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. RESULTS: In 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.
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. RESULTS: In 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.
Authors: Carola Dehmel; Stephan A Braune; Georg Kreymann; Michael Baehr; Claudia Langebrake; Heike Hilgarth; Axel Nierhaus; Dorothee C Dartsch; Stefan Kluge Journal: Intensive Care Med Date: 2011-04-30 Impact factor: 17.440
Authors: Adam G Dunn; Mei-Sing Ong; Johanna I Westbrook; Farah Magrabi; Enrico Coiera; Wayne Wobcke Journal: J Am Med Inform Assoc Date: 2011-05-01 Impact factor: 4.497