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Clinical Trial Summary

Problem Solving Therapy for Primary Care (PST-PC) is an evidence based psychosocial intervention (EBPI) for use in primary care settings, with more than 100 clinical trials.

Despite it's proven efficacy we have found that implementation of PST-PC is complicated, resulting in rapid program drift (deviation from protocol with associated loss of efficacy), among practitioners following completion of training. Many studied have shown that program drift is not uncommon in the implementation of EBPIs and can be mitigated through on-going decision support and supervision. Unfortunately, decision support and supervisors of EBPIs are not widely available in low-resourced primary care clinics. We will address this problem by creating decision support tools to be integrated into electronic health records. Because these tools hare deemed by many practitioners in other field to be burdensome, we will explicitly involve active input on the content, design and function of these support tools. Outcomes may include electronic dashboards for panel management, automated suggestions for application of PST-PC elements based on patient reported outcomes or integration of automated patient tracking, and 4) support of patient engagement. We hypothesize that enhance decision support (target mechanism) will sustained quality delivery of PST-PC, which in turn will improve patient reported outcomes.


Clinical Trial Description

SPECIFIC AIMS. Although evidence-based psychosocial interventions (EBPIs) are a preferred treatment option by vulnerable populations, they are rarely available in community primary care settings and when available, are often delivered with poor fidelity. High quality delivery of evidence-based psychosocial interventions (EBPIs) in primary care medicine is a function of many variables, including clinician training and usability of the intervention. Several studies find that for EBPIs to be delivered with sustained quality, on-going supervision and guidance is critical (this study's focus). While the availability of clinicians trained in EBPIs is scarce, the availability to supervisors trained in EBPIs is even more limited. Given the ubiquity of electronic health records, automated decision support tools and feedback systems have been found to be effective in supporting sustained quality EBPIs7, but in practice have had mixed success on outcomes such that they may actually hinder clinical care and are often ignored by clinicians.In a report by the Agency for Healthcare Research and Quality, a significant barrier to the use of decision support tools is that these tools have not been developed with input from the clinician or in consideration of their work environment. Using the Center's Discover, Design, Build, Test (DDBT) framework, we will work with clinicians from 13 Behavioral Health Integration Program (BHIP) sites to create a clinical decision tool that addresses the common decisional dilemmas clinicians face when implementing EBPIs. We hypothesize that creating tools to support EBPIs will result in improved clinician competency and sustained skill (target) to EBPIs, compared to clinicians without these supports, resulting in better patient outcomes . The specific aims of this study are: Aim 1: Discover Phase (6 months). Using Participant Action research (PAR) informed user-centered design methods we will interview clinicians in primary care about challenges they face in the delivery of two EBPIs, Behavioral Activation and Problem Solving Treatment, observe them delivering these EBPIs, and receiving feedback on cases from experts in these EBPIs. This process will help us to identify the common decisional dilemma's clinician's face in delivering EBPIs, their preferences for expert guidance strategies, and how decision support tools could be embedded into clinic workflow to reduce obstacles and enhance the delivery of EBPIs.

Aim 2: Design/Build Phase (6 months). Based on information obtained in the discover phase, we will engage in a rapid cycle iterative prototype development and testing of decision support tools to support PST-PC will be carried out using user-centered design (UCD). The build of these tools will include the development of prototypes for user testing and refinement with input from care managers across the 13 BHIP sites. Contribution to the Center. Data from this phase will be used to inform the Matrix of EBPI Modifications.

Aim 3: Test Phase (18 months) In the second to third year of the proposed project we will test the decision support tools in a small pilot trial with six providers and thirty patients randomized to the use of the decision support tools. H1: Clinicians with access to decision tools will report better acceptability, usability, and less burden when using BA and PST-PC than clinicians without the tools . H2: Clinicians randomized to decision support tools will more competently deliver EBPI elements than clinicians randomized to unsupported EBPI. H3: Patients treated by clinicians with access to decision tools will have better patient-reported outcomes than patients treated by clinicians without access to these tools as assessed with functional disability and change in depression symptoms over time . ;


Study Design


Related Conditions & MeSH terms


NCT number NCT03516513
Study type Interventional
Source University of Washington
Contact Ian Bennett, MD
Phone 206-221-8692
Email ibennett@uw.edu
Status Not yet recruiting
Phase N/A
Start date January 30, 2020
Completion date December 31, 2022

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