Evidence map›Paper›PMID 39794787›Full record

ArticleBMC medical informatics and decision making2025

Human-centered design of a health recommender system for orthopaedic shoulder treatment.

Akanksha Singh, Benjamin Schooley, John Mobley, Patrick Mobley, Sydney Lindros, John M Brooks, Sarah B Floyd

Abstract read
In one paragraph

Article in BMC medical informatics and decision making, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Akanksha SinghDepartment of Health Services Administration, School of Health Professions, University of Alabama at Birmingham, Birmingham, AL, USA.
Benjamin SchooleyDepartment of Electrical and Computer Engineering, Ira A. Fulton College of Engineering, Brigham Young University, Provo, UT, USA.
John MobleyUniversity of South Carolina School of Medicine Greenville, Greenville, SC, USA.
Patrick MobleyDepartment of Exercise Science, University of South Carolina, Arnold School of Public Health, Columbia, SC, USA.
Sydney LindrosDepartment of Public Health Sciences, Clemson University, Clemson, SC, USA.
John M BrooksDepartment of Health Services Policy and Management, University of South Carolina, Arnold School of Public Health, Columbia, SC, USA.
Sarah B FloydDepartment of Public Health Sciences, Clemson University, Clemson, SC, USA. sbf@clemson.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRich data on diverse patients and their treatments and outcomes within Electronic Health Record (EHR) systems can be used to generate real world evidence. A health recommender system (HRS) framework can be applied to a decision support system application to generate data summaries for similar patients during the clinical encounter to assist physicians and patients in making evidence-based shared treatment decisions.

objectiveA human-centered design (HCD) process was used to develop a HRS for treatment decision support in orthopaedic medicine, the Informatics Consult for Individualized Treatment (I-C-IT). We also evaluate the usability and utility of the system from the physician's perspective, focusing on elements of utility and shared decision-making in orthopaedic medicine.

methodsThe HCD process for I-C-IT included 6 steps across three phases of analysis, design, and evaluation. A team of health informatics and comparative effectiveness researchers directly engaged with orthopaedic surgeon subject matter experts in a collaborative I-C-IT prototype design process. Ten orthopaedic surgeons participated in a mixed methods evaluation of the I-C-IT prototype that was produced.

resultsThe HCD process resulted in a prototype system, I-C-IT, with 14 data visualization elements and a set of design principles crucial for HRS for decision support. The overall standard system usability scale (SUS) score for the I-C-IT Webapp prototype was 88.75 indicating high usability. In addition, utility questions addressing shared decision-making found that 90% of orthopaedic surgeon respondents either strongly agreed or agreed that I-C-IT would help them make data informed decisions with their patients.

conclusionThe HCD process produced an HRS prototype that is capable of supporting orthopaedic surgeons and patients in their information needs during clinical encounters. Future research should focus on refining I-C-IT by incorporating patient feedback in future iterative cycles of system design and evaluation.

Indexed as

Decision Making, SharedDecision Support Systems, ClinicalElectronic Health RecordsOrthopedicsUser-Centered DesignHumansClinical decision supportHealth recommender systemHuman-centered designHuman factorsOrthopaedic treatmentPersonalized medicineProximal humerus fracture

Identifiers

PMID39794787
PMCPMC11720343

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.