Accession Number : AD1022099


Title :   Toward Personalized Pressure Ulcer Care Planning: Development of a Bioinformatics System for Individualized Prioritization of Clinical Pratice Guideline


Descriptive Note : Technical Report,30 Sep 2015,29 Sep 2016


Corporate Author : Cleveland VA Medical Research and Education Foundation Cleveland United States


Personal Author(s) : Bogie,Katherine


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/1022099.pdf


Report Date : 01 Oct 2016


Pagination or Media Count : 11


Abstract : Over 200 risk factors for pressure ulcer and deep tissue injury (PU/DTI) development have been reported spanning multiple domains Veterans with chronic spinal cord injury (SCI) have incidence rates as high as 62-80 and 34 will require at least three hospitalizations. PU/DTI may lead to other serious medical complications, such as osteomyelitis, sepsis and even death. Clinical practice guidelines (CPGs) aid clinicians in primary PU/DTI prevention through evidence based practice and expert opinion. However, there are many factors to consider and limited guidance on how to prioritize for individuals. Correction of all PU/DTI risk factors can be both overwhelming and impractical to implement in clinical practice. The relative importance of risk factors has not yet been investigated, limiting care planning and prioritization of interventions. The need to develop effective clinical tools to prioritize the multiple recommendations of CPG has been identified by experts in the field. We will use bioinformatics to enable data extraction, storage, and analysis to support clinical decision support and user-interface development for complex clinical challenges. Our central hypothesis is that the individuals risk factor profile can provide the basis for adaptive personalized PU prevention care planning based on CPG prioritization. The overall objective is to provide weighted systemic insight to PU risk in persons with SCI to support personalized care plans for primary and secondary PU prevention. The SCIPUD Resource will be developed using data sets extracted from VINCI together with cross-sectional study of tissue health profiles and validated using an observation cohort study.


Descriptors :   biomedical information systems , spinal cord , spinal injuries , decision aids , risk analysis , Preventive medicine , Tissues(Biology) , wounds and injuries , data mining


Distribution Statement : APPROVED FOR PUBLIC RELEASE