Home health care and patterns of subsequent VA and medicare health care utilization for veterans

Gerontologist

Volumn 48, Issue 5, 2008, Pages 668-678

  Van Houtven, Courtney Harold ^a,b   Jeffreys, Amy S ^a   Coffman, Cynthia J ^a,b  

^a DURHAM VA MEDICAL CENTER   (United States)

^b DUKE UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

Formal home care; Health care services use; Stratified analysis; Veterans

Indexed keywords

AGED; ARTICLE; CONTROLLED STUDY; DAY CARE; HEALTH CARE UTILIZATION; HEALTH INSURANCE; HEALTH STATUS; HOME CARE; HOSPICE CARE; HOSPITAL PATIENT; HUMAN; MALE; MEDICARE; NURSING HOME; OUTPATIENT; PREDICTOR VARIABLE; PROBABILITY; RACE DIFFERENCE; RETROSPECTIVE STUDY; VETERAN;

EID: 57149095863     PISSN: 00169013     EISSN: None     Source Type: Journal    
DOI: 10.1093/geront/48.5.668     Document Type: Article

References (46)

1. Abadie, A., Drukker, D., Herr, J., & Imbens, G. (2004). Implementing matching estimators for average treatment effects in STATA. STATA Journal, 1, 1-18.
2. Ash, A. S., Ellis, R. P., Pope, G. C., Ayanian, J. Z., Bates, D. W., Burstin, H., et al. (2000). Using diagnoses to describe populations and predict costs. Health Care Financing Review, 21, 7-28.
3. Austin, P., Grootendorst, P., Normand, S., & Anderson, G. (2007). Conditioning on the propensity score can result in biased estimation of common measures of treatment effect: A Monte Carlo study. Statistics in Medicine, 26, 3208-3210.
4. Bakas, T., Lewis, R., & Parsons, J. E. (2001). Caregiving tasks among family caregivers of patients with lung cancer. Oncology Nursing Forum, 28(5), 847-54.
5. Banaszak-Holl, J., Fendrick, A. M., Foster, N. L., Herzog, A. R., Kabeto, M. U., Kent, D. M., et al. (2004). Predicting nursing home admission: Estimates from a 7-year follow-up of a nationally representative sample of older Americans. Alzheimer Disease and Associated Disorders, 18, 83-89.
6. Bharucha, A. J., Pandav, R., Shen, C., Dodge, H. H., & Ganguli, M. (2004). Predictors of nursing facility admission: A 12-year epidemiological study in the United States. Journal of the American Geriatrics Society, 52, 434-439.
7. Christianson, J. B. (1988). The evaluation of the national long-term care demonstration: The effect of channelling on informal caregiving. Health Services Research, 23, 99-117.
8. DxCG, Inc. (2002). DxCG risk adjustment software analytic guide (release 6.1). Boston, MA.
9. Elixhauser, A., Steiner, C., Harris, D. R., & Coffey, R. M. (1998). Comorbidity measures for use with administrative data. Medical Care, 36, 8-27.
10. Ettner, S. L. (1994). The effect of the Medicaid home care benefit on long-term care choices of the elderly. Economic Inquiry, 32, 103-107.
11. Greene, V. L. (2005). Prospective budgeting for home care: Making titration work. Journal of Aging Health, 17, 399-424.
12. Greene, V. L., Lovely, M. E., Miller, M. D., & Ondrich, J. I. (1995). Reducing nursing home use through community long-term care: An optimization analysis. Journal of Gerontology: Social Sciences, 50B, S259-S268.
13. Greene, V. L., Ondrich, J., & Laditka, S. (1998). Can home care services achieve cost savings in long-term care for older people? Journal of Gerontology: Social Sciences, 53B, S228-S238.
14. Hendricks, A. (2004, May). Evaluation of VA long-term care under the Millennium act. HERC cyber-seminar.
15. Hoerger, T. J., Picone, G., & Sloan, F. (1996). Public subsidies, private provision of care and living arrangements of the elderly. Review of Economics and Statistics, 78, 428-440.
16. Holroyd-Leduc, J. M., Mehta, K. M., & Covinsky, K. E. (2004). Urinary incontinence and its association with death, nursing home admission, and functional decline. Journal of the American Geriatrics Society, 52, 712-718.
17. Hughes, S. L., Weaver, F. M., Giobbie-Hurder, A., Manheim, L., Henderson, W., Kubal, J. D., et al. (2000). Effectiveness of team-managed home-based primary care: A randomized multicenter trial. Journal of the American Medical Association, 284, 2877-2885.
18. Imbens, G. (2003). Semiparametric estimation of average treatment effects under exogeneity: A review. Berkeley: University of California.
19. Imbens, G., & Angrist, J. (1994). Identification and estimation of local average treatment effects. Econometrica, 62, 467-475.
20. Jette, A. M., Branch, L. G., Sleeper, L. A., Feldman, H., & Sullivan, L. M. (1992). High-risk profiles for nursing home admission. The Gerontologist, 32, 634-640.
21. Jette, A. M., Tennstedt, S., & Crawford, S. (1995). How does formal and informal community care affect nursing home use? Journal of Gerontology: Social Sciences, 50B, S4-S12.
22. Kubal, J., Weaver, F., Guihan, M., Cowper, D., & Hynew, D. (2000). An overview of VA long-term care database and information resources. Hines, IL: VA Information Resource Center.
