title: Modelling length bias in a longitudinally-linked record system of HIV cases.
abstract: We compare numbers of hospital admissions for intravenous drug using (IVDU) HIV patients and other HIV patients in acute-care facilities in New York State. Data consist of routinely collected hospital-discharge reports from New York's Statewide Planning and Research Cooperative System, linked into longitudinal case histories. Because recognition of an IVDU depends on an opioid diagnosis on any record in the case history, the observed distribution of the number of admissions per case for recognized IVDU's is biased towards greater numbers of admissions. We develop and apply a model to overcome this biasing. Our findings reveal that the mean numbers of admissions for the two groups differ significantly, but less so than without recognition of the length biasing.
authors.affiliation: School of Public Health, University of Albany, State University of New York.
authors.forename: J
authors.initials: J
authors.lastname: Nedelman
authors.forename: A
authors.initials: A
authors.lastname: Burns
authors.forename: J
authors.initials: J
authors.lastname: Cleary
authors.forename: D
authors.initials: D
authors.lastname: Gordon
authors.forename: P
authors.initials: P
authors.lastname: Vernon
authors.forename: C E
authors.initials: CE
authors.lastname: Lawrence
mesh_terms: D015982:Bias; D015658:HIV Infections / Q000453:epidemiology* / Q000209:etiology; D006801:Humans; D008137:Longitudinal Studies; D008498:Medical Record Linkage; D015233:Models, Statistical; D009294:Narcotics; D009518:New York / Q000453:epidemiology; D011237:Predictive Value of Tests; D011336:Probability; D015819:Substance Abuse, Intravenous / Q000150:complications*
chemical_list: D009294:Narcotics