New Alert Override Codes for the Drug Utilization Review System Derived from Outpatient Prescription Data from a Tertiary Teaching Hospital in Korea

Development and validation of a medication-based risk prediction model for acute kidney injury in older outpatients

BACKGROUND

Older adults are at an increased risk of acute kidney injury (AKI), particularly in community settings, often due to medications. Effective prevention hinges on identifying high-risk patients, yet existing models for predicting AKI risk in older outpatients are scarce, particularly those incorporating medication variables. We aimed to develop an AKI risk prediction model that included medication-related variables for older outpatients.

METHODS

We constructed a cohort of 2,272,257 outpatients aged ≥65 years using a national claims database. This cohort was split into a development (70%) and validation (30%) groups. Our primary goal was to identify newly diagnosed AKI within one month of cohort entry in an outpatient context. We screened 170 variables and developed a risk prediction model using logistic regression.

RESULTS

The final model integrated 12 variables: 2 demographic, 4 comorbid, and 6 medication-related. It showed good performance with acceptable calibration. In the validation cohort, the area under the receiver operating characteristic curve value was 0.720 (95% confidence interval, 0.692-0.748). Sensitivity and specificity were 69.9% and 61.9%, respectively. Notably, the model identified high-risk patients as having a 27-fold increased AKI risk compared with low-risk individuals.

CONCLUSION

We have developed a new AKI risk prediction model for older outpatients, incorporating critical medication-related variables with good discrimination. This tool may be useful in identifying and targeting patients who may require interventions to prevent AKI in an outpatient setting.

Development of a claims-based risk-scoring model to predict emergency department visits in older patients receiving anti-neoplastic therapy

This study developed and validated a risk-scoring model, with a particular emphasis on medication-related factors, to predict emergency department (ED) visits among older Korean adults (aged 65 and older) undergoing anti-neoplastic therapy. Utilizing national claims data, we constructed two cohorts: the development cohort (2016-2018) with 34,642 patients and validation cohort (2019) with 10,902 patients. The model included a comprehensive set of predictors: demographics, cancer type, comorbid conditions, ED visit history, and medication use variables. We employed the least absolute shrinkage and selection operator (LASSO) regression to refine and select the most relevant predictors. Out of 120 predictor variables, 12 were integral to the final model, including seven related to medication use. The model demonstrated acceptable predictive performance in the validation cohort with a C-statistic of 0.76 (95% CI 0.74-0.77), indicating reasonable calibration. This risk-scoring model, after further clinical validation, has the potential to assist healthcare providers in the effective management and care of older patients receiving anti-neoplastic therapy.

Effect of nationwide concurrent drug utilization review program on drug-drug interactions and related health outcome

BACKGROUND

A computerized drug utilization review (DUR) program has provided physicians and pharmacists with alerts on drug-drug interactions (DDIs), drug-age precautions and therapeutic duplication in Korea since 2010.

OBJECTIVE

The purpose of this study was to evaluate the impact of the DUR program on health outcomes associated with DDIs.

METHODS

An uncontrolled before-after study was performed to investigate the impact of the nationwide DUR program on DDIs and related health outcomes. The study population consisted of people who used two types of DDI pairs before DUR implementation (from January 2009 to December 2010) and post-DUR implementation (from January 2012 to December 2013); (i) benzodiazepines with concurrent use of metabolic enzyme inhibitors and (ii) QTc (heart-rate corrected QT interval) prolongation agents. The main outcome measures were all-cause and cause-specific hospitalization admissions or emergency department (ED) visits.

RESULTS

This study included 107 874 people who used benzodiazepines with enzyme inhibitors and 8489 who received co-medication of QTc prolongation agents. For patients receiving a combination of benzodiazepines and enzyme inhibitors, both all-cause hospitalization and cause-specific hospitalization decreased after DUR implementation, from 43.2% to 41.7% and from 4.6% to 4.5% (adjusted odds ratio [OR] = 0.96; 95% confidence interval (CI), 0.93-0.98; OR = 0.89, 95% CI = 0.84-0.99, respectively). For patients receiving co-medication of QTc prolongation agents, all-cause hospitalization (54.2%) was lower than before (54.9%) (OR = 0.87, 95% CI = 0.79-0.96), but no significant change was found for cause-specific hospitalization and ED visits.

CONCLUSION

Implementation of a DUR program may reduce the adverse health outcomes posed by DDIs in patients on combination of benzodiazepines and enzyme inhibitors potentially QTc-prolongation agents.

Duplicated tramadol use in chronic low back pain: A nationwide cross-sectional study

Tramadol is a weak opioid that is commonly used for chronic low back pain (LBP). Despite its effectiveness, duplicated use of tramadol, which may indicate abuse or dependence, may exacerbate potential adverse reactions. This population-based, cross-sectional study aimed to investigate the prevalence of duplication of tramadol and its associated factors among patients with LBP. From a Korean nationwide claims database, non-hospitalized patients aged 40-99 years with LBP without malignancy were prescribed tramadol during 2014-2016. Duplication of tramadol was defined as overlapping of prescription days. Among them, we defined "extensive duplication (ED)" when days of tramadol duplication cover 10% or more of the days prescribed tramadol. Patient and healthcare utilization factors associated with ED were examined using a logistic regression model. The study population was 6 417 503 patients. Of these, 13.7% were ED users. The age- and sex-standardized prevalence of using tramadol twice or more a year was 14.06 per 100 people in 2014, 13.74 per 100 people in 2015 and 13.52 per 100 people in 2016. ED occurred more in those in the group aged 70-79 years (OR 1.12, 95% CI 1.11-1.13) than 40-49 years and in those with comorbidities, such as drug abuse (OR 2.99, 95% CI 2.05-4.36) or depression (OR 1.75, 95% CI 1.72-1.77). Based on the results of this study, a proper management system is needed to avoid tramadol duplication among older people and patients with drug abuse or depression.

National Rules for Drug-Drug Interactions: Are They Appropriate for Tertiary Hospitals?

The application of appropriate rules for drug-drug interactions (DDIs) could substantially reduce the number of adverse drug events. However, current implementations of such rules in tertiary hospitals are problematic as physicians are receiving too many alerts, causing high override rates and alert fatigue. We investigated the potential impact of Korean national DDI rules in a drug utilization review program in terms of their severity coverage and the clinical efficiency of how physicians respond to them. Using lists of high-priority DDIs developed with the support of the U.S. government, we evaluated 706 contraindicated DDI pairs released in May 2015. We evaluated clinical log data from one tertiary hospital and prescription data from two other tertiary hospitals. The measured parameters were national DDI rule coverage for high-priority DDIs, alert override rate, and number of prescription pairs. The coverage rates of national DDI rules were 80% and 3.0% at the class and drug levels, respectively. The analysis of the system log data showed an overall override rate of 79.6%. Only 0.3% of all of the alerts (n = 66) were high-priority DDI rules. These showed a lower override rate of 51.5%, which was much lower than for the overall DDI rules. We also found 342 and 80 unmatched high-priority DDI pairs which were absent in national rules in inpatient orders from the other two hospitals. The national DDI rules are not complete in terms of their coverage of severe DDIs. They also lack clinical efficiency in tertiary settings, suggesting improved systematic approaches are needed.