Evidence map›Paper›PMID 34152278›Full record

ArticleJMIR formative research2021

Modeling the Implementation Context of a Telemedicine Service: Work Domain Analysis in a Surgical Setting.

Hedvig Aminoff, Sebastiaan Meijer, Urban Arnelo, Kristina Groth

Open access · goldAbstract read
In one paragraph

Article in JMIR formative research, 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
1.0field-weighted citation impact, top 24% 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, 6 citations in OpenAlex.

  1. Review
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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 3 institutions in 1 country.

Hedvig AminoffBiomedical Engineering and Health Systems, KTH Royal Institute of Technology, Stockholm, Sweden.ORCID https://orcid.org/0000-0001-8747-9277
Sebastiaan MeijerBiomedical Engineering and Health Systems, KTH Royal Institute of Technology, Stockholm, Sweden.ORCID https://orcid.org/0000-0003-1126-3781
Urban ArneloDepartment of Surgical and Perioperative Sciences, Surgery, Umeå University, Umeå, Sweden.ORCID https://orcid.org/0000-0002-1843-5673
Kristina GrothInnovation Center, Karolinska University Hospital, Stockholm, Sweden.ORCID https://orcid.org/0000-0002-8200-2418
KTH Royal Institute of Technology · SEKarolinska Institutet · SEKarolinska University Hospital · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA telemedicine service enabling remote surgical consultation had shown promising results. When the service was to be scaled up, it was unclear how contextual variations among different clinical sites could affect the clinical outcomes and implementation of the service. It is generally recognized that contextual factors and work system complexities affect the implementation and outcomes of telemedicine. However, it is methodologically challenging to account for context in complex health care settings. We conducted a work domain analysis (WDA), an engineering method for modeling and analyzing complex work environments, to investigate and represent contextual influences when a telemedicine service was to be scaled up to multiple hospitals.

objectiveWe wanted to systematically characterize the implementation contexts at the clinics participating in the scale-up process. Conducting a WDA would allow us to identify, in a systematic manner, the functional constraints that shape clinical work at the implementation sites and set the sites apart. The findings could then be valuable for informed implementation and assessment of the telemedicine service.

methodsWe conducted observations and semistructured interviews with a variety of stakeholders. Thematic analysis was guided by concepts derived from the WDA framework. We identified objects, functions, priorities, and values that shape clinical procedures. An iterative "discovery and modeling" approach allowed us to first focus on one clinic and then readjust the scope as our understanding of the work systems deepened.

resultsWe characterized three sets of constraints (ie, facets) in the domain: the treatment facet, administrative facet (providing resources for procedures), and development facet (training, quality improvement, and research). The constraints included medical equipment affecting treatment options; administrative processes affecting access to staff and facilities; values and priorities affecting assessments during endoscopic retrograde cholangiopancreatography; and resources for conducting the procedure.

conclusionsThe surgical work system is embedded in multiple sets of constraints that can be modeled as facets of the system. We found variations between the implementation sites that might interact negatively with the telemedicine service. However, there may be enough motivation and resources to overcome these initial disruptions given that values and priorities are shared across the sites. Contrasting the development facets at different sites highlighted the differences in resources for training and research. In some cases, this could indicate a risk that organizational demands for efficiency and effectiveness might be prioritized over the long-term outcomes provided by the telemedicine service, or a reduced willingness or ability to accept a service that is not yet fully developed or adapted. WDA proved effective in representing and analyzing these complex clinical contexts in the face of technological change. The models serve as examples of how to analyze and represent a complex sociotechnical context during telemedicine design, implementation, and assessment.

Indexed as

cognitive work analysishealth technologyimplementation contextsurgical guidancetelemedicinetelementoringusabilitywork domain analysis

Identifiers

PMID34152278
PMCPMC8277332
OpenAlexW3158581876

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.