Evaluating the effects of care coordination during the VA MISSION Act Era

Abstract Number:

3624 

Submission Type:

Contributed Abstract 

Contributed Abstract Type:

Poster 

Participants:

Ralph Ward (1), Ahmed Mohamed (2), Robert Neal Axon (3), Mulugeta Gebregziabher (3)

Institutions:

(1) N/A, N/A, (2) VA Health Equity and Rural Outreach Innovation Center, Charleston, SC, (3) VA Health Equity and Rural Outreach Innovation Center, Charleston , SC

Co-Author(s):

Ahmed Mohamed  
VA Health Equity and Rural Outreach Innovation Center
Robert Neal Axon  
VA Health Equity and Rural Outreach Innovation Center
Mulugeta Gebregziabher  
VA Health Equity and Rural Outreach Innovation Center

First Author:

Ralph Ward  
N/A

Presenting Author:

Ralph Ward  
N/A

Abstract Text:

Background: Care coordination (CC) for Veterans with inpatient admissions in the community is an important element of the MISSION Act of 2018, considered vital for reducing poor outcomes due to fragmented care. Few studies have evaluated early impacts of CC. Methods: We compared several ways to extract CC activity from the VA Corporate Data Warehouse and created a matched cohort using propensity scores for the probability of receiving CC. We used generalized linear models with GEE to account for clustered data to estimate the risks for 30-day readmission, 30-day ED visits, 90-day and 1-year mortality. We also developed facility level models by aggregating patient-level data and accounted for facility complexity and percentage of community admissions involving CC. Results: Patient-level models estimated CC was associated with higher risk for each outcome; for example, those assigned 'complex' coordination had 28% greater risk for 30-day readmission (RR:1.28,95%CI:1.26, 1.3) and 21% greater risk of 90-day mortality (RR:1.21,95%CI:1.17, 1.3). Facility level models indicated increased CC activity was not associated with a significant risk change for any outcome.

Keywords:

VA care coordination|MISSION Act|Healthcare outcomes research|Effectiveness research| |

Sponsors:

Biometrics Section

Tracks:

Risk Prediction

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