Implementation of an audit with feedback knowledge translation intervention to promote medication error reporting in health care: a protocol.

BACKGROUND: Health professionals strive to deliver high-quality care in an inherently complex and error-prone environment. Underreporting of medical errors challenges attempts to understand causative factors and impedes efforts to implement preventive strategies. Audit with feedback is a knowledge translation strategy that has potential to modify health professionals\u27 medical error reporting behaviour. However, evidence regarding which aspects of this complex, multi-dimensional intervention work best is lacking. The aims of the Safe Medication Audit Reporting Translation (SMART) study are to: 1. Implement and refine a reporting mechanism to feed audit data on medication errors back to nurses 2. Test the feedback reporting mechanism to determine its utility and effect 3. Identify characteristics of organisational context associated with error reporting in response to feedback METHODS/DESIGN: A quasi-experimental design, incorporating two pairs of matched wards at an acute care hospital, is used. Randomisation occurs at the ward level; one ward from each pair is randomised to receive the intervention. A key stakeholder reference group informs the design and delivery of the feedback intervention. Nurses on the intervention wards receive the feedback intervention (feedback of analysed audit data) on a quarterly basis for 12 months. Data for the feedback intervention come from medication documentation point-prevalence audits and weekly reports on routinely collected medication error data. Weekly reports on these data are obtained for the control wards. A controlled interrupted time series analysis is used to evaluate the effect of the feedback intervention. Self-report data are also collected from nurses on all four wards at baseline and at completion of the intervention to elicit their perceptions of the work context. Additionally, following each feedback cycle, nurses on the intervention wards are invited to complete a survey to evaluate the feedback and to establish their intentions to change their reporting behaviour. To assess sustainability of the intervention, at 6 months following completion of the intervention a point-prevalence chart audit is undertaken and a report of routinely collected medication errors for the previous 6 months is obtained. This intervention will have wider application for delivery of feedback to promote behaviour change for other areas of preventable error and adverse events

Real-Time decision support using data mining to predict blood pressure critical events in intensive medicine patients

Patient blood pressure is an important vital signal to the physicians take a decision and to better understand the patient condition. In Intensive Care Units is possible monitoring the blood pressure due the fact of the patient being in continuous monitoring through bedside monitors and the use of sensors. The intensivist only have access to vital signs values when they look to the monitor or consult the values hourly collected. Most important is the sequence of the values collected, i.e., a set of highest or lowest values can signify a critical event and bring future complications to a patient as is Hypotension or Hypertension. This complications can leverage a set of dangerous diseases and side-effects. The main goal of this work is to predict the probability of a patient has a blood pressure critical event in the next hours by combining a set of patient data collected in real-time and using Data Mining classification techniques. As output the models indicate the probability (%) of a patient has a Blood Pressure Critical Event in the next hour. The achieved results showed to be very promising, presenting sensitivity around of 95%

The effect of clinical experience, judgment task difficulty and time pressure on nurses’ confidence calibration in a high fidelity clinical simulation

Background: Misplaced or poorly calibrated confidence in healthcare professionals’ judgments compromises the quality of health care. Using higher fidelity clinical simulations to elicit clinicians’ confidence 'calibration' (i.e. overconfidence or underconfidence) in more realistic settings is a promising but underutilized tactic. In this study we examine nurses’ calibration of confidence with judgment accuracy for critical event risk assessment judgments in a high fidelity simulated clinical environment. The study also explores the effects of clinical experience, task difficulty and time pressure on the relationship between confidence and accuracy. Methods: 63 student and 34 experienced nurses made dichotomous risk assessments on 25 scenarios simulated in a high fidelity clinical environment. Each nurse also assigned a score (0–100) reflecting the level of confidence in their judgments. Scenarios were derived from real patient cases and classified as easy or difficult judgment tasks. Nurses made half of their judgments under time pressure. Confidence calibration statistics were calculated and calibration curves generated. Results: Nurse students were underconfident (mean over/underconfidence score −1.05) and experienced nurses overconfident (mean over/underconfidence score 6.56), P = 0.01. No significant differences in calibration and resolution were found between the two groups (P = 0.80 and P = 0.51, respectively). There was a significant interaction between time pressure and task difficulty on confidence (P = 0.008); time pressure increased confidence in easy cases but reduced confidence in difficult cases. Time pressure had no effect on confidence or accuracy. Judgment task difficulty impacted significantly on nurses’ judgmental accuracy and confidence. A 'hard-easy' effect was observed: nurses were overconfident in difficult judgments and underconfident in easy judgments. Conclusion: Nurses were poorly calibrated when making risk assessment judgments in a high fidelity simulated setting. Nurses with more experience tended toward overconfidence. Whilst time pressure had little effect on calibration, nurses’ over/underconfidence varied significantly with the degree of task difficulty. More research is required to identify strategies to minimize such cognitive biases