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  • Diagnostic accuracy of predicting somatization from patients’ ICD-9 diagnoses

Diagnostic accuracy of predicting somatization from patients’ ICD-9 diagnoses

Smith, RC., Gardiner, JC., Luo, Z., & Rost, K. (2009). Diagnostic accuracy of predicting somatization from patients’ ICD-9 diagnoses. Psychosomatic Medicine, 71(3), 366-371. https://doi.org/10.1097/PSY.0b013e31819cc783

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Abstract

Objectives: To hypothesize in a new and different population that administrative database (ADB) screening would identify somatizing patients by increasing numbers of visits, female gender, and greater percent of International Classification of Diseases, 9th Edition (ICD-9) primary diagnosis codes in musculoskeletal, nervous, gastrointestinal (GI), and ill-defined body systems. We labeled these codes as having "somatization potential." Our earlier study demonstrated that ICD-9 codes and other data from the ADB effectively identified somatization.
Methods: Using a prospective observational design in a staff model health maintenance organization, we evaluated 1364 patients aged 18 to 65 years who had 8 visits yearly in the 2 years before study. Clinician raters applied a reliable method of medical chart review to identify patients meeting the criteria for somatization. We randomly selected 2/3 for the derivation set (n = 901) for logistic regression to evaluate the contribution of potential ADB correlates (age, gender, all encounters, primary diagnosis codes (ICD-9), revenue codes, and charges) of a diagnosis of somatization. This prediction rule was then applied to the remaining 1/3 of subjects, the validation set (n = 463). Results: Patients averaged 47.1 years, 12.8 visits per year, and 71.6% were female; 319 had somatization. Age, visits, and somatization potential were associated with clinician-rated somatization, with a c-statistic 0.72 in the derivation set and 0.68 in the validation set. Conclusions: These data support our earlier findings that selected ICD-9 diagnoses in the ADB predict somatization, suggesting their potential in identifying a common, costly, and usually unrecognized problem.

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