Evidence map›Paper›PMID 37091095›Full record

ArticleImplementation research and practice

Augmenting systems-level implementation of patient-reported outcomes for depression care through the use of structured analysis and design technique.

Elizabeth J Austin, Joseph A Heim, Savitha Sangameswaran, Courtney Segal, Denise Chang, Danielle C Lavallee

Open access · goldAbstract read
In one paragraph

Article in Implementation research and practice. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.8field-weighted citation impact, top 22% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Patient adherence to patient-reported outcome measure (PROM) completion in clinical care: current understanding and future recommendations.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2024
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 2 countries.

Elizabeth J AustinDepartment of Health Systems and Population Health, University of Washington, Seattle, WA, USA.ORCID https://orcid.org/0000-0002-4221-1362
Joseph A HeimDepartment of Health Systems and Population Health, University of Washington, Seattle, WA, USA.
Savitha SangameswaranDepartment of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA.
Courtney SegalDepartment of Health Systems and Population Health, University of Washington, Seattle, WA, USA.
Denise ChangDepartment of Psychiatry and Behavioral Health Sciences, School of Medicine, University of Washington, Seattle, WA, USA.
Danielle C LavalleeDepartment of Health Systems and Population Health, University of Washington, Seattle, WA, USA.
University of Washington · USUniversity of Washington Medical Center · US

Funding

AHRQ HHS R01 HS023785
6 · The paper itself

Abstract

Background: Health systems increasingly need to implement complex practice changes such as the routine capture of patient-reported outcome (PRO) measures. Yet, health systems have met challenges when trying to bring practice change to scale across systems at large. While implementation science can guide the evaluation of implementation determinants, teams first need tools to systematically understand and compare workflow activities across practice sites. Structured analysis and design technique (SADT), a system engineering method of workflow modeling, may offer an opportunity to enhance the scalability of implementation evaluation for complex practice change like PROs. Method: We utilized SADT to identify the core workflow activities needed to implement PROs across diverse settings and goals for use, establishing a generalizable PRO workflow diagram. We then used the PRO workflow diagram to guide implementation monitoring and evaluation for a 1-year pilot implementation of the electronic Patient Health Questionnaire-9 (ePHQ). The pilot occurred across multiple clinical settings and for two clinical use cases: depression screening and depression management. Results: SADT identified five activities central to the use of PROs in clinical care: deploying PRO measures, collecting PRO data, tracking PRO completion, reviewing PRO results, and documenting PRO data for future use. During the 1-year pilot, 8,596 patients received the ePHQ for depression screening via the patient portal, of which 1,719 (21%) submitted the ePHQ; 367 patients received the ePHQ for depression management, of which 174 (47%) submitted the ePHQ. We present three case examples of how the SADT PRO workflow diagram augmented implementation monitoring, tailoring, and evaluation activities. Conclusions: Use of a generalizable PRO workflow diagram aided the ability to systematically assess barriers and facilitators to fidelity and identify needed adaptations. The use of SADT offers an opportunity to align systems science and implementation science approaches, augmenting the capacity for health systems to advance system-level implementation. Plain Language Summary: Health systems increasingly need to implement complex practice changes such as the routine capture of patient-reported outcome (PRO) measures. Yet these system-level changes can be challenging to manage given the variability in practice sites and implementation context across the system at large. We utilized a systems engineering method-structured analysis and design technique-to develop a generalizable diagram of PRO workflow that captures five common workflow activities: deploying PRO measures, collecting PRO data, tracking PRO completion, reviewing PRO results, and documenting PRO data for future use. Next, we used the PRO workflow diagram to guide our implementation of PROs for depression care in multiple clinics. Our experience showed that use of a standard workflow diagram supported our implementation evaluation activities in a systematic way. The use of structured analysis and design technique may enhance future implementation efforts in complex health settings.

Indexed as

implementation processpatient-reported outcomesworkflow modeling

Identifiers

PMID37091095
PMCPMC9924240
OpenAlexW4313028635

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.