DETECTING ADVERSE DRUG REACTIONS IN THE NURSING HOME SETTING USING A CLINICAL EVENT MONITOR

Adverse drug reactions (ADRs) are the most clinically significant and costly medication-related problems in nursing homes (NH), and are associated with an estimated 93,000 deaths a year and as much as $4 billion of excess healthcare expenditures. Current ADR detection and management strategies that rely on pharmacist retrospective chart reviews (i.e., usual care) are inadequate. Active medication monitoring systems, such as clinical event monitors, are recommended by many safety organizations as an alternative to detect and manage ADRs. These systems have been shown to be less expensive, faster, and identify ADRs not normally detected by clinicians in the hospital setting. The main research goal of this dissertation is to review the rationale for the development and subsequent evaluation of an active medication monitoring system to automate the detection of ADRs in the NH setting. This dissertation includes three parts and each part has its own emphasis and methodology centered on the main topic of better understanding of how to detect ADRs in the NH setting.The first paper describes a systematic review of pharmacy and laboratory signals used by clinical event monitors to detect ADRs in hospitalized adult patients. The second paper describes the development of a consensus list of agreed upon laboratory, pharmacy, and Minimum Data Set signals that can be used by a clinical event monitor to detect potential ADRs. The third paper describes the implementation and pharmacist evaluation of a clinical event monitor using the signals developed by consensus.The findings in the papers described will help us to better understand, design, and evaluate active medication monitoring systems to automate the detection of ADRs in the NH setting. Future research is needed to determine if NH patients managed by physicians who receive active medication monitoring alerts have more ADRs detected, have a faster ADR management response time, and result in more cost-savings from a societal perspective, compared to usual care

Automatic Detection of Adverse Drug Events in Geriatric Care: Study Proposal

BACKGROUND One-third of older inpatients experience adverse drug events (ADEs), which increase their mortality, morbidity, and health care use and costs. In particular, antithrombotic drugs are among the most at-risk medications for this population. Reporting systems have been implemented at the national, regional, and provider levels to monitor ADEs and design prevention strategies. Owing to their well-known limitations, automated detection technologies based on electronic medical records (EMRs) are being developed to routinely detect or predict ADEs. OBJECTIVE This study aims to develop and validate an automated detection tool for monitoring antithrombotic-related ADEs using EMRs from 4 large Swiss hospitals. We aim to assess cumulative incidences of hemorrhages and thromboses in older inpatients associated with the prescription of antithrombotic drugs, identify triggering factors, and propose improvements for clinical practice. METHODS This project is a multicenter, cross-sectional study based on 2015 to 2016 EMR data from 4 large hospitals in Switzerland: Lausanne, Geneva, and Zürich university hospitals, and Baden Cantonal Hospital. We have included inpatients aged ≥65 years who stayed at 1 of the 4 hospitals during 2015 or 2016, received at least one antithrombotic drug during their stay, and signed or were not opposed to a general consent for participation in research. First, clinical experts selected a list of relevant antithrombotic drugs along with their side effects, risks, and confounding factors. Second, administrative, clinical, prescription, and laboratory data available in the form of free text and structured data were extracted from study participants' EMRs. Third, several automated rule-based and machine learning-based algorithms are being developed, allowing for the identification of hemorrhage and thromboembolic events and their triggering factors from the extracted information. Finally, we plan to validate the developed detection tools (one per ADE type) through manual medical record review. Performance metrics for assessing internal validity will comprise the area under the receiver operating characteristic curve, F$_{1}$-score, sensitivity, specificity, and positive and negative predictive values. RESULTS After accounting for the inclusion and exclusion criteria, we will include 34,522 residents aged ≥65 years. The data will be analyzed in 2022, and the research project will run until the end of 2022 to mid-2023. CONCLUSIONS This project will allow for the introduction of measures to improve safety in prescribing antithrombotic drugs, which today remain among the drugs most involved in ADEs. The findings will be implemented in clinical practice using indicators of adverse events for risk management and training for health care professionals; the tools and methodologies developed will be disseminated for new research in this field. The increased performance of natural language processing as an important complement to structured data will bring existing tools to another level of efficiency in the detection of ADEs. Currently, such systems are unavailable in Switzerland. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) DERR1-10.2196/40456

