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Implementation and Impact of a Consensus Diagnostic and Management Algorithm for Complicated Pneumonia in Children
  1. Dinesh Pillai, MD*†**,
  2. Xiaoyan Song, PhD§**,
  3. William Pastor, MA, MPH,
  4. Mary Ottolini, MD, MPH∥**,
  5. David Powell, MD¶**,
  6. Bernhard L. Wiedermann, MD, MA§**,
  7. Roberta L. DeBiasi, MD§**
  1. From the *Division of Pediatric Pulmonary Medicine, †Department of Integrative Systems Biology, Children’s National Medical Center, ‡The George Washington University School of Medicine and Health Sciences; §Division of Pediatric Infectious Diseases, ∥Quality Improvement and Clinical Support Services, ¶Division of Hospitalist Medicine, and **Division of Pediatric Surgery, Children’s National Medical Center, Washington, DC.
  1. Received January 4, 2011, and in revised form May 3, 2011.
  2. Accepted for publication July 18, 2011.
  3. Reprints: Dinesh Pillai, MD, Pediatrics, Division of Pulmonary Medicine, The George Washington University School of Medicine and Health Sciences, Children’s National Medical Center, 111 Michigan Ave, NW, Washington, DC 20010. E-mail: dpillai{at}
  4. This work was not supported by any grant/funding.
  5. Supplemental digital content is available for this article. Direct URL citation appears inthe printed text and is provided in the HTML and PDF versions of this article on the journal’s Web site (


Introduction Variable treatment exists for children with bacterial pneumonia complications such as pleural effusion and empyema. Subspecialists at an urban academic tertiary children’s hospital created a literature-based diagnosis and management algorithm for complicated pneumonia in children. We proposed that algorithm implementation would reduce use of computed tomography (CT) for diagnosis of pleural infection, thereby decreasing radiation exposure, without increased adverse outcomes.

Materials and Methods A cross-sectional study was undertaken in children (3 months to 20 years old) with principal or secondary diagnosis codes for empyema and/or pleural effusion in conjunction with bacterial pneumonia. Study cohorts consisted of subjects admitted 15 months before (cohort 1, n = 83) and after (cohort 2, n = 87) algorithm implementation. Data were collected using clinical and financial data systems. Imaging studies and procedures were identified using Current Procedural Terminology codes. Statistical analysis included χ2 test, linear and ordinal regression, and analysis of variance.

Results Age (P = 0.56), sex (P = 0.30), diagnoses (P = 0.12), and severity level (P = 0.84) were similar between cohorts. There was a significant decrease in CT use in cohort 2 (cohort 1, 60% vs cohort 2, 17.2%; P = 0.001) and reduction in readmission rate (7.7% vs 0%; P = 0.01) and video-assisted thoracoscopic surgery procedures (44.6% vs 28.7; P = 0.03), without concomitant increases in vancomycin use (34.9% vs 34.5%; P = 0.95) or hospital length of stay (6.4 vs 7.6 days; P = 0.4). Among patients who received video-assisted thoracoscopic surgery drainage (n = 57), there were no significant differences between cohorts in median time from admission to video-assisted thoracoscopic surgery (2 days; P = 0.29) or median duration of chest tube drainage (3 vs 4 days; P = 0.10). There was a statistically nonsignificant trend for higher rate of pathogen identification in cohort 2 (cohort 1, 33% vs cohort 2, 54.1%; P = 0.12); Streptococcus pneumonia was the most commonly identified pathogen in both cohorts (37.5% vs 27%; P = 0.23).

Discussion Implementation of an institutional complicated pneumonia management algorithm reduced CT scan use/radiation exposure, VATS procedures, and readmission rate in children with a diagnosis of pleural infection, without associated increases in length of stay or vancomycin use. This algorithm provides the framework for future prospective quality improvement studies in pediatric patients with complicated pneumonia.

Key Words
  • bacterial pneumonia
  • empyema
  • pleural effusion
  • ultrasound
  • computed tomography

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