Evidence map›Paper›PMID 39712727›Full record

ArticleCureus2024

A Quality Improvement Project on Team-Based Care for Depression Screening Before and During the COVID-19 Pandemic in a Specialty Clinic.

Alvina D Brueggemann, Peter G Harper, Holly Boyer, Shannon Fjestad, Lynn A Burmeister

Abstract read
In one paragraph

Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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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

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

5 authors.

Alvina D BrueggemannQuality Improvement, M Health Fairview, Minneapolis, USA.
Peter G HarperFamily Medicine, University of Minnesota School of Medicine, Minneapolis, USA.
Holly BoyerOtolaryngology, University of Minnesota School of Medicine, Minneapolis, USA.
Shannon FjestadClinical Informatics, M Health Fairview, Minneapolis, USA.
Lynn A BurmeisterEndocrinology, Diabetes and Metabolism, University of Minnesota School of Medicine, Minneapolis, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDepression screening is an important first step to identifying patients who might benefit from depression treatment. Merit-based incentive payment system (MIPS) quality measures can yield financial benefits or losses for healthcare systems, including depression screening.

objectivesThis study aims to (1) develop a team-based care workflow to improve MIPS depression screening in a specialty clinic and (2) modify the workflow to include a virtual nursing and behavioral health resource after the COVID-19 pandemic hit.

methodsA quality improvement project, utilizing Lean Six Sigma process improvement methods, was implemented to improve team-based depression screening in a specialty clinic. A multidisciplinary team implemented plan-do-study-act cycles, created educational materials tailored to each role, developed electronic medical record (EMR) tools to alert and assist team members in screening, and ensured the EMR aligned with the MIPS criteria. The percentage of eligible visits where depression screening was performed was analyzed across four study periods: pre-intervention, post-intervention, COVID-19, and recovery. Recovery strategies included developing telehealth workflows, establishing centralized registered nurse triage groups, and using phone-based triage and support resources at virtual visits.

resultsUtilizing team-based strategy and available or newly developed tools, the percentage of eligible visits with completed depression screening was as follows: 1.4% pre-intervention, 58.2% post-intervention, 3.5% COVID-19, and 64.0% recovery. With the COVID-19 pandemic outbreak, initially, improved screening performance declined sharply. Recovery was achieved through the revision of workflows, team members, and support tools.

conclusionsA team-based care approach can successfully improve and maintain depression screening in a specialty clinic and was versatile enough to be readapted to virtual visits during the COVID-19 pandemic. In addition to impacting MIPS quality incentives, the depression screening workflows described in this article can be adapted to other uses, including virtual and in-person visits and in other specialty or chronic disease settings.

Indexed as

covid-19 impact of lockdowndepression in diabetesdepression screeningquality improvement projectsspecialty healthcare

Identifiers

PMID39712727
PMCPMC11663417

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LicenceCC BY
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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.