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J Biomed Inform. 2017 Feb;66:180-193. doi: 10.1016/j.jbi.2016.12.013. Epub 2017 Jan 3.

Development and validation of a continuously age-adjusted measure of patient condition for hospitalized children using the electronic medical record.

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PeraHealth, Inc., 6302 Fairview Rd., Suite 310, Charlotte, NC 28203, United States. Electronic address:
University of Florida, Jacksonville, FL, United States.
Department of Pediatrics, Children's Hospital of Pittsburgh, University of Pittsburgh School of Medicine, 4401 Penn Ave., Pittsburgh, PA 15224, United States.
Yale New Haven Health System, 20 York St., New Haven, CT 06510, United States.
Rutgers New Jersey Medical School, 65 Bergen St., Newark, NJ 07107, United States; MedERA, Inc., United States.
Yale New Haven Health System, 20 York St., New Haven, CT 06510, United States; Yale School of Medicine, 333 Cedar St., New Haven, CT 06510, United States.


Awareness of a patient's clinical status during hospitalization is a primary responsibility for hospital providers. One tool to assess status is the Rothman Index (RI), a validated measure of patient condition for adults, based on empirically derived relationships between 1-year post-discharge mortality and each of 26 clinical measurements available in the electronic medical record. However, such an approach cannot be used for pediatrics, where the relationships between risk and clinical variables are distinct functions of patient age, and sufficient 1-year mortality data for each age group simply do not exist. We report the development and validation of a new methodology to use adult mortality data to generate continuously age-adjusted acuity scores for pediatrics. Clinical data were extracted from EMRs at three pediatric hospitals covering 105,470 inpatient visits over a 3-year period. The RI input variable set was used as a starting point for the development of the pediatric Rothman Index (pRI). Age-dependence of continuous variables was determined by plotting mean values versus age. For variables determined to be age-dependent, polynomial functions of mean value and mean standard deviation versus age were constructed. Mean values and standard deviations for adult RI excess risk curves were separately estimated. Based on the "find the center of the channel" hypothesis, univariate pediatric risk was then computed by applying a z-score transform to adult mean and standard deviation values based on polynomial pediatric mean and standard deviation functions. Multivariate pediatric risk is estimated as the sum of univariate risk. Other age adjustments for categorical variables were also employed. Age-specific pediatric excess risk functions were compared to age-specific expert-derived functions and to in-hospital mortality. AUC for 24-h mortality and pRI scores prior to unplanned ICU transfers were computed. Age-adjusted risk functions correlated well with similar functions in Bedside PEWS and PAWS. Pediatric nursing data correlated well with risk as measured by mortality odds ratios. AUC for pRI for 24-h mortality was 0.93 (0.92, 0.94), 0.93 (0.93, 0.93) and 0.95 (0.95, 0.95) at the three pediatric hospitals. Unplanned ICU transfers correlated with lower pRI scores. Moreover, pRI scores declined prior to such events. A new methodology to continuously age-adjust patient acuity provides a tool to facilitate timely identification of physiologic deterioration in hospitalized children.


Acuity score; Electronic medical record; Nursing assessments; Patient condition; Pediatrics; Risk measure; Rothman Index

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