Socioeconomic status and readmissions: Evidence from an urban teaching hospital

Health Affairs

Volumn 34, Issue 5, 2014, Pages 778-785

  Hu, Jianhui ^a   Gonsahn, Meredith D ^a,b   Nerenz, David R ^a  

^a HENRY FORD HEALTH SYSTEM   (United States)

^b ATLANTA VA MEDICAL CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AGED; ARTICLE; COHORT ANALYSIS; CONTROLLED STUDY; DEMOGRAPHY; FEMALE; HEALTH CARE DISPARITY; HOSPITAL FINANCE; HOSPITAL PATIENT; HOSPITAL PERSONNEL; HOSPITAL READMISSION; HOSPITALIZATION; HUMAN; MAJOR CLINICAL STUDY; MALE; MARRIED PERSON; NEIGHBORHOOD; ORGANIZATIONAL STRUCTURE; POVERTY; PROBABILITY; RETROSPECTIVE STUDY; RISK FACTOR; RISK REDUCTION; SOCIAL STATUS; SOCIAL SUPPORT; SOCIOECONOMICS; TEACHING HOSPITAL; URBAN POPULATION; ADULT; ECONOMICS; GOVERNMENT; HEALTH CARE POLICY; HOSPITAL; MARRIAGE; MIDDLE AGED; RISK ASSESSMENT; STATISTICAL MODEL; STATISTICS AND NUMERICAL DATA; UNITED STATES;

ADULT; AGED; CENTERS FOR MEDICARE AND MEDICAID SERVICES (U.S.); COHORT STUDIES; FEMALE; HEALTH CARE REFORM; HOSPITALS, TEACHING; HOSPITALS, URBAN; HUMANS; LIKELIHOOD FUNCTIONS; MALE; MARITAL STATUS; MICHIGAN; MIDDLE AGED; MODELS, STATISTICAL; PATIENT READMISSION; POVERTY AREAS; RETROSPECTIVE STUDIES; RISK ASSESSMENT; SOCIAL SUPPORT; SOCIOECONOMIC FACTORS; UNITED STATES;

EID: 84899828325     PISSN: 02782715     EISSN: 15445208     Source Type: Journal    
DOI: 10.1377/hlthaff.2013.0816     Document Type: Article

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31. To access the Appendix, click on the Appendix link in the box to the right of the article online.
32. The effect of age is often nonlinear. For instance, the risk of readmission can increase at an accelerated rate until, say, age seventy-five and then increase at a decelerated rate after that. Therefore, we included an age squared variable. A significant age squared variable indicated that the effect of age was nonlinear.
33. The correlation coefficients between socioeconomic measures were 0.58 between poverty and education, -0.66 between poverty and income, and -0.65 between income and education; all were significant (p < 0:001). We checked collinearity diagnostics, including variance inflation factor and eigensystem analysis of correlation matrix. No multicollinearity problem was detected.
34. As a sensitivity check, we used discharge codes for diagnosis-related groups of index admissions only as our clinical risk adjuster. The results were similar.
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