year survival rates showed no difference between both study groups (p = 0.312). In conclusion, alcoholic LC patients were younger and had lower rates of concomitant comorbidities compared with non-alcoholic LC patients. However, all-cause mortality was not different between alcoholic and non-alcoholic LC patients.

A disease-specific comorbidity index for predicting mortality in patients admitted to hospital with a cardiac condition

BACKGROUND

Comorbidity indexes derived from administrative databases are essential tools of research in global health. We sought to develop and validate a novel cardiac-specific comorbidity index, and to compare its accuracy with the generic Charlson-Deyo and Elixhauser comorbidity indexes.

METHODS

We derived the cardiac-specific comorbidity index from consecutive patients who were admitted to hospital at a tertiary-care cardiology hospital in Quebec. We used logistic regression analysis and incorporated age, sex and 22 clinically relevant comorbidities to build the index. We compared the cardiac-specific comorbidity index with refitted Charlson-Deyo and Elixhauser comorbidity indexes using the C-statistic and net reclassification improvement to predict in-hospital death, and the Akaike information criterion to predict length of stay. We validated our findings externally in an independent cohort obtained from a provincial registry of coronary disease in Alberta.

RESULTS

The novel cardiac-specific comorbidity index outperformed the refitted generic Charlson-Deyo and Elixhauser comorbidity indexes for predicting in-hospital mortality in the derivation population (n = 10 137): C-statistic 0.95 (95% confidence interval [CI] 0.94-0.9) v. 0.81 (95% CI 0.77-0.84) and 0.86 (95% CI 0.82-0.89), respectively. In the validation population (n = 17 877), the cardiac-specific comorbidity index was similarly better: C-statistic 0.92 (95% CI 0.89-0.94) v. 0.76 (95% CI 0.71-0.81) and 0.82 (95% CI 0.78-0.86), respectively, and also numerically outperformed the Charlson-Deyo and Elixhauser comorbidity indexes for predicting 1-year mortality (C-statistic 0.78 [95% CI 0.76-0.80] v. 0.75 [95% CI 0.73-0.77] and 0.77 [95% CI 0.75-0.79], respectively). Similarly, the cardiac-specific comorbidity index showed better fit for the prediction of length of stay. The net reclassification improvement using the cardiac-specific comorbidity index for the prediction of death was 0.290 compared with the Charlson-Deyo comorbidity index and 0.192 compared with the Elixhauser comorbidity index.

INTERPRETATION

The cardiac-specific comorbidity index predicted in-hospital and 1-year death and length of stay in cardiovascular populations better than existing generic models. This novel index may be useful for research of cardiology outcomes performed with large administrative databases.

Screening for impaired liver function as a risk factor for drug safety at hospital admission of surgical patients

Background Hepatic insufficiency can affect patient safety and should therefore be considered during drug therapy. Hospital admission offers an ideal point to screen for patients at risk and to adjust drug therapy accordingly. Objective To assess the number of patients admitted to hospital with clinically elevated liver parameters. To identify high-risk patients in need of potential drug therapy adjustment to liver function by calculation of liver scores. Finally, to investigate whether pre-hospital medication needed adjustment to liver function. Setting Patients admitted to surgical wards of a tertiary teaching hospital. Method Surgical patients were included in a 3-month retrospective study. A pharmacist-led screening process, including recording of elevated liver parameters and calculation of liver scores (Child-Pugh-score, Model of End-stage Liver Disase [MELD], MELDNa), was used to assess frequency of hepatic insufficiency and patients potentially needing medication adjustment. Additionally, pre-hospital medication was checked for contraindications and correct dosage with regard to liver function. Main outcome measure Percentage of surgical patients with clinically elevated liver parameters at admission, percentage of patients with hepatic insufficiency potentially needing drug therapy adjustment, and percentage of pre-hospital drug intakes not adjusted to liver function. Results Of 1200 patients, 130 (11%) had at least one clinically relevant elevated liver parameter at hospital admission. Of these, need for drug adjustment to liver function was found for 16-36%, depending on the liver score used (equivalent to 2-4% of all patients), with the highest number of patients detected by the MELD- and MELDNa-score. Pre-hospital medication concerned 719 drug intakes and was contraindicated in 2%, dosage not adjusted in 3%, and evaluation not possible in 44% of all drug intakes due to lack of information on the drug. Conclusion A significant proportion of patients admitted for surgery have clinically elevated liver parameters and potentially need medication adjustment. A pharmacist-led screening already at hospital admission can support the identification of patients with clinically relevant elevated liver parameters and patients at risk by calculating liver scores under routine conditions. Evaluation of drug adjustment to liver function is challenging, since no data are available in routine resources for a considerable number of drugs.

