Understanding collaborative care implementation in the Department of Veterans Affairs: core functions and implementation challenges.

BACKGROUND: The collaborative care model is an evidence-based practice for treatment of depression in which designated care managers provide clinical services, often by telephone. However, the collaborative care model is infrequently adopted in the Department of Veterans Affairs (VA). Almost all VA medical centers have adopted a co-located or embedded approach to integrating mental health care for primary care patients. Some VA medical centers have also adopted a telephone-based collaborative care model where depression care managers support patient education, patient activation, and monitoring of adherence and progress over time. This study evaluated two research questions: (1) What does a dedicated care manager offer in addition to an embedded-only model? (2) What are the barriers to implementing a dedicated depression care manager? METHODS: This study involved 15 qualitative, multi-disciplinary, key informant interviews at two VA medical centers where reimbursement options were the same- both with embedded mental health staff, but one with a depression care manager. Participant interviews were recorded and transcribed. Thematic analysis was used to identify descriptive and analytical themes. RESULTS: Findings suggested that some of the core functions of depression care management are provided as part of embedded-only mental health care. However, formal structural attention to care management may improve the reliability of care management functions, in particular monitoring of progress over time. Barriers to optimal implementation were identified at both sites. Themes from the care management site included finding assertive care managers to hire, cross-discipline integration and collaboration, and primary care provider burden. Themes from interviews at the embedded site included difficulty getting care management on leaders' agendas amidst competing priorities and logistics (staffing and space). CONCLUSIONS: Providers and administrators see depression care management as a valuable healthcare service that improves patient care. Barriers to implementation may be addressed by team-building interventions to improve cross-discipline integration and communication. Findings from this study are limited in scope to the VA healthcare system. Future investigation of whether alternative barriers exist in implementation of depression care management programs in non-VA hospital systems, where reimbursement rates may be a more prominent concern, would be valuable.

Practical application of opt-out recruitment methods in two health services research studies.

BACKGROUND: Participant recruitment is an ongoing challenge in health research. Recruitment may be especially difficult for studies of access to health care because, even among those who are in care, people using services least often also may be hardest to contact and recruit. Opt-out recruitment methods (in which potential participants are given the opportunity to decline further contact about the study (opt out) following an initial mailing, and are then contacted directly if they have not opted out within a specified period) can be used for such studies. However, there is a dearth of literature on the effort needed for effective opt-out recruitment. METHODS: In this paper we describe opt-out recruitment procedures for two studies on access to health care within the U.S. Department of Veterans Affairs. We report resource requirements for recruitment efforts (number of opt-out packets mailed and number of phone calls made). We also compare the characteristics of study participants to potential participants via t-tests, Fisher's exact tests, and chi-squared tests. RESULTS: Recruitment rates for our two studies were 12 and 21%, respectively. Across multiple study sites, we had to send between 4.3 and 9.2 opt-out packets to recruit one participant. The number of phone calls required to arrive at a final status for each potentially eligible Veteran (i.e. study participation or the termination of recruitment efforts) were 2.9 and 6.1 in the two studies, respectively. Study participants differed as expected from the population of potentially eligible Veterans based on planned oversampling of certain subpopulations. The final samples of participants did not differ statistically from those who were mailed opt-out packets, with one exception: in one of our two studies, participants had higher rates of mental health service use in the past year than did those mailed opt-out packets (64 vs. 47%). CONCLUSIONS: Our results emphasize the practicality of using opt-out methods for studies of access to health care. Despite the benefits of these methods, opt-out alone may be insufficient to eliminate non-response bias on key variables. Researchers will need to balance considerations of sample representativeness and feasibility when designing studies investigating access to care.