Hostname: page-component-8448b6f56d-jr42d Total loading time: 0 Render date: 2024-04-18T12:28:59.885Z Has data issue: false hasContentIssue false

Cost-effectiveness of interpersonal psychotherapy for elderly primary care patients with major depression

Published online by Cambridge University Press:  01 October 2007

Judith E. Bosmans
Affiliation:
VU University Medical Center
Digna J. F. van Schaik
Affiliation:
VU University Medical Center and GGZ Buitenamstel
Martijn W. Heymans
Affiliation:
VU University Medical Center
Harm W. J. van Marwijk
Affiliation:
VU University Medical Center
Hein P. J. van Hout
Affiliation:
VU University Medical Center
Martine C. de Bruijne
Affiliation:
VU University Medical Center

Abstract

Objectives: Major depression is common in elderly patients. Interpersonal psychotherapy (IPT) is a potentially effective treatment for depressed elderly patients. The objective of this study was to evaluate the cost-effectiveness of IPT delivered by mental health workers in primary care practices, for depressed patients 55 years of age and older identified by screening, in comparison with care as usual (CAU).

Methods: We conducted a full economic evaluation alongside a randomized controlled trial comparing IPT with CAU. Outcome measures were depressive symptoms, presence of major depression, and quality of life. Resource use was measured from a societal perspective over a 12-month period by cost diaries. Multiple imputation and bootstrapping were used to analyze the data.

Results: At 6 and 12 months, the differences in clinical outcomes between IPT and CAU were small and nonsignificant. Total costs at 12 months were €5,753 in the IPT group and €4,984 in the CAU group (mean difference, €769; 95 percent confidence interval, −2,459 – 3,433). Cost-effectiveness planes indicated that there was much uncertainty around the cost-effectiveness ratios.

Conclusions: Based on these results, provision of IPT in primary care to elderly depressed patients was not cost-effective in comparison to CAU. Future research should focus on improvement of patient selection and treatments that have more robust effects in the acute and maintenance phase of treatment.

