Comparison of Weighting Methods to Understand Improved Outcomes Attributable to Public Health Nursing Interventions.

BACKGROUND: The complex work of public health nurses (PHNs) specifically related to mental health assessment, intervention, and outcomes, makes it difficult to quantify and evaluate the improvement in client outcomes attributable to their interventions. OBJECTIVES: We examined heterogeneity across parents of infants served by PHNs receiving different interventions; compared the ability of traditional propensity scoring methods versus energy balancing weight techniques to adjust for the complex and stark differences in baseline characteristics among those receiving different interventions; and evaluated the causal effects of the quantity and variety of PHN interventions on client health and social outcomes. METHODS: This retrospective study of 4,109 clients used existing Omaha System data generated during the routine documentation of PHN home visit data. We estimated the effects of intervention by computing and comparing weighted averages of the outcomes within the different treatment groups using two weighting methods: (a) inverse probability of treatment (propensity score) weighting and (b) energy balancing weights (EBWs). RESULTS: Clients served by PHNs differed in baseline characteristics with clients with more signs/symptoms. Both weighting methods reduced heterogeneity in the sample. EBWs were more effective than inverse probability of treatment weighting in adjusting for multifaceted confounding and resulted in close balance of 105 baseline characteristics. Weighting the sample changed outcome patterns, especially when using energy-balancing weights. Clients who received more PHN interventions and a wider variety of them had improved knowledge, behavior, and status outcomes with no plateau over time, whereas the unweighted sample showed plateaus in outcomes over the course of home visiting services. DISCUSSION: Causal analysis of PHN-generated data demonstrated PHN intervention effectiveness for clients with mental health signs/symptoms. EBWs are a promising tool for evaluating the true causal effect of PHN home-visiting interventions.

Examining Resilient Pain Behaviors for Chronic Low Back Pain: A Scoping Review.

OBJECTIVES: The objective of this scoping review was to examine resilience and resilient pain behaviors for those with CLBP in relation to resilience definitions, operationalization (e.g. trait or behavior), and application of theoretical frameworks. DESIGN: This scoping review examined resilience and resilient pain behaviors for those with CLBP in relation to resilience definitions, operationalization (e.g. trait or behavior), and application of theoretical frameworks. DATA SOURCES: To gather data, we used five databases: Cumulative Index to Nursing and Allied Health Literature (CINAHL), Embase, Ovid MEDLINE, PsycInfo, and Scopus. REVIEW/ANALYSIS METHODS: Authors used a systematic data charting spreadsheet (Microsoft Excel) to review and analyze the extracted data. RESULTS: A total of 26 articles, from 2011-2021, were included in the final analysis. A majority of articles were conducted in the United States (11) and cross-sectional secondary data analysis design (13). Resilience definitions varied across the studies. Three studies operationalized resilience as a trait and only one as a behavior. Most studies (20) did not include a theoretical framework. CONCLUSION: The majority cross-sectional design and heterogeneity of a resilience definition indicates resilience research is still emerging. The lack of operationalized resilience, specifically as a behavior, and the limited use of theoretical frameworks suggest advancements in resilience pain research are needed. NURSING PRACTICE IMPLICATIONS: This research has implications for nursing practice to support nurse's holistic perspective and the ability to incorporate resilience within nursing care. This research provides the initial steps to developing standard resilience definitions and frameworks to guide nursing practice.

A Systematic Review of Nurses' Perceptions of Electronic Health Record Usability Based on the Human Factor Goals of Satisfaction, Performance, and Safety.

The poor usability of electronic health records contributes to increased nurses' workload, workarounds, and potential threats to patient safety. Understanding nurses' perceptions of electronic health record usability and incorporating human factors engineering principles are essential for improving electronic health records and aligning them with nursing workflows. This review aimed to synthesize studies focused on nurses' perceived electronic health record usability and categorize the findings in alignment with three human factor goals: satisfaction, performance, and safety. This systematic review was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analysis. Five hundred forty-nine studies were identified from January 2009 to June 2023. Twenty-one studies were included in this review. The majority of the studies utilized reliable and validated questionnaires (n = 15) to capture the viewpoints of hospital-based nurses (n = 20). When categorizing usability-related findings according to the goals of good human factor design, namely, improving satisfaction, performance, and safety, studies used performance-related measures most. Only four studies measured safety-related aspects of electronic health record usability. Electronic health record redesign is necessary to improve nurses' perceptions of electronic health record usability, but future efforts should systematically address all three goals of good human factor design.

