Depression Care Management is a model of depression treatment demonstrating effectiveness in diverse settings and studies. The Program to Encourage Active and Rewarding Lives for Seniors (PEARLS) is a specific, multi-component, depression care management intervention that effectively treats minor depression and dysthymia in homebound elders. Despite its effectiveness, successful translation into everyday practice has been slow and incomplete. Use of an implementation consultant has been shown to effectively overcome organizational barriers. The purpose of this research application is to study the effects of adding consultation by an implementation management team to usual PEARLS implementation through case manager referral. The investigators hypothesize that the consultation team will facilitate greater reach of PEARLS to homebound elderly depressed patients across a county-wide region as compared to current referral-based implementation efforts. The Seattle Aging and Disabilities Services program has 50 case managers serving over 2000 homebound elderly clients, of whom 400 have depression scores consistent with dysthymia or minor depression. 25 case managers will be randomly allocated to work with PEARLS referral-based care augmented by an implementation management team and the remaining 25 will continue with usual referral-based care. One of the specific aims is to develop an implementation management team to improve PEARLS implementation. The team will include a geriatric psychiatrist, a person with PEARLS intervention expertise, and a case manager.
A second aim i s to develop an implementation plan for organizational assessment, staff education and training, monitoring of outcomes, and collaborative problem solving.
The third aim i s to conduct the trial testing the implementation methods to usual implementation and the fourth aim is to evaluate the trial. The evaluation plan will use mixed methods including both qualitative and quantitative methods to determine the reach, effectiveness, adoption, implementation fidelity, and maintenance of this implementation approach to determine the benefits of using an implementation management team. ? ? ? ?
| Steinman, Lesley; Hammerback, Kristen; Snowden, Mark (2015) It Could Be a Pearl to You: Exploring Recruitment and Retention of the Program to Encourage Active, Rewarding Lives (PEARLS) With Hard-to-Reach Populations. Gerontologist 55:667-76 |
| Karr, Jonathan R; Williams, Alex H; Zucker, Jeremy D et al. (2015) Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models. PLoS Comput Biol 11:e1004096 |
| Hughey, Jacob J; Gutschow, Miriam V; Bajar, Bryce T et al. (2015) Single-cell variation leads to population invariance in NF-?B signaling dynamics. Mol Biol Cell 26:583-90 |
| Karr, Jonathan R; Guturu, Harendra; Chen, Edward Y et al. (2015) NetworkPainter: dynamic intracellular pathway animation in Cytobank. BMC Bioinformatics 16:172 |
| Carrera, Javier; Covert, Markus W (2015) Why Build Whole-Cell Models? Trends Cell Biol 25:719-722 |
| Regot, Sergi; Hughey, Jacob J; Bajar, Bryce T et al. (2014) High-sensitivity measurements of multiple kinase activities in live single cells. Cell 157:1724-34 |
| Birch, Elsa W; Udell, Madeleine; Covert, Markus W (2014) Incorporation of flexible objectives and time-linked simulation with flux balance analysis. J Theor Biol 345:12-21 |
| Karr, Jonathan R; Phillips, Nolan C; Covert, Markus W (2014) WholeCellSimDB: a hybrid relational/HDF database for whole-cell model predictions. Database (Oxford) 2014: |
| Sanghvi, Jayodita C; Regot, Sergi; Carrasco, Silvia et al. (2013) Accelerated discovery via a whole-cell model. Nat Methods 10:1192-5 |
| Karr, Jonathan R; Sanghvi, Jayodita C; Macklin, Derek N et al. (2013) WholeCellKB: model organism databases for comprehensive whole-cell models. Nucleic Acids Res 41:D787-92 |
Showing the most recent 10 out of 13 publications
