Evaluating Intensive Outpatient Primary Care: VA Experience
Steven M. Asch MD MPH Director, Center for Innovation to Implementation Professor and Vice Chief, Stanford Division of Primary Care
Evaluating Intensive Outpatient Primary Care: VA Experience Steven - - PowerPoint PPT Presentation
Evaluating Intensive Outpatient Primary Care: VA Experience Steven M. Asch MD MPH Director, Center for Innovation to Implementation Professor and Vice Chief, Stanford Division of Primary Care Same problem as everywhere: Concentration of
Steven M. Asch MD MPH Director, Center for Innovation to Implementation Professor and Vice Chief, Stanford Division of Primary Care
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Percent of Total VA Patients Total VA Health Care Costs Bottom 90% Top 10%
Source: Analysis of 2010 HERC Average Cost data
Intensive Management PACT (ImPACT)
0% 20% 40% 60% 80% 100% General Satisfaction Communication Satisfaction Baseline Follow-Up P P < 0.01 P P < 0.05
From Zulman DM. JAMA Int Med. 2017.
From Zulman DM. JAMA Int Med. 2017.
Atlanta CBOC Cleveland VAMC and CBOC Milwaukee VAMC Salisbury VAMC San Francisco VAMC and 2 CBOCs
Site A Site B Site C Site D Site E Screened patients, triaged and assessed for services X X X X X Interdisciplinary care team X X X X X Social work X X X X X Mental health/addiction support X X X X Care coordination X X X X X Home visits X X X X X Assisted with medications X X X X X Health coaching X X X X X Replace PACT team X Medic support X
High risk for hosp (CAN score) + hosp/ED visit <6 months
PIM
N=1105
Opt in
N=691
Opt out of program N=414
PACT N=1102
0% 10% 20% 30% 40% 50% 60% 70% Help with coordination of care Have a trusted provider Respect from provider Easily accessible provider Ease in getting care Got needed services PIM PACT
Strongly Agree
2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 18,000 PIM Pre-Randomization PIM Post-Randomization PACT Pre-Randomization PACT Post- Randomization Difference-in-Difference
^Predicted means from regression models
* p<0.01
2,638 5,000 10,000 15,000 20,000 25,000
PIM Pre-Randomization PIM Post-Randomization PACT Pre-Randomization PACT Post-Randomization Difference-in-Difference
^Predicted means from regression models
*Translation- did not save money
Donna Zulman Evelyn Chang Jean Yoon Susan Stockdale Gordon Schectman Lisa Rubenstein Michael Ong David Atkins Frances Wu Debra Hummel Marian Katz Elvira Jimenez Mingming Wang Ava Wong Angel Park Brook Watts Jessica Eng Neha Pathak Parag Dalsania Andrew Lanto Shoutzu Lin Carrie Patton Belinda Black Jeff Jackson