Movement through motherhood: Exploring mood, wellbeing, and prenatal emotional availability (EA) through EA-based dance intervention.

Emotional availability (EA) is a construct that describes the observed emotional connection in parent-child relationships. During pregnancy, EA is assessed only using caregiver sensitivity and nonhostility. We used the nonverbal aspects of these qualities to create a new dance/movement intervention ("EA-Based Dance Intervention"). Given the scarcity of pregnancy interventions, we provided training to participants on how to be emotionally engaged with their unborn babies through dance/movement. The EA-Based Dance Intervention alone comprised the first intervention arm (n = 12). A second intervention arm involved the combination of EA-Based Dance Intervention with brief psychoeducation (n = 10). The third arm was a control group, which received only the assessments (n = 7). Measures of self-reported symptoms of depression and anxiety, emotional expressivity, flourishing, and the (newly developed) self-reported prenatal EA were used at pre- and posttest. The measure of observed prenatal EA was used to compare intervention versus control at posttest only. In this pilot study, we found that participants receiving the EA-Based Dance Intervention alone or combined with psychoeducation, self-reported improved anxiety symptoms and self-reported higher prenatal EA. When compared with the control group, those experiencing EA-Based Dance Intervention reported fewer depressive symptoms from pre- to posttest.

La disponibilidad emocional (EA) es una construcción que describe la observada conexión emocional en las relaciones entre progenitor y niño. Durante el embarazo, EA se evalúa solamente usando la sensibilidad y el nivel de no hostilidad de quien presta el cuidado. Usamos los aspectos no verbales de estas cualidades para crear una nueva intervención de baile/movimiento ("Intervención de Baile con Base en la Disponibilidad Emocional"). Dada la escasez de intervenciones de embarazo, les ofrecimos entrenamiento a las participantes en cuanto a cómo interactuar emocionalmente con sus bebés no nacidos por medio del baile/movimiento. La Intervención de Baile con Base en la Disponibilidad Emocional abarca por sí sola el primer grupo o brazo de la intervención (n = 12). Un segundo grupo o brazo de intervención incluyó la combinación de la Intervención de Baile con Base en la Disponibilidad Emocional con psicoeducación breve (n = 10). El tercer grupo o brazo de intervención fue un grupo de control, el cual sólo recibió las evaluaciones (n = 7). Anterior y posteriormente a la prueba, se usaron medidas de auto reportados síntomas de depresión y ansiedad, de expresividad emocional, de mejorar y salir adelante, y la (recién desarrollada) EA prenatal auto reportada. La medida de EA prenatal observada se usó para comparar los grupos de intervención vs. de control sólo con posterioridad a la prueba. En este estudio piloto, encontramos que las participantes que recibían la Intervención de Baile con Base en la Disponibilidad Emocional solamente o combinada con psicoeducación, auto reportaron mejoras en los síntomas de ansiedad y auto reportaron una EA prenatal más alta. Cuando se les comparó con el grupo de control, quienes experimentaban la Intervención de Baile con Base en la Disponibilidad Emocional reportaron menos síntomas depresivos desde antes hasta después de la prueba.

Mother-Child and Father-Child Emotional Availability during the COVID-19 Pandemic.

While the body of literature on COVID-19's impacts on family life is rapidly expanding, most studies are based entirely on self-report data, leaving a critical gap in observational studies of parent-child interactions. The goal of this study was to evaluate parent-child relationships during the COVID-19 pandemic using the observational emotional availability (EA) construct. Parents (n = 43) were assessed using the Epidemic-Pandemic Impacts Inventory (EPII), the Flourishing Scale (FLS), and the adverse childhood experiences (ACEs) questionnaires. The subcategories of the EPII were used to develop an EPII negative and an EPII positive for each parent. EA (sensitivity, structuring, nonhostility, nonintrusiveness, child responsiveness, and child involvement) was coded from filmed parent-child interactions. Separate hierarchical multiple regressions (HMRs) were run to evaluate each of the variables of interest (EPII and FLS) as predictive of EA. Child age (M = 6, SD = 4.68) and ACEs were added in subsequent steps for EPII negative and positive if the initial step was significant. For mothers (n = 25), results demonstrated EPII negative as a significant predictor of EA with child age and ACEs adding only small amount of variance to the prediction. The same HMR process was repeated for flourishing, with the covariate child age alone. For fathers (n = 18), flourishing was a significant predictor of EA and child age added only a small amount of variance to the prediction. Results indicate that experiencing high COVID-19-related stressors is associated with lower EA for mothers, but not fathers. Having high levels of flourishing during the pandemic was predictive of higher EA for fathers, but not mothers.

