Evidence map›Paper›PMID 36048400›Full record

ArticlePrevention science : the official journal of the Society for Prevention Research2024

Scaling Interventions to Manage Chronic Disease: Innovative Methods at the Intersection of Health Policy Research and Implementation Science.

Emma E McGinty, Nicholas J Seewald, Sachini Bandara, Magdalena Cerdá, Gail L Daumit, Matthew D Eisenberg, Beth Ann Griffin, Tak Igusa, John W Jackson, Alene Kennedy-Hendricks and 7 more

Erratum issuedOpen access · hybridAbstract read
In one paragraph

Article in Prevention science : the official journal of the Society for Prevention Research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
6.1field-weighted citation impact, top 3% 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

16 citing papers in PubMed, 22 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

17 authors at 4 institutions in 1 country.

Emma E McGintyDepartment of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA. bmcginty@jhu.edu.
Nicholas J SeewaldDepartment of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Sachini BandaraDepartment of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Magdalena CerdáDepartment of Population Health, New York University Grossman School of Medicine, New York, NY, USA.
Gail L DaumitDivision of General Internal Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA.
Matthew D EisenbergDepartment of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Beth Ann GriffinRAND Corporation, Washington, DC, USA.
Tak IgusaDepartment of Engineering, Johns Hopkins University, Baltimore, MD, USA.
John W JacksonDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Alene Kennedy-HendricksDepartment of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Jill MarstellerDepartment of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Edward J MiechIndiana University School of Medicine, Indianapolis, USA.
Jonathan PurtleDepartment of Public Health Policy and Management, New York University School of Global Public Health, New York City, New York, USA.
Ian SchmidDepartment of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Megan S SchulerRAND Corporation, Washington, DC, USA.
Christina T YuanDepartment of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Elizabeth A StuartDepartment of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Johns Hopkins University · USNew York University · USRAND Corporation · USIndiana University – Purdue University Indianapolis · US

Funding

Optimal Methods for Estimating Policy Effect Heterogeneity in Opioid Policy ResearchP50DA046351 · NIDA · RAND CORPORATION · PI Rosanna Smart · 2018 to 2026
$20.8M
Using an innovative quality improvement process to increase delivery of evidenced-based CVD risk factor care in community mental health organizationsP50MH115842 · NIMH · JOHNS HOPKINS UNIVERSITY · PI Christina T. Yuan · 2018 to 2026
$16.2M
Integrating data for causal inference in behavioral healthT32MH122357 · NIMH · JOHNS HOPKINS UNIVERSITY · PI Rashelle Jean Musci, Elizabeth A. Stuart · 2020 to 2026
$1.8M
Policy Implementation Research on Earmarked Taxes for Mental Health ServicesR21MH125261 · NIMH · NEW YORK UNIVERSITY · PI PURTLE, JONATHAN · 2021 to 2022
$404k
NIDA NIH HHS P50 DA046351NIMH NIH HHS P50 MH115842NIMH NIH HHS R21 MH125261NIMH NIH HHS T32 MH122357
6 · The paper itself

Abstract

Policy implementation is a key component of scaling effective chronic disease prevention and management interventions. Policy can support scale-up by mandating or incentivizing intervention adoption, but enacting a policy is only the first step. Fully implementing a policy designed to facilitate implementation of health interventions often requires a range of accompanying implementation structures, like health IT systems, and implementation strategies, like training. Decision makers need to know what policies can support intervention adoption and how to implement those policies, but to date research on policy implementation is limited and innovative methodological approaches are needed. In December 2021, the Johns Hopkins ALACRITY Center for Health and Longevity in Mental Illness and the Johns Hopkins Center for Mental Health and Addiction Policy convened a forum of research experts to discuss approaches for studying policy implementation. In this report, we summarize the ideas that came out of the forum. First, we describe a motivating example focused on an Affordable Care Act Medicaid health home waiver policy used by some US states to support scale-up of an evidence-based integrated care model shown in clinical trials to improve cardiovascular care for people with serious mental illness. Second, we define key policy implementation components including structures, strategies, and outcomes. Third, we provide an overview of descriptive, predictive and associational, and causal approaches that can be used to study policy implementation. We conclude with discussion of priorities for methodological innovations in policy implementation research, with three key areas identified by forum experts: effect modification methods for making causal inferences about how policies' effects on outcomes vary based on implementation structures/strategies; causal mediation approaches for studying policy implementation mechanisms; and characterizing uncertainty in systems science models. We conclude with discussion of overarching methods considerations for studying policy implementation, including measurement of policy implementation, strategies for studying the role of context in policy implementation, and the importance of considering when establishing causality is the goal of policy implementation research.

Indexed as

Health PolicyImplementation ScienceChronic DiseaseDisease ManagementHumansPatient Protection and Affordable Care ActUnited StatesImplementationPolicyScale-up

Identifiers

PMID36048400
PMCPMC11042861
OpenAlexW4294129017

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.