ABSTRACT
OBJECTIVES: The prevalence, types, severity, risk ratings, and common pairs of involved drugs, and the most important potential drug-drug interactions (pDDIs) in coronavirus disease 2019 (-COVID-19) deceased cases were evaluated. MATERIALS AND METHODS: We reviewed the medical records of 157 confirmed COVID-19 deceased cases hospitalized in 27 province-wide hospitals. Patients' demographics and clinical data (including comorbidities, vital signs, length of in-hospital survival, electrocardiograms (ECGs), medications, and lab test results) were extracted. The online Lexi-interact database and Stockley's drug interactions reference were used to detect pDDIs retrospectively. The QTc interval and total Tisdale risk score were also calculated. Descriptive analysis, analysis of variance, Fisher exact test, and multivariate analysis were conducted for data analysis. RESULTS: Of 157 study cases, 63% were male, had a mean age of 68 years, and 55.7% had one or more underlying diseases. All patients had polypharmacy, with 69.2% having ≥ 15 drugs/day. We detected 2,416 pDDIs in patients' records, of which 658 (27.2%) were interactions with COVID drugs. Lopinavir/ritonavir among -COVID drugs and fentanyl among non-COVID drugs were commonly involved in the interactions. pDDIs was significantly higher in the polypharmacy group of ≥ 15 medications (p < 0.001). A majority (83%) had received drug(s) with the QTc prolongation effect, of whom 67% had actual QTc prolongations in their ECGs. The regression analysis showed that by increasing 6.7% in polypharmacy, one day increase in-hospital survival can be expected. Moreover, an increase of 2.3% in white blood cells or 10.5% in serum potassium level decreased in-hospital survival by 1%. CONCLUSION: The findings underscored the importance of careful drug choice, especially in the hectic search for early treatments in pandemics of novel diseases. Close monitoring of patients' drug choice is warranted for reducing pDDIs and their adverse effects in any new disease outbreak.
Subject(s)
COVID-19 , Drug-Related Side Effects and Adverse Reactions , Humans , Male , Aged , Female , Retrospective Studies , Drug Interactions , Polypharmacy , Multicenter Studies as TopicABSTRACT
BACKGROUND: Electronic personal health records (ePHRs) are defined as electronic applications through which individuals can access, manage, and share health information in a private, secure, and confidential environment. Existing evidence shows their benefits in improving outcomes, especially for chronic disease patients. However, their use has not been as widespread as expected partly due to barriers faced in their adoption and use. We aimed to identify the types of barriers to a patient, provider, and caregiver adoption/use of ePHRs and to analyze their extent in chronic disease care. METHODS: A systematic search in Medline, PubMed, Science Direct, Cumulative Index to Nursing and Allied Health Literature (CINAHL), the Cochrane Central Register of Controlled Trials, and the Institute of Electrical and Electronics Engineers (IEEE) database was performed to find original studies assessing barriers to ePHR adoption/use in chronic care until the end of 2018. Two researchers independently screened and extracted data. We used the PHR adoption model and the Unified Theory of Acceptance and Use of Technology to analyze the results. The Mixed Methods Appraisal Tool (MMAT) version 2018 was used to assess the quality of evidence in the included studies. RESULTS: Sixty publications met our inclusion criteria. Issues found hindering ePHR adoption/use in chronic disease care were associated with demographic factors (e.g., patient age and gender) along with key variables related to health status, computer literacy, preferences for direct communication, and patient's strategy for coping with a chronic condition; as well as factors related to medical practice/environment (e.g., providers' lack of interest or resistance to adopting ePHRs due to workload, lack of reimbursement, and lack of user training); technological (e.g., concerns over privacy and security, interoperability with electronic health record systems, and lack of customized features for chronic conditions); and chronic disease characteristics (e.g., multiplicities of co-morbid conditions, settings, and providers involved in chronic care). CONCLUSIONS: ePHRs can be meaningfully used in chronic disease care if they are implemented as a component of comprehensive care models specifically developed for this care. Our results provide insight into hurdles and barriers mitigating ePHR adoption/use in chronic disease care. A deeper understating of the interplay between these barriers will provide opportunities that can lead to an enhanced ePHR adoption/use.