Evidence map›Paper›PMID 29602435›Full record

ArticleInternational journal of medical informatics2018

Physician nurse care: A new use of UMLS to measure professional contribution: Are we talking about the same patient a new graph matching algorithm?

Andrew D Boyd, Karen Dunn Lopez, Camillo Lugaresi, Tamara Macieira, Vanessa Sousa, Sabita Acharya, Abhinaya Balasubramanian, Khawllah Roussi, Gail M Keenan, Yves A Lussier and 3 more

Abstract read
In one paragraph

Article in International journal of medical informatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–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

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  6. Review
  7. The Usability of IT Systems in Document Management, Using the Example of theInternational journal of environmental research and public health · 2022
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Andrew D BoydDepartment of Biomedical and Health Information Sciences, College of Applied Health Sciences, University of Illinois at Chicago, 1919 W Taylor St., Chicago, IL 60612, United States. Electronic address: boyda@uic.edu.
Karen Dunn LopezDepartment of Health System Science, College of Nursing, University of Illinois at Chicago, 845 South Damen Ave, Chicago, IL 60612, United States.
Camillo LugaresiDepartment of Computer Science, College of Engineering, University of Illinois at Chicago, 851 South Morgan Street, Chicago, IL 60607, United States.
Tamara MacieiraDepartment of Health System Science, College of Nursing, University of Illinois at Chicago, 845 South Damen Ave, Chicago, IL 60612, United States.
Vanessa SousaDepartment of Health System Science, College of Nursing, University of Illinois at Chicago, 845 South Damen Ave, Chicago, IL 60612, United States.
Sabita AcharyaDepartment of Computer Science, College of Engineering, University of Illinois at Chicago, 851 South Morgan Street, Chicago, IL 60607, United States.
Abhinaya BalasubramanianDepartment of Computer Science, College of Engineering, University of Illinois at Chicago, 851 South Morgan Street, Chicago, IL 60607, United States.
Khawllah RoussiDepartment of Biomedical and Health Information Sciences, College of Applied Health Sciences, University of Illinois at Chicago, 1919 W Taylor St., Chicago, IL 60612, United States.
Gail M KeenanDepartment of Health Care Environments and Systems, College of Nursing, University of Florida, PO Box 100187, Gainesville, FL 32610, United States.
Yves A LussierDepartment of Medicine, College of Medicine, University of Arizona, 1501 N. Campbell Dr, Tucson, AZ 85724, United States; The University of Arizona Health Sciences Center, 1295 North Martin Ave, Tucson, AZ 85721, United States.
Jianrong 'John' LiDepartment of Medicine, College of Medicine, University of Arizona, 1501 N. Campbell Dr, Tucson, AZ 85724, United States; The University of Arizona Health Sciences Center, 1295 North Martin Ave, Tucson, AZ 85721, United States.
Michel BurtonDepartment of Biomedical and Health Information Sciences, College of Applied Health Sciences, University of Illinois at Chicago, 1919 W Taylor St., Chicago, IL 60612, United States.
Barbara Di EugenioDepartment of Computer Science, College of Engineering, University of Illinois at Chicago, 851 South Morgan Street, Chicago, IL 60607, United States.

Funding

A Biomedical Natural Language Processing ResourceR01LM008635 · NLM · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI FRIEDMAN, CAROL · 2005 to 2008
$2.1M
SCH: INT: MyPHA: Automatically generating personalized accounts of in-patient hospitalizationR01CA225446 · NCI · UNIVERSITY OF ILLINOIS AT CHICAGO · PI DI EUGENIO, BARBARA · 2018 to 2021
$1.5M
NCI NIH HHS R01 CA225446NLM NIH HHS R01 LM008635
6 · The paper itself

Abstract

backgroundPhysician and nurses have worked together for generations; however, their language and training are vastly different; comparing and contrasting their work and their joint impact on patient outcomes is difficult in light of this difference. At the same time, the EHR only includes the physician perspective via the physician-authored discharge summary, but not nurse documentation. Prior research in this area has focused on collaboration and the usage of similar terminology.

objectiveThe objective of the study is to gain insight into interprofessional care by developing a computational metric to identify similarities, related concepts and differences in physician and nurse work.

methods58 physician discharge summaries and the corresponding nurse plans of care were transformed into Unified Medical Language System (UMLS) Concept Unique Identifiers (CUIs). MedLEE, a Natural Language Processing (NLP) program, extracted "physician terms" from free-text physician summaries. The nursing plans of care were constructed using the HANDS

resultsWe found that only 26% of patients had synonyms (identical UMLS CUIs) between the two professions' documentation. On average, physicians' discharge summaries contain 27 terms and nurses' documentation, 18. Traversing the UMLS network, we found an average of 4 terms related (distance less than 2) between the professions, leaving most concepts as unrelated between nurse and physician care.

conclusionOur hypothesis that physician's and nurse's practice domains are markedly different is supported by the preliminary, quantitative evidence we found. Leveraging the UMLS network and graph traversal algorithms, allows us to compare and contrast nursing and physician care on a single patient, enabling a more complete picture of patient care. We can differentiate professional contributions to patient outcomes and related and divergent concepts by each profession.

Indexed as

AlgorithmsUnified Medical Language SystemDelivery of Health CareHumansNatural Language ProcessingPatient Care PlanningPractice Patterns, Nurses'Practice Patterns, Physicians'SoftwareHealth informaticsNursing documentationPhysician documentationProfessional discontinuityUMLS

Identifiers

PMID29602435
PMCPMC5909845

What OpenQuestion holds

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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.