Participatory Design of Electronic Health Record Tools for Problem Solving Therapy

NCT ID: NCT03516513

Last Updated: 2024-08-13

Basic Information

• Recruitment Status: COMPLETED
• Clinical Phase: NA
• Total Enrollment: 24 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2020-01-30
• Study Completion Date: 2023-04-30

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 .

Conditions

Depression

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: HEALTH_SERVICES_RESEARCH
• Blinding Strategy: SINGLE

Study Groups

Problem Solving Therapy as Usual

Clinicians in this arm of care will have access to the Case Management Tracking System which is already in use.

Intervention: unguided PST

Group Type: ACTIVE_COMPARATOR

Problem Solving Therapy as Usual

Intervention Type: BEHAVIORAL

Treatment as usual to deliver 6 weekly sessions to teach patients how to use the seven step process to solve problems.

Assisted Problem Solving Therapy

This arm will be designed and finalized in Phase 1 and 2 of the project. We anticipate that the intervention will leverage clinical notes required to be completed by clinicians and will provide information to clinicians to help patients improve over time, as well as help clinicians implement PST to high quality.

Intervention: guided PST

Group Type: EXPERIMENTAL

Assisted Problem Solving Therapy

Intervention Type: BEHAVIORAL

Smart note assisted delivery of 6 weekly session to teach patients how to use the seven step process to solve problems

Interventions

Problem Solving Therapy as Usual

Treatment as usual to deliver 6 weekly sessions to teach patients how to use the seven step process to solve problems.

Intervention Type: BEHAVIORAL

Assisted Problem Solving Therapy

Smart note assisted delivery of 6 weekly session to teach patients how to use the seven step process to solve problems

Intervention Type: BEHAVIORAL

Other Intervention Names

Problem Solving Therapy

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

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

National Institute of Mental Health (NIMH)

NIH

Sponsor Role: collaborator

University of Washington

OTHER

Sponsor Role: lead

Responsible Party

Ian Bennett

Professor, School of Medicine: Family Medicine

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

Ian Bennett, PhD

Role: STUDY_CHAIR

UWMC Psychiatry

Locations

Behavioral Health Integration Program

Seattle, Washington, United States

Countries

United States

References

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.

Reference Type: DERIVED

PMID: 31599736 (View on PubMed)

Provided Documents

Document Type: Study Protocol and Statistical Analysis Plan

View Document

Other Identifiers

1P50MH115837-01

Identifier Type: NIH

Identifier Source: secondary_id

View Link

STUDY00004274

Identifier Type: -

Identifier Source: org_study_id