Type
GENERAL ESSAYS
Copyright
Copyright © Cambridge University Press 2007

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

1.American Psychiatric Association. Practice guideline for the treatment of patients with major depressive disorder (revision). American Psychiatric Association. Am J Psychiatry. 2000;157:145.Google Scholar
2.Barry, KL, Fleming, MF, Manwell, LB, Copeland, LA, Appel, S. Prevalence of and factors associated with current and lifetime depression in older adult primary care patients. Fam Med. 1998;30:366371.Google ScholarPubMed
3.Bartels, SJ, Coakley, EH, Zubritsky, C, et al. Improving access to geriatric mental health services: A randomized trial comparing treatment engagement with integrated versus enhanced referral care for depression, anxiety, and at-risk alcohol use. Am J Psychiatry. 2004;161:14551462.Google Scholar
4.Beekman, AT, Deeg, DJ, Braam, AW, Smit, JH, Van Tilburg, W. Consequences of major and minor depression in later life: A study of disability, well-being and service utilization. Psychol Med. 1997;27:1397–409.CrossRefGoogle ScholarPubMed
5.Beekman, AT, Deeg, DJ, van Tilburg, T, et al. Major and minor depression in later life: A study of prevalence and risk factors. J Affect Disord. 1995;36:6575.Google Scholar
6.Beekman, AT, Geerlings, SW, Deeg, DJ, et al. The natural history of late-life depression: A 6-year prospective study in the community. Arch Gen Psychiatry. 2002;59:605611.Google Scholar
7.Briggs, A. Economic evaluation and clinical trials: Size matters. BMJ. 2000;321:13621363.CrossRefGoogle ScholarPubMed
8.Briggs, A, Clark, T, Wolstenholme, J, Clarke, P. Missing. . . presumed at random: Cost-analysis of incomplete data. Health Econ. 2003;12:377392.Google Scholar
9.Briggs, AH, O'Brien, BJ. The death of cost-minimization analysis? Health Econ. 2001;10:179184.CrossRefGoogle ScholarPubMed
10.Briggs, AH, Wonderling, DE, Mooney, CZ. Pulling cost-effectiveness analysis up by its bootstraps: A non-parametric approach to confidence interval estimation. Health Econ. 1997;6:327340.Google Scholar
11.Callahan, CM, Hui, SL, Nienaber, NA, Musick, BS, Tierney, WM. Longitudinal study of depression and health services use among elderly primary care patients. J Am Geriatr Soc. 1994;42:833838.CrossRefGoogle ScholarPubMed
12.Coyne, JC, Schwenk, TL, Fechner-Bates, S. Nondetection of depression by primary care physicians reconsidered. Gen Hosp Psychiatry. 1995;17:312.Google Scholar
13.Dolan, P. Modeling valuations for EuroQol health states. Med Care. 1997;35:10951108.Google Scholar
14.EuroQol Group. EuroQol–a new facility for the measurement of health-related quality of life. The EuroQol Group. Health Policy. 1990;16:199208.Google Scholar
15.Frazer, CJ, Christensen, H, Griffiths, KM. Effectiveness of treatments for depression in older people. Med J Aust. 2005;182:627632.Google Scholar
16.Hawley, CJ, Gale, TM, Sivakumaran, T. Defining remission by cut off score on the MADRS: Selecting the optimal value. J Affect Disord. 2002;72:177184.Google Scholar
17.Katon, WJ, Schoenbaum, M, Fan, MY, et al. Cost-effectiveness of improving primary care treatment of late-life depression. Arch Gen Psychiatry. 2005;62:13131320.CrossRefGoogle ScholarPubMed
18.Kearns, NP, Cruickshank, CA, McGuigan, KJ, et al. A comparison of depression rating scales. Br J Psychiatry. 1982;141:4549.Google Scholar
19.Koopmanschap, MA, Rutten, FF. A practical guide for calculating indirect costs of disease. Pharmacoeconomics. 1996;10:460466.Google Scholar
20.Lamers, LM, Stalmeier, PF, McDonnell, J, Krabbe, PF, van Busschbach, JJ. [Measuring the quality of life in economic evaluations: The Dutch EQ-5D tariff]. Ned Tijdschr Geneeskd. 2005;149:15741578.Google ScholarPubMed
21.Lave, JR, Frank, RG, Schulberg, HC, Kamlet, MS. Cost-effectiveness of treatments for major depression in primary care practice. Arch Gen Psychiatry. 1998;55:645651.Google Scholar
22.Luber, MP, Meyers, BS, Williams-Russo, PG, et al. Depression and service utilization in elderly primary care patients. Am J Geriatr Psychiatry. 2001;9:169176.Google Scholar
23.Miller, MD, Wolfson, L, Frank, E, et al. Using interpersonal psychotherapy (IPT) in a combined psychotherapy/medication research protocol with depressed elders. A descriptive report with case vignettes. J Psychother Pract Res. 1997;7:4755.Google Scholar
24.Mittmann, N, Mitter, S, Borden, EK, et al. Montgomery-Asberg severity gradations. Am J Psychiatry. 1997;154:13201321.Google Scholar
25.Montgomery, SA, Asberg, M. A new depression scale designed to be sensitive to change. Br J Psychiatry. 1979;134:382389.CrossRefGoogle ScholarPubMed
26.Mottram, P, Wilson, K, Copeland, J. Validation of the Hamilton Depression Rating Scale and Montgommery and Asberg Rating Scales in terms of AGECAT depression cases. Int J Geriatr Psychiatry. 2000;15:11131119.Google Scholar
27.Oostenbrink, JB, Al, MJ. The analysis of incomplete cost data due to dropout. Health Econ. 2005;14:763776.Google Scholar
28.Oostenbrink, JB, Koopmanschap, MA, Rutten, FF. Standardisation of costs: The Dutch Manual for Costing in economic evaluations. Pharmacoeconomics. 2002;20:443454.Google Scholar
29.Penninx, BW, Deeg, DJ, van Eijk, JT, Beekman, AT, Guralnik, JM. Changes in depression and physical decline in older adults: A longitudinal perspective. J Affect Disord. 2000;61:112.CrossRefGoogle ScholarPubMed
30.Reesal, RT, Lam, RW. Clinical guidelines for the treatment of depressive disorders. II. Principles of management. Can J Psychiatry. 2001;46 (Suppl 1):21S-28S.Google Scholar
31.Reynolds, CF III, Frank, E, Perel, JM, Mazumdar, S, Kupfer, DJ. Maintenance therapies for late-life recurrent major depression: Research and review circa 1995. Int Psychogeriatr. 1995;7 (Suppl):2739.Google Scholar
32.Rubin, DB. Multiple imputation for nonresponse in surveys. New York: John Wiley & Sons; 1987.Google Scholar
33.Schafer, JL. Multiple imputation: A primer. Stat Methods Med Res. 1999;8:315.Google Scholar
34.Sheikh, JI, Yesavage, JA. Geriatric Depression Scale (GDS); Recent evidence and development of a shorter version. Clin Gerontol. 1986;5:165173.Google Scholar
35.Spitzer, RL, Williams, JB, Kroenke, K, et al. Utility of a new procedure for diagnosing mental disorders in primary care. The PRIME-MD 1000 study. JAMA. 1994;272:17491756.CrossRefGoogle ScholarPubMed
36.Statistics Netherlands/Centraal Bureau voor de Statistiek. 2002.Google Scholar
37.Unutzer, J, Patrick, DL, Simon, G, et al. Depressive symptoms and the cost of health services in HMO patients aged 65 years and older. A 4-year prospective study. JAMA. 1997;277:16181623.Google Scholar
38.van Buuren, S, Oudshoorn, CGM. Multivariate imputation by chained equations. Leiden: TNO; 2000.Google Scholar
39.van Marwijk, HWJ, Grundmeijer, HGLM, Bijl, D, et al. NHG-Standaard Depressieve stoornis (depressie). Huisarts Wet. 2003;46:614623.Google Scholar
40.van Schaik, DJ, Klijn, AF, van Hout, HP, et al. Patients’ preferences in the treatment of depressive disorder in primary care. Gen Hosp Psychiatry. 2004;26:184189.Google Scholar
41.van Schaik, DJ, van Marwijk, HW, Ader, HJ, et al. Interpersonal psychotherapy for elderly patients in primary care. Am J Geriatr Psychiatry. 2006; 14:777786.Google Scholar
42.Weissman, M, Markowitz, J, Klerman, G. Comprehensive guide to interpersonal psychotherapy. New York: Basic Books; 2000.Google Scholar
43.Z-index. G-Standaard. The Hague, The Netherlands: Z-index; 2002.Google Scholar
Supplementary material: File

Bosmans_tables

Bosmans_tables

Download Bosmans_tables(File)
File 74.2 KB