Assessing patient safety risk before the injury occurs: an introduction to sociotechnical probabilistic risk modelling in health care

Marx, David

doi:10.1136/qhc.12.suppl_2.ii33

Cited by 75 publications

(83 citation statements)

References 25 publications

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“…Described as a hybrid between traditional decision support models and process analysis techniques (e.g., rootcause analysis, failure modes, effects analysis), ST-PRA was designed to address rare adverse events associated with high mortality and high costs in instances where traditional research methods have not captured the behavioral and technological aspects of risk [35].…”

Section: Methodsmentioning

confidence: 99%

Sociotechnical probabilistic risk modeling to predict injurious falls in community living centers

Powell‐Cope¹,

Campbell²,

Hahm³

et al. 2016

J Rehabil Res Dev

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Abstract-The goal of this study was to apply sociotechnical probabilistic risk assessment to prioritize risks and prevention strategies for serious injurious falls of residents in nursing homes. Risk modeling teams consisted of 26 clinical and nonclinical staff from three Department of Veterans Affairs community living centers and one state Veterans' nursing home. Participants met in groups several times to identify and assign probabilities to provider and resident at-risk behaviors and equipment failures. They identified prevention strategies for the failures that accounted for the highest levels of risk. Six scenarios were modeled: (1) transferring from bed to wheelchair, (2) propelling from bedside to bathroom, (3) transferring from wheelchair to toilet, (4) transferring from toilet to wheelchair, (5) propelling from bathroom to bedside, and (6) transferring from wheelchair to bed. The greatest paths of risk were for residents with impaired mobility and high fragility. A 26% reduction in injurious falls could be achieved by (1) reducing the number of unassisted transfers through a modest improvement in response time to alarms, (2) installing automatic brake locks on 90% of wheelchairs, (3) making the wheelchair maintenance process highly reliable, and (4) decreasing improper transfer techniques by 10%.

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Section: Methodsmentioning

confidence: 99%

Sociotechnical probabilistic risk modeling to predict injurious falls in community living centers

Powell‐Cope¹,

Campbell²,

Hahm³

et al. 2016

J Rehabil Res Dev

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“…Although suggestions to apply PRA to patient-safety issues have recently been made [10,11], its use remains embryonic in health care. One reason for its slow dissemination is that it relies on data that are seldom found in medical literature.…”

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confidence: 99%

Measuring human-error probabilities in drug preparation: a pilot simulation study

Garnerin

Pellet-Meier

Chopard

et al. 2007

Eur J Clin Pharmacol

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Objectives Designing a safe medication process requires the ability to model its reliability using methods such as probabilistic risk assessment (PRA). However, lack of data, especially on human-error probabilities (HEPs), limits its use. To assess whether small-scale simulations could help generate HEP data, a pilot study was conducted among nurses and anaesthetists. It focused on two core activities, namely, the manual preparation of medications and the arithmetic necessary to prepare drugs. Its specific objectives were to evaluate whether HEPs could be high enough to be measurable and to determine whether these HEPs could be sensitive to individuals and task details. These would give some insight into the level of detail required by PRA analysis. Methods Thirty nurse and 28 anaesthetist volunteers were involved in the experiment. Nurses and anaesthetists had to prepare medications for 20 patients and 22 syringes of various drugs, respectively. Both groups had to perform 22 calculations relating to the preparation of drugs. HEPs, distribution of HEPs and dependency of HEPs on individuals and task details were assessed. ResultsIn the preparation tasks, overall HEP was 3.0% for nurses and 6.5% for anaesthetists. In the arithmetic tasks, overall HEP was 23.8% for nurses and 8.9% for anaesthetists. A statistically significant difference was noted between the two groups. In both preparation and arithmetic tasks, HEPs were dependent on individual nurses but not on individual anaesthetists. In every instance, HEPs were dependent on task details. Conclusion Our study illustrates that small-scale simulations represent an interesting way of generating HEPs. HEPs are, indeed, in the range of 10 −2 and 10 −1 . But in most cases, HEPs depend heavily on operators and task details. This dependency means that the influence of these parameters must be determined before advanced PRA analysis. There is therefore an urgent need to develop experimental research into assessing this influence by means of randomised controlled trials.

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“…Specific medical applications of these tree structures include assessment of radiation treatment systems [3] and patient safety risks [1]. However, these structures are based on a binary model whereby a system either operates in a fully functional or a complete failure mode.…”

Section: Introductionmentioning

confidence: 99%

“…While the term "threats" is commonly used to indicate areas of possible system security violations, in this paper we expand the definition of threats to include any item that has the potential to adversely affect system operation, such as faults. For medical systems, health care delivery relies upon a complex series of interactions between medical providers, equipment, and patients [1]. Specific medical system threat examples include component failures [2], misdiagnosis of the patient's symptoms, wrong treatment strategy selection, and errors in administration of the treatment [3].…”

Section: Introductionmentioning

confidence: 99%

“…As a result, Probabilistic Risk Assessment (PRA) techniques that use fault trees to model the combination of multiple failures that lead to a specific adverse outcome were adapted from aviation and other industrial fault tolerant disciplines [21]. Since adverse outcomes in patient safety are the result of a combination of machine and human errors, a PRA variant technique called Sociotechnical Probabilistic Risk Assessment (ST-PRA) has been promoted [1].…”

Section: Introductionmentioning

confidence: 99%

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Modeling Medical System Threats with Conditional Probabilities Using Multiple-Valued Logic Decision Diagrams

Manikas

Feinstein²,

Thornton

2012

2012 IEEE 42nd International Symposium on Multiple-Valued Logic

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Abstract-Design for medical system reliability has become an area of increasing importance. Medical system threats, which include system failures as well as malicious attacks, often have interdependent events that can adversely affect system operation.To address these problems, we build upon our previous threat cataloging methodology such that a large number of interdependent threats can be efficiently cataloged and analyzed for common features. Our approach utilizes Multiple-Valued Logic for describing the state of a large system and a multiplevalued decision diagram (MDD) for the threat catalog and analysis.

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Assessing patient safety risk before the injury occurs: an introduction to sociotechnical probabilistic risk modelling in health care

Cited by 75 publications

References 25 publications

Sociotechnical probabilistic risk modeling to predict injurious falls in community living centers

Sociotechnical probabilistic risk modeling to predict injurious falls in community living centers

Measuring human-error probabilities in drug preparation: a pilot simulation study

Modeling Medical System Threats with Conditional Probabilities Using Multiple-Valued Logic Decision Diagrams

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