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.

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.

Removing the roadblocks to promoting health equity: finding the social determinants of health addressed in standardized nursing classifications.

Providing 80% of healthcare worldwide, nurses focus on physiologic and psychosocial aspects of health, which incorporate social determinants of health (SDOH). Recognizing their important role in SDOH, nurse informatics scholars included standardized measurable terms that identify and treat issues with SDOH in their classification systems, which have been readily available for over 5 decades. In this Perspective, we assert these currently underutilized nursing classifications would add value to health outcomes and healthcare, and to the goal of decreasing disparities. To illustrate this, we mapped 3 rigorously developed and linked classifications: NANDA International (NANDA-I), Nursing Interventions Classification (NIC), and Nursing Outcomes Classification (NOC) called NNN (NANDA-I, NIC, NOC), to 5 Healthy People 2030 SDOH domains/objectives, revealing the comprehensiveness, usefulness, and value of these classifications. We found that all domains/objectives were addressed and NNN terms often mapped to multiple domains/objectives. Since SDOH, corresponding interventions and measurable outcomes are easily found in standardized nursing classifications (SNCs), more incorporation of SNCs into electronic health records should be occurring, and projects addressing SDOHs should integrate SNCs like NNN into their ongoing work.

Elaboration of a nursing record standard for an Emergency Care Unit.

OBJECTIVE: To develop a registration standard with diagnoses, outcomes and nursing interventions for an Emergency Care Unit. METHOD: This is applied research of technological development developed in three steps: elaboration of diagnoses/outcomes and interventions statements following the International Classification for Nursing Practice; assessment of diagnosis/outcome relevance; organization of diagnosis/outcome and interventions statements according to health needs described in TIPESC. RESULTS: A total of 185 diagnoses were prepared, of which 124 (67%) were constant in the classification, and 61 had no correspondence. Of the 185 diagnoses, 143 (77%) were rated as relevant by 32 experienced emergency room nurses, and 495 nursing interventions were correlated to diagnoses/outcomes. CONCLUSION: It was possible to build a record standard for the Emergency Care Unit following standardized terminology, containing diagnostic statements/outcomes and relevant interventions for nursing practice assessed by nurses with practice in emergency.

Comparison of SIREN social needs screening tools and Simplified Omaha System Terms: informing an informatics approach to social determinants of health assessments.

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.

Documentos psicológicos: um estudo comparativo das resoluções CFP n. º 006/2019 e CFP n. º 007/2003 / Psychological documents: a comparative study of resolutions CFP n. º 06/2019 and CFP n. º 07/2003 / Documentos psicológicos: un estudio comparativo entre las resoluciones CFP n. º 006/2019 y CFP n. º 007/2003

As resoluções emitidas pelo Sistema Conselhos são instrumentos essenciais de orientação e promoção de práticas éticas que denotem qualidade técnica no exercício profissional da Psicologia. Dada a complexidade que envolve a elaboração de documentos psicológicos, esta pesquisa teve como objetivo identificar as principais mudanças observadas no texto da recém-publicada Resolução CFP n.º 006/2019 quando comparada à Resolução CFP n.º 007/2003, ambas referidas à elaboração de documentos psicológicos. Trata-se de uma pesquisa descritiva-comparativa de abordagem qualitativa, que utilizou da análise de conteúdo no tratamento e interpretação dos dados oriundos de fonte exclusivamente documental. Os resultados indicaram poucas diferenças qualitativas entre os marcos resolutivos, embora se vislumbre altamente relevante o ganho adquirido com a proibição de escritos descritivos, a exigência de referencial teórico para fundamentar o raciocínio profissional e a obrigatoriedade da devolutiva documental. Entre os achados que ganham notoriedade consta a preocupação com os princípios que regem a elaboração de documentos, cuja apresentação tautológica responde a um cenário político de retrocessos que tem favorecido o desrespeito aos direitos humanos e às minorias.(AU)

Resolutions issued by Sistema Conselhos are essential tools to guide and promote ethical and quality psychology practices. Given the complexity involved in elaborating such documents, this descriptive, qualitative research outlines the main changes in the text of the recently published CFP Resolution no. 006/2019 when compared with CFP Resolution no. 007/2003, both addressing the elaboration of psychological documents. Documentary data was investigated by content analysis. Results indicated few qualitative differences between the analyzed Resolutions, among them the prohibition of descriptive writing, the requirement for a theoretical framework to support professional reasoning, and the obligation to return documents. Concern with the principles that guide document elaboration stands out, responding to a political scenario of major setbacks regarding respect for human rights and minorities.(AU)

