Surgical experience, hospital size and severity adjusted mortality: James Y Simpson, 1869

The effects of an enhanced simulation programme on medical students' confidence responding to clinical deterioration

BACKGROUND

Clinical deterioration in adult hospital patients is an identified issue in healthcare practice globally. Teaching medical students to recognise and respond to the deteriorating patient is crucial if we are to address the issue in an effective way. The aim of this study was to evaluate the effects of an enhanced simulation exercise known as RADAR (Recognising Acute Deterioration: Active Response), on medical students' confidence.

METHODS

A questionnaire survey was conducted; the instrument contained three sections. Section 1 focused on students' perceptions of the learning experience; section 2 investigated confidence. Both sections employed Likert-type scales. A third section invited open responses. Questionnaires were distributed to a cohort of third-year medical students (n = 158) in the North East of Scotland 130 (82 %) were returned for analysis, employing IBM SPSS v18 and ANOVA techniques.

RESULTS

Students' responses pointed to many benefits of the sessions. In the first section, students responded positively to the educational underpinning of the sessions, with all scores above 4.00 on a 5-point scale. There were clear learning outcomes; the sessions were active and engaging for students with an appropriate level of challenge and stress; they helped to integrate theory and practice; and effective feedback on their performance allowed students to reflect and learn from the experience. In section 2, the key finding was that scores for students' confidence to recognise deterioration increased significantly (p. < .001) as a result of the sessions. Effect sizes (Eta(2)) were high, (0.68-0.75). In the open-ended questions, students pointed to many benefits of the RADAR course, including the opportunity to employ learned procedures in realistic scenarios.

CONCLUSIONS

The use of this enhanced form of simulation with simulated patients and the judicious use of moulage is an effective method of increasing realism for medical students. Importantly, it gives them greater confidence in recognising and responding to clinical deterioration in adult patients. We recommend the use of RADAR as a safe and cost-effective approach in the area of clinical deterioration and suggest that there is a need to investigate its use with different patient groups.

The findings of the Mid-Staffordshire Inquiry do not uphold the use of hospital standardized mortality ratios as a screening test for 'bad' hospitals

The Mid-Staffordshire Public Inquiry has published its findings. The initial investigations were triggered by an elevated hospital standardized mortality ratio (HSMR). This shows that the HSMR is being used as a screening test for substandard care; whereby hospitals that fail the test are scrutinized, whilst those that pass the test are not. But screening tests are often misunderstood and misused and so it is prudent to critically examine the HSMR before casting it in the role of a screening test for 'bad' hospitals. A screening test should be valid, have adequate performance characteristics and a clear post-test action plan. The HSMR is not a valid screening test (because the empirical relationship between clinically avoidable mortality and the HSMR is unknown). The HSMR has a poor performance profile (10 of 11 elevated HSMRs would be false alarms and 10 of 11 poorly performing hospitals would escape attention). Crucially, the aim of a post-test investigation into an elevated HSMR is unclear. The use of the HSMR as a screening test for clinically avoidable mortality and thereby substandard care, although well intentioned, is seriously flawed. The findings of the Mid-Staffordshire Public Inquiry have no bearing on this conclusion because a 'bad' hospital cannot uphold a bad screening test. Nonetheless, HSMRs continue to pose a grave public challenge to hospitals, whilst the unsatisfactory nature of the HSMR remains a largely unacknowledged and unchallenged private affair. This asymmetric relationship is inappropriate, unhelpful, costly and potentially harmful. The use of process measures remains a valid way to measure quality of care.

Comparison of four methods for deriving hospital standardised mortality ratios from a single hierarchical logistic regression model

There is interest in deriving case-mix adjusted standardised mortality ratios so that comparisons between healthcare providers, such as hospitals, can be undertaken in the controversial belief that variability in standardised mortality ratios reflects quality of care. Typically standardised mortality ratios are derived using a fixed effects logistic regression model, without a hospital term in the model. This fails to account for the hierarchical structure of the data - patients nested within hospitals - and so a hierarchical logistic regression model is more appropriate. However, four methods have been advocated for deriving standardised mortality ratios from a hierarchical logistic regression model, but their agreement is not known and neither do we know which is to be preferred. We found significant differences between the four types of standardised mortality ratios because they reflect a range of underlying conceptual issues. The most subtle issue is the distinction between asking how an average patient fares in different hospitals versus how patients at a given hospital fare at an average hospital. Since the answers to these questions are not the same and since the choice between these two approaches is not obvious, the extent to which profiling hospitals on mortality can be undertaken safely and reliably, without resolving these methodological issues, remains questionable.

Getting the best of both worlds--clinical excellence at a peripheral unit

Audit of hospital practice in remote areas and military practice indicates that it is possible to provide a high degree of patient safety with the advantages of care close to home in a small hospital with less than 100 beds. However such an approach requires strict attention to training and retraining, good clinical networking, attention to quality control and a well defined system for identifying those patients who need to be transferred to a specialist centre.