Safer Interactive Medical Device Design: Insights from the CHI+MED Project

Curzon, Paul; Blandford, Ann; Thimbleby, Harold; Cox, Anna L.

doi:10.4108/eai.14-10-2015.2261752

Cited by 4 publications

(2 citation statements)

References 11 publications

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“…Even taking this into account, there are studies to show infusion errors specifically caused by usability error with the device interface. 34 The National Patient Safety Agency (NPSA) produced design guidance to help address these issues. 35 Previous studies have highlighted factors influencing flow rates in infusion devices.…”

Section: Discussionmentioning

confidence: 99%

Flow rate accuracy of infusion devices within healthcare settings: a systematic review

Atanda,

West,

Stables

et al. 2023

Therapeutic Advances in Drug Safety

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Background: One in five patients admitted to the hospital treated with intravenous (IV) fluid therapy suffer complications due to inappropriate administration. Errors have been reported in 13–84% of the preparation and administration of IV medications. The safe delivery of IV fluids requires precise rate administration. Objectives: This systematic review aims to determine the accuracy of infusion sets and devices and examine the factors that affect the flow rate accuracy of devices. Data Sources and Methods: Six databases (CINAHL, MEDLINE PubMed, EMBASE, Web of Science and Cochrane Database of systematic reviews) were systematically searched. Search terms included infusion pumps, infusion devices, flow rate accuracy, fluid administration rate, gravity-led infusion set and fluid balance. Studies were included if they examined infusion devices’ flow rate accuracy and drop rates for fluids or non-oncological drugs. Findings were tabulated and synthesised qualitatively. The quality of the studies was examined based on the design of the studies due to their heterogeneity. Results: Eight studies were included: Four studies were conducted on human subjects in the hospital environment; studies recruited 182 participants between the ages of 18 and 94 years. Two studies examined flow rate accuracy in recruited patients across 509 observations and 2387 drip hours. No trials prospectively assessed the accuracy of infusion pumps in the clinical domain, and no studies were reported on patient safety outcomes. Four studies examined the impact of mechanical and physiological factors on the flow rate accuracies of infusion devices. Height and back pressure simulated vibrating conditions, the viscosity of IV fluid and the positions of patients were reported to have a significant impact on infusion volume and flow rates of infusion devices. Additionally, giving sets that vary from the manufacturer’s specifications are reported to increase error percent by 10–20%. Conclusion: Infusion devices are an important source of error in administering IV fluids. Yet, there needs to be more prospective trial data to support their clinical accuracy and the impact on patient outcomes. Future flow variability and accuracy studies should capture their impact on patient safety and clinical outcomes.

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Section: Discussionmentioning

confidence: 99%

Flow rate accuracy of infusion devices within healthcare settings: a systematic review

Atanda,

West,

Stables

et al. 2023

Therapeutic Advances in Drug Safety

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“…In 2010, Zhang et al introduced a generic insulin pump model and a preliminary hazard analysis based on this model [11]; they divided the hazardous situations into 5 categories associated with the generic insulin infusion pump, including therapeutic, energetic, chemical or biological, mechanical, and environmental. Curzon et al established a tool focused on understanding how the design of interactive medical devices (such as infusion pumps, monitors, and diagnostic devices help save lives) can support safety [12]. Masci presented a hazard analysis that identified a substantial set of root causes of use hazards in software design, which is general in the sense that the problematic functionalities are common in broad classes of infusion pumps [13].…”

Section: Introductionmentioning

confidence: 99%

A Hazard Analysis of Class I Recalls of Infusion Pumps

Xue-mei

Wen²,

Duan

et al. 2019

JMIR Hum Factors

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Background The adverse event report of medical devices is one of the postmarket surveillance tools used by regulators to monitor device performance, detect potential device-related safety issues, and contribute to benefit-risk assessments of these products. However, with the development of the related technologies and market, the number of adverse events has also been on the rise, which in turn results in the need to develop efficient tools that help to analyze adverse events monitoring data and to identify risk signals. Objective This study aimed to establish a hazard classification framework of medical devices and to apply it over practical adverse event data on infusion pumps. Subsequently, it aimed to analyze the risks of infusion pumps and to provide a reference for the risk management of this type of device. Methods The authors define a general hierarchical classification of medical device hazards. This classification is combined with the Trace Intersecting Theory to form a human-machine-environment interaction model. Such a model was applied to the dataset of 2001 to 2017 class I infusion pump recalls extracted from the Food and Drug Administration (FDA) website. This dataset does not include cases involving illegal factors. Results The proposed model was used for conducting hazard analysis on 70 cases of class I infusion pump recalls by the FDA. According to the analytical results, an important source of product technical risk was that the infusion pumps did not infuse accurate dosage (ie, over- or underdelivery of fluid) . In addition, energy hazard and product component failure were identified as the major hazard form associated with infusion pump use and as the main direct cause for adverse events in the studied cases, respectively. Conclusions The proposed human-machine-environment interaction model, when applied to adverse event data, can help to identify the hazard forms and direct causes of adverse events associated with medical device use.

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Modelling the User

Curzon

Rukšėnas

2017

Human–Computer Interaction Series

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Safer Interactive Medical Device Design: Insights from the CHI+MED Project

Cited by 4 publications

References 11 publications

Flow rate accuracy of infusion devices within healthcare settings: a systematic review

Flow rate accuracy of infusion devices within healthcare settings: a systematic review

A Hazard Analysis of Class I Recalls of Infusion Pumps

Modelling the User

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