Evidence map›Paper›PMID 34713278›Full record

ArticleProceedings of the ... Americas Conference on Information Systems. Americas Conference on Information Systems2020

Do Novice and Expert Users of Clinical Decision Support Tools Need Different Explanations?

Haadi Mombini, Bengisu Tulu, Diane Strong, Emmanuel Agu, Clifford Lindsay, Lorraine Loretz, Peder Pedersen, Raymond Dunn

Abstract read
In one paragraph

Article in Proceedings of the ... Americas Conference on Information Systems. Americas Conference on Information Systems, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Haadi MombiniWPI.
Bengisu TuluWPI.
Diane StrongWPI.
Emmanuel AguWPI.
Clifford LindsayUMass Medical School.
Lorraine LoretzUMass Memorial.
Peder PedersenWPI.
Raymond DunnUMass Memorial.

Funding

SCH:Smartphone Wound Image Parameter Analysis and Decision Support in Mobile EnvR01EB025801 · NIBIB · WORCESTER POLYTECHNIC INSTITUTE · PI AGU, EMMANUEL · 2018 to 2021
$1.6M
NIBIB NIH HHS R01 EB025801
6 · The paper itself

Abstract

A key requirement for the successful adoption of clinical decision support systems (CDSS) is their ability to provide users with reliable explanations for any given recommendation which can be challenging for some tasks such as wound management decisions. Despite the abundance of decision guidelines, wound non-expert (novice hereafter) clinicians who usually provide most of the treatments still have decision uncertainties. Our goal is to evaluate the use of a Wound CDSS smartphone App that provides explanations for recommendations it produces. The App utilizes wound images taken by the novice clinician using smartphone camera. This study experiments with two proposed variations of rule-tracing explanations called verbose-based and gist-based. Deriving upon theories of decision making, and unlike prior literature that says rule-tracing explanations are only preferred by novices, we hypothesize that, rule-tracing explanations are preferred by both clinicians but in different forms: novices prefer verbose-based rule-tracing and experts prefer gist-based rule-tracing.

Indexed as

Clinical decision support systemsdecision explanationsdecision makingfuzzy-trace theorywound care

Identifiers

PMID34713278
PMCPMC8549570

What OpenQuestion holds

Textmetadata
LicenceTDM
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.