Integrated telehealth and care management program for medicare beneficiaries with chronic disease linked to savings

Health Affairs

Volumn 30, Issue 9, 2011, Pages 1689-1697

  Baker, Laurence C ^a   Johnson, Scott J ^b   Macaulay, Dendy ^c   Birnbaum, Howard ^b  

^a STANFORD UNIVERSITY   (United States)

^b ANALYSIS GROUP   (United States)

^c Analysis Group   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; FAMILY; GOVERNMENT; HEALTH CARE; HEALTH CARE COST; HEALTH INSURANCE; HUMAN; INCOME; LOWEST INCOME GROUP; TAX; UNITED STATES;

EID: 84855644165     PISSN: 02782715     EISSN: 15445208     Source Type: Journal    
DOI: 10.1377/hlthaff.2011.0216     Document Type: Article

References (23)

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9. Bott DM, Kapp MC, Johnson LB, Magno LM. Disease management for chronically ill beneficiaries in traditional Medicare. Health Aff (Millwood). 2009;28(1):87-98.
10. These questions provide information to the care provider about the patient's symptoms and vital signs and knowledge of their underlying condition and behavior. Additional questions such as quality-of-life surveys (such as the SF-12), diseaserelated surveys (such as the Geriatric Depression Scale), and educational materials are also sent to the patient regularly.
11. The Wenatchee clinic counties are Chelan, Okanogan, Douglas, and Grant. The Bend clinic counties are Deschutes, Jefferson, Crook, Lake, and Harney.
12. To access the Appendix, click on the Appendix link in the box to the right of the article online.
13. Cohort 1 data are available from February 2005 through January 2008; cohort 2 data are available from February 2006 through January 2009.
14. The sixteen control counties were Clallam, WA; Douglas, Coos, Josephine, Klamath, Wasco, Hood River, Sherman, and Gillam, OR; Cascade, Lewis and Clark, Flathead, Powell, and Jefferson, MT; and Shasta and Plumas, CA.
15. Rosenbaum PR, Rubin DB. Constructing a control group using multivariate matched sampling methods that incorporate the propensity score. Am Stat. 1985;39(1):33-8.
16. The Hierarchical Condition Category scores are risk-adjustment factors used to adjust Medicare reimbursement. See Pope GC, Kautter J, Ellis RP, Ash AS, Ayanian JZ, Lezzoni LI, et al. Risk adjustment of Medicare capitation payments using the CMSHCC model. Health Care Financ Rev. 2004;25(4):119-41.
17. The 5 percent sample data only identify dates of service according to standard calendar quarters, so these measures were constructed on a calendar-quarter basis, and our multivariate methodology accounted for the difference between the quarter definition for the control and intervention groups.
18. We inflation-adjusted spending measures to 2009 US dollars based on the medical Consumer Price Index.
19. Covariates with p values of less than 0.1 include coronary artery disease, ischemic heart disease, other cardiovascular disease, diabetes mellitus, skilled nursing home visits, home health visits, outpatient visits, emergency department visits, and any hospice. See the online Appendix, as in Note 12.
20. Efron B, Tibshirani RJ. An introduction to the bootstrap. London: Chapman and Hall; 1993.
21. Sample sizes for the disease subgroups do not add to the sample total because patients could have more than one chronic disease. Also, there were patients included in the overall analysis but not in the disease subgroups who had no evidence of these conditions once their final claims were processed.
22. Manning WG. The logged dependent variable, heteroscedasticity, and the retransformation problem. J Health Econ. 1998;17(34):283-95.
23. Afendulis CC, He Y, Zaslavsky AM, Chernew M. The impact of Medicare Part D on hospitalization rates. Health Serv Res. 2011;46(4):1022-38.