Events / Matrixed Multiple Case Study: A systematic mixed-methods approach to examine factors impacting implementation success

Matrixed Multiple Case Study: A systematic mixed-methods approach to examine factors impacting implementation success

June 20, 2023
4:00 pm - 5:00 pm
Brown Lounge, Brown Hall

Matrixed Multiple Case Study (MMCS): A systematic mixed-methods approach to examine factors impacting implementation success will be presented by Bo Kim of the VA Center for Healthcare Organization and Implementation Research and Harvard Medical School. This event is part of the Dissemination & Implementation Seminar Series, which features leaders in the field to speak on a variety of relevant and timely topics.

Learning objectives

  1. Recognize defining features, unique strengths, and current limitations of MMCS
  2. Identify examples of MMCS being applied in different implementation contexts
  3. Describe potential directions for continued development and refinement of MMCS


This seminar will be an in-person event in the Brown Lounge. Virtual attendance will not be an option, but the recording of the seminar will be available for viewing after the event.

This event is free and open to all. Registration is strongly encouraged.

Directions & parking

The Brown Lounge is located inside Brown Hall on the southeast corner of Washington University’s Danforth Campus.

General visitors are encouraged to park in the East End Garage, located underground immediately east of Hillman Hall (number 55 on the map below). Garage rates are $2.00 per two-hour block for up to six hours, with a daily maximum of $9.00 for a full day:

  • Designated visitor spaces are available on the first level, P1, of the East End Garage.

Click here for driving directions to the East End Garage via Google Maps. To approximate the address for GPS, use: 6453 Centennial Parkway, St. Louis, MO.

A note about finding our buildings using GPS: Individual buildings on Washington University campus do not have street addresses. However, typing in the following address approximates the Brown School Campus location, at the intersection of Forsyth Boulevard and Hoyt Drive: 6350 Forsyth Blvd., St. Louis, MO 63105. For parking instructions, see above.


If you have any accessibility needs, please contact Emily Hickner at We need to be notified at least five business days prior to the event to guarantee accommodation for interpretation and CART (Communication Access Realtime Translation) services.


Featured Speaker

Bo Kim, PhD
Investigator, VA Center for Healthcare Organization and Implementation Research (CHOIR) Assistant Professor of Psychiatry, Harvard Medical School

Dr. Bo Kim directs the evaluation core of the VA Behavioral Health Quality Enhancement Research Initiative (QUERI) Program and is the systems analysis lead for the implementation core of the VA Bridging the Care Continuum QUERI Program. Her research interests are in applying interdisciplinary methodologies toward studying the quality and implementation of health and related services, such as for her QUERI grant in partnership with the VA Homeless Programs Office that evaluates the implementation of VA’s efforts to improve access to legal services for veterans.

The Topic

Many implementation studies seek to understand not only whether implementation strategies work, but also what works, for whom, and how. For instance, when an innovation is implemented at multiple sites, questions of interest include: How are the sites similar or different in their implementation? What factors are associated with implementation success, in what ways, and under what circumstances? To help answer these questions, the Matrixed Multiple Case Study (MMCS) method examines data from multiple sources to (i) comprehensively identify factors that influence the implementation process and (ii) understand their impact on implementation outcomes. Grounded in formal case study research methodology, MMCS delineates explicit steps from establishing the research goal to conducting cross-site analyses, arranging data into an array of matrices that can be easily sorted/filtered to test hypothesized patterns and identify less expected patterns regarding factors that influence implementation success.