Validation of a hierarchical algorithm to define chronic liver disease and cirrhosis etiology in administrative healthcare data.

BACKGROUND AND AIMS: Chronic liver disease (CLD) and cirrhosis are leading causes of death globally with the burden of disease rising significantly over the past several decades. Defining the etiology of liver disease is important for understanding liver disease epidemiology, healthcare planning, and outcomes. The aim of this study was to validate a hierarchical algorithm for CLD and cirrhosis etiology in administrative healthcare data. METHODS: Consecutive patients with CLD or cirrhosis attending an outpatient hepatology clinic in Ontario, Canada from 05/01/2013-08/31/2013 underwent detailed chart abstraction. Gold standard liver disease etiology was determined by an attending hepatologist as hepatitis C (HCV), hepatitis B (HBV), alcohol-related, non-alcoholic fatty liver disease (NAFLD)/cryptogenic, autoimmune or hemochromatosis. Individual data was linked to routinely collected administrative healthcare data at ICES. Diagnostic accuracy of a hierarchical algorithm incorporating both laboratory and administrative codes to define etiology was evaluated by calculating sensitivity, specificity, positive (PPV) and negative predictive values (NPV), and kappa's agreement. RESULTS: 442 individuals underwent chart abstraction (median age 53 years, 53% cirrhosis, 45% HCV, 26% NAFLD, 10% alcohol-related). In patients with cirrhosis, the algorithm had adequate sensitivity/PPV (>75%) and excellent specificity/NPV (>90%) for all etiologies. In those without cirrhosis, the algorithm was excellent for all etiologies except for hemochromatosis and autoimmune diseases. CONCLUSIONS: A hierarchical algorithm incorporating laboratory and administrative coding can accurately define cirrhosis etiology in routinely collected healthcare data. These results should facilitate health services research in this growing patient population.

Acceptability and efficacy of naltrexone for criminal justice-involved individuals with opioid use disorder: a systematic review and meta-analysis.

BACKGROUND AND AIMS: Criminal justice-involved individuals carry a disproportionately higher burden of opioid use disorder (OUD) than those not involved with the criminal justice system, and are often unable to access opioid agonist therapies such as methadone and buprenorphine. The opioid receptor antagonist naltrexone (NTX) is effective for the prevention of relapse to OUD and may be more acceptable in criminal justice settings. The objectives of this review were to: (1) provide an overall summary effect across studies for the efficacy and acceptability of oral and injectable NTX for the treatment of OUD among criminal justice-involved individuals and (2) examine systematic variations in study results to explain heterogeneity among study-specific effects. METHODS: Systematic review and meta-analysis of 1045 patients across 11 studies (10 randomized controlled trials, one quasi-experimental study). All available outcomes were pooled using random-effects meta-analysis. Subgroup analyses were conducted for oral and injectable naltrexone; meta-regression analyses were conducted for socio-demographic and study-level characteristics. RESULTS: NTX improved retention in treatment [risk ratio (RR) = 1.31; 95% confidence interval (CI) = 1.05, 1.63], reduced rates of re-incarceration (RR = 0.70, 95% CI = 0.54-0.92), reduced opioid relapse (RR = 0.63, 95% CI = 0.53-0.76) and improved opioid abstinence (RR = 1.38, 95% CI = 1.16-1.65). While NTX was associated with a greater burden of adverse events overall (RR = 1.49, 95% CI = 1.13-1.95), the findings were inconclusive as to whether or not a difference was present for the number of serious adverse events or overdoses. CONCLUSIONS: Naltrexone appears to be efficacious and acceptable for the treatment of opioid use disorder among criminal justice-involved individuals; however, the risk for adverse events must be weighed against the potential benefits.

Identifying cirrhosis, decompensated cirrhosis and hepatocellular carcinoma in health administrative data: A validation study.

BACKGROUND: To evaluate screening and treatment strategies, large-scale real-world data on liver disease-related outcomes are needed. We sought to validate health administrative data for identification of cirrhosis, decompensated cirrhosis and hepatocellular carcinoma among patients with known liver disease. METHODS: Primary patient data were abstracted from patients of the Toronto Center for Liver Disease with viral hepatitis (2006-2014), and all patients with liver disease from the Kingston Health Sciences Centre Hepatology Clinic (2013). We linked clinical information to health administrative data and tested a range of coding algorithms against the clinical reference standard. RESULTS: A total of 6,714 patients had primary chart data abstracted. A single physician visit code for cirrhosis was sensitive (98-99%), and a single hospital diagnostic code for cirrhosis was specific (91-96%). The most sensitive algorithm for decompensated cirrhosis was one cirrhosis code with any of: a hospital diagnostic code, death code, or procedure code for decompensation (range 88-99% across groups). The most specific was one cirrhosis code and one hospital diagnostic code (range 89-98% across groups). Two physician visit codes or a single hospital diagnostic code, death code, or procedure code combined with a code for cirrhosis were sensitive and specific for hepatocellular carcinoma (sensitivity 94-96%, specificity 93-98%). CONCLUSION: These sensitive and specific algorithms can be used to define patient cohorts or detect clinical outcomes using health administrative data. Our results will facilitate research into the adequacy of screening and treatment for patients with chronic viral hepatitis or other liver diseases.