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Can doctors identify older patients at risk of medication harm following hospital discharge?

Peer Reviewed, Prospective Study, Human

Published: 02 Jul 2018 in Journal news

Medication-related harm (MRH) is common in older adults following hospital discharge. A new British Journal of Clinical Pharmacology study has examined whether doctors can predict which older patients will experience MRH requiring care following hospital discharge, and whether clinical experience and confidence in prediction influence the accuracy of predictions.

The study found that clinical judgement of doctors is not a reliable tool to predict MRH in older adults post-discharge.

In the multicentre observational prospective study involving five teaching hospitals in England between September 2013 and November 2015, there were 1066 patients with completed predictions and follow-up. Doctors discharging older patients from medical wards predicted the likelihood of their patient experiencing MRH requiring care in the initial 8 week period post-discharge.

Most predictions (85%) were made by junior doctors with less than five years’ clinical experience. There was no relationship between doctors’ predictions and patient MRH, irrespective of years of clinical experience. Doctors’ predictions were more likely to be accurate when they reported higher confidence in their prediction, especially in predicting MRH-associated hospital readmissions.

“These findings confirm the complexity of predicting medication-related harm. This makes it very challenging to target medication-related strategies to the right individuals,”

said Dr. Khalid Ali, chief investigator of the study and senior lecturer in Geriatrics at Brighton and Sussex Medical School.

“Clinical pharmacology and therapeutics teaching has not been particularly prominent in undergraduate medical training. This is perhaps an area requiring review, given an ageing population that is prescribed ever increasing quantities of medicine.”

Dr. Ali added that there is a need to consider new approaches to identify individuals at high risk of medication-related harm given its serious impact on patients and health care services.