The research team noted their study failed to capture the constant pressure on hospital care teams, such as workload and staffing shortages, which likely influence the professional standard of care.....”
I have two comments.
The first is that Artificial Intelligence is being touted as the end all and be all of the future. One of the examples is that AI can more accurately and quickly examine CT & MRI's for underlying medical conditions than most doctors. So AI may help ease some of the testing and diagnosis errors due to under-staffing pressure.
My second comment is that it has long been known in just about every “industry” that a Total Quality Management program reduces errors and improves quality. A very famous TQM example was a dramatic reduction in heart attack deaths after a hospital with a bad track record implemented a TQM program. The doctors and nurses really pushed back, but they didn't want their patients dying on them and once they saw the result they became missionaries.
TQM and the concept of continuous improvement as implemented through objective outcome measurements and Kaizen team process improvement works. It just needs strong leadership to implement. These concepts have been demonstrated to work in the health care field.
TQM or AI...it still takes smart, committed, kind pros to make those systems work. What can happen is that the folks who work start thinking that TQM or AI is flawless and stop being alert to the imperfections of those initiatives and then mistakes and total BS happens.
Perfect example...we used to have our smart infusion pumps calculate infusion rates of Intravenous solutions...supposed to decrease error rates...right? Soon, the nurses were less proficient at doing the arithmetic...and needed help to calculate a rate when a non standard solution was available. Demanded a new infusion bag with standard concentration.