Using data visualization to characterize whole-person health of public health nurses.

OBJECTIVE: To characterize patterns in whole-person health of public health nurses (PHNs). DESIGN AND SAMPLE: Survey of a convenience sample of PHNs (n = 132) in 2022. PHNs self-identified as female (96.2%), white (86.4%), between the ages 25-44 (54.5%) and 45-64 (40.2%), had bachelor's degrees (65.9%) and incomes of $50-75,000 (30.3%) and $75-100,000/year (29.5%). MEASUREMENTS: Simplified Omaha System Terms (SOST) within the MyStrengths+MyHealth assessment of whole-person health (strengths, challenges, and needs) across Environmental, Psychosocial, Physiological, and Health-related Behaviors domains. RESULTS: PHNs had more strengths than challenges; and more challenges than needs. Four patterns were discovered: (1) inverse relationship between strengths and challenges/needs; (2) Many strengths; (3) High needs in Income; (4) Fewest strengths in Sleeping, Emotions, Nutrition, and Exercise. PHNs with Income as a strength (n = 79) had more strengths (t = 5.570, p < .001); fewer challenges (t = -5.270, p < .001) and needs (t = -3.659, p < .001) compared to others (n = 53). CONCLUSIONS: PHNs had many strengths compared to previous research with other samples, despite concerning patterns of challenges and needs. Most PHN whole-person health patterns aligned with previous literature. Further research is needed to validate and extend these findings toward improving PHN health.

Critical consciousness of public health nurses: A descriptive, comparative survey.

BACKGROUND: Public Health Nurses (PHN) caring for vulnerable populations amid systemic inequality must navigate complex situations, and consequently they may experience serious moral distress known to be detrimental to PHN wellbeing. OBJECTIVE: Given PHN awareness of social inequities, the study aimed to determine if PHNs were motivated to enact social change and engage in social and political action to address inequality. DESIGN AND SAMPLE: A survey of 173 PHNs was conducted in fall 2022. The convenience sample was mainly female (96.5%), White (85%), had associate/bachelor's degrees (71.7%), and worked in governmental public health settings (70.7%). MEASURE: The study employed the Short Critical Consciousness Scales' subscales: Critical Reflection, Critical Motivation, and Critical Action. RESULTS: PHNs were highly motivated to address inequities (Critical Motivation = 20.83; SD = 3.16), with similarly high awareness (Critical Reflection = 17.89; SD = 5.18). However, social and political action scores were much lower (Critical Action = 7.13; SD = 2.63). A subgroup of PHNs with strong agreement regarding the impact of poverty were more likely to be younger (p = .039) and work in a community setting (p = .003); with higher scores across subscales (p < .001). CONCLUSIONS: High critical reflection and motivation among PHNs aligned with literature. Lower Critical Action scores warrant investigation into validity for PHNs, and possible role constraints.

Algorithm development to improve intervention effectiveness for parents with mental health signs and symptoms.

OBJECTIVES: In this study we aimed to describe and compare groups formed by a rules-based algorithm to prospectively identify clients at risk of poor outcomes in order to guide tailored public health nursing (PHN) intervention approaches. DESIGN: Data-driven methods using standardized Omaha System PHN documentation. SAMPLE: Clients ages 13-40 who received PHN home visiting services for both the Caretaking/parenting and Mental health problems (N = 4109). MEASUREMENT: We applied a theory-based algorithm consisting of six rules using existing Omaha System data. We examined the groups formed by the algorithm using standard descriptive, inferential statistics, and Latent Class Analysis. RESULTS: Clients (N = 4109) were 25.1 (SD = 5.9) years old and had an average of 7.3 (SD = 3.2) problems, 250 (SD = 319) total interventions, and 32 (SD = 44) Mental health interventions. Overall outcomes improved after PHN interventions (p < .001 for all) and having more Mental health signs/symptoms was negatively associated with outcome scores (p < .001 for all). CONCLUSIONS: This algorithm may be helpful in identifying high-risk clients during a baseline assessment who may benefit from more intensive mental health interventions. Findings show there is value using the Omaha System for PHN documentation and algorithm clinical decision support development. Future research should focus on algorithm implementation in PHN clinical practice.

Public Health Nurse Tailored Home Visiting and Parenting Behavior for Families at Risk for Referral to Child Welfare Services, Colorado: 2018-2019.

