Lisiane Pruinelli

Brazilian validation of the nursing outcomes for acute pain

PURPOSE Validate the outcomes from the Nursing Outcomes Classification (NOC) for the Acute Pain nursing diagnosis. METHODS The content validation of the seven NOC outcomes and their respective indicators was performed using an adaptation of Fehrings model and was analyzed by descriptive statistics. FINDINGS Six were classified as critical and one was classified as supplemental. From the total of 118 indicators, 103 were validated. Of these, 27 were classified as critical and 76 as supplemental. CONCLUSIONS The use of the NOC is a viable alternative for the assessment and identification of best practices in nursing care. CLINICAL RELEVANCE Validation studies of nursing classifications corroborate the use of the component elements of these instruments in a variety of care settings.PURPOSE:  Validate the outcomes from the Nursing Outcomes Classification (NOC) for the Acute Pain nursing diagnosis. METHODS:  The content validation of the seven NOC outcomes and their respective indicators was performed using an adaptation of Fehrings model and was analyzed by descriptive statistics. FINDINGS:  Six were classified as critical and one was classified as supplemental. From the total of 118 indicators, 103 were validated. Of these, 27 were classified as critical and 76 as supplemental. CONCLUSIONS:  The use of the NOC is a viable alternative for the assessment and identification of best practices in nursing care. CLINICAL RELEVANCE:  Validation studies of nursing classifications corroborate the use of the component elements of these instruments in a variety of care settings.

Biomedical informatics advancing the national health agenda: the AMIA 2015 year-in-review in clinical and consumer informatics

The field of biomedical informatics experienced a productive 2015 in terms of research. In order to highlight the accomplishments of that research, elicit trends, and identify shortcomings at a macro level, a 19-person team conducted an extensive review of the literature in clinical and consumer informatics. The result of this process included a year-in-review presentation at the American Medical Informatics Association Annual Symposium and a written report (see supplemental data). Key findings are detailed in the report and summarized here. This article organizes the clinical and consumer health informatics research from 2015 under 3 themes: the electronic health record (EHR), the learning health system (LHS), and consumer engagement. Key findings include the following: (1) There are significant advances in establishing policies for EHR feature implementation, but increased interoperability is necessary for these to gain traction. (2) Decision support systems improve practice behaviors, but evidence of their impact on clinical outcomes is still lacking. (3) Progress in natural language processing (NLP) suggests that we are approaching but have not yet achieved truly interactive NLP systems. (4) Prediction models are becoming more robust but remain hampered by the lack of interoperable clinical data records. (5) Consumers can and will use mobile applications for improved engagement, yet EHR integration remains elusive.

Forensic Style Analysis with Survival Trajectories

Electronic Health Records (EHRs) consists of patient information such as demographics, medications, laboratory test results, diagnosis codes and procedures. Mining EHRs could lead to improvement in patient healthcare management as EHRs contain detailed information related to disease prognosis for large patient populations. We hypothesize that a patients condition does not deteriorate at random, the trajectories, sequences in which diseases appear in a patient, are determined by a finite number of underlying disease mechanisms. In this work, we exploit this idea by predicting a patients risk of mortality in the context of the metabolic syndrome by assessing which of many available trajectories a patient is following and progression along this trajectory. Implementing this idea required innovative enhancements both for the study design and also for the fitting algorithm. We propose a forensic-style study design, which aligns patients on last follow-up and measures time backwards. We modify the time-dependent covariate Cox proportional hazards model to better capture coefficients of covariate that follow a particular temporal sequence, such as trajectories. Knowledge extracted from such analysis can lead to personalized treatments, thereby forming the basis for future trajectory-centered guidelines.

Big data science: A literature review of nursing research exemplars

BACKGROUND Big data and cutting-edge analytic methods in nursing research challenge nurse scientists to extend the data sources and analytic methods used for discovering and translating knowledge. PURPOSE The purpose of this study was to identify, analyze, and synthesize exemplars of big data nursing research applied to practice and disseminated in key nursing informatics, general biomedical informatics, and nursing research journals. METHODS A literature review of studies published between 2009 and 2015. There were 650 journal articles identified in 17 key nursing informatics, general biomedical informatics, and nursing research journals in the Web of Science database. After screening for inclusion and exclusion criteria, 17 studies published in 18 articles were identified as big data nursing research applied to practice. DISCUSSION Nurses clearly are beginning to conduct big data research applied to practice. These studies represent multiple data sources and settings. Although numerous analytic methods were used, the fundamental issue remains to define the types of analyses consistent with big data analytic methods. CONCLUSION There are needs to increase the visibility of big data and data science research conducted by nurse scientists, further examine the use of state of the science in data analytics, and continue to expand the availability and use of a variety of scientific, governmental, and industry data resources. A major implication of this literature review is whether nursing faculty and preparation of future scientists (PhD programs) are prepared for big data and data science.

