Achieving change in primary care—causes of the evidence to practice gap : systematic reviews of reviews

Acknowledgements The Evidence to Practice Project (SPCR FR4 project number: 122) is funded by the National Institute of Health Research (NIHR) School for Primary Care Research (SPCR). KD is part-funded by the National Institute for Health Research (NIHR) Collaborations for Leadership in Applied Research and Care West Midlands and by a Knowledge Mobilisation Research Fellowship (KMRF-2014-03-002) from the NIHR. This paper presents independent research funded by the National Institute of Health Research (NIHR). The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. Funding This study is funded by the National Institute for Health Research (NIHR) School for Primary Care Research (SPCR).Peer reviewedPublisher PD

A six-year repeated evaluation of computerized clinical decision support system user acceptability

OBJECTIVE: Long-term acceptability among computerized clinical decision support system (CDSS) users in pediatrics is unknown. We examine user acceptance patterns over six years of our continuous computerized CDSS integration and updates. MATERIALS AND METHODS: Users of Child Health Improvement through Computer Automation (CHICA), a CDSS integrated into clinical workflows and used in several urban pediatric community clinics, completed annual surveys including 11 questions covering user acceptability. We compared responses across years within a single healthcare system and between two healthcare systems. We used logistic regression to assess the odds of a favorable response to each question by survey year, clinic role, part-time status, and frequency of CHICA use. RESULTS: Data came from 380 completed surveys between 2011 and 2016. Responses were significantly more favorable for all but one measure by 2016 (OR range 2.90-12.17, all p < 0.01). Increasing system maturity was associated with improved perceived function of CHICA (OR range 4.24-7.58, p < 0.03). User familiarity was positively associated with perceived CDSS function (OR range 3.44-8.17, p < 0.05) and usability (OR range 9.71-15.89, p < 0.01) opinions. CONCLUSION: We present a long-term, repeated follow-up of user acceptability of a CDSS. Favorable opinions of the CDSS were more likely in frequent users, physicians and advanced practitioners, and full-time workers. CHICA acceptability increased as it matured and users become more familiar with it. System quality improvement, user support, and patience are important in achieving wide-ranging, sustainable acceptance of CDSS

Nurses As Knowledge Work Agents: Measuring The Impact Of A Clinical Decision Support System On Nurses\u27 Perceptions Of Their Practice And The Work Environment

Background: The HITECH act\u27s financial incentives and meaningful use mandates have resulted in unprecedented rates of EHR and CDSS adoption. These systems are premised on evidenced-based guidelines, the standardization of care, and the reduction of subjective clinical decisions. They are designed to record clinical events, synchronize the efforts of care teams, facilitate the exchange of information, and improve the control and design of clinical processes. Knowledge workers are challenged to assimilate these changes into a deliberative and autonomous style of practice. Aims: The study examined the impact of a CDSS implementation on nurses\u27 perceptions of their ability to perform aspects of knowledge work and on the nursing practice environment. Nurse and clinical unit characteristics were examined to identify those that predicted outcome variance. Methods: This study used The Impact of Health Information Technology (I-HIT) and The Essentials of Magnetism II (EOM II) instruments. Guided by the Quality Health Outcomes Model, this pre-post, quasi-experimental study includes t-tests, repeated measure and univariate general linear model regression analyses. Two groups comprised the convenience sample of 1,045 nurses: a paired (n=458) and independent (n=587). Results: The functionality of the CDSS was perceived to reduce nurses\u27 ability to efficiently practice, communicate, share information, and interfered with workflow in ways that depersonalized care. Perceptions of the practice environment, interestingly, remained essentially unchanged, with slight improvements and no statistically significant declines. This included perceptions about autonomy, patient-centered values, professional satisfaction and quality care. Even though the CDSS\u27s functionality interfered with practice, and may be poised to deemphasize subjective judgment and autonomy, nurses did not seem to reject the CDSS\u27s ability to standardize aspects of care. This study also found that nurse and clinical unit characteristics such as clinical unit type, shift, expertise, race, and whether or not nurse education was obtained outside of the USA, explained more variance than years of experience, institutional tenure, and level of education. Conclusion: Results suggest that nursing science needs to investigate and advise the design of CDSSs, as well as, develop tactics to reap the benefits of processes and guidelines, while preserving knowledge works\u27 emphasis on expertise, intuition, and holistic care

On Intelligence Augmentation and Visual Analytics to Enhance Clinical Decision Support Systems

Human-in-the-loop intelligence augmentation (IA) methods combined with visual analytics (VA) have the potential to provide additional functional capability and cognitively driven interpretability to Decision Support Systems (DSS) for health risk assessment and patient-clinician shared decision making. This paper presents some key ideas underlying the synthesis of IA with VA (IA/VA) and the challenges in the design, implementation, and use of IA/VA-enabled clinical decision support systems (CDSS) in the practice of medicine through data driven analytical models. An illustrative IA/VA solution provides a visualization of the distribution of health risk, and the impact of various parameters on the assessment, at the population and individual levels. It also allows the clinician to ask “what-if” questions using interactive visualizations that change actionable risk factors of the patient and visually assess their impact. This approach holds promise in enhancing decision support systems design, deployment and use outside the medical sphere as well

CONTEMPORARY CLINICAL DECISION SUPPORT SYSTEMS: A PRELIMINARY REVIEW AND RESEARCH AGENDA

Clinical decision support systems (CDSS) improve healthcare delivery by providing data-driven opinions to care providers throughout the entire care process. The Information Systems (IS) community has produced many works on the subject in the last decade, and it is necessary to comprehensively examine the current state of research to determine the most promising themes to explore in future research. In this short paper, we conducted a literature review of the past five years to synthesise research efforts. By reviewing a preliminary sample of papers, we found that three major areas may be of interest to the IS Community: \u27Positive\u27 and \u27negative\u27 CDSS discontinuance, patient-centric value creation of CDSSs and the role of policy-makers in mitigating harmful social effects of CDSS policies. This research-in-progress will hopefully lead to the creation of a research agenda for CDSSs

A qualitative study of prescribing errors among multi-professional prescribers within an e-prescribing system

Background Computerised Physician Order Entry (CPOE) is considered to enhance the safety of prescribing. However, it can have unintended consequences and new forms of prescribing error have been reported. Objective The aim of this study was to explore the causes and contributing factors associated with prescribing errors reported by multidisciplinary prescribers working within a CPOE system. Main Outcome Measure Multidisciplinary prescribers experience of prescribing errors in an CPOE system. Method This qualitative study was conducted in a hospital with a well-established CPOE system. Semi-structured qualitative interviews were conducted with prescribers from the professions of pharmacy, nursing, and medicine. Interviews analysed using a mixed inductive and deductive approach to develop a framework for the causes of error. Results Twenty-three prescribers were interviewed. Six main themes influencing prescribing were found: the system, the prescriber, the patient, the team, the task of prescribing and the work environment. Prominent issues related to CPOE included, incorrect drug name picking, default auto-population of dosages, alert fatigue and remote prescribing. These interacted within a complex prescribing environment. No substantial differences in the experience of CPOE were found between the professions. Conclusion Medical and non-medical prescribers have similar experiences of prescribing errors when using CPOE, aligned with existing published literature about medical prescribing. Causes of electronic prescribing errors are multifactorial in nature and prescribers describe how factors interact to create the conditions errors. While interventions should focus on direct CPOE issues, such as training and design, socio-technical, and environmental aspects of practice remain important. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11096-020-01192-0) contains supplementary material, which is available to authorized users