Objectives. To examine public health nurse (PHN) intervention tailoring through the Colorado Nurse Support Program (NSP). Our 2 specific aims were to describe the NSP program and its outcomes and to determine the effects of modifying interventions on short- and long-term outcomes among NSP clients. Methods. In our retrospective causal investigation of 150 families in Colorado in 2018-2019, intervention effects were modeled via longitudinal modified treatment policy analyses. Results. Families served by PHNs improved in terms of knowledge, behavior, and status outcomes after receiving multidimensional, tailored home visiting interventions. Case management interventions provided in the first month of PHN home visits had lasting effects on behavior outcomes, and 2 additional case management interventions in the first month were estimated to have even more of an impact. Conclusions. Modern causal inference methods and real-world PHN data revealed a nuanced, fine-grained understanding of the real impact of tailored PHN interventions. Public Health Implications PHN programs such as the NSP and use of the Omaha System should be supported and extended to advance evaluations of intervention effectiveness and knowledge discovery and improve population health. (Am J Public Health. 2022;112(S3):S306-S313. https://doi.org/10.2105/AJPH.2022.306792).

Using data visualization to detect patterns in whole-person health data.

Data visualization techniques are useful for examining large multidimensional data sets. In this exploratory data analysis (EDA) study, we applied a visualization pattern detection and testing process to deidentified data to discover patterns in whole-person health for adults 65 and older. Whole-person health examines a person's environmental, psychosocial, and physical health, as well as their health-related behaviors; and assesses their strengths, challenges, and needs. Strengths are defined as assets and capabilities in the face of short-or long-term stressors. We collected data using a mobile application that delivers a comprehensive whole-person assessment using a simplified version of a standardized instrument, the Omaha System. The visualization pattern detection process is iterative, includes various techniques, and requires visualization literacy. The data visualization techniques applied in this analysis included bubble charts, parallel coordinates line graphs, box plots, and alluvial flow diagrams. We discovered six patterns within the visualizations. We formulated and tested six hypotheses based on these six patterns, and all six hypotheses were supported. Adults 65 and older had more strengths than challenges and more challenges than needs (p < 0.001). Strengths and challenges were negatively correlated (p < 0.001). Unexpectedly, a subset of adults 65 and older who had many, but not all, strengths had significantly more needs (p = 0.04). The use of standardized terminology with its inherent data interrelationships was key to discovering patterns in whole-person health. This methodology may be used in future EDA research using new data sets.

Exploring Large Community- and Clinically-Generated Datasets to Understand Resilience Before and During the COVID-19 Pandemic.

PURPOSE: To explore resilience in the context of whole-person health and the social determinants of health at the individual and community levels using large, standardized nursing datasets. DESIGN: A retrospective, observational, correlational study of existing deidentified Health Insurance Portability and Accountability Act (HIPAA)-compliant data using the Omaha System and its equivalent, Simplified Omaha System Terms. METHODS: We used three samples to explore for patterns of resilience: pre-COVID-19 community-generated data (N = 383), pre-COVID-19 clinical documentation data (N = 50,509), and during-COVID-19 community-generated data (N = 102). Community participants used the My Strengths + My Health (MSMH) app to generate the two community datasets. The clinical data were obtained from the Omaha System Data Collaborative. We operationalized resilience as Omaha System Status scores of 4 (minimal signs or symptoms) or 5 (no signs or symptoms) as a discrete strengths measure for each of 42 Omaha System problem concepts. We used visualization techniques and standard descriptive and inferential statistics for analysis. FINDINGS: It was feasible to examine resilience, operationalized as strengths by problem concept, within existing Omaha System or Simplified Omaha System Terms (MSMH) data. We identified several patterns indicating strengths and resilience that were consistent with literature related to community connectedness for community participants, and sleep for individuals in the clinical data. CONCLUSIONS: When used consistently, the Omaha System within MSMH enabled robust data collection for a comprehensive, holistic assessment, resulting in better whole-person data including strengths, and enabled us to discover a potentially useful approach for defining resilience in new ways using standardized nursing data. CLINICAL RELEVANCE: The notion that how we assess individuals and communities (i.e., the completeness of our assessments in relation to whole-person health) determines what we can know about resilience is seemingly in opposition to the critical need to decrease documentation burden, despite the potential to shift from a problem deficit-based assessment to one of strengths and resilience. However, a patient-facing comprehensive assessment that includes resilience and the social determinants of health can provide a transformative, whole-person platform for strengths-based care and population management.

