OBJECTIVES: We sought to test the ability of large health care utilization databases to accurately identify serious bacterial infections and opportunistic infections leading to hospital admission. STUDY DESIGN AND SETTING: We conducted a cross-sectional validation study using patients admitted to hospitals in the administrative database of the Department of Veterans Affairs, VISN 1, between 2001 and 2004. Detailed hospital chart abstraction protocols were developed to define a gold-standard diagnosis of serious bacterial infections and opportunistic infections. Hospital acquired infections were not considered. RESULTS: A total of 158 patients who were hospitalized for selected bacterial infections and 69 patients for opportunistic infections were identified using ICD-9 discharge diagnoses. The positive predictive values (PPV) of identifying specific bacterial infections that lead to hospital admissions varied between 100% and 66%. All conditions combined yielded a PPV of 80%. Once the gold-standard definition of bacterial conditions was broadened to hospital admissions due to any acute infectious condition, the PPV increased to 90%. Excluding systemic candidiasis, the average PPV for the selected opportunistic infections was 76%. CONCLUSION: Our findings suggest that ICD-9 codes of selected serious infections from hospital discharge files can be used as substitutes for chart-based diagnoses.
OBJECTIVES: We sought to test the ability of large health care utilization databases to accurately identify serious bacterial infections and opportunistic infections leading to hospital admission. STUDY DESIGN AND SETTING: We conducted a cross-sectional validation study using patients admitted to hospitals in the administrative database of the Department of Veterans Affairs, VISN 1, between 2001 and 2004. Detailed hospital chart abstraction protocols were developed to define a gold-standard diagnosis of serious bacterial infections and opportunistic infections. Hospital acquired infections were not considered. RESULTS: A total of 158 patients who were hospitalized for selected bacterial infections and 69 patients for opportunistic infections were identified using ICD-9 discharge diagnoses. The positive predictive values (PPV) of identifying specific bacterial infections that lead to hospital admissions varied between 100% and 66%. All conditions combined yielded a PPV of 80%. Once the gold-standard definition of bacterial conditions was broadened to hospital admissions due to any acute infectious condition, the PPV increased to 90%. Excluding systemic candidiasis, the average PPV for the selected opportunistic infections was 76%. CONCLUSION: Our findings suggest that ICD-9 codes of selected serious infections from hospital discharge files can be used as substitutes for chart-based diagnoses.
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