One-Way and Round-Trip Analysis Demonstrates Surprising Limitations of Standards-Based Terminology Maps.

The informatics community has a long-standing vision of freely flowing and highly re-usable patient-specific clinical data that improves care quality and safety. We sought to evaluate the extent to which a standards-based mapping approach is sufficient to support semantic interoperability. We simulated large-scale clinical data transmission and measured semantic success between VA and DoD systems via one-way testing (OWT) and round-trip testing (RTT). Simulations were accomplished via SQL queries and production standards-based maps for medications, allergens, document titles, vitals and payers. Success rates for mapping local codes to national standards varied from 62.5% for DoD document titles and medications, to 100% for VA and DoD vital signs. Successful, one-way testing was considerably lower, ranging from 8.52% to 62.7%. Round-trip success rates were lower still, ranging from 1.7% to 76.3%. We present an error framework, lessons learned, and proposed mitigating steps to enhance standards-based semantic interoperability.

Interoperability of Medication Classification Systems: Lessons Learned Mapping Established Pharmacologic Classes (EPCs) to SNOMED CT.

Interoperability among medication classification systems is known to be limited. We investigated the mapping of the Established Pharmacologic Classes (EPCs) to SNOMED CT. We compared lexical and instance-based methods to an expert-reviewed reference standard to evaluate contributions of these methods. Of the 543 EPCs, 284 had an equivalent SNOMED CT class, 205 were more specific, and 54 could not be mapped. Precision, recall, and F1 score were 0.416, 0.620, and 0.498 for lexical mapping and 0.616, 0.504, and 0.554 for instance-based mapping. Each automatic method has strengths, weaknesses, and unique contributions in mapping between medication classification systems. In our experience, it was beneficial to consider the mapping provided by both automated methods for identifying potential matches, gaps, inconsistencies, and opportunities for quality improvement between classifications. However, manual review by subject matter experts is still needed to select the most relevant mappings.

Drug knowledge expressed as computable semantic triples.

The majority of questions that arise in the practice of medicine relate to drug information. Additionally, adverse reactions account for as many as 98,000 deaths per year in the United States. Adverse drug reactions account for a significant portion of those errors. Many authors believe that clinical decision support associated with computerized physician order entry has the potential to decrease this adverse drug event rate. This decision support requires knowledge to drive the process. One important and rich source of drug knowledge is the DailyMed product labels. In this project we used computationally extracted SNOMED CT™ codified data associated with each section of each product label as input to a rules engine that created computable assertional knowledge in the form of semantic triples. These are expressed in the form of "Drug" HasIndication "SNOMED CT™". The information density of drug labels is deep, broad and quite substantial. By providing a computable form of this information content from drug labels we make these important axioms (facts) more accessible to computer programs designed to support improved care.

Role of the odontologist in the investigation of domestic violence, neglect of the vulnerable, and institutional violence and torture.

