Representing and Retrieving Patients' Falls Risk Factors and Risk for Falls Among Adults in Acute Care Through the Electronic Health Record
Date of Award
Doctor of Philosophy
Laura Joosse, Julie Darmody, Timothy Patrick, Laura Burke, Norma Lang
Data, Electronic, Fall, Falls, Health, Warehouse
Defining fall risk factors and predicting fall risk status among patients in acute care has been a topic of research for decades. With increasing pressure on hospitals to provide quality care and prevent hospital-acquired conditions, the search for effective fall prevention interventions continues. Hundreds of risk factors for falls in acute care have been described in the literature. However, due to variations in the terms utilized to represent each fall risk factor, an effort to compare findings across settings and replicate research is hampered. As the expectations for the effective use of electronic health records increase, an opportunity exists to create infrastructure within clinical information systems, constructed with evidence-based knowledge and standardized terms, that will support interoperability between systems and enable comparative research. The purpose of this study is to identify to what extent selected fall risk factors and the problem, `risk for falls' are represented and retrievable, in patients' electronic health record, in one acute care setting. Specifically, this study sought to answer three questions: 1) How can the selected fall risk factors and the problem, `risk for falls' be represented through selected standardized terminologies? 2) How are the selected fall risk factors and problem, `risk for falls' represented in a clinical information system? and 3) Which of the selected fall risk factors and problem, `risk for falls' can be retrieved from the electronic health record? The study was guided by the Knowledge Based Nursing Initiative (KBNI) framework. The study was conducted at a local health system within the hospital division, utilizing electronic, patient clinical data. Five selected fall risk factors and the problem, `risk for falls,' were mapped to five standardized terminologies utilizing lexical matching. The terms mapped from the five terminologies were compared to the terms, located in discrete fields within the study site's clinical information system. In addition to SNOMED CT and ICD-9 CM terms, a mixture of vendor and site-specific terms that represented the problem, `risk for falls,' and the five selected fall risk factors were located in the study site's clinical information system. The mapped ICD-9 CM terms and fourteen of the twenty-two SNOMED CT terms were located in the `Problem List' and `Medical History' sections of the clinical information system, while the vendor and site-specific terms were located in `Orders,' `Nursing Flow Sheet,' and `Rehabilitation Flow Sheet' sections. Although both the ICD-9 CM and SNOMED CT terminologies were visible to the clinicians, one of the two mapped SNOMED CT terms representing the problem, `risk for falls,' and fourteen of the twenty-two mapped fall risk factors were not visible because they did not correspond to ICD-9 CM terms. Site-specific terms representing `cognitive impairment' and `impaired gait' were located in both the `Nursing Flow Sheet' and `Rehabilitation Flow Sheet' section. While the terms were lexically similar, the terms were not exact matches and the machine-readable codes differed.Data recorded in 995 episodes of care were retrieved from the electronic data warehouse for analysis. While the SNOMED CT terms were not available for retrieval from the electronic data warehouse, the ICD-9 CM, vendor, and site-specific terms were available. As there were not SNOMED CT terms available for retrieval from the electronic data warehouse, the representation of the problem, `risk for falls,' was not retrievable as a standardized term; however, it was retrieved as a Morse Fall Scale score of 40 or greater among 64.7% of the sample. The percentage of the five fall risk factors represented with the ICD-9 CM terms was lower than the percentage of fall risk factors represented with vendor and site-specific terms. While it is promising that two standardized terminologies have been embedded in the study site's system, limiting the SNOMED CT terms to those that have corresponding ICD-9 terms limits the representation of both the problem, `risk for falls,' and the five selected fall risk factors. It is recommended that hospital administrators embed standardized terminologies in their entirety to allow for adequate representation of terms. Accepting terminologies in their entirety would allow for interoperability between health systems and enable comparative research. Additionally, if vendor and site-specific terms are embedded, clinical information analysts in partnership with clinicians should assure that terms representing the same clinical data (e.g., disorientation), match across different sections of the clinical information system or a cross-mapping of those terms exist in order to support interoperability within the system.
Pfaff, Jann, "Representing and Retrieving Patients' Falls Risk Factors and Risk for Falls Among Adults in Acute Care Through the Electronic Health Record" (2013). Theses and Dissertations. 371.