Does an HBPC model reduce Medicare Fee-For Service (FFS) costs? K. Eric De Jonge, M. D. Medstar Washington Hospital Center May 14, 2014 No Financial Conflicts of Interest ©AAHCM
JAGS- In Press Title: Effects of Home-Based Primary Care on Medicare Costs in High-Risk Elders K. Eric De Jonge M. D. 1, Namirah Jamshed M. B. B. S. 1, Daniel Gilden, MS 2, Joanna Kubisiak, MPH 2, Stephanie R. Bruce M. D. 1, George Taler M. D. 1 Med. Star Washington Hospital Center (MWHC), Section of Geriatrics, Washington D. C. 2 JEN Associates, Cambridge, MA 1 ©AAHCM
Background- 4 year project Hypothesis: ◦ Home-Based Primary Care (HBPC) reduces total Medicare FFS costs Problems: ◦ Major selection bias for those who enter HBPC Low function, severity of illness, terminal stage, SES ◦ Control group challenges ◦ Ethical barriers to RCT ◦ Lack of full CMS cost and survival data ©AAHCM
Study - MWHC House Call Program 2009 ◦ Define question What are Medicare FFS costs and survival for similar HBPC and control populations? ◦ Found JEN Associates (Dan Gilden and team, www. jen. com) ◦ Funding to hire JEN, then buy CMS data ($75 K) ◦ Case-control concurrent study (full CMS data) ©AAHCM
Valid Control Group? - 2010 Apply for CMS Data- Many hoops, IRB, privacy 2004 -2008 CMS Database ◦ 909 New HBPC Cases 722 Eligible Cases ◦ 1, 765, 972 Medicare pts. 2161 Controls Longitudinal picture -- Cases and Controls ◦ Define major selection biases, incident dates ◦ Match 3: 1 by gender, age bands, race, SES, LTC status, frailty, major chronic illnesses, cognitive impairment ◦ Check Baseline utilization (prior 4 months) ©AAHCM
Intervention Home-Based PC team at MWHC ◦ 4 Geriatricians, 4 NPs, 4 SWs, 4 Coordinators, 1 LPN ◦ Intensive home-based 24/7 care, over time/setting ◦ Directly manage all primary and urgent care, specialists, social services, and hospital care ©AAHCM
Analysis Main Outcomes ◦ Medicare costs, pattern of utilization, mortality CMS Data- All Medicare files except Part D Death events - SSA benefit records Multivariate regression model with covariates ◦ Major chronic diseases, baseline utilization ◦ Premodel matching of patient characteristics ©AAHCM
Results Variable Cases (722) Controls (2161) Female 76. 7% Mean Age 83. 7 years 82. 0 years African-American 90. 2 90. 3 Low SES (Medicare buy-in) 36. 3 % 36. 3% Dementia 57. 5% 57. 4% High JFI Frailty Index 37. 0% 36. 9% ©AAHCM
Results Outcome Cases- 722 Controls- 2161 P-value Mean F/U period 23. 3 months 24. 2 months p=. 18 Total Medicare $44, 455 Costs (FFS) $50, 978 p=. 01 Hospital Care $17, 805 $22, 096 p=. 003 SNF Care $4, 812 $6, 098 p=. 001 Home Health $6, 579 $4, 169 p=. 001 Hospice $3, 144 $1, 505 P=. 005 Other $7, 962 $11, 392 P=. 001 Mortality 40% 36% HR=1. 06, p=. 44 ©AAHCM
Results Cases ◦ 105% more generalist visits (p=. 001) ◦ 23% less specialist visits (p=. 001) Multivariate Regression Model Cases Average $8, 477 less per patient (2 years) 17% Lower total Medicare Costs (p=. 003) ©AAHCM
Conclusions A Home-Based Primary Care model reduced total Medicare costs by 17% for ill elders, with similar survival outcomes. Such results argue for payment reform (e. g. IAH) to scale such teams across the U. S. ©AAHCM
Thanks Patients and Families in MWHC program MWHC Geriatrics team, Bruce Leff JEN Associates- Dan Gilden, Joanna Kubisiak Deerbrook Charitable Trust ©AAHCM
MWHC House Call Team ©AAHCM
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