Health services utilization was defined using four separate variables: total number

of hospital outpatient visits, total hospital inpatient nights at discharge, total number of all

emergency room visits, and total number of office-based provider visits.

Independent Variables

 The medical conditions of interest were identified using the MEPS HC medical

conditions file. The medical conditions file codes each self-reported medical condition

the individual experiences during the year. In order to preserve respondent

confidentiality, the condition codes provided on this file have been collapsed from fully-

specified codes to 3-digit code categories. Medical conditions were coded using the

International Classification of Diseases, Ninth Revision (ICD-9) codes and classification

codes (CC) as constructed using AHRQ's Clinical Classification Software (CCS). CCS

aggregates ICD-9 codes into clinically meaningful categories and these categories were

collapsed based on the clinical significance of categories, accurate reporting from

respondents, and the frequency of the reported condition.

 From past research identifying spending and service use trends for various medical

conditions, pulmonary conditions were identified from the MEPS HC medical conditions

file using CC 127-134 and cardiac conditions were identified using CC 96, 97, 100-108

(Olin & Rhoades, 2005). For a breakdown of CC categories, see Table A-1.

 Depression was identified using ICD-9 code 311. Although ICD-9 code 296

corresponds to depression, it also includes individuals with bipolar disorder. When

considering ICD-9 codes 296 and 311, 93 percent of respondents had a code of 311,

which corresponds to unspecified depression. The large number of patients with ICD-9

code 311 suggests that respondents are likely self-reporting depression (as opposed to

major depression), which then received a code of 311 instead of 296. Thus, ICD-9 code