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Objective Theory-based research of social and behavioral determinants of health (SBDH) found SBDH-related patterns in interventions and outcomes for pregnant/birthing people. The objectives of this study were to replicate the theory-based SBDH study with a new sample, and to compare these findings to a data-driven SBDH study. Materials and Methods Using deidentified public health nurse-generated Omaha System data, 2 SBDH indices were computed separately to create groups based on SBDH (0–5+ signs/symptoms). The data-driven SBDH index used multiple linear regression with backward elimination to identify SBDH factors. Changes in Knowledge, Behavior, and Status (KBS) outcomes, numbers of interventions, and adjusted R-squared statistics were computed for both models. Results There were 4109 clients ages 13–40 years. Outcome patterns aligned with the original research: KBS increased from admission to discharge with Knowledge improving the most; discharge KBS decreased as SBDH increased; and interventions increased as SBDH increased. Slopes of the data-driven model were steeper, showing clearer KBS trends for data-driven SBDH groups. The theory-based model adjusted R-squared was 0.54 (SE = 0.38) versus 0.61 (SE = 0.35) for the data-driven model with an entirely different set of SBDH factors. Conclusions The theory-based approach provided a framework to identity patterns and relationships and may be applied consistently across studies and populations. In contrast, the data-driven approach can provide insights based on novel patterns for a given dataset and reveal insights and relationships not predicted by existing theories. Data-driven methods may be an advantage if there is sufficiently comprehensive SBDH data upon which to create the data-driven models. [ABSTRACT FROM AUTHOR]

Nursing terminologies like the Omaha System are foundational in realizing the vision of formal representation of social determinants of health (SDOH) data and whole-person health across biological, behavioral, social, and environmental domains. This study objective was to examine standardized consumer-generated SDOH data and resilience (strengths) using the MyStrengths+MyHealth (MSMH) app built using Omaha System. Overall, 19 SDOH concepts were analyzed including 19 Strengths, 175 Challenges, and 76 Needs with additional analysis around Income Challenges. Data from 919 participants presented an average of 11(SD = 6.1) Strengths, 21(SD = 15.8) Challenges, and 15(SD = 14.9) Needs. Participants with at least one Income Challenge (n  = 573) had significantly (P  < .001) less Strengths [9.4(6.4)], more Challenges [27.4(15.5)], and more Needs [15.1(14.9)] compared to without an Income Challenge (n  = 337) Strengths [13.4(4.5)], Challenges [10.5(8.9)], and Needs [5.1(10.0)]. This standards-based approach to examining consumer-generated SDOH and resilience data presents a great opportunity in understanding 360-degree whole-person health as a step towards addressing health inequities. [ABSTRACT FROM AUTHOR]

Objective Numerous studies indicate that the social determinants of health (SDOH), conditions in which people work, play, and learn, account for 30%–55% of health outcomes. Many healthcare and social service organizations seek ways to collect, integrate, and address the SDOH. Informatics solutions such as standardized nursing terminologies may facilitate such goals. In this study, we compared one standardized nursing terminology, the Omaha System, in its consumer-facing form, Simplified Omaha System Terms (SOST), to social needs screening tools identified by the Social Interventions Research and Evaluation Network (SIREN). Materials and Methods Using standard mapping techniques, we mapped 286 items from 15 SDOH screening tools to 335 SOST challenges. The SOST assessment includes 42 concepts across 4 domains. We analyzed the mapping using descriptive statistics and data visualization techniques. Results Of the 286 social needs screening tools items, 282 (98.7%) mapped 429 times to 102 (30.7%) of the 335 SOST challenges from 26 concepts in all domains, most frequently from Income , Home , and Abuse. No single SIREN tool assessed all SDOH items. The 4 items not mapped were related to financial abuse and perceived quality of life. Discussion SOST taxonomically and comprehensively collects SDOH data compared to SIREN tools. This demonstrates the importance of implementing standardized terminologies to reduce ambiguity and ensure the shared meaning of data. Conclusions SOST could be used in clinical informatics solutions for interoperability and health information exchange, including SDOH. Further research is needed to examine consumer perspectives regarding SOST assessment compared to other social needs screening tools. [ABSTRACT FROM AUTHOR]

Objective This study aimed to identify phenotypes of nutritional needs of home-visited clients with low income, and compare overall changes in knowledge, behavior, and status of nutritional needs before and after home visits by identified phenotypes. Materials and methods Omaha System data collected by public health nurses from 2013 to 2018 were used in this secondary data analysis study. A total of 900 low-income clients were included in the analysis. Latent class analysis (LCA) was used to identify phenotypes of nutrition symptoms or signs. Score changes in knowledge, behavior, and status were compared by phenotype. Results The five subgroups included Unbalanced Diet, Overweight, Underweight, Hyperglycemia with Adherence, and Hyperglycemia without Adherence. Only the Unbalanced Diet and Underweight groups showed an increase in knowledge. No other changes in behavior and status were observed in any of the phenotypes. Discussion and conclusions This LCA using standardized Omaha System Public Health Nursing data allowed us to identify phenotypes of nutritional needs among home-visited clients with low income and prioritize nutrition areas that public health nurses may focus on as part of public health nursing interventions. The sub-optimal changes in knowledge, behavior, and status suggest a need to re-examine the intervention details by phenotype and develop strategies to tailor public health nursing interventions to effectively meet the diverse nutritional needs of home-visited clients. [ABSTRACT FROM AUTHOR]

Objective: To identify the risk factors home healthcare (HHC) clinicians associate with patient deterioration and understand how clinicians respond to and document these risk factors.Methods: We interviewed multidisciplinary HHC clinicians from January to March of 2021. Risk factors were mapped to standardized terminologies (eg, Omaha System). We used directed content analysis to identify risk factors for deterioration. We used inductive thematic analysis to understand HHC clinicians' response to risk factors and documentation of risk factors.Results: Fifteen HHC clinicians identified a total of 79 risk factors that were mapped to standardized terminologies. HHC clinicians most frequently responded to risk factors by communicating with the prescribing provider (86.7% of clinicians) or following up with patients and caregivers (86.7%). HHC clinicians stated that a majority of risk factors can be found in clinical notes (ie, care coordination (53.3%) or visit (46.7%)).Discussion: Clinicians acknowledged that social factors play a role in deterioration risk; but these factors are infrequently studied in HHC. While a majority of risk factors were represented in the Omaha System, additional terminologies are needed to comprehensively capture risk. Since most risk factors are documented in clinical notes, methods such as natural language processing are needed to extract them.Conclusion: This study engaged clinicians to understand risk for deterioration during HHC. The results of our study support the development of an early warning system by providing a comprehensive list of risk factors grounded in clinician expertize and mapped to standardized terminologies. [ABSTRACT FROM AUTHOR]