Las resoluciones que expide el Sistema Conselhos consisten en instrumentos fundamentales que guían y promueven prácticas éticas respecto a la calidad técnica en el ejercicio profesional de la Psicología. Dada la complejidad que implica la elaboración de documentos psicológicos, esta investigación tuvo como objetivo identificar los principales cambios observados en la Resolución CFP n.º 006/2019, de reciente publicación, en comparación con la Resolución CFP n.º 007/2003, ambas abordan la elaboración de documentos psicológicos. Se trata de una investigación descriptiva-comparativa con enfoque cualitativo, que utilizó el análisis de contenido en el tratamiento e interpretación de datos de fuente exclusivamente documental. Los resultados indicaron pocas diferencias cualitativas entre los marcos resolutivos (aunque el logro de prohibir los escritos descriptivos es muy relevante), la exigencia de un marco teórico para sostener el razonamiento profesional y la devolución obligatoria de los documentos. Entre los hallazgos que cobran notoriedad está la preocupación por los principios que rigen la elaboración de documentos, cuya presentación tautológica responde a un escenario político de retrocesos que ha favorecido la falta de respeto a los derechos humanos y las minorías.(AU)

Comparative Assessment of Completeness of CDISC Controlled Terminology.

The CDISC Controlled Terminology (CT) defines the terms that may be used to represent clinical trial data in the CDISC standards. Despite its unique importance, there has been limited systematic examination of the coverage of this terminology. In this work, we performed an assessment of the completeness of CDISC CT's coverage by comparing clinical outcomes for multiple sclerosis (MS) available in CDISC CT with two independent high-fidelity benchmarks: (1) 71 expert-selected outcomes catalogued by the National Institute of Neurological Disorders and Stroke (NINDS), and, (2) 66 common outcomes used in MS trials registered on ClinicalTrials.gov (CTG). We employed a semi-automated search and term-mapping process to identify possible CDISC equivalents to the benchmarks' measures. We found that 55% of the NINDS outcomes and 52% of the CTG outcomes are absent from the CDISC Terminology, indicating a need for expanding the terminology to take into account other established standards and real-world practice.

Trends in Controlled Vocabulary and Health Equity.

Medical librarians collaborate with physicians and other healthcare professionals to improve the quality and accessibility of medical information, which includes assembling the best evidence to advance health equality through teaching and research. This column brings together brief cases highlighting the experiences and perspectives of medical librarians, educators, and healthcare professionals using their organizational, pedagogical, and information-analysis skills to advance health equality indexing.

Defining health data elements under the HL7 development framework for metadata management.

BACKGROUND: Health data from different specialties or domains generallly have diverse formats and meanings, which can cause semantic communication barriers when these data are exchanged among heterogeneous systems. As such, this study is intended to develop a national health concept data model (HCDM) and develop a corresponding system to facilitate healthcare data standardization and centralized metadata management. METHODS: Based on 55 data sets (4640 data items) from 7 health business domains in China, a bottom-up approach was employed to build the structure and metadata for HCDM by referencing HL7 RIM. According to ISO/IEC 11179, a top-down approach was used to develop and standardize the data elements. RESULTS: HCDM adopted three-level architecture of class, attribute and data type, and consisted of 6 classes and 15 sub-classes. Each class had a set of descriptive attributes and every attribute was assigned a data type. 100 initial data elements (DEs) were extracted from HCDM and 144 general DEs were derived from corresponding initial DEs. Domain DEs were transformed by specializing general DEs using 12 controlled vocabularies which developed from HL7 vocabularies and actual health demands. A model-based system was successfully established to evaluate and manage the NHDD. CONCLUSIONS: HCDM provided a unified metadata reference for multi-source data standardization and management. This approach of defining health data elements was a feasible solution in healthcare information standardization to enable healthcare interoperability in China.

Centers for Disease Control and Prevention 2019 novel coronavirus disease (COVID-19) information management: addressing national health-care and public health needs for standardized data definitions and codified vocabulary for data exchange.

OBJECTIVE: The 2019 novel coronavirus disease (COVID-19) outbreak progressed rapidly from a public health (PH) emergency of international concern (World Health Organization [WHO], 30 January 2020) to a pandemic (WHO, 11 March 2020). The declaration of a national emergency in the United States (13 March 2020) necessitated the addition and modification of terminology related to COVID-19 and development of the disease's case definition. During this period, the Centers for Disease Control and Prevention (CDC) and standard development organizations released guidance on data standards for reporting COVID-19 clinical encounters, laboratory results, cause-of-death certifications, and other surveillance processes for COVID-19 PH emergency operations. The CDC COVID-19 Information Management Repository was created to address the need for PH and health-care stakeholders at local and national levels to easily obtain access to comprehensive and up-to-date information management resources. MATERIALS AND METHODS: We introduce the clinical and health-care informatics community to the CDC COVID-19 Information Management Repository: a new, national COVID-19 information management tool. We provide a description of COVID-19 informatics resources, including data requirements for COVID-19 data reporting. RESULTS: We demonstrate the CDC COVID-19 Information Management Repository's categorization and management of critical COVID-19 informatics documentation and standards. We also describe COVID-19 data exchange standards, forms, and specifications. CONCLUSIONS: This information will be valuable to clinical and PH informaticians, epidemiologists, data analysts, standards developers and implementers, and information technology managers involved in the development of COVID-19 situational awareness and response reporting and analytics.

