Understanding tailored PHN interventions and outcomes of Latina mothers

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.

Impact of standardized nursing terminologies on patient and organizational outcomes: A systematic review and meta-analysis

AIMS

To explore the impact of 12 American Nurses Association recognized standardized nursing terminologies (SNTs) on patient and organizational outcomes.

BACKGROUND

Previous studies reported an effect of SNTs on outcomes, but no previous frameworks nor meta-analyses were found.

DESIGN

Systematic review and meta-analyses.

REVIEW METHODS

PubMed, Scopus, CINAHL, and OpenGrey databases were last consulted in July 2021. All abstracts and full texts were screened independently by two researchers. The review included primary quantitative studies that reported an association between recognized SNTs and outcomes. Two reviewers independently assessed the risk of bias and certainty of evidence for each meta-analyzed outcome using the "Grading of Recommendations, Assessment, Development and Evaluation" (GRADE) approach.

RESULTS

Fifty-three reports were included. NANDA-NIC-NOC and Omaha System were the most frequently reported SNTs used in the studies. Risk of bias in randomized controlled trials and not-randomized controlled trials ranged from high to unclear, this risk was low in cross-sectional studies. The number of nursing diagnoses NANDA-I moderately correlated with the intensive care unit length of stay (r = 0.38; 95% CI = 0.31-0.44). Using the Omaha System nurse-led transitional care program showed a large increase in both knowledge (d = 1.21; 95% CI = 0.97-1.44) and self-efficacy (d = 1.23; 95% CI = 0.97-1.48), while a reduction on the readmission rate (OR = 0.46; 95% CI = 0.09-0.83). Nursing diagnoses were found to be useful predictors for organizational (length of stay) and patients' outcomes (mortality, quality of life). The GRADE indicated that the certainty of evidence was rated from very low to low.

CONCLUSIONS

Studies using SNTs demonstrated significant improvement and prediction power in several patients' and organizational outcomes. Further high-quality research is required to increase the certainty of evidence of these relationships.

CLINICAL RELEVANCE

SNTs should be considered by healthcare policymakers to improve nursing care and as essential reporting data about patient's nursing complexity to guide reimbursement criteria.

Advantages and disadvantages of using theory-based versus data-driven models with social and behavioral determinants of health data

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.

Using Omaha System data to explore relationships between client outcomes, phenotypes, and targeted home intervention approaches: an exemplar examining practice effectiveness for older women with circulation problems

BACKGROUND

Improved health among older women remains elusive and may be linked to limited knowledge of and interventions targeted to population subgroups. Use of structured community nurse home visit data exploring relationships between client outcomes, phenotypes, and targeted intervention approaches may reveal new understandings of practice effectiveness.

MATERIALS AND METHODS

Omaha System data of 2363 women 65 years and older with circulation problems receiving at least 2 community nurse home visits were accessed. Previously identified phenotypes (Poor circulation; Irregular heart rate; and Limited symptoms), 7 intervention approaches (High-Surveillance; High-Teaching/Guidance/Counseling; Balanced-All; Balanced-Surveillance-Teaching/Guidance/Counseling; Low-Teaching/Guidance/Counseling-Balanced Other; Low-Surveillance-Mostly-Teaching/Guidance/Couseling-TreatmentProcedure-CaseManagement; and Mostly-TreatementProcedure+CaseManagement), and client knowledge, behavior, and status outcomes were used. Client-linked intervention approach counts, proportional use per phenotypes, and associations with client outcome scores were descriptively analyzed. Associations between intervention approach proportional use by phenotype and outcome scores were analyzed using parallel coordinate graph methodology for intervention approach effectiveness.

RESULTS

Percent use of intervention approach differed significantly by phenotype. The 2 most widely employed intervention approaches were characterized by either a high use of surveillance interventions or a balanced use of all intervention categories (surveillance, teaching/guidance/counseling, treatment-procedure, case-management). Mean outcome discharge and change scores significantly differed by intervention approach. Proportionally deployed intervention approach patterns by phenotype were associated with outcome small effects improvement.

