The use of a clinical decision support tool to assess the risk of QT drug–drug interactions in community pharmacies

Introduction: The handling of drug–drug interactions regarding QTc-prolongation (QT-DDIs) is not well defined. A clinical decision support (CDS) tool will support risk management of QT-DDIs. Therefore, we studied the effect of a CDS tool on the proportion of QT-DDIs for which an intervention was considered by pharmacists. Methods: An intervention study was performed using a pre- and post-design in 20 community pharmacies in The Netherlands. All QT-DDIs that occurred during a before- and after-period of three months were included. The impact of the use of a CDS tool to support the handling of QT-DDIs was studied. For each QT-DDI, handling of the QT-DDI and patient characteristics were extracted from the pharmacy information system. Primary outcome was the proportion of QT-DDIs with an intervention. Secondary outcomes were the type of interventions and the time associated with handling QT-DDIs. Logistic regression analysis was used to analyse the primary outcome. Results: Two hundred and forty-four QT-DDIs pre-CDS tool and 157 QT-DDIs post-CDS tool were included. Pharmacists intervened in 43.0% and 35.7% of the QT-DDIs pre- and post-CDS tool respectively (odds ratio 0.74; 95% confidence interval 0.49–1.11). Substitution of interacting agents was the most frequent intervention. Pharmacists spent 20.8 ± 3.5 min (mean ± SD) on handling QT-DDIs pre-CDS tool, which was reduced to 14.9 ± 2.4 min (mean ± SD) post-CDS tool. Of these, 4.5 ± 0.7 min (mean ± SD) were spent on the CDS tool. Conclusion: The CDS tool might be a first step to developing a tool to manage QT-DDIs via a structured approach. Improvement of the tool is needed in order to increase its diagnostic value and reduce redundant QT-DDI alerts. Plain Language Summary: The use of a tool to support the handling of QTc-prolonging drug interactions in community pharmacies Introduction: Several drugs have the ability to cause heart rhythm disturbances as a rare side effect. This rhythm disturbance is called QTc-interval prolongation. It may result in cardiac arrest. For health care professionals, such as physicians and pharmacists, it is diffic

Clinical decision support systems in the care of hospitalised patients with diabetes

This thesis explored the role of health informatics (decision support systems) in caring for hospitalised patients with diabetes through a systematic review and by analysing data from University Hospital Birmingham, UK. Findings from the thesis: 1) highlight the potential role of computerised physician order entry system in improving guideline based anti-diabetic medication prescription in particular insulin prescription, and their effectiveness in contributing to better glycaemic control; 2) quantify the occurrence of missed discharge diagnostic codes for diabetes using electronic prescription data and suggests 60% of this could be potentially reduced using an algorithm that could be introduced as part of the information system; 3) found that hypoglycaemia and foot disease in hospitalised diabetes patients were independently associated with higher in-hospital mortality rates and longer length of stay; 4) quantify the hypoglycaemia rates in non-diabetic patients and proposes one method of establishing a surveillance system to identify non diabetic hypoglycaemic patients; and 5) introduces a prediction model that may be useful to identify patients with diabetes at risk of poor clinical outcomes during their hospital stay

A Generic Approach to Supporting the Management of Computerised Clinical Guidelines and Protocols

Clinical guidelines or protocols (CGPs) are statements that are systematically developed for the purpose of guiding the clinician and the patient in making decisions about appropriate healthcare for specific clinical problems. Using CGPs is one of the most effective and proven ways to attaining improved quality, optimised resource utilisation, cost containment and reduced variation in healthcare practice. CGPs exist mainly as paper-based natural language statements, but are increasingly being computerised. Supporting computerised CGPs in a healthcare environment so that they are incorporated into the routine used daily by clinicians is complex and presents major information management challenges. This thesis contends that the management of computerised CGPs should incorporate their manipulation (operations and queries), in addition to their specification and execution, as part of a single unified management framework. The thesis applies modern advanced database technology to the task of managing computerised CGPs. The event-condition-action (ECA) rule paradigm is recognised to have a huge potential in supporting computerised CGPs. In this thesis, a unified generic framework, called SpEM and an approach, called MonCooS, were developed for enabling computerised CGPs, to be specified by using a specification language, called PLAN, which follows the ECA rule paradigm; executed by using a software mechanism based on the ECA mechanism within a modern database system, and manipulated by using a manipulation language, called TOPSQL. The MonCooS approach focuses on providing clinicians with assistance in monitoring and coordinating clinical interventions while leaving the reasoning task to domain experts. A proof-of-concepts system, TOPS, was developed to show that CGP management can be easily attained, within the SpEM framework, by using the MonCooS approach. TOPS is used to evaluate the framework and approach in a case study to manage a microalbuminuria protocol for diabetic patients. SpEM and MonCooS were found to be promising in supporting the full-scale management of information and knowledge for the computerised clinical protocol. Active capability within modern DBMS is still experiencing significant limitations in supporting some requirements of this application domain. These limitations lead to pointers for further improvements in database management system (DBMS) functionality for ECA rule support. The main contributions of this thesis are: a generic and unified framework for the management of CGPs; a general platform and an advanced software mechanism for the manipulation of information and knowledge in computerised CGPs; a requirement for further development of the active functionality within modern DBMS; and a case study for the computer-based management of microalbuminuria in diabetes patients

