Discovering Public Health Nurse–Specific Family Home Visiting Intervention Patterns Using Visualization Techniques

Abstract

Visualization is a Big Data method for detecting and validating previously unknown and hidden patterns within large data sets. This study used visualization techniques to discover and test novel patterns in public health nurse (PHN)-client-risk-intervention-outcome relationships. To understand the mechanism underlying risk reduction among high risk mothers, data representing complex social interventions were visualized in a series of three steps, and analyzed with other important contextual factors using standard descriptive and inferential statistics. Overall, client risk decreased after clients received personally tailored PHN services. Clinically important and unique PHN-client-risk-intervention-outcome patterns were discovered through pattern detection using streamgraphs, heat maps, and parallel coordinates techniques. Statistical evaluation validated that PHN intervention tailoring leads to improved client outcomes. The study demonstrates the importance of exploring data to discover ways to improve care quality and client outcomes. Further research is needed to examine additional factors that may influence PHN-client-risk-intervention-outcome patterns, and to test these methods with other data sets.

Feasibility of using the Omaha System to represent Nurse Coaching practice

“…The finding that the data from three case studies could be aggregated, analyzed, and interpreted demonstrates the value of using standardized terminology for Nc intervention documentation and aligns with previous research using large Omaha System datasets from acute care, home care, and family home visiting in the United States as well as globally [20][21][22][23][24][25][26]. This type of data is important for quality improvement, orientation in all three case studies, the Health care supervision problem was an essential focus of Nc practice and an important component in care planning that guided interventions.…”

“…it also supports interoperability, exchange, and re-use of Nc data for research and evaluation related to Nc care quality. There is also potential to use the Omaha System to capture assessment and outcome data for cost/benefit analysis [13,14,18,[20][21][22][23][24][25][26]. Defining Nc practices in documentation using the Omaha system can advance the quality of these practices in a consistent way.…”

Informatics and Artificial Intelligence Approaches that Promote Use of Integrative Health Therapies in Nursing Practice: A Scoping Review

“…These guidelines demonstrate how the Omaha System can be used to represent nursing IH therapies in a structured manner. With structured IH therapy data, a data-driven approach can be applied to evaluate the use and outcomes of nursing IH therapies for inspiring future research and informing clinical and policy decisions [28,29,36,37].…”

Relationships among interventions and health literacy outcomes for sub-populations: A data-driven approach

“…The nursing profession is well positioned to help alleviate health inequity by engaging in patient-centered health literacy practices to minimize negative outcomes associated with limited health literacy and improve the skill and abilities needed in complex health systems [7,9,[14][15][16]. Public health nursing data sources, using the Omaha System, have been used to highlight nursing interventions provided during home care visits [17][18][19]. A recent study revealed that home visits by public health nurses can improve health literacy [19].…”

“…Public health nursing data sources, using the Omaha System, have been used to highlight nursing interventions provided during home care visits [17][18][19]. A recent study revealed that home visits by public health nurses can improve health literacy [19].…”