23. Landrum, M. B., & Ayanian, J. Z. (2001). Causal effect of ambulatory specialty care on mortality following myocardial infarction: A comparison of propensity score and instrumental variable analyses. Health Services and Outcomes Research Methodology, 2, 221-245.
24. Maynard, C., & Chapko, M. K. (2004). Data resources in the Department of Veterans Affairs. Diabetes Care, 27(Suppl. 2), B22-B26.
25. McCarthy, J. F., & Blow, F. C. (2004). Older patients with serious mental illness: Sensitivity to distance barriers for outpatient care. Medical Care, 42, 1073-1080.
26. Miller, E. A., & Rosenheck, R. A. (2006). Risk of nursing home admission in association with mental illness nationally in the Department of Veterans Affairs. Medical Care, 44, 343-351.
27. Newgard, C. D., Hedges, J. R., Arthur, M., & Mullins, R. J. (2004). Advanced statistics: The propensity score-A method for estimating treatment effect in observational research. Academy of Emergency Medicine, 11, 953-961.
28. Normand, S. T., Landrum, M. B., Guadagnoli, E., Ayanian, J. Z., Ryan, T. J., Cleary, P. D., et al. (2001). Validating recommendations for coronary angiography following acute myocardial infarction in the elderly: A matched analysis using propensity scores. Journal of Clinical Epidemiology, 54, 387-398.
29. Nuotio, M., Tammela, T. L., Luukkaala, T., & Jylha, M. (2003). Predictors of institutionalization in an older population during a 13-year period: The effect of urge incontinence. Journal of Gerontology: Medical Science, S8A, 756-762.
30. Parsons LS, Ovation Research Group (2001). Reducing bias in a propensity score matched-pair sample using greedy matching techniques. In: Proceedings of the Twenty-Sixth Annual SAS Users Group International Conference, 214-226. Cary: SAS Institute Inc.
31. Pezzin, L. E., Kemper, P., & Reschovsky, J. (1996). Does publicly provided home care substitute for family care? Experimental evidence with endogenous living arrangements. The Journal of Human Resources, 31, 650-676.
32. Rosenbaum, P. R., & Rubin, D. B. (1985). The bias due to incomplete matching. Biometrics, 41, 103-116.
33. Rubin, D. B. (1997). Estimating causal effects from large data sets using propensity scores. Annals of Internal Medicine, 127(8 Part 2), 757-763.
34. Schulz, R., Beach, S. R., Lind, B., Martire, L. M., Zdaniuk, B., Hirsch, C., et al. (2001). Involvement in caregiving and adjustment to death of a spouse: Findings from the caregiver health effects study. Journal of the American Medical Association, 285, 3123-3129.
35. Stabile, M., Laporte, A., & Coyte, P. C. (2006). Household responses to public home care programs. Journal of Health Economics, 25, 674-701.
36. Van Houtven, C. H., & Norton, E. C. (2008). Informal care and Medicare expenditures: Testing for heterogeneous treatment effects. Journal of Health Economics, 27, 134-156.
37. VIReC. (2005a). VIReC research user guide: FY2004 VHA medical SAS outpatient datasets. Hines, IL: Veterans Affairs Information Resource Center.
38. VIReC. (2005b). VIReC research user guide: VHA medical SAS inpatient datasets FY2004. Hines, IL: Veterans Affairs Information Resource Center.
39. VIReC. (2006). VIReC researcher's guide to VA data: Data Issues Brief, October. http://www.virec.research.va.gov/References/DataIssuesBrief/2006/ DIB-0610er.pdf Hines, IL: Veterans Affairs Information Resource Center.
40. Weissert, W., Chernew, M., & Hirth, R. (2001). Beyond managed long-term care: Paying for home care based on risk of adverse outcomes. Health Affairs (Millwood), 20, 172-180.
41. Weissert, W., Chernew, M., & Hirth, R. (2003). Titrating versus targeting home care services to frail elderly clients: An application of agency theory and cost-benefit analysis to home care policy. Journal of Aging and Health, 15, 99-123.
42. Weissert, W. G., & Hedrick, S. C. (1994). Lessons learned from research on effects of community-based long-term care. Journal of the American Geriatrics Society, 42, 348-353.
43. Weissert, W. G., Lesnick, T., Musliner, M., & Foley, K. A. (1997). Cost savings from home and community-based services: Arizona's capitated Medicaid long-term care program. Journal of Health Politics, Policy and Law, 22, 1329-1357.
44. Wooldridge, J., & Schore, J. (1988). The evaluation of the national long term care demonstration. 7. The effect of channeling on the use of nursing homes, hospitals, and other medical services. Health Services Research, 23, 119-127.
45. Yang, Z., Norton, E. C., & Stearns, S. C. (2003). Longevity and health care expenditures: The real reasons older people spend more. Journal of Gerontology: Social Sciences, 58B, S2-S10.
46. Zhao, Z. (2004). Using matching to estimate treatment effects: Data requirements, matching metrics, and Monte Carlo evidence. Review of Economics and Statistics, 86, 91-107.