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Health status, resource consumption, and costs of dysthymic patients in Italian primary care

Published online by Cambridge University Press:  11 October 2011

Corrado Barbui
Affiliation:
Laboratory of Epidemiology and Social Psychiatry, “Mario Negri”Institute for Pharmacological Research, Milan, Italy
Livio Garattini*
Affiliation:
Laboratory of Epidemiology and Social Psychiatry, “Mario Negri”Institute for Pharmacological Research, Milan, Italy
Iva Krulichova
Affiliation:
CESAV, Center for Health Economics, “Mario Negri”Institute for Pharmacological Research, Ranica (Bg), Italy
Giovanni Apolone
Affiliation:
Laboratory of Clinical Research, Oncology Dept., “Mario Negri”Institute for Pharmacological Research, Milan, Italy
*
Address for correspondence: Dr. L. Garattini, CESAV, Center for Health Economics A.A. Valenti, Mario Negri Institute, c/o Villa Camozzi, via Camozzi 3, 24020 Ranica (Bergamo). Fax: +39-035-453.5372 E-mail: liviogarattini@tiscalinet.it

Summary

Aims – To describe the health status, resource consumption and costs of patients with dysthymic disorder in the Italian primary care setting. Methods – A total of 79 general practitioners (GPs) participated the study. Diagnosis was based on each GP's clinical assessment. At entry the Mini-International Neuropsychiatric Interview (MINI) was used as a supporting diag- nostic aid. Health status was measured with the SF-36 questionnaire. Resource consumption and costs regarded the six months before enrolment. Results – Out of 598 patients enrolled by GPs according to their clinical assessment, 503 fulfilled the MINI cri- teria and 95 did not. The latter had a better perception of their health than the former. Resource consumption was similar in the two groups; and the total per patient six-month costs did not differ significantly. Conclusions – The study confirms there may be a gap between standardised criteria for defining dysthymia and everyday clinical practice. All dysthymic patients diagnosed by GPs might be considered together from a health policy perspective.

Declaration of Interest: this research was partly supported by a contribution from Sanofi-Synthelabo Italy.

Type
Original Papers
Copyright
Copyright © Cambridge University Press 2004

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References

REFERENCES

Cohen, J. (1988). Statistical Power Analysis for the Behavioural Sciences. Lawrence Erlbaum: Hillsdale, NJ.Google Scholar
Dubini, A., Mannheimer, R. & Pancheri, P. (2001). Depression in the community: results of the first Italian survey. International Clinical Psychopharmacology 16, 4953.CrossRefGoogle ScholarPubMed
Garattini, L., Castelnuovo, E., Lanzeni, D. & Viscarra, C. (2003). Durata e costo delle visite in medicina generate: il progetto DYSCO. Farmeconomia e Percorsi Terapeutici 4(2), 109114.CrossRefGoogle Scholar
Howland, R.H. (1993). General health, health care utilisation, and med- ical comorbidity in dysthymia. International Journal of Psychiatry in Medicine 23, 211238.CrossRefGoogle Scholar
Jaffe, A., Froom, J. & Galambos, N. (1994). Minor depression and func- tional impairment. Archives of Family Medicine 3, 10811086.CrossRefGoogle Scholar
Judd, L.L. & Akiskal, H.S. (2000). Delineating the longitudinal structure of depressive illness: beyond clinical subtypes and duration thresh- olds. Pharmacopsychiatry 33, 37.CrossRefGoogle Scholar
Judd, L.L. & Rapaport, M.H. (1994) Economics of depression and cost- benefit comparisons of selective serotonin reuptake inhibitors and tricyclic antidpressants. Depression 2(3), 173177.CrossRefGoogle Scholar
Kazis, L.E., Anderson, J.J. & Meenan, R.F. (1989). Effect sizes for inter- preting changes in health status. Medical Care 27, 178181.CrossRefGoogle Scholar
Keller, M.B., Klein, D.N., Hirschfeld, R.M., Kocsis, J.H., McCullough, J.P., Miller, I., First, M.B., Holzer, C.P., Keitner, G.I. & Marin, D.B. (1995). Results of the DSM-IV mood disorder field trial. American Journal of Psychiatry 152, 843849.Google Scholar
Klein, D.N., Schwartz, J.E., Rose, S. & Leader, J.B. (2000). Five-year course and outcome of dysthymic disorder: a prospective, naturalis- tic follow-up study. American Journal of Psychiatry 157, 931938.CrossRefGoogle Scholar
Lepine, J.P., Gastpar, M., Mendlewicz, J. & Tylee, A., on behalf of the DEPRES steering Committee (1997). Depression in the community: the first pan-European study DEPRES (DEPression Research in European Society). International Clinical Psychopharmacology 12, 1929.CrossRefGoogle Scholar
McHorney, C.A. & Ware, J.E. & Raczek, A.E. (1994). The MOS 36-Item Short Form Health Survey (SF-36), II: psychometric and clinical tests of validity in measuring physical and mental health constructs. Medical Care 31, 247283.CrossRefGoogle Scholar
Nease, D.E. (2001). Dysthymia in primary care. Who needs treatment and how do we know? Journal of Family Practice 50, 413.Google ScholarPubMed
Pagano, E., Brunetti, M, Tediosi, F. & Garattini, L. (1999). Costs of Diabetes. A Methodological Analysis of the Literature. Pharmacoeconomics 15(6), 583595.CrossRefGoogle ScholarPubMed
Ware, J.E. (1993). SF-36 Health Survey. Manual and Interpretation Guide. Health Institute, New England medical Centre: Boston, MA.Google Scholar
Ware, J.E. & Sherborurne, C.D. (1992). The MOS 36-Item Short-Form Health Survey (SF-36), I: conceptual framework and item selection. Medical Care 30, 473483.CrossRefGoogle ScholarPubMed
Wells, K.B., Stewart, A. & Hays, R.D. (1989). The functioning and well- being of depressed patients. Results from the Medical Outcome Study. Journal of the American Medical Association 262, 914919.CrossRefGoogle Scholar
Westermeyer, J., Eames, S. & Nugent, S. (1998). Comorbid Dysthymia and Substance Disorder: Treatment History and Cost. American Journal of Psychiatry 155, 15561560.CrossRefGoogle ScholarPubMed
Williams, J., Kerber, C., Mulrow, C., Medina, A. & Aguilar, C. (1995). Depressive disorders in primary care: prevalence, functional dis- ability, and identification. Journal of General Internal Medicine 10, 712.CrossRefGoogle Scholar
Apolone, G. & Mosconi, P. (1998). The Italian SF-36 health survey: translation, validation and norming. Journal of Clinical Epidemiology 51, 10251036.CrossRefGoogle ScholarPubMed
Apolone, G., Mosconi, P. & Ware, J.E. (1997). Questionario sullo Stato di Salute SF-36. Manuale d'Uso e Guida all'Interpretazione del Risultati. Guerini Editore & Associati: MilanoGoogle Scholar
Barber, J.A. & Thompson, S.G. (2000). Analysis of cost data in ran- domised trials: an application of the non-parametric bootstrap. Statistical Medicine 19, 32193236.3.0.CO;2-P>CrossRefGoogle Scholar