Abstract
Background: Pressure 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.
Objective: The 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.
Methods: The 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.
Results: The results from this study are pending.
Conclusions: PU/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.
Document Type
Article
Publication Date
9-6-2018
Digital Object Identifier (DOI)
https://doi.org/10.2196/10871
Funding Information
This project has been supported by funding from the Congressionally Directed Medical Research Programs (CDMRP) Spinal Cord Injury Research Program (Grant #: W81XWH-15-1-0342).
Repository Citation
Bogie, Kathie M.; Zhang, Guo-Qiang; Roggenkamp, Steven K.; Zeng, Ningzhou; Seton, Jacinta; Tao, Shiqiang; Bloostein, Arielle L.; and Sun, Jiayang, "Individualized Clinical Practice Guidelines for Pressure Injury Management: Development of an Integrated Multi-Modal Biomedical Information Resource" (2018). Institute for Biomedical Informatics Faculty Publications. 9.
https://uknowledge.uky.edu/bmi_facpub/9
Notes/Citation Information
Published in JMIR Research Protocols, v. 7, issue 9, e10871, p. 1-11.
©Kath M Bogie, Guo-Qiang Zhang, Steven K Roggenkamp, Ningzhou Zeng, Jacinta Seton, Shiqiang Tao, Arielle L Bloostein, Jiayang Sun. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 06.09.2018.
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