DISCUSSIONS AND CONCLUSIONS

The Omaha System taxonomy supported the management and exploration of large multidimensional community nursing data of older women with circulation problems. This study offers a new way to examine intervention effectiveness using phenotype- and targeted intervention approach-informed structured data.

Public health nursing workforce and learning needs: A national sample survey analysis

OBJECTIVES

Generate national estimates of the public health nursing workforce's (1) demographic and work characteristics and (2) continuing education learning needs in the United States.

DESIGN

Secondary data analysis of the 2018 National Sample Survey of Registered Nurses.

SAMPLE

Total 7352 of the 50,273 survey respondents were categorized as public health nurses (PHNs), representing an estimated 467,271 national workforce.

MEASUREMENTS

Survey items for demographics, practice setting, training topics, and language(s) spoken fluently were analyzed.

RESULTS

Workforce demographic characteristics are included. Mental health training was the most frequently endorsed topic by PHNs, followed by patient-centered care and evidence-based care. Training topic needs vary by practice setting.

CONCLUSIONS

Results here can be used as a needs assessment for national public health nursing professional development and education initiatives. Further research is needed to refine and survey a nationally representative sample in a manner meaningful to public health nursing practice.

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).

Frailty and Social and Behavioral Determinants of Health: Algorithm Refinement and Pattern Validation

Existing frailty and social and behavioral determinants of health (SBDH) algorithms were refined and used to examine SBDH and frailty groups, revealing patterns in interventions and outcomes of older adults in a large community-based care data-set. The dataset was randomly split into training (n = 2,881) and testing (n = 1,441) sets. The training set was used to visually identify patterns in associations among SBDH, frailty, intervention doses, and outcomes, and the testing set was used to validate the patterns. Seven valid patterns were identified, showing increases in SBDH and frailty were associated with poorer health outcomes and more interventions (all p < 0.01). Findings suggest that the refined SBDH and frailty algorithms facilitate the identification of older adults with SBDH and frailty for intervention tailoring. [Journal of Gerontological Nursing, 48(4), 41-48.].

There's a Problem With the Problem List: Incongruence of Patient Problem Information Across the Home Care Admission

OBJECTIVES

Illustrate patterns of patient problem information received and documented across the home health care (HHC) admission process and offer practice, policy, and health information technology recommendations to improve information transfer.

DESIGN

Observational field study.

SETTING AND PARTICIPANTS

Three diverse HHC agencies using different commercial point-of-care electronic health records (EHRs). Six nurses per agency each admitted 2 patients (36 total).

METHODS

Researchers observed the admission process and photographed documents and EHR screens across 3 phases: referral, assessment, and plan of care (POC). To create a standardized data set, we mapped terms within medical diagnoses, signs, symptoms, and Problems to 5 of the 42 Omaha System Problem Classification Scheme problem terms. This created 180 problem pattern cases (5 problem patterns per patient).

RESULTS

Each pattern of problem information being present or absent was observed. In 52 cases (28.9%), a problem did not appear. In 36 cases (20%), the problem appeared in all 3 phases. In 46 cases (25.6%), the problem appeared in referral and/or assessment phases and not on the POC. Conversely, in 37 cases (20.5%), the problem appeared in referral or assessment phases and on the POC. In 9 cases (5%), the problem only appeared on the POC. Within the EHRs, there were no rationale fields to clarify including Problems or not and no problem status fields to identify active, resolved, or potential ones.

CONCLUSIONS AND IMPLICATIONS

Diagnosis or problem information transferred from the referral source or gathered during an in-home assessment did not appear in the POC. Because of the EHR structure, clinicians could not identify inactive problem or problem priority. Documentation or mapping of a structured problem list using a standardized interprofessional terminology such as the Omaha System coupled with identification of rationale could support the documentation of problem status and priority and reduce information loss.