Looking for Trouble in All the Right Places: The Legal Implications Associated with 'Electronic Signatures' and High-Risk Clinical Situations

摘要

The investigators sought to define probabilistic strategies that could support quality improvement and medical error detection by decreasing the need for unselected manual chart review. Combinations of administrative data and laboratory test results ('electronic signatures') were employed to identify discrete, high-risk clinical situations among health plan members of a large managed care organization. The design used was a retrospective cohort study linking hospitalization records, outpatient records, and laboratory results that were formatted using approaches developed for physiologic severity scoring. The original outcomes of interest for the study were clinical situations (e.g., birth injuries or delayed diagnosis of myocardial infarction) that have a strong association with human error. When presented with preliminary results, senior leaders in the investigators' parent organizations raised a number of objections to any public presentation or publication of the results. Because of these objections, the quantitative results presented in this report focus on rapid detection of one outcome-prolonged neonatal assisted ventilation-that has a weak association with human error. Using recursive partitioning, the investigators were able to define subsets of newborns for whom the frequency of the outcome of interest was substantially higher than in the general population (1 percent). For example, an electronic signature identified a subset of infants (comprising 4 percent of the birth cohort) in which the outcome of interest occurred in 22 percent of the newborns. Use of probabilistic electronic strategies could yield significant benefits in medical error research as well as major operational improvements in medical error detection and reporting, quality assurance, and quality improvement.