Clinical Trial Details
— Status: Completed
Administrative data
NCT number |
NCT03516513 |
Other study ID # |
STUDY00004274 |
Secondary ID |
1P50MH115837-01 |
Status |
Completed |
Phase |
N/A
|
First received |
|
Last updated |
|
Start date |
January 30, 2020 |
Est. completion date |
April 30, 2023 |
Study information
Verified date |
May 2023 |
Source |
University of Washington |
Contact |
n/a |
Is FDA regulated |
No |
Health authority |
|
Study type |
Interventional
|
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.
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 .