Person:

Klompas, Michael

Background: Automatic identification of notifiable diseases from electronic medical records can potentially improve the timeliness and completeness of public health surveillance. We describe the development and implementation of an algorithm for prospective surveillance of patients with acute hepatitis B using electronic medical record data. Methods: Initial algorithms were created by adapting Centers for Disease Control and Prevention diagnostic criteria for acute hepatitis B into electronic terms. The algorithms were tested by applying them to ambulatory electronic medical record data spanning 1990 to May 2006. A physician reviewer classified each case identified as acute or chronic infection. Additional criteria were added to algorithms in serial fashion to improve accuracy. The best algorithm was validated by applying it to prospective electronic medical record data from June 2006 through April 2008. Completeness of case capture was assessed by comparison with state health department records. Findings: A final algorithm including a positive hepatitis B specific test, elevated transaminases and bilirubin, absence of prior positive hepatitis B tests, and absence of an ICD9 code for chronic hepatitis B identified 112/113 patients with acute hepatitis B (sensitivity 97.4%, 95% confidence interval 94–100%; specificity 93.8%, 95% confidence interval 87–100%). Application of this algorithm to prospective electronic medical record data identified 8 cases without false positives. These included 4 patients that had not been reported to the health department. There were no known cases of acute hepatitis B missed by the algorithm. Conclusions: An algorithm using codified electronic medical record data can reliably detect acute hepatitis B. The completeness of public health surveillance may be improved by automatically identifying notifiable diseases from electronic medical record data.

There is a striking paradox in the literature supporting high-profile measures to reduce ventilator-associated pneumonia (VAP): many studies show significant reductions in VAP rates but almost none show any impact on patients' duration of mechanical ventilation, length of stay in the intensive care unit and hospital, or mortality. The paradox is largely attributable to lack of specificity in the VAP definition. The clinical and microbiological criteria for VAP capture a population of patients with an array of conditions that range from serious to benign. Many of the benign events are manifestations of bacterial colonization superimposed upon pulmonary edema, atelectasis, or other non-infectious processes. VAP prevention measures that work by decreasing bacterial colonization preferentially lower the frequency of these mislabelled, more benign events. In addition, misclassification obscures detection of an impact of prevention measures on bona fide pneumonias. Together, these effects create the possibility of the paradox where a prevention measure may have a large impact on VAP rates but minimal impact on patients' outcomes. The paradox makes changes in VAP rates alone an unreliable measure of whether VAP prevention measures are truly beneficial to patients and behooves us to measure their impact on patient outcomes before advocating their adoption.