Use of Emergency Department Chief Complaint and Diagnostic Codes for Identifying Respiratory Illness in a Pediatric Population

Objectives: (1) To determine the value of emergency department chief complaint (CC) and International Classification of Disease diagnostic codes for identifying respiratory illness in a pediatric population and (2) to modify standard respiratory CC and diagnostic code sets to better identify respiratory illness in children. Results: We determined the sensitivity and specificity of CC and diagnostic codes by comparing code groups with a criterion standard. CC and diagnostic codes for 500 pediatric emergency department patients were retrospectively classified as respiratory or nonrespiratory. Respiratory diagnostic codes were further classified as upper or lower respiratory. The criterion standard was a blinded, reviewer-assigned illness category based on history, physical examination, test results, and treatment. We also modified our respiratory code sets to better identify respiratory illness in this population. Methods: Four hundred ninety-six charts met inclusion criteria. By the criterion standard, 87 (18%) patients had upper and 47 (10%) had lower respiratory illness. The specificity of CC and diagnostic codes groups was >0.97 [95% confidence interval (CI) 0.95-0.98]. The code group sensitivities were as follows: CC was 0.47 (95% CI 0.38-0.55), upper respiratory diagnostic was 0.56 (95% CI 0.45-0.67), lower respiratory diagnostic was 0.87 (95% CI 0.74-0.95), and combined CC and/or diagnostic was 0.72 (95% CI 0.63-0.79). Modifying the respiratory code sets to better identify respiratory illness increased sensitivity but decreased specificity. Conclusions: Diagnostic and CC codes have substantial value for emergency department syndromic surveillance. Adapting our respiratory code sets to a pediatric population forced a tradeoff between sensitivity and specificity.

[1]  D. Talan,et al.  Syndromic surveillance for bioterrorism following the attacks on the World Trade Center--New York City, 2001. , 2003, MMWR. Morbidity and mortality weekly report.

[2]  Richard Platt,et al.  Use of Automated Ambulatory-Care Encounter Records for Detection of Acute Illness Clusters, Including Potential Bioterrorism Events , 2002, Emerging infectious diseases.

[3]  Galit Shmueli,et al.  Early statistical detection of anthrax outbreaks by tracking over-the-counter medication sales , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[4]  Vickie L. O’Dell,et al.  Recognition of illness associated with the intentional release of a biologic agent. , 2001, MMWR. Morbidity and mortality weekly report.

[5]  Michael M. Wagner,et al.  Accuracy of ICD-9-coded chief complaints and diagnoses for the detection of acute respiratory illness , 2001, AMIA.

[6]  C. Irvin,et al.  Syndromic analysis of computerized emergency department patients' chief complaints: an opportunity for bioterrorism and influenza surveillance. , 2003, Annals of emergency medicine.

[7]  P. Duncan,et al.  Inaccuracy of the International Classification of Diseases (ICD-9-CM) in identifying the diagnosis of ischemic cerebrovascular disease , 1997, Neurology.

[8]  J. Prescott,et al.  The emergency department log as a simple injury-surveillance tool. , 1995, Annals of emergency medicine.

[9]  C. Bombardier,et al.  Lack of concordance between the ICD-9 classification of soft tissue disorders of the neck and upper limb and chart review diagnosis: one steel mill's experience. , 1996, American journal of industrial medicine.

[10]  Philip K. Russell,et al.  Anthrax as a biological weapon: medical and public health management. Working Group on Civilian Biodefense. , 1999, JAMA.

[11]  M. Mocny.  A Comparison of Two Methods for Biosurveillance of Respiratory Disease in the Emergency Department: Chief Complaint vs ICD9 Diagnosis Code , 2003 .

[12]  William B. Lober,et al.  Roundtable on bioterrorism detection: information system-based surveillance. , 2002, Journal of the American Medical Informatics Association : JAMIA.

[13]  B. Rowe.  Reasons Why Patients Leave without Being Seen from the Emergency Department , 2003 .

[14]  L I Iezzoni,et al.  Does clinical evidence support ICD-9-CM diagnosis coding of complications? , 2000, Medical care.

[15]  C. Muir,et al.  Registration of colorectal cancer in Scotland: an assessment of data accuracy based on review of medical records. , 1995, Public health.

[16]  Charlton Wilson,et al.  Patients with Diagnosed Diabetes Mellitus Can Be Accurately Identified in an Indian Health Service Patient Registration Database , 2001, Public health reports.

[17]  L. Jacobs,et al.  Accuracy of e-codes assigned to emergency department records. , 1995, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[18]  Lisa J. Trigg,et al.  Roundtable on Bioterrorism Detection , 2002 .

[19]  R. Platt,et al.  Using automated medical records for rapid identification of illness syndromes (syndromic surveillance): the example of lower respiratory infection , 2001, BMC public health.