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K. Eric De Jonge, M.D. Medstar Washington Hospital Center May 14, 2014 No Financial Conflicts of Interest ©AAHCM.

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Presentation on theme: "K. Eric De Jonge, M.D. Medstar Washington Hospital Center May 14, 2014 No Financial Conflicts of Interest ©AAHCM."— Presentation transcript:

1 K. Eric De Jonge, M.D. Medstar Washington Hospital Center May 14, 2014 No Financial Conflicts of Interest ©AAHCM

2  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  1 MedStar Washington Hospital Center (MWHC), Section of Geriatrics, Washington D.C.  2 JEN Associates, Cambridge, MA ©AAHCM

3  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

4  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)www.jen.com ◦ Funding to hire JEN, then buy CMS data ($75K) ◦ Case-control concurrent study (full CMS data) ©AAHCM

5  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

6  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

7  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

8 VariableCases (722)Controls (2161) Female76.7% Mean Age83.7 years82.0 years African-American90.290.3 Low SES (Medicare buy-in)36.3 % Dementia57.5%57.4% High JFI Frailty Index37.0%36.9% ©AAHCM

9 OutcomeCases- 722Controls- 2161P-value Mean F/U period 23.3 months24.2 monthsp=.18 Total Medicare Costs (FFS) $44,455$50,978p=.01 Hospital Care$17,805$22,096p=.003 SNF Care$4,812$6,098p=.001 Home Health$6,579$4,169p=.001 Hospice$3,144$1,505P=.005 Other$7,962$11,392P=.001 Mortality40%36%HR=1.06, p=.44 ©AAHCM

10  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

11  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

12  Patients and Families in MWHC program  MWHC Geriatrics team, Bruce Leff  JEN Associates- Dan Gilden, Joanna Kubisiak  Deerbrook Charitable Trust ©AAHCM

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