Discovering New Social Determinants of Health Concepts from Unstructured Data: Framework and Evaluation.

Social determinants of health (SDoH) are the complex set of circumstances in which individuals are born, or with which they live, that impact their health. Integrating SDoH into practice requires that information systems are able to identify SDoH-related concepts from charts and case notes through vocabularies or terminologies. Despite significant standardisation efforts across healthcare domains, SDoH coverage remains sparse in existing terminologies due to the broad spectrum of this domain, ranging from family relations, risk factors, to social programs and benefits, which are not consistently captured across administrative and clinical settings. This paper presents a framework to mine, evaluate and recommend new multidisciplinary concepts that relate to or impact the health and well-being of individuals using a word embedding model trained from a large dynamic corpus of unstructured data. Five key SDoH domains were selected and evaluated by domain experts. The concepts resulting from the trained model were matched against well-established meta-thesaurus UMLS and terminology SNOMED-CT and, overall, a significant proportion of concepts from a set of 10,000 candidates were not found (31% and 28% respectively). The results confirm both the gaps in current terminologies and the feasibility and impact of the methods presented in this paper for the incremental discovery and validation of new SDoH concepts together with domain experts. This sustainable approach facilitates the development and refinement of new and existing terminologies and, in turn, it allows systems such as Natural Language Processing (NLP) annotators to leverage SDoH concepts across integrated care settings.

The Role and Promise of Artificial Intelligence in Medical Toxicology.

Artificial intelligence (AI) refers to machines or software that process information and interact with the world as understanding beings. Examples of AI in medicine include the automated reading of chest X-rays and the detection of heart dysrhythmias from wearables. A key promise of AI is its potential to apply logical reasoning at the scale of data too vast for the human mind to comprehend. This scaling up of logical reasoning may allow clinicians to bring the entire breadth of current medical knowledge to bear on each patient in real time. It may also unearth otherwise unreachable knowledge in the attempt to integrate knowledge and research across disciplines. In this review, we discuss two complementary aspects of artificial intelligence: deep learning and knowledge representation. Deep learning recognizes and predicts patterns. Knowledge representation structures and interprets those patterns or predictions. We frame this review around how deep learning and knowledge representation might expand the reach of Poison Control Centers and enhance syndromic surveillance from social media.

Understanding tailored PHN interventions and outcomes of Latina mothers.

OBJECTIVE: To examine associations of data-driven intervention approaches (IAs) with the outcomes of adolescent or adult Latina mothers with or without the Mental health problem. DESIGN AND SAMPLE: Retrospective observational study using public health nurse (PHN)-generated data for 676 Latina mothers aged 14-52. MEASURES: Mothers' age, having the Mental health problem, number of problems and interventions, and Knowledge, Behavior, and Status scores using the Omaha System. Mother-specific percentages of interventions to the total number received were calculated. Visualizations and statistical tests were used to analyze the association of IAs relating mothers' characteristics, problems, interventions, and outcomes. RESULTS: Four IAs were discovered. Sample characteristics differed significantly among IAs by age and having the Mental health problems. There was a small effect of age on outcomes (<0.10). PHNs differentially addressed problems in IA1-IA4 compared with IA2-IA3 (p < 0.001). Mothers who received IA3 had the most improvement and highest scores in Knowledge and Behavior (all p < 0.001). Mothers who received IA2 had the most improvement and highest scores in Status (both p < 0.001). CONCLUSIONS: The IAs were associated with outcomes differentially among Latina mothers, depending on multiple complex factors. These methods may be useful in understanding intervention tailoring and should be replicated with other populations and datasets.

Using the Omaha System to determine health problems of urban Syrian immigrants.

OBJECTIVE(S): This study assessed the health problems of Syrian immigrants living in urban areas using the Omaha System. DESIGN: A descriptive and observational study was conducted in Istanbul. SAMPLE: The sample included 51 Syrian immigrant families and 248 Syrian refugees. MEASURES: Data were collected using the Omaha System-Problem Classification List and a sociodemographic questionnaire. RESULTS: The average household size was 6.36; 71% of those over the age of 18 were not employed. Only 8.5% of children aged 0-15 were vaccinated; 15 nursing problems and 46 signs and symptoms were diagnosed using the Problem Classification List scale. Personal care was the most frequently diagnosed problem, followed by Sanitation, Communication with community resources, Mental health, and Residence. CONCLUSIONS: Health and social problems are common Syrian immigrants living in urban areas. The Omaha System-Problem Classification List can be used as a tool by public health nurses to identify health problems encountered by immigrants.

