From Bryan Liang and colleagues: Legal implications of "electronic signatures"

http://www.ncbi.nlm.nih.gov/pubmed/21249995

Looking for Trouble in All the Right Places: The Legal Implications Associated with “Electronic Signatures” and High-risk Clinical Situations.

Escobar GJ, Folck BF, Gardner MN, Ma J, Palmer LI, Liang B, Nozick LK.
In: Henriksen K, Battles JB, Marks ES, Lewin DI, editors. Advances in Patient Safety: From Research to Implementation (Volume 3: Implementation Issues). Rockville (MD): Agency for Healthcare Research and Quality (US); 2005 Feb.
Advances in Patient Safety.
Excerpt

Background: Voluntary reporting systems identify only a fraction of medical errors. Electronic identification mechanisms, which are more efficient, have been defined for adverse drug events. However, similar systems are lacking for other types of errors. Objective: 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. Design: 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. Results: 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. Conclusions: 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. However, three barriers are likely to limit the use of such “electronic signatures”—fear of malpractice litigation, fear of lawsuits invoking “enterprise liability,” and high development costs. Entities most likely to benefit from these approaches are those with a critical mass of experienced personnel, a circumstance that can spread the development costs over a large number of hospitals and/or clinics.