Intravenous Infusion Practices and Patient Safety: Insights from ECLIPSE
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1 Intravenous Infusion Practices and Patient Safety: Insights from ECLIPSE
2 Acknowledgement and disclaimer Funding acknowledgement: This project is funded by the National Institute for Health Research Health Services and Delivery Research programme (project no. 12/209/27) Department of Health disclaimer: The views and opinions expressed herein are those of the authors and do not necessarily reflect those of the HS&DR programme, NIHR, NHS, or the Department of Health 2
3 ECLIPSE Research questions What different IV infusion administration practices are there in England? How often and what type of errors occur? What factors increase or reduce the likelihood of error? Do smart pumps deliver safer IV infusion practice? What is best practice in infusion device design, deployment and training? How does our data compare to the US study? 3
4 Methods Quantitative observational study of IV administrations across 16 hospitals General Surgery, General Medicine, ICU, Paediatrics, Oncology Day Care Debriefs and focus groups with key staff at participating sites to understand practices Mixed methods analyses In-depth qualitative studies (five hospitals) Developing dialogues with stakeholders to jointly identify and communicate best practices 4
5 Summary results from Phase 1 observations 1326 patients receiving infusions Of 6491 patients in the areas observed 2008 infusions 640 (31.9%) administered using a smart pump 11.5% error rate (n=231 infusions) 1.1% (n=23) potentially harmful No statistically significant difference with smart pumps 52.9% discrepancy rate (n=1063 infusions) IF there are 45 million infusions p.a. in England, this equates to approx. 5.2 million errors p.a. nationally 5
6 Analysis of incidents in NRLS dataset Data from inclusive 125 cases involving intravenous infusion Moderate harm or worse Analysis inconclusive on which might have been prevented by a different kind of pump because there are so many factors in system configuration Haven t had capacity to analyse pump log data to establish what DERS has prevented 6
7 Errors and discrepancies Classified together as deviations in this study Errors are B (adapted NCC MERP severity index) and above Discrepancies are A1 & A2 Often deviations that are judged to have low clinical significance or Workarounds that add resilience to the system, e.g.: Doing things in a timely way Managing time as a finite resource to devote attention where most needed 7
8 Rating the severity of discrepancies/errors Discrepancy 8 Error Harm No error Error, no harm Error, harm Error, death Category Description A1 A2 B C D E F G H I Discrepancy but no error Capacity to cause error An error occurred but is unlikely to reach the patient An error occurred but is unlikely to cause harm despite reaching the patient An error occurred that would be likely to have required increased monitoring and/or intervention to preclude harm An error occurred that would be likely to have caused temporary harm An error occurred that would be likely to have caused temporary harm and prolonged hospitalization An error occurred that would be likely to have contributed to or resulted in permanent harm An error occurred that would be likely to have required intervention to sustain life An error occurred that would be likely to have contributed to or resulted in the patient s death
9 Sources of variability for errors Fewer errors in critical care Fewer errors with PCA pumps and syringe drivers; more with gravity feed. Higher error rate with fluids than drugs or blood products Variations in discrepancy rates often result from differences in policy 9
10 Staff as a source of resilience Staff picked up and corrected prescribing errors Deviations are sometimes corrections May also be work-arounds e.g., when the prescribed bag size is not available Flushes and KVO fluids are not always prescribed Depends on local policy and practice Staff may judge patient needs rather than always seeking a prescription for fluids There s a system-level issue that prescriber is often not available when medication administration starts / needed 10
11 Emerging themes (1) Locally rational / globally variable system Behaviours emerge from many local and organisational factors Staff manage by prioritising and doing informal risk assessments Results in fairly high resilience in a complex adaptive system Behaviours Behaviours Behaviours Behaviours Behaviours Behaviours Behaviours Behaviours Behaviours Behaviours Local factors Local factors Local factors Local factors Local factors Local factors Local factors Local factors Local factors Local factors Organisational factors Organisational factors Organisational Organisational factors Organisational factors factors Organisational factors Organisational factors Organisational factors Organisational factors Organisational factors Policy and cultural factors Policy and cultural factors Policy and Policy cultural and cultural factors Policy factors and cultural factors Policy and cultural Policy factors and cultural factors Policy and cultural factors Policy and cultural factors Policy and cultural factors 11
12 Emerging themes (2) Huge variations in policy Local policy has to be fit for purpose Challenge is to review policies and practices to identify which actually contribute to safety and which distract from safety The outcome of such an analysis is unlikely to be identical everywhere, but there will be common themes No evidence for the benefits of smart pumps Smart pumps are one component of an ecology of tools and practices Context-specific factors make them more or less fit for purpose 12
13 Insights: smart pumps / DERS The numbers and severities of errors were not significantly different with DERS than without. It depends on nuanced details of how drug libraries are set up as to what kinds of harm might be detected and prevented by DERS. Drug libraries for smart pumps are time consuming to construct and difficult to manage. Both updating and loading drug libraries are challenging. Trusts were rarely downloading or analysing pump log data missed learning opportunities. 13
14 Insights: Medication administration policy and practice Trust policies relating to IV administration are very variable. Needs are substantially different in different areas. Localised policies and practices often enhance safety. Nurses often have limited time to do IVs. Interruptions are frequent. The golden triangle of patient, prescription, medication is often broken by e-prescribing. 14
15 Insights: don t forget the patient Patient s experiences are adversely affected by alarms that are too frequent and that they don t understand. Some are irritated by alerts; a few interact with pumps. Frequent alarms also impact on staff workload and working practices. Many patients want to know what medications they are on and why. E-prescribing makes this harder. 15
16 Insights: Organisational practices Some sites had developed local organisational practices to cope with the demands and pressures of IV administration. Hospital staff have different levels of maturity in terms of learning culture and systems thinking. Trusts audited prescribing practices and infection control but not IV administration. 16
17 Insights: Infrastructure There is huge demand on pumps at specific times of day IV rounds are done at the same time. Branding, packaging and storage of drugs can contribute to deviations. There needs to be compatibility between the medication, the syringe and the pump. Standardisation would probably help. Done well. Nurses are often expected to translate between technologies (electronic health records, pumps, e-prescribing, etc.). Physical space shapes activities. e.g. where rooms to prepare IVs are multipurpose or too cramped. 17
18 Summary Devices are components in a complex ecosystem. Good design and interoperability matter People are at the heart of the ecosystem The work system needs to support them. Technology should serve, not dictate, practices. Need to think of these as complex adaptive systems There is huge scope for learning Within organisations, within specialisms, nationally Standardisation will help in some situations
19 Models of safety Vincent & Amalberti 2016 Ultra-adaptive power to experts High reliability power to the group Ultra-safe power to regulators and supervision 19
20 Complicated and complex systems Complicated systems have multiple components, demand expertise, agents cooperate, solutions can be engineered. Complex systems have multiple agents, interdependencies, emergent behaviours, can t be engineered Need to create the environment in which desired performance emerges 20
21 Discussion Pressure towards ultra-safe solutions for complex problems is unlikely to work There aren t simple ways to measure error or harm, or simple interventions to improve safety. Too many interdependencies Need to think in terms of complex adaptive systems and localized interventions Safety II rather than Safety I, creating conditions for good performance, not just barriers to poor performance 21
22 Thank You Website: 22
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