Feasibility of describing community strengths relative to Omaha system concepts.

OBJECTIVES: The purpose was to determine the feasibility of using a standardized language, the Omaha System, to describe community-level strengths. The objectives were: (a) to evaluate the feasibility of using the Omaha System at the community level to reflect community strengths and (b) to describe preliminary results of community strengths observations across international settings. DESIGN AND SAMPLE: A descriptive qualitative design was used. The sample was a data set of 284 windshield surveys by nursing students in 5 countries: Mexico, New Zealand, Norway, Turkey, and the United States. MEASURES: An online survey included a checklist and open-ended questions on community strengths for 11 concepts of the Omaha System Problem Classification Scheme: Income, Sanitation, Residence, Neighborhood/workplace safety, Communication with community resources, Social contact, Interpersonal relationship, Spirituality, Nutrition, Substance use, and Health care supervision. Themes were derived through content analysis of responses to the open-ended questions. RESULTS: Feasibility was demonstrated: Students were able to use the Omaha System terms and collect data on strengths. Common themes were described among the five countries. CONCLUSIONS: The Omaha System appears to be useful in documenting community-level strengths. Themes and exemplar quotes provide a first step in developing operational definitions of strengths at a more granular level.

Development of an algorithm to link electronic health record prescriptions with pharmacy dispense claims.

Objective: Medication adherence is an important aspect of chronic disease management. Electronic health record (EHR) data are often not linked to dispensing data, limiting clinicians' understanding of which of their patients fill their medications, and how to tailor care appropriately. We aimed to develop an algorithm to link EHR prescribing to claims-based dispensing data and use the results to quantify how often patients with diabetes filled prescribed chronic disease medications. Materials and Methods: We developed an algorithm linking EHR prescribing data (RxNorm terminology) to claims-based dispensing data (NDC terminology), within sample of adult (19-64) community health center (CHC) patients with diabetes from a network of CHCs across 12 states. We demonstrate an application of the method by calculating dispense rates for a set of commonly prescribed diabetes and cardio-protective medications. To further inform clinical care, we computed adjusted odds ratios of dispense by patient-, encounter-, and clinic-level characteristics. Results: Seventy-six percent of cardio-protective medication prescriptions and 74% of diabetes medications were linked to a dispensing record. Age, income, ethnicity, insurance, assigned primary care provider, comorbidity, time on EHR, and clinic size were significantly associated with odds of dispensing. Discussion: EHR prescriptions and pharmacy dispense data can be linked at the record level across different terminologies. Dispensing rates in this low-income population with diabetes were similar to other populations. Conclusion: Record linkage resulted in the finding that CHC patients with diabetes largely had their chronic disease medications dispensed. Understanding factors associated with dispensing rates highlight barriers and opportunities for optimal disease management.

Diversity of indoor activities and economic development of neighborhoods.

Over the last few decades, public life has taken center stage in urban studies, but that is about to change. At times, indoor activities have been shown to matter more than what is publicly visible (they have been found to be more predictive of future crimes, for example). Until recently, however, data has not been available to study indoor activities at city scale. To that end, we propose a new methodology that relies on tagging information of geo-referenced pictures and unfolds in three main steps. First, we collected and classified a comprehensive set of activity-related words, creating the first dictionary of urban activities. Second, for both London and New York City, we collected geo-referenced Flickr tags and matched them with the words in the dictionary. This step produced both a systematic classification (our activity-related words were best classified in eleven categories) and two city-wide indoor activity maps which, when compared to open data of public amenities and sensory maps of smell and sound matched theoretical expectations. Third, we studied, for the first time, activities happening indoor in relation to neighborhood socio-economic conditions. We found the very same result for both London and New York City. In deprived areas, people focused on any of the activity types (leading to specialization), and it did not matter on which one they did so. By contrast, in well-to-do areas, people engaged not in one type of activity but in a variety of them (leading to diversification).

Clinical Concept Value Sets and Interoperability in Health Data Analytics.

This paper focuses on value sets as an essential component in the health analytics ecosystem. We discuss shared repositories of reusable value sets and offer recommendations for their further development and adoption. In order to motivate these contributions, we explain how value sets fit into specific analytic tasks and the health analytics landscape more broadly; their growing importance and ubiquity with the advent of Common Data Models, Distributed Research Networks, and the availability of higher order, reusable analytic resources like electronic phenotypes and electronic clinical quality measures; the formidable barriers to value set reuse; and our introduction of a concept-agnostic orientation to vocabulary collections. The costs of ad hoc value set management and the benefits of value set reuse are described or implied throughout. Our standards, infrastructure, and design recommendations are not systematic or comprehensive but invite further work to support value set reuse for health analytics. The views represented in the paper do not necessarily represent the views of the institutions or of all the co-authors.