Development and Validation of a Model Consisting of Comorbidity Burden to Calculate Risk of Death Within 6 Months for Patients With Suspected Drug-Induced Liver Injury

BACKGROUND & AIMS

Patients with drug-induced liver injury (DILI) frequently have comorbid conditions, but the effects of non-liver comorbidities on outcomes are not well understood. We investigated the association between comorbidity burden and outcomes of patients with DILI, and developed and validated a model to calculate risk of death within 6 months.

METHODS

A multiple logistic regression model identified variables independently associated with death within 6 months of presenting with suspected DILI (6-month mortality) for 306 patients enrolled in the Drug-Induced Liver Injury Network prospective study at Indiana University (discovery cohort). The model was validated using data from 247 patients with suspected DILI enrolled in the same study at the University of North Carolina (validation cohort). Medical comorbidity burden was calculated using the Charlson Comorbidity Index-patients with scores higher than 2 were considered to have significant comorbidities.

RESULTS

Six-month mortality was 8.5% in the discovery cohort and 4.5% in the validation cohort. In the discovery cohort, significant comorbidities (odds ratio, 5.4; 95% confidence interval [CI], 2.1-13.8), Model for End-Stage Liver Disease score (odds ratio, 1.11; 95% CI, 1.04-1.17), and serum level of albumin at presentation (odds ratio, 0.39; 95% CI, 0.2-0.76) were independently associated with 6-month mortality. A model based on these 3 variables identified patients who died within 6 months, with c-statistic values of 0.89 (95% CI, 0.86-0.94) in the discovery cohort and 0.91 (95% CI, 0.83-0.99) in the validation cohort. We developed a web-based calculator for use in the clinic to determine risk of death within 6 months for patients with suspected DILI.

CONCLUSIONS

We developed and validated a model based on comorbidity burden, Model for End-Stage Liver Disease score, and serum level of albumin that predicts 6-month mortality in patients with suspected DILI.

Potential savings in the treatment pathway of liver transplantation: an inter-sectorial analysis of cost-rising factors

INTRODUCTION

Identification of cost-driving factors in patients undergoing liver transplantation is essential to target reallocation of resources and potential savings.

AIM

The aim of this study is to identify main cost-driving factors in liver transplantation from the perspective of the Statutory Health Insurance.

METHODS

Variables were analyzed with multivariable logistic regression to determine their influence on high cost cases (fourth quartile) in the outpatient, inpatient and rehabilitative healthcare sectors as well as for medications.

RESULTS

Significant cost-driving factors for the inpatient sector of care were a high labMELD-score (OR 1.042), subsequent re-transplantations (OR 7.159) and patient mortality (OR 3.555). Expenditures for rehabilitative care were significantly higher in patients with a lower adjusted Charlson comorbidity index (OR 0.601). The indication of viral cirrhosis and hepatocellular carcinoma resulted in significantly higher costs for medications (OR 21.618 and 7.429). For all sectors of care and medications each waiting day had a significant impact on high treatment costs (OR 1.001). Overall, cost-driving factors resulted in higher median treatment costs of 211,435 €.

CONCLUSIONS

Treatment costs in liver transplantation were significantly influenced by identified factors. Long pre-transplant waiting times that increase overall treatment costs need to be alleviated by a substantial increase in donor organs to enable transplantation with lower labMELD-scores. Disease management programs, the implementation of a case management for vulnerable patients, medication plans and patient tracking in a transplant registry may enable cost savings, e.g., by the avoidance of otherwise necessary re-transplants or incorrect medication.

The effects of patient cost sharing on inpatient utilization, cost, and outcome

Background

Health insurance and provider payment reforms all over the world beg a key empirical question: what are the potential impacts of patient cost-sharing on health care utilization, cost and outcomes? The unique health insurance system and rich electronic medical record (EMR) data in China provides us a unique opportunity to study this topic.

Methods

Four years (2010 to 2014) of EMR data from one medical center in China were utilized, including 10,858 adult patients with liver diseases. We measured patient cost-sharing using actual reimbursement ratio (RR) which is allowed us to better capture financial incentive than using type of health insurance. A rigorous risk adjustment method was employed with both comorbidities and disease severity measures acting as risk adjustors. Associations between RR and health use, costs and outcome were analyzed by multivariate analyses.

Results

After risk adjustment, patients with more generous health insurance coverage (higher RR) were found to have longer hospital stay, higher total cost, higher medication cost, and higher ratio of medication to total cost, as well as higher number and likelihood that specific procedures were performed.

Conclusion

Our study implied that patient cost-sharing affects health care services use and cost. This reflects how patients and physicians respond to financial incentives in the current healthcare system in China, and the responses could be a joint effect of both demand and supply side moral hazard. In order to contain cost and improve efficiency in the system, reforming provide payment and insurance scheme is urgently needed.