Owning Attention: Applying Human Factors Principles to Support Clinical Decision Support

In the best examples, clinical decision support (CDS) systems guide clinician decision-making and actions, prevent errors, improve quality, reduce costs, save time, and promote the use of evidence-based recommendations. However, the potential solution that CDS represents are limited by problems associated with improper design, implementation, and local customization. Despite an emphasis on electronic health record usability, little progress has been made to protect end-users from inadequately designed workflows and unnecessary interruptions. Intelligent and personalized design creates an opportunity to tailor CDS not just at the patient level but specific to the disease condition, provider experience, and available resources at the healthcare system level. This chapter leverages the Five Rights of CDS framework to demonstrate the application of human factors engineering principles and emerging trends to optimize data analytics, usability, workflow, and design

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

Clinical decision support systems for opioid prescribing for chronic non-cancer pain in primary care : a scoping review

Background and Objectives: Clinical decision support systems (CDSSs) may help clinicians prescribe opioids for chronic noncancer pain (CNCP) more appropriately. This scoping review determined the extent and range of the current evidence on CDSSs for opioid prescribing for CNCP in primary care, and whether investigators followed best evidence and current guidance in designing, implementing and evaluating these complex interventions. Methods: We searched 9 electronic databases and other data sources for studies from January 1, 2008 to October 11, 2019. Two reviewers independently screened the citations. One reviewer extracted data and a second verified for accuracy. INCLUSION CRITERIA: study of a CDSS for opioid prescribing for CNCP in a primary care clinical setting. We reported quantitative results in tables and qualitative results in narrative form. Results: Our search yielded 5068 records, of which 14 studies met our inclusion criteria. All studies were conducted in the United States. Six studies examined local (eg, health center) CDSSs and 8 examined prescription drug monitoring program CDSSs. Three CDSSs incorporated evidence-based components. Study aims were heterogeneous and study designs included both quantitative and qualitative methodologies. No studies assessed patient health outcomes. Few studies appeared to be following guidance for evaluating complex interventions.  Conclusions: Few studies have rigorously assessed the use of CDSSs for opioid prescribing for CNCP in primary care settings. Going forward, investigators should include evidence-based components into the design of CDSSs and follow guidance for the development and evaluation of complex interventions.PostprintPeer reviewe

E-Health Hazards: Provider Liability and Electronic Health Record Systems

In the foreseeable future, electronic health record (EHR) systems are likely to become a fixture in medical settings. The potential benefits of computerization could be substantial, but EHR systems also give rise to new liability risks for health care providers that have received little attention in the legal literature. This Article features a first of its kind, comprehensive analysis of the liability risks associated with use of this complex and important technology. In addition, it develops recommendations to address these liability concerns. Appropriate measures include federal regulations designed to ensure the quality and safety of EHR systems along with agency guidance and well crafted clinical practice guidelines for EHR system users. In formulating its recommendations, the Article proposes a novel, uniform process for developing authoritative clinical practice guidelines and explores how EHR technology itself can enable experts to gather evidence of best practices. The authors argue that without thoughtful interventions and sound guidance from government and medical organizations, this promising technology may encumber rather than support clinicians and may hinder rather than promote health outcome improvements