Understanding Women's Cardiovascular Health Using MyStrengths+MyHealth: A Patient-Generated Data Visualization Study of Strengths, Challenges, and Needs Differences.

PURPOSE: The purpose of this data visualization study was to identify patterns in patient-generated health data (PGHD) of women with and without Circulation signs or symptoms. Specific aims were to (a) visualize and interpret relationships among strengths, challenges, and needs of women with and without Circulation signs or symptoms; (b) generate hypotheses based on these patterns; and (c) test hypotheses generated in Aim 2. DESIGN: The design of this visualization study was retrospective, observational, case controlled, and exploratory. METHODS: We used existing de-identified PGHD from a mobile health application, MyStrengths+MyHealth (N = 383). From the data, women identified with Circulation signs or symptoms (n = 80) were matched to an equal number of women without Circulation signs or symptoms. Data were analyzed using data visualization techniques and descriptive and inferential statistics. FINDINGS: Based on the patterns, we generated nine hypotheses, of which four were supported. Visualization and interpretation of relationships revealed that women without Circulation signs or symptoms compared to women with Circulation signs or symptoms had more strengths, challenges, and needs-specifically, strengths in connecting; challenges in emotions, vision, and health care; and needs related to info and guidance. CONCLUSIONS: This study suggests that visualization of whole-person health including strengths, challenges, and needs enabled detection and testing of new health patterns. Some findings were unexpected, and perspectives of the patient would not have been detected without PGHD, which should be valued and sought. Such data may support improved clinical interactions as well as policies for standardization of PGHD as sharable and comparable data across clinical and community settings. CLINICAL RELEVANCE: Standardization of patient-generated whole-person health data enabled clinically relevant research that included the patients' perspective.

Incorporating a Whole-Person Perspective in Consumer-Generated Data: Social Determinants, Resilience, and Hidden Patterns.

Given the complex health and social needs of older adults, the rapid growth of the aging population, and the increasing use of information technology in healthcare, there is a critical need for informatics solutions that advance gerontological nursing care and knowledge discovery. This article illustrates the value of standardized data for healthcare quality improvement throughout the life cycle of data capture and reuse. One such informatics solution is the MyStrengths+MyHealth app, which incorporates a whole-person perspective through the Simplified Omaha System Terms assessment, including the social and behavioral determinants of health, as well as resilience. The data describe whole-person health of older adults from MyStrengths+MyHealth for use in clinical encounters and as raw data for research. There is potential to use such standardized data to improve gerontological nursing care at the bedside and for population health management and research.

Evaluating Systemized Nomenclature of Medicine Clinical Terms Coverage of Complementary and Integrative Health Therapy Approaches Used Within Integrative Nursing, Health, and Medicine.

The use of complementary and integrative health therapy strategies for a wide variety of health conditions is increasing and is rapidly becoming mainstream. However, little is known about how or if complementary and integrative health therapies are represented in the EHR. Standardized terminologies provide an organizing structure for health information that enable EHR representation and support shareable and comparable data; which may contribute to increased understanding of which therapies are being used for whom and for what purposes. Use of standardized terminologies is recommended for interoperable clinical data to support sharable, comparable data to enable the use of complementary and integrative health therapies and to enable research on outcomes. In this study, complementary and integrative health therapy terms were extracted from multiple sources and organized using the National Center for Complementary and Integrative Health and former National Center for Complementary and Alternative Medicine classification structures. A total of 1209 complementary and integrative health therapy terms were extracted. After removing duplicates, the final term list was generated via expert consensus. The final list included 578 terms, and these terms were mapped to Systemized Nomenclature of Medicine Clinical Terms. Of the 578, approximately half (48.1%) were found within Systemized Nomenclature of Medicine Clinical Terms. Levels of specificity of terms differed between National Center for Complementary and Integrative Health and National Center for Complementary and Alternative Medicine classification structures and Systemized Nomenclature of Medicine Clinical Terms. Future studies should focus on the terms not mapped to Systemized Nomenclature of Medicine Clinical Terms (51.9%), to formally submit terms for inclusion in Systemized Nomenclature of Medicine Clinical Terms, toward leveraging the data generated by use of these terms to determine associations among treatments and outcomes.

Examining standardized consumer-generated social determinants of health and resilience data supported by Omaha System terminology.

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.