Usability analysis of contending electronic health record systems

In this paper, we report measured usability of two leading EHR systems during procurement. A total of 18 users participated in paired-usability testing of three scenarios: ordering and managing medications by an outpatient physician, medicine administration by an inpatient nurse and scheduling of appointments by nursing staff. Data for audio, screen capture, satisfaction rating, task success and errors made was collected during testing. We found a clear difference between the systems for percentage of successfully completed tasks, two different satisfaction measures and perceived learnability when looking at the results over all scenarios. We conclude that usability should be evaluated during procurement and the difference in usability between systems could be revealed even with fewer measures than were used in our study. © 2019 American Psychological Association Inc. All rights reserved.Peer reviewe

Closed loop medication administration using mobile nursing information system

Through this long journey of PhD study including a research on ‘Closed Loop Medication Administration Using Mobile Nursing Information System’ and the thesis writing, I obtained a lot of knowledge and experience about research method and writing. I really very appreciate the help of all my supervisors

IHI Global Trigger Tool and patient safety monitoring in Finnish hospitals : Current experiences and future trends

Patient safety work relies on the service provider s ability to monitor the levels of patient safety achieved, identify where improvements are needed and follow the impact of implemented interventions. Trigger tools - means for performing focused medical records reviews either manually or automatically, are a strong candidate for supporting these tasks. This report examines the research evidence on the IHI Global Trigger Tool (GTT) and presents experiences accumulated in Finland during implementation of the tool in the hospital environment, as well as experimentations for further developments. In addition, the up-to-date evidence and future prospects on automated trigger tools are reviewed and discussed. The report aims to serve healthcare management and clinical staff working with patient safety issues on the organisational level, by providing background evidence with regard to trigger tool methodology and its implementation requirements. The report constitutes useful reading also for policy makers, developers and researchers in the fields of patient safety, healthcare quality and health information technology

Telemedicine

Telemedicine is a rapidly evolving field as new technologies are implemented for example for the development of wireless sensors, quality data transmission. Using the Internet applications such as counseling, clinical consultation support and home care monitoring and management are more and more realized, which improves access to high level medical care in underserved areas. The 23 chapters of this book present manifold examples of telemedicine treating both theoretical and practical foundations and application scenarios

Improving the reporting of adverse drug reactions by healthcare professionals in Australia: a mixed methods study

Introduction. Under-reporting adverse drug reactions (ADRs) is a significant healthcare problem as it delays identifying safety issues. Various strategies have been implemented to improve ADR reporting, however these have only been temporarily effective. Therefore, there is a need to create an effective intervention. Methods A mixed methods study was used for this research. In phase one, a retrospective analysis of hospital records identified whether ADR related admissions were reported. An analysis of a regulatory intervention to improve ADR reporting utilised a time series analysis to assess any improvement in this area. In phase 2, a survey was deployed to identify the barriers and enablers of ADR reporting, which were mapped to the Theoretical Domains Framework (TDF). In phase 3, the evidence was integrated to create a proposed intervention to improve ADR reporting. Results A total of 9% of admissions were considered ADR related. Up to 99% of all known ADRs were not reported. The impact of a regulatory intervention on ADR reporting showed that there was an increase of 0.41 reports per medicine (95%CI 0.02 – 0.80) and an almost 3-fold improvement in the quality of reporting. The survey was completed by 133 HCPs and knowing how to report ADRs (OR 3.58, 95%CI 1.05 – 12.2) and encountering ADRs (OR 18.6, 95%CI 5.52 – 62.5) were predictors of reporting. Content analysis identified three categories: modifying the reporting process, enabling clinicians to report ADRs, and creating a positive reporting culture. These were mapped to 3 domains: knowledge, environmental context/resources, and beliefs about consequences. Conclusion The findings from this mixed methods research suggest that a multifaceted approach targeting the three TDF behavioural domains would be required to improve the quantity and quality of reporting