Evidence map›Paper›PMID 32865770›Full record

ArticleJournal of general internal medicine2021

Using Health Systems Engineering Approaches to Prepare for Tailoring of Implementation Interventions.

Geoffrey D Barnes, Jennifer Acosta, Jacob E Kurlander, Anne E Sales

Open access · hybridAbstract read
In one paragraph

Article in Journal of general internal medicine, 2021. 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
1.3field-weighted citation impact, top 14% 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, 7 citations in OpenAlex.

  1. Review
  2. Article
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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

4 authors at 1 institution in 1 country.

Geoffrey D BarnesFrankel Cardiovascular Center, University of Michigan, Ann Arbor, MI, USA. gbarnes@umich.edu.ORCID http://orcid.org/0000-0002-6532-8440
Jennifer AcostaCenter for Bioethics and Social Science in Medicine, University of Michigan, Ann Arbor, MI, USA.
Jacob E KurlanderInstitute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI, USA.
Anne E SalesInstitute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI, USA.
University of Michigan · US

Funding

Developing an Implementation Strategy to Improve Peri-procedural Anticoagulation Management for Patients with Atrial FibrillationK01HL135392 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BARNES, GEOFFREY DOUGLAS · 2017 to 2021
$842k
NHLBI NIH HHS K01 HL135392NHLBI NIH HHS K01HL135392
6 · The paper itself

Abstract

backgroundImplementation of evidence-based practices often requires tailoring implementation strategies to local contextual factors, including available resources, expertise, and cultural norms. Using an exemplar case, we describe how health systems engineering methods can be used to understand system-level variation that must be accounted for prior to broad implementation.

methodsWithin the context of a single-center quality improvement activity, a multi-disciplinary stakeholder team used health systems engineering methods to describe how pre-endoscopy antithrombotic management was executed, and implemented a redesigned process to improve clinical care. The research team then conducted multiple stakeholder focus groups at four different health-care systems to describe and compare current processes for pre-endoscopy antithrombotic medication management. Detailed work flow maps for each health-care system were developed, analyzed, and integrated to develop an overarching current work flow map, identify key process steps, and describe areas of process variation.

resultsFive key process steps were identified across the four health systems: (1) place an endoscopy order, (2) screen for antithrombotic use, (3) coordinate medication management, (4) instruct the patient, and (5) confirm appropriate medication management before procedure. Across health systems, we found a high degree of variation in each step (e.g., who performed, use of technology, systematic vs. ad hoc process). This variation was influenced by two key system-level contextual factors: (1) degree of health system integration and (2) role and training level of available staff. These key steps, areas of variation, and contextual factors were integrated into an assessment tool designed to facilitate tailoring of a future implementation and dissemination strategy.

conclusionsTools from health systems engineering can be used to identify key work flow process steps, variations in how those steps are executed, and influential contextual factors. This process and the associated assessment tool may facilitate broader implementation tailoring.

Indexed as

Delivery of Health CareQuality ImprovementGovernment ProgramsHumansadaptationdisseminationhealth systems engineeringimplementationquality improvement

Identifiers

PMID32865770
PMCPMC7859134
OpenAlexW3082038901

What OpenQuestion holds

Textmetadata
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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.