Clinical Information Systems (CIS) such as Electronic Medical Records (EMRs) have become pervasive in modern health care. They have great potential for improving efficiency and outcomes. However, there is also significant published evidence about the risks posed by low quality CIS solutions, with respect to patient safety, security and privacy. As a result stakeholders have called for quality certification and regulation of CIS – and indeed some efforts have been made in this direction. However, the emphasis on pre-market controls (traditionally used for medical devices) does not seem to fit well to these systems. Many quality issues arise only due to interactions of the CIS software with its specific employment environment. Regulators such as the FDA and Health Canada have therefore started to shift focus to post-market controls. To some degree, user experience and incident reporting systems operated by regulators (such as the FDA’s MAUDE) serve this purpose. But anybody who has tried to analyze data from the MAUDE for the purpose of quality surveillance and improvement will have noticed that the information in such systems are very hard to query and analyze. It is not really actionable.
Can we come up with a better way of performing “continuous certification” of CIS?
It is this problem that Craig Kuziemsky and I have been discussing today at our paper presentation at FHIES/SEHC (hosted by the Software Engineering Institute). We developed a conceptual model for continuous certification and apply it to a case study. The framework is shown in the picture below. You can read about it in our paper