Identifying undiagnosed primary immunodeficiency diseases in minority subjects by using computer sorting of diagnosis...

Primary immunodeficiency diseases occur in all populations, but these diagnoses are rarely made in minority subjects in the United States.

We sought to develop and validate a method to identify patients without diagnoses but with immunodeficiency in an urban hospital with a substantial minority patient population.

We developed a scoring algorithm on the basis of International Classification of Disease, Ninth Revision (ICD-9) codes to identify all hospitalized patients age 60 years or less who had been given a diagnosis of 2 or more of 174 ICD-9-coded complications associated with immunodeficiency. Codes were weighted for severity and expressed as a sum for all admissions between October 1, 1995, and December 31, 2002. Patients with, for example, cancer or HIV or those after transplantation or major surgery were excluded. Demographic features of subjects with aggregated ICD-9 codes suggestive of immunodeficiency were compared with those of other inpatients; 59 computer-selected subjects were then tested for immune defects.

The computer-identified group contained 533 patients (0.4% of all inpatients), who had been hospitalized 2683 times. The median age was 6.6 years. Sixty-five percent were African American or Hispanic, and 61% were insured by Medicaid, which is significantly more than other inpatients younger than 60 years of age (median age, 32.6 years; 37% minority, 27% insured by Medicaid; P<.0001). Primary immunodeficiency was found in 17 (29%) of the 59 subjects tested. Thirteen other patients had secondary immune defects, and 86% of immunodeficient subjects were Hispanic or African American.

An ICD-9-based scoring algorithm identifies patients demographically different from other hospitalized subjects who have multiple illnesses suggestive of immunodeficiency. This group contains undiagnosed minority patients with immunodeficiency.