Bar-Code Technology and Nursing Adaptations

Background: Medication administration errors (MAEs) have long been a prevalent problem and endanger patient safety. Bar-code medication administration (BCMA) systems were developed for the purpose of preventing the occurrence of MAEs. However, it has been demonstrated that the implementation of BCMA has brought about unanticipated consequences on nursing work and new, potential predictable paths to MAEs. More recently, investigators have introduced a new approach to describe the impact of BCMA on nursing work, which reflects nurses’ adaptations to the operational problems of BCMA under difficult circumstances. A more complete understanding of the process of nurses’ adaptations to technology will better inform intervention program for performance and safety improvement. Specific Aims: The specific aims of this study were to: 1) conduct an integrative literature review about operational problems of BCMA, 2) validate a typology of operational problems of BCMA yielded in the literature review, and 3) assess nurses’ adaptations to BCMA operational problems and describe their perceptions about the adaptations. Conceptual Framework: The conceptual framework guided this study was an integration of the work system from the Systems Engineering Initiative for Patient Safety (SEIPS) model and the frames perspective. When there is a collision between the frames (system frame and practice frame), the operational problems occur, and then nurses make adaptations to the operational problems. In this study, it is considered that the “system frame” is functionalized as the “work system”, which is the core of the SEIPS model. Methods: A prospective, exploratory design was conducted to meet the study aims. This descriptive study included two convenience samples of registered nurses working on identified medical and surgical adult acute care units. An observation of BCMA use and a semi-structured interview was conducted with each participant of one group of sample (N=22) to collect data about the operational problems of BCMA. Another group of sample (N=21) conducted scenario interviews and follow-up interviews to describe their adaptations to the operational problems of BCMA. Results: This study found that 1) the triggers of operational problems of BCMA can be categorized according to the elements of the work system of the SEIPS model, which are technology and tools, tasks, person, environment, and organization; 2) the five elements of the SEIPS work system were validated for use as a typology of the triggers of operational problems of BCMA; 3) nurses conducted different adaptations with various strategies to accommodate to the operational problems of medication administration using BCMA; and 4) the perceptions of nurses about the adaptations to the operational problems of BCMA can be addressed by the sequential steps, implying nurses think in a logic and objective way during adaptations. Conclusions: This study provides a new way to approach the impact of BCMA on nursing work – adaptations. This is one of the first studies that attempts to understand nurses’ adaptations to the operational problems of BCMA, and also one of the first studies that investigates nurses’ perceptions about adaptations. Future research should more rigorously study nurses’ adaptive behaviors to operational problems.PHDNursingUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/146043/1/liujia_1.pd

Contextualized Drug–Drug Interaction Management Improves Clinical Utility Compared With Basic Drug–Drug Interaction Management in Hospitalized Patients

Drug–drug interactions (DDIs) frequently trigger adverse drug events or reduced efficacy. Most DDI alerts, however, are overridden because of irrelevance for the specific patient. Basic DDI clinical decision support (CDS) systems offer limited possibilities for decreasing the number of irrelevant DDI alerts without missing relevant ones. Computerized decision tree rules were designed to context-dependently suppress irrelevant DDI alerts. A crossover study was performed to compare the clinical utility of contextualized and basic DDI management in hospitalized patients. First, a basic DDI-CDS system was used in clinical practice while contextualized DDI alerts were collected in the background. Next, this process was reversed. All medication orders (MOs) from hospitalized patients with at least one DDI alert were included. The following outcome measures were used to assess clinical utility: positive predictive value (PPV), negative predictive value (NPV), number of pharmacy interventions (PIs)/1,000 MOs, and the median time spent on DDI management/1,000 MOs. During the basic DDI management phase 1,919 MOs/day were included, triggering 220 DDI alerts/1,000 MOs; showing 57 basic DDI alerts/1,000 MOs to pharmacy staff; PPV was 2.8% with 1.6 PIs/1,000 MOs costing 37.2 minutes/1,000 MOs. No DDIs were missed by the contextualized CDS system (NPV 100%). During the contextualized DDI management phase 1,853 MOs/day were included, triggering 244 basic DDI alerts/1,000 MOs, showing 9.6 contextualized DDIs/1,000 MOs to pharmacy staff; PPV was 41.4% (P < 0.01), with 4.0 PIs/1,000 MOs (P < 0.01) and 13.7 minutes/1,000 MOs. The clinical utility of contextualized DDI management exceeds that of basic DDI management

