Analysis of preventable deaths and errors in trauma care in a Scandinavian trauma level-I centre

BACKGROUND

The wide disparity in the methodology of preventable death analysis has created a lack of comparability among previous studies. The guidelines for the peer review (PR) procedure suggest the inclusion of risk-adjustment methods to identify patients to review, that is, exclude non-preventable deaths (probability of survival [Ps] < 25%) or focus on preventable deaths (Ps > 50%). We aimed to, through PR process, (1) identify preventable death and errors committed in a level-I trauma centre, and (2) explore the use of different risk-adjustment methods as a complement.

METHODS

A multidisciplinary committee reviewed all trauma patients, which died a trauma-related death, within 30 days of admission to Karolinska University Hospital, Stockholm, in the period of 2012-2016. Ps was calculated according to TRISS and NORMIT and their accuracy where compared.

RESULTS

Two hundred and ninety-eight deaths were identified and 252 were reviewed. The majority of deaths occurred between 1 and 7 days. Ten deaths (4.0%) were classified as preventable. Sixty-seven errors were identified in 53 (21.0%) deaths. The most common error was inappropriate treatment in all deaths (21 of 67) and in preventable deaths (5 of 13). Median Ps in non-preventable deaths was higher than the cut-off (<25%) and Ps-TRISS was almost twice as high as Ps-NORMIT (65% vs 33%, P < .001). Two clinically judged preventable deaths with Ps <25% would have been missed with both models. Median Ps in preventable deaths was above the cut-off (>50%) and higher with Ps-TRISS vs Ps-NORMIT (75% vs 58%, P < .001). Three and 4 clinically judged preventable deaths would have been missed, respectively, for TRISS and NORMIT, if using this cut-off.

CONCLUSION

Preventable deaths were commonly caused by clinical judgment errors in the early phases but death occurred late. Ps calculated with NORMIT was more accurate than TRISS in predicting mortality, but both perform poorly in identifying preventable and non-preventable deaths when applying the cut-offs. PR of all trauma death is still the golden standard in preventability analysis.

Mental disorders of known aetiology and precision medicine in psychiatry: a promising but neglected alliance

Personalized or precision medicine is predicated on the assumption that the average response to treatment is not necessarily representative of the response of each individual. A commitment to personalized medicine demands an effort to bring evidence-based medicine and personalized medicine closer together. The use of relatively homogeneous groups, defined using a priori criteria, may constitute a promising initial step for developing more accurate risk-prediction models with which to advance the development of personalized evidence-based medicine approaches to heterogeneous syndromes such as schizophrenia. However, this can lead to a paradoxical situation in the field of psychiatry. Since there has been a tendency to loosely define psychiatric disorders as ones without a known aetiology, the discovery of an aetiology for psychiatric syndromes (e.g. 22q11.2 deletion syndrome in some cases of schizophrenia), while offering a path toward more precise treatments, may also lead to their reclassification away from psychiatry. We contend that psychiatric disorders with a known aetiology should not be removed from the field of psychiatry. This knowledge should be used instead to guide treatment, inasmuch as psychotherapies, pharmacotherapies and other treatments can all be valid approaches to mental disorders. The translation of the personalized clinical approach inherent to psychiatry into evidence-based precision medicine can lead to the development of novel treatment options for mental disorders and improve outcomes.