Cost of noninfectious comorbidities in patients with HIV
Authors Guaraldi G, Zona S, Menozzi M, Carli F, Bagni P, Berti A, Rossi E, Orlando G, Zoboli G, Palella F
Received 22 November 2012
Accepted for publication 24 January 2013
Published 23 September 2013 Volume 2013:5 Pages 481—488
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Giovanni Guaraldi,1 Stefano Zona,1 Marianna Menozzi,1 Federica Carli,1 Pietro Bagni,1 Alessandra Berti,2 Elisa Rossi,2 Gabriella Orlando,1 Giuliana Zoboli,3 Frank Palella4
1Department of Medical and Surgical Sciences for Children & Adults, University of Modena and Reggio Emilia, Modena, Italy; 2Health Care Systems Department, CINECA Consortium of Universities, Bologna, Italy; 3Infectious Disease Clinic, Arcispedale of Reggio Emilia, Reggio Emilia, Italy; 4Division of Infectious Diseases, Northwestern University, Feinberg School of Medicine, Chicago, IL, USA
Objectives: We hypothesized that the increased prevalence of noninfectious comorbidities (NICMs) observed among HIV-infected patients may result in increased direct costs of medical care compared to the general population. Our objective was to provide estimates of and describe factors contributing to direct costs for medical care among HIV-infected patients, focusing on NICM care expenditure.
Methods: A case-control study analyzing direct medical care costs in 2009. Antiretroviral therapy (ART)-experienced HIV-infected patients (cases) were compared to age, sex, and race-matched adults from the general population, included in the CINECA ARNO database (controls). NICMs evaluated included cardiovascular disease, hypertension, diabetes mellitus, bone fractures, and renal failure. Medical care cost information evaluated included pharmacy, outpatient, and inpatient hospital expenditures. Linear regression models were constructed to evaluate predictors of total care cost for the controls and cases.
Results: There were 2854 cases and 8562 controls. Mean age was 46 years and 37% were women. We analyzed data from 29,275 drug prescription records. Positive predictors of health care cost in the overall population: HIV infection (β = 2878; confidence interval (CI) = 2001–3755); polypathology (β = 8911; CI = 8356–9466); age (β = 62; CI = 45–79); and ART exposure (β = 18,773; CI = 17,873–19,672). Predictors of health care cost among cases: Center for Disease Control group C (β = 1548; CI = 330–2766); polypathology (β = 11,081; CI = 9447–12,716); age > 50 years (β = 1903; CI = 542–3264); protease inhibitor exposure (per month of use; β = 69; CI = 53–85); CD4 count < 200 cells/mm3 (β = 5438; CI = 3082–7795); and ART drug change (per change; β = 911; CI = 716–1106).
Conclusion: Total cost of medical care is higher in cases than controls. Lower medical costs associated with higher CD4 strata are offset by increases in the care costs needed for advancing age, particularly for NICMs.
Keywords: pharmacoeconomics, HIV, antiretroviral therapy, noninfectious comorbidities
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