ABSTRACT
BACKGROUND: The present study sought to determine the prevalence of chronic non-cancer pain (CNCP) among older adult inpatients with polypharmacy. It also aimed to analyse prescription patterns and assess the therapy adequacy and patient complexity for those with and without CNCP. METHODS: This 4-year longitudinal study examined data from an exhaustive acute care hospital register on home-dwelling older adult patients (≥65) with polypharmacy. Commonly known combinations of potentially inappropriate medications were used to estimate therapy adequacy. Patient complexity was evaluated by comparing number of comorbidities and investigating physical and cognitive deficits. RESULTS: We determined a prevalence of CNCP of 9.7% among all older adult inpatients with polypharmacy, rising to 11.3% for those aged ≥85. Overall, CNCP patients were prescribed more drugs and had more comorbidities and physical and cognitive deficits than patients without CNCP. Older adult patients with CNCP received more analgesics, greater quantities of opioids, paracetamol and co-analgesics and elevated opioid dosages. Older adult patients with CNCP aged ≥85 received fewer analgesics, opioids, non-steroidal anti-inflammatory drugs and co-analgesics but more paracetamol. Older adult patients with CNCP were prescribed more potentially inappropriate medications involving opioids. In particular, 24.5% received an opioid and a hypnotic (benzodiazepine or Z-drug), and 8.6% received an opioid and a gabapentinoid. CONCLUSION: Observed differences in medication use between older adult inpatients with or without CNCP may be relevant for clinical practice. Potentially inadequate co-prescribing (such as hypnotics and opioids) affects a higher proportion of patients with CNCP and may have serious unintended consequences. SIGNIFICANCE STATEMENT: This study describes differences in prescription patterns between people with and without chronic non-cancer pain in a large dataset of 20,422 discharges. The differences found may be relevant to clinical practice. In particular, high co-prescribing of opioids and hypnotics may have serious unintended consequences. Greater physical and cognitive deficits may indicate greater patient complexity, and appropriate interventions need to be developed to improve the management of this vulnerable patient group.
ABSTRACT
BACKGROUND: Medication-related readmissions challenge healthcare systems by burdening patients, increasing costs and straining resources. However, to date, there has been no consensus study on indicators for medication-related readmissions. OBJECTIVES: This Delphi study aimed to develop a consensus-based set of indicators for detecting patients at risk of medication-related readmission. METHODS: An expert panel of clinical pharmacists, physicians and nursing experts participated in a two-round Delphi study. In round 1, 31 indicators taken from the literature were rated for relevance on a scale from 1 to 9, with a median rating of 7 or higher suggesting relevance. The RAND/UCLA method was used to determine consensus. In round 2, indicators lacking consensus were re-rated together with a series of new indicators generated by the experts. Additional details were sought for some indicators. The main outcomes were the relevance of, consensus on, and completeness of the proposed indicators for identifying risks of 30-day medication-related readmission. RESULTS: Thirty-eight experts participated in round 1. Consensus was found for all the indicators, with 25 included and 6 excluded. Thirty-four experts participated in round 2. Consensus was found for all 5 newly suggested indicators, and 4 were included. The expert panel prioritized the following indicators: (1) insufficient communication between different healthcare providers, (2) polypharmacy (≥7 medications), (3) low rates of medication adherence (twice-weekly mistakes or missing administration), (4) complex medication regimens (≥3 doses, ≥2 dosage forms and ≥2 administration routes per day), and (5) multimorbidity (≥3 chronic conditions). The final set comprised 29 indicators. CONCLUSIONS: The indicator set developed for flagging potential medication-related readmissions could guide priorities for clinical pharmacy services at hospital discharge, improving patient outcomes and resource use. A validation study of these indicators is planned.
Subject(s)
Consensus , Delphi Technique , Patient Readmission , Pharmacists , Humans , Patient Readmission/statistics & numerical data , Pharmacists/organization & administration , Female , Male , PhysiciansABSTRACT
Voriconazole is among the first-line antifungal drugs to treat invasive fungal infections in children and known for its pronounced inter- and intraindividual pharmacokinetic variability. Polymorphisms in genes involved in the metabolism and transport of voriconazole are thought to influence serum concentrations and eventually the therapeutic outcome. To investigate the impact of these genetic variants and other covariates on voriconazole trough concentrations, we performed a retrospective data analysis, where we used medication data from 36 children suffering from invasive fungal infections treated with voriconazole. Data were extracted from clinical information systems with the new infrastructure SwissPKcdw, and linear mixed effects modelling was performed using R. Samples from 23 children were available for DNA extraction, from which 12 selected polymorphism were genotyped by real-time PCR. 192 (49.1%) of 391 trough serum concentrations measured were outside the recommended range. Voriconazole trough concentrations were influenced by polymorphisms within the metabolizing enzymes CYP2C19 and CYP3A4, and within the drug transporters ABCC2 and ABCG2, as well as by the co-medications ciprofloxacin, levetiracetam, and propranolol. In order to prescribe an optimal drug dosage, pre-emptive pharmacogenetic testing and careful consideration of co-medications in addition to therapeutic drug monitoring might improve voriconazole treatment outcome of children with invasive fungal infections.
ABSTRACT
The aminoglycoside gentamicin is used for the empirical treatment of pediatric infections. It has a narrow therapeutic window. In this prospective study at University Children's Hospital Zurich, Switzerland, we aimed to characterize the pharmacokinetics of gentamicin in pediatric patients and predict plasma concentrations at typical recommended doses. We recruited 109 patients aged from 1 day to 14 years, receiving gentamicin (7.5 mg/kg at age ≥ 7 d or 5 mg/kg). Plasma levels were determined 30 min, 4 h and 24 h after the infusion was stopped and then transferred, together with patient data, to the secure BioMedIT node Leonhard Med. Population pharmacokinetic modeling was performed with the open-source R package saemix on the SwissPKcdw platform in Leonhard Med. Data followed a two-compartment model. Bodyweight, plasma creatinine and urea were identified as covariates for clearance, with bodyweight as a covariate for central and peripheral volumes of distribution. Simulations with 7.5 mg/kg revealed a 95% CI of 13.0-21.2 mg/L plasma concentration at 30 min after the stopping of a 30-min infusion. At 24 h, 95% of simulated plasma levels were <1.8 mg/L. Our study revealed that the recommended dosing is appropriate. It showed that population pharmacokinetic modeling using R provides high flexibility in a secure environment.
