Examining the use of ICD-9 diagnosis codes for primary immune deficiency diseases in New York State.

PURPOSE: To use International Classification of Disease Codes (ICD-9) codes to investigate primary immune deficiency (PID) in New York State. METHODS: We investigated the diagnosis of Primary Immune Deficiency (PID) in New York State (NYS) using the Statewide Planning and Research Cooperative System (SPARCS) database, a comprehensive data reporting system that collects ICD-9 codes for each patient hospitalized in NYS. RESULTS: From 2000-2004 there were 13,539,358 hospitalizations for 4,777,295 patients; of these, 2,361 patients (0.05 %) were diagnosed with one or more of the ICD-9 codes for PID. Antibody defects were the most common diagnoses made. The PID population had significantly more Caucasians, and fewer African American or Hispanic subjects compared to the general population. Subjects with PID codes were younger, had longer hospitalizations, were less likely to have Medicare and more likely to have Medicaid or Blue Cross insurance. Most hospitalizations were due to respiratory and infectious diseases. Most patients resided in the most populous counties, Kings, New York and Queens, but the distribution of home zip codes was not proportional to county populations. CONCLUSIONS: These data provide useful information on incidence and complications of selected PID diagnoses in one large state.

Subspecialty evaluation of chronically ill hospitalized patients with suspected immune defects.

BACKGROUND: The diagnosis of primary immunodeficiency is suggested by recurrent or unusual infections and inflammatory and autoimmune conditions. Because the diversity of immune defects and clinical presentations poses a diagnostic challenge in hospital populations, a computer algorithm was devised to help identify patients. OBJECTIVE: To assess use of pertinent subspecialty clinics by patients with clinical features of immunodeficiency. METHODS: Using a validated algorithm based on International Classification of Diseases, Ninth Revision (ICD-9), codes applied to The Mount Sinai Hospital billing records, we investigated hospitalized patients, 60 years or younger, who had been diagnosed as having conditions associated with immunodeficiency, excluding those with confounding medical conditions. Immunodeficiency-related disease codes were given a weighted score based on relative severity and expressed as a sum for admissions between January 1, 1999, and December 31, 2003. Demographic features, subspecialty care, and clinic attendance were determined. RESULTS: The 296 computer-identified patients with illnesses characteristic of immunodeficiency were 35.8% Hispanic, 27.0% African American, and 21.6% white; their median age was 13.3 years. Patients were hospitalized 1,261 times, or a median of 4.2 times each (range, 1-42 times), and had 5,700 diagnoses. Of the patients, 75.0% received primary care at The Mount Sinai Hospital. Although the most common diagnosis was pneumonia (n = 243), 45% of patients never received allergy/immunology or pulmonary subspecialty care. CONCLUSION: Despite receiving primary medical care at the same hospital, many frequently hospitalized subjects with features of immunodeficiency do not receive medical care in appropriate subspecialty clinics.

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

BACKGROUND: Primary immunodeficiency diseases occur in all populations, but these diagnoses are rarely made in minority subjects in the United States. OBJECTIVE: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.