Clinical trial NCT03516513: Participatory Design of Electronic Health Record Tools for Problem Solving Therapy
Official title: Participatory Design of Electronic Health Record Tools for Problem Solving Therapy
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Depression
Lead sponsor: University of Washington
Sponsor class: OTHER
Collaborators: name: National Institute of Mental Health (NIMH)
First posted: 2018-05-04
Enrollment: 24
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Intervention model description: Phase 1 will consist of qualitative interviews; Phase 2 will consist of rapid iterative design that includes qualitative interviews; Phase 3 will be an interventional pilot randomized trial. Data reported on ClinicalTrials.gov are for Phase 3.
Primary purpose: HEALTH_SERVICES_RESEARCH

Brief 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 its 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 are deemed by many practitioners in other fields 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 support of patient engagement. We hypothesize that enhanced decision support (target mechanism) will sustain quality delivery of PST-PC, which in turn will improve patient reported outcomes.

Detailed 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 EBPIs, 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, to 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. 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 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 .

Eligibility criteria: Inclusion Criteria:

Clinicians: 18 years of age, able to read and speak English, provides psychotherapy as part of the University of Washington Medicine network, and willing to video-record PST sessions with patient participants Clients: 18+ years of age, able to read and speak English, willing to receive psychotherapy from a clinician who is also participating in the study, willing to have therapy sessions video-recorded, Patient Health Questionnaire-9 score of 10 or higher

Exclusion Criteria:

Client: History or presence of psychiatric diagnoses other than unipolar, non-psychotic depression or generalized anxiety disorder

Primary outcomes:
measure: Acceptability of Intervention Measure
timeFrame: Clinicians: Six months after certification in the intervention. Clients: Six week follow-up
measure: User Burden Scale
timeFrame: Clinicians: Six months follow-up after they have been certified in PST. Clients: six week follow-up timepoint
measure: System Usability Scale
timeFrame: Clinicians: 6 month follow-up after certification in PST. Clients: Six week follow-up
Secondary outcomes:
measure: Patient Health Questionnaire
timeFrame: Baseline, 6 week follow-up
measure: Sheehan Disability Assessment Scale
timeFrame: Baseline, 6 week follow up
measure: Problem Solving Therapy Clinician Certification
timeFrame: Expert clinicians reviewed audiotapes of therapy sessions for each clinician participant over a six month period of time after initial training.
Other outcomes:
Locations:
city: Seattle
country: United States
facility: Behavioral Health Integration Program
state: Washington
Study officials:
affiliation: UWMC Psychiatry
name: Ian Bennett, PhD
role: STUDY_CHAIR
References:
citation: Lyon AR, Munson SA, Renn BN, Atkins DC, Pullmann MD, Friedman E, Arean PA. Use of Human-Centered Design to Improve Implementation of Evidence-Based Psychotherapies in Low-Resource Communities: Protocol for Studies Applying a Framework to Assess Usability . JMIR Res Protoc. 2019 Oct 9;8(10):e14990. doi: 10.2196/14990.