Parkinson's Disease Management through ICT

Parkinson's Disease (PD) is a neurodegenerative disorder that manifests with motor and non-motor symptoms. PD treatment is symptomatic and tries to alleviate the associated symptoms through an adjustment of the medication. As the disease is evolving and this evolution is patient specific, it could be very difficult to properly manage the disease.The current available technology (electronics, communication, computing, etc.), correctly combined with wearables, can be of great use for obtaining and processing useful information for both clinicians and patients allowing them to become actively involved in their condition.Parkinson's Disease Management through ICT: The REMPARK Approach presents the work done, main results and conclusions of the REMPARK project (2011 – 2015) funded by the European Union under contract FP7-ICT-2011-7-287677. REMPARK system was proposed and developed as a real Personal Health Device for the Remote and Autonomous Management of Parkinson’s Disease, composed of different levels of interaction with the patient, clinician and carers, and integrating a set of interconnected sub-systems: sensor, auditory cueing, Smartphone and server. The sensor subsystem, using embedded algorithmics, is able to detect the motor symptoms associated with PD in real time. This information, sent through the Smartphone to the REMPARK server, is used for an efficient management of the disease

An investigation of healthcare professionals’ experiences of training and using electronic prescribing systems: four literature reviews and two qualitative studies undertaken in the UK hospital context

Electronic prescribing (ePrescribing) is the process of ordering medicines electronically for a patient and has been associated with reduced medication errors and improved patient safety. However, these systems have also been associated with unintended adverse consequences. There is a lack of published research about users’ experiences of these systems in UK hospitals. The aim of this research was therefore to firstly describe the literature pertaining to the recent developments and persisting issues with ePrescribing and clinical decision support systems (CDS) (chapter 2). Two further systematic literature reviews (chapters 3 and 4) were then conducted to understand the unintended consequences of ePrescribing and clinical decision support (CDS) systems across both adult and paediatric patients. These revealed a taxonomy of factors, which have contributed to errors during use of these systems e.g., the screen layout, default settings and inappropriate drug-dosage support. The researcher then conducted a qualitative study (chapters 7-10) to explore users’ experiences of using and being trained to use ePrescribing systems. This study involved conducting semi-structured interviews and observations, which revealed key challenges facing users, including issues with using the ‘Medication List’ and how information was presented. Users experienced benefits and challenges when customising the system, including the screen display; however, the process was sometimes overly complex. Users also described the benefits and challenges associated with different forms of interruptive and passive CDS. Order sets, for instance, encouraged more efficient prescribing, yet users often found them difficult to find within the system. A lack of training resulted in users failing to use all features of the ePrescribing system and left some healthcare staff feeling underprepared for using the system in their role. A further literature review (chapter 5) was then performed to complement emerging themes relating to how users were trained to use ePrescribing systems, which were generated as part of a qualitative study. This review revealed the range of approaches used to train users and the need for further research in this area. The literature review and qualitative study-based findings led to a follow-on study (chapter 10), whereby the researcher conducted semi-structured interviews to examine how users were trained to use ePrescribing systems across four NHS Hospital Trusts. A range of approaches were used to train users; tailored training, using clinically specific scenarios or matching the user’s profession to that of the trainer were preferred over lectures and e-learning may offer an efficient way of training large numbers of staff. However, further research is needed to investigate this and whether alternative approaches such as the use of students as trainers could be useful. This programme of work revealed the importance of human factors and user involvement in the design and ongoing development of ePrescribing systems. Training also played a role in users’ experiences of using the system and hospitals should carefully consider the training approaches used. This thesis provides recommendations gathered from the literature and primary data collection that can help inform organisations, system developers and further research in this area

Decision Support Systems

Decision support systems (DSS) have evolved over the past four decades from theoretical concepts into real world computerized applications. DSS architecture contains three key components: knowledge base, computerized model, and user interface. DSS simulate cognitive decision-making functions of humans based on artificial intelligence methodologies (including expert systems, data mining, machine learning, connectionism, logistical reasoning, etc.) in order to perform decision support functions. The applications of DSS cover many domains, ranging from aviation monitoring, transportation safety, clinical diagnosis, weather forecast, business management to internet search strategy. By combining knowledge bases with inference rules, DSS are able to provide suggestions to end users to improve decisions and outcomes. This book is written as a textbook so that it can be used in formal courses examining decision support systems. It may be used by both undergraduate and graduate students from diverse computer-related fields. It will also be of value to established professionals as a text for self-study or for reference