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“Best Practice for conducting morbidity and mortality reviews: a literature review”

Authors: Corey J, Garruba M, Melder A, Loh E.   Published: The Quarterly 2015.

I read the ‘Best practice for conducting morbidity and mortality reviews: a literature review’ by Joseph Corey, Marie Garruba, Angela Melder and Professor Erwin Loh with great interest. As the authors note, there is a clear need for medical leaders to put in place rigorous, systematic effective processes to enable the assessment of quality of care in a timely manner. The main message from their literature review is the marked variation in reported practice of mortality and morbidity reviews and little evidence of their effectiveness in reducing harm.

A significant reason for this may be case identification. The predominant practice described appears to be self-reported sentinel events or morbidity. Naessens et al (1) compared three widely used detection methods for identifying adverse events at the Mayo Clinic. The authors compared administrative data, self-reported incidents and Global Trigger Tool data. In the small but randomly selected cases in the trigger tool subset, harm was identified in approximately 27% of cases.

Administrative data identified 2.6% of admissions affected by potential adverse events. Only 1.5% of admissions were identified as being affected by adverse events using self-report. There was little overlap in cases identified by the three methods. The Mayo Clinic now reviews every death in hospital. This process is described by Jeanne Huddleston in her article ‘Learning from every death’ (2).  Dr Huddleston noted that even in expected deaths, important lessons can be learnt about improving patients’ experience of care. However, for many hospitals the resources required to carry out such extensive reviews may be prohibitive.

So how can we effectively prioritise mortality reviews? Raj Behal (3) reported on a process of the systematic identification of factors contributing to potentially preventable mortality. This process included the development of a risk adjusted mortality model so that an expected mortality rate could be generated and a mortality index defined. The key factors identified included delay in responding to deteriorating patients, suboptimal critical care, hospital acquired infections, postoperative complications, medical errors and access to palliative care. Having identified these factors, 12 of the 16 hospitals involved were able to reduce their mortality index. Those with the greatest improvement had a broad level of engagement by hospital and physician leaders.

I would argue that using such a risk adjusted model to identify cases for consideration by Mortality and Morbidity Review meetings should be a first step in developing systematic effective learning from case review.

Dr David Hughes
Candidate

References:

1.Behal, R. and Finn, J., 2009. Understanding and improving inpatient mortality in academic medical centers. Academic Medicine, 84(12), pp.1657-1662.
2. Huddleston, J.M., Diedrich, D.A., Kinsey, G.C., Enzler, M.J. and Manning, D.M., 2014. Learning from every death. Journal of patient safety, 10(1), pp.6-12.
3. Naessens, J.M., Campbell, C.R., Huddleston, J.M., Berg, B.P., Lefante, J.J., Williams, A.R. and Culbertson, R.A., 2009. A comparison of hospital adverse events identified by three widely used detection methods. International Journal for Quality in Health Care, 21(4), pp.301-307.
Last Updated on Wednesday, 12 April 2017 16:59