Dentists have a significant role to identify and intervene in domestic abuse, violence, and neglect of the vulnerable. Over 75% of abuse victims have injuries to the head, face, mouth, and neck and so dentists are often first responders. However, under recognition and under reporting of domestic abuse and violence is a particular problem among health care providers, including dentists. Forensic odontologists are well suited to lead the training of their clinical colleagues in the various cultural determinants to abuse, including etiology, symptoms, physical signs of abuse, as well as appropriate reporting. In addition to leading their colleagues, forensic odontologists play an essential role as part of multidisciplinary teams that investigate conflict situations, serious crimes, exploitation of disadvantaged populations, and other serious violence and abuse. Whether in conflict zones or within private families, early detection and intervention is important to prevent establishment of abusive social and family patterns that perpetuate a "cycle of violence". This is especially true in young children, the most vulnerable population of all. To support this theory of early and effective intervention, this paper comprehensively reviews the most recent evidence concerning the etiology, detection, and prevention of violence and abuse.

Exchange of computable patient data between the Department of Veterans Affairs (VA) and the Department of Defense (DoD): terminology mediation strategy.

Complete patient health information that is available where and when it is needed is essential to providers and patients and improves healthcare quality and patient safety. VA and DoD have built on their previous experience in patient data exchange to establish data standards and terminology services to enable real-time bi-directional computable (i.e., encoded) data exchange and achieve semantic interoperability in compliance with recommended national standards and the eGov initiative. The project uses RxNorm, UMLS, and SNOMED CT terminology standards to mediate codified pharmacy and allergy data with greater than 92 and 60 percent success rates respectively. Implementation of the project has been well received by users and is being expanded to multiple joint care sites. Stable and mature standards, mediation strategies, and a close relationship between healthcare institutions and Standards Development Organizations are recommended to achieve and maintain semantic interoperability in a clinical setting.

Use of RxNorm to exchange codified drug allergy information between Department of Veterans Affairs (VA) and Department of Defense (DoD).

Under a congressional mandate, VA and DoD have built a framework to exchange standardized, codified patient drug allergy information through a mediation terminology. Initially, the Unified Medical Language System (UMLS) was deemed to be the most appropriate translator. After both agency files were mapped to UMLS, DoD could understand 45 percent of VA's mapped terms and VA could understand 26 percent of DoD's mapped terms. A significant portion of the non-mediated information was brand names in DoD with generic counterparts in VA. Recently, a Consolidated Health Informatics (CHI) group designated RxNorm as the standard for trade name allergies. An analysis was conducted to estimate mediation improvement using RxNorm. Both agency files were re-mapped to RxNorm. By utilizing the RxNorm defined relationships between brand names and generics and between variants of therapeutic moieties , DoD will understand 74 percent of VA terms and VA will understand 58 percent of DoD terms.

Model-driven CDA Clinical Document Development Framework.

The Health Level 7 (HL7) Clinical Document Architecture, Release 2 (CDA R2) standardizes the structure and semantics of clinical documents in order to permit interchange. We have applied this standard to generate a platform independent CDA model and write a toolset that permits model specialization, generation of XML implementation artifacts, and provides an interface for clinical data managers. The resulting work was tested using US Department of Veterans Affairs Operative Note templates.

Direct comparison of MEDCIN and SNOMED CT for representation of a general medical evaluation template.

BACKGROUND: Two candidate terminologies to support entry of general medical data are SNOMED CT and MEDCIN. We compare the ability of SNOMED CT and MEDCIN to represent concepts and interface terms from a VA general medical examination template. METHODS: We parsed the VA general medical evaluation template and mapped the resulting expressions into SNOMED CT and MEDCIN. Internists conducted double independent reviews on 864 expressions. Exact concept level matches were used to evaluate reference coverage. Exact term level matches were required for interface terms. RESULTS: Sensitivity of SNOMED CT as a reference terminology was 83% vs. 25% for MEDCIN (p<0.001). The sensitivity of SNOMED CT as an interface terminology was 53% vs. 7% for MEDCIN (P< 0.001). DISCUSSION: The content coverage of SNOMED CT as a reference terminology and as an interface terminology outperformed MEDCIN. We did not evaluate other aspects of interface terminologies such as richness of clinical linkages.

A simple strategy for implementing standard reference terminologies in a distributed healthcare delivery system with minimal impact to existing applications.

