| Literature DB >> 23799943 |
Alex H Krist1, Beth A Glenn, Russell E Glasgow, Bijal A Balasubramanian, David A Chambers, Maria E Fernandez, Suzanne Heurtin-Roberts, Rodger Kessler, Marcia G Ory, Siobhan M Phillips, Debra P Ritzwoller, Dylan H Roby, Hector P Rodriguez, Roy T Sabo, Sherri N Sheinfeld Gorin, Kurt C Stange.
Abstract
BACKGROUND: There is a pressing need for greater attention to patient-centered health behavior and psychosocial issues in primary care, and for practical tools, study designs and results of clinical and policy relevance. Our goal is to design a scientifically rigorous and valid pragmatic trial to test whether primary care practices can systematically implement the collection of patient-reported information and provide patients needed advice, goal setting, and counseling in response.Entities:
Mesh:
Year: 2013 PMID: 23799943 PMCID: PMC3694031 DOI: 10.1186/1748-5908-8-73
Source DB: PubMed Journal: Implement Sci ISSN: 1748-5908 Impact factor: 7.327
Distinguishing differences between pragmatic and traditional clinical efficacy trials
| Stakeholder involvement | Engaged in all study phases including study design, conducting the study, collecting data, interpreting results, disseminating findings | Limited engagement, often in response to investigator ideas or study subjects |
| Research Design | Includes internal and external validity, design fidelity and local adaptation, real life settings and populations, contextual assessments | Focus on limiting threats to internal validity, typically uses randomized controlled trial, participants and settings typically homogenous |
| Outcomes | Reach, effectiveness, adoption, implementation, comparative effectiveness, sustainability | Efficacy, mechanism identification, component analysis |
| Measures | Brief, valid, actionable with rapid clinical utility, feasible in real world and low-resource settings | Validated measures that minimize bias, focus on internal consistency and theory rather than clinical relevance |
| Costs | Assessments include intervention costs and replication costs in relation to outcomes | Often not collected or reported |
| Data Source | May include existing data (electronic health records, administrative data) and brief patient reports. | Data generation and collection part of clinical trial |
| Analyses | Process and outcome analyses relevant to stakeholders and from different perspectives | Specified a priori and typically restricted to investigator hypotheses |
| Availability of findings | Rapid learning and implementation | Delay between trial completion and analytic availability |
Figure 1MOHR study overview and timeline. The study started in January 2013. The approximate implementation date for the early implementation practices is March 2013 and July 2013 for the delayed implementation practices. (IRB = institutional review board, EIS = early implementation sites, DIS = delayed implementation sites).
Figure 2MOHR study organization and coordination. The four general partners include funders, project coordination, local research teams, and study practices. The funders provide project coordinators general input into the study implementation and design. Overall project coordination includes the five working groups, MOHR planning committee, and the coordination center. The local research teams directly coordinate with the nine practice pairs to carry out and support the MOHR implementation and evaluation. (ACORN = Virginia Ambulatory Care Outcomes Research Network, UV = University of Vermont, UNC = University of North Carolina, UCLA = University of California, Los Angeles, and UTH = University of Texas Houston).
Participating practice characteristics
| 1 | VA | S | 5,000 | 2 | 4 | 15% | 10% | 5% | 0% | 30% |
| 2 | VA | S | 1,500 | 1 | 2 | 20% | 10% | 1% | 0% | 9% |
| 3 | VA | R | 2,500 | 1.6 | 7 | 1% | 49% | 12% | 1% | 49% |
| 4 | VA | S | 5,200 | 4 | 11 | 2% | 18% | 15% | 2% | 18% |
| 5 | VA | U | 3,700 | 5.9 | 17.3 | 2% | 39% | 24% | 2% | 39% |
| 6 | VA | U | 3,400 | 5.3 | 16.9 | 1% | 17% | 26% | 1% | 17% |
| 7 | CA | R | 3,500 | 5.5 | 15 | 3% | 1% | 13% | 3% | 1% |
| 8 | CA | R | 5,400 | 7 | 25.5 | 13% | 2% | 12% | 13% | 2% |
| 9 | VT | R | 9,500 | 5 | 13.5 | 1% | 5% | 13% | 1% | 5% |
| 10 | VT | R | 10,000 | 5 | 14 | 1% | 2% | 15% | 1% | 2% |
| 11 | NC | R | 1,100 | 4.5 | 12 | 2% | 60% | 49% | 2% | 60% |
| 12 | NC | R | 7,500 | 3.5 | 10 | 40% | 60% | 10% | 10% | 70% |
| 13 | CA | U | 2,040 | 1 | 7 | 75% | 25% | 5% | 45% | 50% |
| 14 | CA | U | 2,180 | 2 | 6 | 75% | 25% | 5% | 45% | 50% |
| 15 | TX | R | 4,800 | 2 | 6 | 48% | 23% | 2% | 48% | 23% |
| 16 | TX | R | 3,800 | 2 | 6 | 23% | 32% | 2% | 23% | 32% |
| 17 | TX | U | 2,800 | 3 | 19 | 82% | 6% | 1% | 82% | 6% |
| 18 | TX | U | 2,800 | 3.6 | 12 | 80% | 5% | 1% | 80% | 5% |
Notes:
Practices 1-10 belong to a practice based research network and practices 11-18 belong to the Cancer Prevention and Control Research Network.
All practices except Site 2 and 3 have an electronic health record.
All practices have experience with prior research or quality improvement projects.
FTE Full Time Equivalent.
S Suburban, R Rural, U Urban.
Figure 3Patient summary and feedback from http://www.MyOwnHealthReport.org. The first page demonstrates the patient’s health behavior and psychosocial scores, level of concern, and whether the patient reported readiness to change and interest in talking with their doctor. The second page includes patient workspace for notes, creation of SMART health goals, and a follow-up plan.
Figure 4MOHR study CONSORT flow diagram.
Figure 5Depiction of the MOHR study PRECIS characteristics. The MOHR study design receives completely pragmatic scores for intervention flexibility, control flexibility, and practitioner expertise. The MOHR study design receives the next most pragmatic rating on the remaining seven dimensions.