DECISION RULES FOR PREDICTING VACCINATION STATUS OF PRESCHOOL-AGE EMERGENCY DEPARTMENT PATIENTS

We produced and tested rules to predict undervaccination among prescho ol-age emergency department (ED) patients. Data were gathered on demog raphics, vaccination status, health status, and health care utilizatio n from parents, ED physicians, and ED charts at an urban teaching hosp ital in Rochester, N.Y. Primary core charts were reviewed to verify va ccination status. Using recursive partitioning, we developed decision rules to predict undervaccination. Decision rules were developed on a sample of 602 ED patients 4 to 48 months of age and then prospectively tested on 1832 ED patients aged 6 to 36 months. Factors associated wi th undervaccination for any vaccine included parental report of vaccin ation delay (odds ratio = 8.1; p<0.001), inability to report the recei pt of the appropriate number of vaccines (odds ratio = 4.5; p<0.001), lack of health insurance (odds ratio = 3.6, p<0.001), elapsed time sin ce the lost visit to primary care provider (p<0.001), household size ( p<0.001), and maternal age (p<0.01). Eight decision rules were produce d that varied in their number of questions (one to six), sensitivity ( 0.27 to 0.87), and specificity (0.54 to 0.98). No single rule was both highly sensitive and highly specific. The rules sensitivities and spe cificities were similar for the validation sample of 1832 patients. Th us a decision rule could not be produced that was both sensitive and s pecific. Identification of undervaccinated children by means of inform ation available at an ED visit is inherently difficult. Interventions in the ED may be inefficient unless better methods of assessing vaccin ation status can be developed.