Project Background: Effective healthcare delivery requires effective management of interdependencies between multiple different professions with their own cultural traditions as well as between different organizational units with unique perceived purposes and boundaries of work to be delivered. For the patient navigating the boundaries between units, it should feel like a well-constructed continuum in which each part communicates and cooperates with the next for the explicit purpose of helping him/her achieve wellness. The VHA is theoretically positioned to deliver integrated care along such a continuum. Despite this, VHA's performance has been similar or worse than the Medicare population with regard to outcomes that reflect these complex interdependencies such as readmissions. We propose that these poor outcomes are related to difficulties managing the complex interdependencies among organizational units in VHA and to a lack of effective sense making among individuals regarding how best to coordinate Veteran needs. We propose studying readmissions as an exemplar of processes requiring a high level of interdependencies and sense making. By studying VHA facilities that have successfully improved early readmissions over a 4 year period of time, we will not only improve our understanding of the readmissions processes themselves but also the sense making within the organization needed to implement change when there is no single responsible part of the organization. Project Objectives: Using reduction of early readmissions as an example of a task that requires management of complex organizational interdependencies: 1) Elucidate how sense making unfolds across professional cultures and organizational units to reduce readmissions, the origins of which cannot easily be attributed to any one single organizational or patient level failure. 2) Build an agent-based model based on results from the qualitative data to gain further insights into the interdependencies and relative effects of the various agents and their actions on readmission rates. Project Methods: Objective 1: Conduct a qualitative field study of 4 facilities that have had a significant improvement in their readmissio rates from FY07 through FY11 and have a minimum of 100 admissions per month. Conduct semi-structured interviews with multiple levels of leadership: VISN, facility, inpatient services (Medicine/Hospital Medicine, Surgery, Psychiatry), Primary Care. Also with a sample of staff involved in discharge planning and inpatient/outpatient or vice/versa hand-offs. The interviews will probe on the constructs of sense making described by Weick, Sutcliffe and others: grounded in identity construction;retrospective;enactive of sensible environments;social;ongoing;focused on and by extracted cues;driven by plausibility rather than accuracy. Directly observe the work of inpatient teams around discharge planning, the work of any discharge coordinators or advocates, and committee work that deals with discharges. Observe the same staff in structured review of 10 readmitted cases from 3 months prior to visit. Analysis of each facility's data will in turn inform data collection for the subsequent facility. Objective 2: Based on the dat from the field study, we will build an agent-based model to better understand how sense making among physicians, between physicians and nurse coordinators and/social workers, between leadership and inpatient teams, and between leadership and support of patient needs after discharge emerges to create lower readmission rates. Agent-based modeling is a computer simulation of a process over time where autonomous agents interact in an environment to produce emergent--sometimes surprising--system properties.
By achieving better understanding of how some VHA facilities have improved their management of interdependencies to accomplish reduced readmissions, we will lay the groundwork for future testing of the efficacy of implementing similar methods in other facilities. If the average reduction in readmission rate of 3.37% for the 12 improving facilities in our sample could be achieved for all VA facilities, readmissions would be reduced from 17% to 14%, , saving Veterans risky hospitalizations.. In FY11 that would have been a reduction of admissions of about 17,500. In addition by understanding sensemaking within VA facilities we may be able to apply similar techniques to other complex problems such as reduction of polypharmacy or transition of Veterans from DoD to VA.
