Evidence map›Paper›PMID 30190252›Full record

ArticleJMIR research protocols2018

Individualized Clinical Practice Guidelines for Pressure Injury Management: Development of an Integrated Multi-Modal Biomedical Information Resource.

Kath M Bogie, Guo-Qiang Zhang, Steven K Roggenkamp, Ningzhou Zeng, Jacinta Seton, Shiqiang Tao, Arielle L Bloostein, Jiayang Sun

Open access · goldAbstract read
In one paragraph

Article in JMIR research protocols, 2018. 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
2.7field-weighted citation impact, top 10% 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, 13 citations in OpenAlex.

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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

8 authors at 3 institutions in 1 country.

Kath M BogieLouis Stokes Cleveland VA Medical Center, Cleveland, OH, United States.ORCID http://orcid.org/0000-0003-1020-9695
Guo-Qiang ZhangInstitute for Biomedical Informatics, University of Kentucky, Lexington, KY, United States.ORCID http://orcid.org/0000-0002-3663-1109
Steven K RoggenkampInstitute for Biomedical Informatics, University of Kentucky, Lexington, KY, United States.ORCID http://orcid.org/0000-0002-6773-0468
Ningzhou ZengInstitute for Biomedical Informatics, University of Kentucky, Lexington, KY, United States.ORCID http://orcid.org/0000-0001-9807-0004
Jacinta SetonLouis Stokes Cleveland VA Medical Center, Cleveland, OH, United States.ORCID http://orcid.org/0000-0001-5771-6294
Shiqiang TaoInstitute for Biomedical Informatics, University of Kentucky, Lexington, KY, United States.ORCID http://orcid.org/0000-0003-1515-3184
Arielle L BloosteinDepartment of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, United States.ORCID http://orcid.org/0000-0002-2658-3924
Jiayang SunDepartment of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, United States.ORCID http://orcid.org/0000-0002-0870-7014
University of Kentucky · USCase Western Reserve University · USLouis Stokes Cleveland VA Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPressure ulcers (PU) and deep tissue injuries (DTI), collectively known as pressure injuries are serious complications causing staggering costs and human suffering with over 200 reported risk factors from many domains. Primary pressure injury prevention seeks to prevent the first incidence, while secondary PU/DTI prevention aims to decrease chronic recurrence. Clinical practice guidelines (CPG) combine evidence-based practice and expert opinion to aid clinicians in the goal of achieving best practices for primary and secondary prevention. The correction of all risk factors can be both overwhelming and impractical to implement in clinical practice. There is a need to develop practical clinical tools to prioritize the multiple recommendations of CPG, but there is limited guidance on how to prioritize based on individual cases. Bioinformatics platforms enable data management to support clinical decision support and user-interface development for complex clinical challenges such as pressure injury prevention care planning.

objectiveThe central hypothesis of the study is that the individual's risk factor profile can provide the basis for adaptive, personalized care planning for PU prevention based on CPG prioritization. The study objective is to develop the Spinal Cord Injury Pressure Ulcer and Deep Tissue Injury (SCIPUD+) Resource to support personalized care planning for primary and secondary PU/DTI prevention.

methodsThe study is employing a retrospective electronic health record (EHR) chart review of over 75 factors known to be relevant for pressure injury risk in individuals with a spinal cord injury (SCI) and routinely recorded in the EHR. We also perform tissue health assessments of a selected sub-group. A systems approach is being used to develop and validate the SCIPUD+ Resource incorporating the many risk factor domains associated with PU/DTI primary and secondary prevention, ranging from the individual's environment to local tissue health. Our multiscale approach will leverage the strength of bioinformatics applied to an established national EHR system. A comprehensive model is being used to relate the primary outcome of interest (PU/DTI development) with over 75 PU/DTI risk factors using a retrospective chart review of 5000 individuals selected from the study cohort of more than 36,000 persons with SCI. A Spinal Cord Injury Pressure Ulcer and Deep Tissue Injury Ontology (SCIPUDO) is being developed to enable robust text-mining for data extraction from free-form notes.

resultsThe results from this study are pending.

conclusionsPU/DTI remains a highly significant source of morbidity for individuals with SCI. Personalized interactive care plans may decrease both initial PU formation and readmission rates for high-risk individuals. The project is using established EHR data to build a comprehensive, structured model of environmental, social and clinical pressure injury risk factors. The comprehensive SCIPUD+ health care tool will be used to relate the primary outcome of interest (pressure injury development) with covariates including environmental, social, clinical, personal and tissue health profiles as well as possible interactions among some of these covariates. The study will result in a validated tool for personalized implementation of CPG recommendations and has great potential to change the standard of care for PrI clinical practice by enabling clinicians to provide personalized application of CPG priorities tailored to the needs of each at-risk individual with SCI. REGISTERED REPORT IDENTIFIER: RR1-10.2196/10871.

Indexed as

bioinformaticselectronic health recordpressure injury

Identifiers

PMID30190252
PMCPMC6231753
OpenAlexW2809400677

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.