RESUMO
BACKGROUND: During COVID pandemic response, an early signal was desired beyond typical financial classifications or order sets. The foundational work of Virginia K Saba informed the essential, symbiotic relationship of nursing practice and resource utilization by means of the Clinical Care Classification System [CCC]. Scholars have confirmed the use of the CCC as the structure for data modeling, focusing on the concept of nursing cost [1]. Therefore, the purpose of this retrospective, descriptive study was to determine if analysis of CCC Care Component codes could provide a high granularity signal of early shifts in patient demographics and in nursing care interventions and to, then, determine if nursing care intervention shifts indicated changes in resource utilization. METHODS: For a large multi-facility healthcare system in the USA, patients cared for in an acute care setting/hospital-based care unit were the population of interest. Through prior and ongoing efforts of ensuring Evidenced-Based Clinical Documentation [EBCD], a data model was utilized to determine changes in the patient's nursing diagnoses, nursing interventions, during care episodes, for patients with acute symptoms or diagnosed/confirmed COVID. RESULTS: The structure of CCC revealed 22 billion individual instances of the CCC Care Component/Concept codes for the data sets for 2017 and during COVID, a considerably large data set suitable for pre- and post- event analyses. The component codes were included in a string data set for concept/diagnosis/intervention. DISCUSSION: By our analysis, these CCC Information Model elements determined a clear ability to detect increasing demands of nursing and resources, prior to other data models, including supply chain data, provider documented diagnostic codes, or laboratory test codes. Therefore, we conclude CCC System structure and Nursing Intervention codes allow for earlier detection of pandemic care nursing resource demands, despite the perceived challenges of "timeliness of documentation" attributed to more constrained timelines of data models of nursing care.
