Inpatient opioid prescribing patterns and their effect on rehospitalisations: a nested case-control study using data from a Swiss public acute hospital.

AIMS OF THE STUDY: Opioid prescriptions have increased in Switzerland, even though current guidelines warn of their harms. If opioids for postoperative analgesia are not tapered before hospital discharge, patients are at risk of adverse events such as constipation, drowsiness, dependence, tolerance and withdrawal. The aim of this study was to investigate and quantify the potential association between opioids prescribed at discharge from hospital and rehospitalisation. METHODS: We conducted a nested case-control study using routinely collected electronic health records from a Swiss public acute hospital. Cases were patients aged 65 years or older admitted between November 2014 and December 2018, with documented opioid administration on the day of discharge and rehospitalisation within 18 or 30 days after discharge. Each case was matched to five controls for age, sex, year of hospitalisation and Charlson Comorbidity Index. We calculated odds ratios for 18-day and 30-day rehospitalisation based on exposure to opioids using a conditional logistic regression adjusted for potential confounders. Secondary analyses included stratifications into morphine-equivalent doses of <50 mg, 50-89 mg and ≥90 mg, and co-prescriptions of gabapentinoids and benzodiazepines. RESULTS: Of 22,471 included patients, 3144 rehospitalisations were identified, of which 1698 were 18-day rehospitalisations and 1446 were 30-day rehospitalisations. Documented opioid administration on the day of discharge was associated with 30-day rehospitalisation after adjustment for confounders (adjusted odds ratio 1.48; 95% CI 1.25-1.75, p <0.001), while no difference was observed in the likelihood of 18-day rehospitalisation. The combined prescription of opioids with benzodiazepines or gabapentinoids and morphine-equivalent doses >50 mg were rare. CONCLUSIONS: Patients receiving opioids on the day of discharge were 48% more likely to be readmitted to hospital within 30 days. Clinicians should aim to discontinue opioids started in hospital before discharge if possible. Patients receiving an opioid prescription should be educated and monitored as part of opioid stewardship programmes.

Drug-drug interactions with oral anticoagulants: information consistency assessment of three commonly used online drug interactions databases in Switzerland.

Background: Toxicity or treatment failure related to drug-drug interactions (DDIs) are known to significantly affect morbidity and hospitalization rates. Despite the availability of numerous databases for DDIs identification and management, their information often differs. Oral anticoagulants are deemed at risk of DDIs and a leading cause of adverse drug events, most of which being preventable. Although many databases include DDIs involving anticoagulants, none are specialized in them. Aim and method: This study aims to compare the DDIs information content of four direct oral anticoagulants and two vitamin K antagonists in three major DDI databases used in Switzerland: Lexi-Interact, Pharmavista, and MediQ. It evaluates the consistency of DDIs information in terms of differences in severity rating systems, mechanism of interaction, extraction and documentation processes and transparency. Results: This study revealed 2'496 DDIs for the six anticoagulants, with discrepant risk classifications. Only 13.2% of DDIs were common to all three databases. Overall concordance in risk classification (high, moderate, and low risk) was slight (Fleiss' kappa = 0.131), while high-risk DDIs demonstrated a fair agreement (Fleiss' kappa = 0.398). The nature and the mechanism of the DDIs were more consistent across databases. Qualitative assessments highlighted differences in the documentation process and transparency, and similarities for availability of risk classification and references. Discussion: This study highlights the discrepancies between three commonly used DDI databases and the inconsistency in how terminology is standardised and incorporated when classifying these DDIs. It also highlights the need for the creation of specialised tools for anticoagulant-related interactions.

Predicting delirium in older non-intensive care unit inpatients: development and validation of the DELIrium risK Tool (DELIKT).

BACKGROUND: Effective delirium prevention could benefit from automatic risk stratification of older inpatients using routinely collected clinical data. AIM: Primary aim was to develop and validate a delirium prediction model (DELIKT) suitable for implementation in hospitals. Secondary aim was to select an anticholinergic burden scale as a predictor. METHOD: We used one cohort for model development and another for validation with electronically available data collected within the first 24 h of admission. Included were patients aged ≥ 65, hospitalised ≥ 48 h with no stay > 24 h in an intensive care unit. Predictors, such as administrative and laboratory variables or an anticholinergic burden scale, were selected using a combination of feature selection filter method and forward/backward selection. The final model was based on logistic regression and the DELIKT was derived from the ß-coefficients. We report the following performance measures: area under the curve, sensitivity, specificity and odds ratio. RESULTS: Both cohorts were similar and included over 10,000 patients each (mean age 77.6 ± 7.6 years) with 11% experiencing delirium. The model included nine variables: age, medical department, dementia, hemi-/paraplegia, catheterisation, potassium, creatinine, polypharmacy and the anticholinergic burden measured with the Clinician-rated Anticholinergic Scale (CrAS). The external validation yielded an AUC of 0.795. With a cut-off at 20 points in the DELIKT, we received a sensitivity of 79.7%, specificity of 62.3% and an odds ratio of 5.9 (95% CI 5.2, 6.7). CONCLUSION: The DELIKT is a potentially automatic tool with predictors from standard care including the CrAS to identify patients at high risk for delirium.