The Veterans Administration (VA) has adopted an ambitious program to standardize its clinical terminology to comply with industry-wide standards. The VA is using commercially available tools and in-house software to create a high-quality reference terminology system. The terminology will be used by current and future applications with no planned disruption to operational systems. The first large customer of the group is the national VA Health Data Repository (HDR). Unique enterprise identifiers are assigned to each standard term, and a rich network of semantic relationships makes the resulting data not only recognizable, but highly computable and reusable in a variety of applications, including decision support and data sharing with partners such as the Department of Defense (DoD). This paper describes the specific methods and approaches that the VA has employed to develop and implement this innovative program in existing information system. The goal is to share with others our experience with key issues that face our industry as we move toward an electronic health record for every individual.

Categorical information in pharmaceutical terminologies.

Drug information sources use category labels to assist in navigating and organizing information. Some category labels describe drugs from multiple perspectives (e.g., both structure and function). The National Drug File - Reference Terminology (NDF RT) is a drug information source that augments a "legacy" categorization system with a formal reference model specifying Chemical Structure, Cellular or Sub-Cellular Mechanism of Action, Organ- or System-Level Physiological Effect, and Therapeutic Intent categories. We examined drug category names from three sources to better understand their information content and evaluate NDF RT's semantic coverage. On average, category names contain more than 1.5 attributes. NDF RT's reference model covers more than 76% of the information identified in drug category labels. A new NDF RT reference axis of drug formulations could improve NDF RT's coverage to 85%. The distinction between Physiological Effect and Therapeutic Intent, prompted many questions among category reviewers, suggesting that further clarification of these reference concepts is required. Careful review of existing categorization schemes may guide structured terminology and ontology development efforts toward greater fidelity to deployed information sources.

U.S. Department of Veterans Affairs Enterprise Reference Terminology strategic overview.

The Veterans Health Affairs (VHA) branch of the Department of Veterans Affairs has undertaken an Enterprise Reference Terminology (ERT). VHA, arguably the largest integrated healthcare provider in the United States, has completely computerized virtually all clinical transactions, including physician orders and documentation. The VA is now integrating its clinical records across hundreds of sites of care by means of a Health Data Repository (HDR) project. ERT has been designed to provide a terminology development environment, terminology services, and maintenance services for the clinical and business content in HDR and other VHA applications. Drug, laboratory observations, and clinical document title files have been developed, and the ERT will encompass all HDR domains by 2008. Commercial tools are used to host the VHA's ERT terminology development and server environments. We will select and adopt both open-source and licensable terminology systems to provide ERT content, as well as reuse existing VA-specific terminology content.

VA National Drug File Reference Terminology: a cross-institutional content coverage study.

BACKGROUND: Content coverage studies provide valuable information to potential users of terminologies. We detail the VA National Drug File Reference Terminology's (NDF-RT) ability to represent dictated medication list phrases from the Mayo Clinic. NDF-RT is a description logic-based resource created to support clinical operations at one of the largest healthcare providers in the US. METHODS: Medication list phrases were extracted from dictated patient notes from the Mayo Clinic. Algorithmic mappings to NDF-RT using the SmartAccess Vocabulary Server (SAVS) were presented to two non-VA physicians. The physicians used a terminology browser to determine the accuracy of the algorithmic mapping and the content coverage of NDF-RT. RESULTS: The 509 extracted documents on 300 patients contained 847 medication concepts in medication lists. NDF-RT covered 97.8% of concepts. Of the 18 phrases that NDF-RT did not represent, 10 were for OTC's and food supplements, 5 were for prescription medications, and 3 were missing synonyms. The SAVS engine properly mapped 773 of 810 phrases with an overall sensitivity (precision) was 95.4% and positive predictive value (recall) of 99.9%. CONCLUSIONS: This study demonstrates that NDF-RT has more general utility than its initial design parameters dictated

Evaluation of SNOMED coverage of Veterans Health Administration terms.

Veterans Health Administration (VHA) is now evaluating use of SNOMED-CT. This paper reports the first phase of this evaluation, which examines the coverage of SNOMED-CT for problem list entries. Clinician expressions in VA problem lists are quite diverse compared to the content of the current VA terminology Lexicon. We selected a random set of 5054 narratives that were previously "unresolved" against the Lexicon. These narratives were mapped to SNOMED-CT using two automated tools. Experts reviewed a subset of the tools' matched, partly matched, and un-matched narratives. The automated tools produced exact or partial matches for over 90% of the 5054 unresolved narratives. SNOMED-CT has promise as a coding system for clinical problems. In subsequent studies, VA will examine the coverage of SNOMED for other clinical domains, such as drugs, allergies, and physician orders.

Data representation in healthcare: a design for a freely-available openly-developed international reference terminology for healthcare.

The importance of data representation in healthcare has been of concern for centuries. In the last fifty years there has been an increasing awareness of the need for formal representations of terminological systems. We propose that terminological system development should be consensus driven and the product of iterative open refinement in order to practically serve the needs of the healthcare community. The system of development and maintenance of such a system must involve recruitment of the best and the brightest in the medical community to take responsibility for insuring the accuracy and completeness of such an effort. We suggest a method for algorithmically building a starting point for such a reference terminology. Further we suggest a distributed authoring environment that would allow domain experts to contribute regardless of their location or language. Open intellectual contribution is the necessary ingredient for a consensus based international health reference terminology.

Dentists' qualifications affect the accuracy of radiographic identification.

This study assessed the effects of forensic odontologists' training and experience upon the accuracy of their dental radiographic identifications. Forty participating odontologists with various levels of training and experience completed a Web-based survey of their qualifications and then completed nine Web-based radiographic identification cases. They made their identifications using the American Board of Forensic Odontology Categories and Terminology for Body Identification. The results indicate that odontologists with high levels of training and experience performed significantly more accurately than those with lower levels. We conclude that high levels of training and experience in forensic odontology should be developed, maintained, and required of dentists who participate in a forensic team dealing with challenging identification cases.

A formal representation for messages containing compositional expressions.

Clinically useful controlled vocabularies should represent healthcare concepts completely and with high reliability. Anticipating and pre-coordinating all possible expressions (e.g. 'fracture of the left femur' and 'fracture of the right femur') is not feasible. Variation in practice styles, requirements for the granularity of content, the exponential growth of terminology size, and increased cost of maintaining pre-coordinated terminologies lead us to conclude that no enumerated terminology can ever be truly comprehensive. Compositional terminologies are one potential solution to the problem of content completeness, but carry a risk of generating expressions whose equivalency cannot be easily determined. In order for post-coordinated expressions to be comparable, a sufficiently detailed formal mechanism for information representation is necessary. Comparable data for post-coordinated expressions requires normalization of both the contents and the semantics of the contents of the terminology with the information captured in post-coordinated expressions. In addition, comparable data requires a storage and messaging paradigm robust enough to faithfully represent the information contained within arbitrarily complex compositional expressions. We present a formalism for storing, and sending messages containing compositional expressions using a large-scale reference terminology. It is our intent that this formalism be used to algorithmically determine whether or not messages contain comparable data. In addition, we advocate transmitting the upward transitive closure of subsumption of all concepts, to improve comparability of data and to decrease reliance on locally stored versions of the underlying reference terminology.

VistA--U.S. Department of Veterans Affairs national-scale HIS.

The Veterans Health Administration of the U.S. Department of Veterans Affairs has a long, successful, and interesting history of using information technology to meet its mission. Each medical center is computerized to a degree that surprises the uninitiated. For example, medical documentation and ordering are computerized at every facility. A sophisticated national infrastructure has been developed to replicate, support, and evolve single-center successes. With advances in inter-facility networking, data sharing, and specialized central support and technical tools, VistA is becoming a single, highly scalable national health information system (HIS) solution. In this paper, we present an historical overview of VistA's development, describe its current functionality, and discuss its emergence as a national-scale hospital information system.