Biopolítica e doação de órgãos: estratégias e táticas da mídia no Brasil

This study aims to analyze the strategies and tactics that the Brazilian media links to constitute organ donor subjects. The corpus of analysis was a newspaper of wide national circulation that is considered the most influent of Brazil. This study is qualitative in nature with an exploratory approach and is associated with Cultural Studies in its post-structuralist slant, using tools proposed by Michael Foucault. The newspaper article analysis allows forms of power that establish truths about organ donation and what constitutes donor subjects to emerge. We consider that these speeches are seen as a biopolitical strategy that uses a tangle of tactics to conduct the population, revolving around the possibilities of organ donation. DESCRIPTORS: Communication media. Organ transplantation. Tissue donors. Organ donors. BIOPOLÍTICA Y DONACIÓN DE ÓRGANOS: ESTRATEGIAS Y TÁCTICAS DE LOS MEDIOS DE COMUNICACIÓN DE BRASIL RESUMEN: El estudio tiene como finalidad analizar las estrategias y tácticas que los medios de comunicación transmiten para constituir sujetos donantes de órganos. El corpus de análisis fue un periódico de circulación nacional, que es considerado el más influyente de Brasil. Es un estudio cualitativo con enfoque exploratorio, relacionado a los Estudios Culturales en su vertiente postestructuralista, basado en las herramientas ofrecidas por Michel Foucault. El análisis de los artículos del periódico indica formas de poder que establecen verdades sobre la donación de órganos. Creemos que esos discursos son vistos como una estrategia biopolítica que utiliza una red de tácticas para conducir la población, en torno de las posibilidades de donación de órganos. DESCRIPTORES: Medios de comunicación. Trasplantes de órganos. Donadores de tejido. Donadores de órganos. 675ABSTRACT: This study aims to analyze the strategies and tactics that the Brazilian media links to constitute organ donor subjects. The corpus of analysis was a newspaper of wide national circulation that is considered the most influent of Brazil. This study is qualitative in nature with an exploratory approach and is associated with Cultural Studies in its post-structuralist slant, using tools proposed by Michael Foucault. The newspaper article analysis allows forms of power that establish truths about organ donation and what constitutes donor subjects to emerge. We consider that these speeches are seen as a biopolitical strategy that uses a tangle of tactics to conduct the population, revolving around the possibilities of organ donation. DESCRIPTORS: Communication media. Organ transplantation. Tissue donors. Organ donors. BIOPOLITICA Y DONACION DE ORGANOS: ESTRATEGIAS Y TACTICAS DE LOS MEDIOS DE COMUNICACION DE BRASIL RESUMEN: El estudio tiene como finalidad analizar las estrategias y tacticas que los medios de comunicacion transmiten para constituir sujetos donantes de organos. El

Predictors of liver transplant patient survival: A critical review using a holistic framework

Objective: Liver transplantation is a costly and risky procedure, representing 25 050 procedures worldwide in 2013, with 6729 procedures performed in the United States in 2014. Considering the scarcity of organs and uncertainty regarding prognosis, limited studies address the variety of risk factors before transplantation that might contribute to predicting patient’s survival and therefore developing better models that address a holistic view of transplant patients. This critical review aimed to identify predictors of liver transplant patient survival included in large-scale studies and assess the gap in risk factors from a holistic approach using the Wellbeing Model and the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement. Data Source: Search of the Cumulative Index to Nursing and Allied Health Literature (CINAHL), Medline, and PubMed from the 1980s to July 2014. Study Selection: Original longitudinal large-scale studies, of 500 or more subjects, published in English, Spanish, or Portuguese, which described predictors of patient survival after deceased donor liver transplantation. Data Extraction: Predictors were extracted from 26 studies that met the inclusion criteria. Data Synthesis: Each article was reviewed and predictors were categorized using a holistic framework, the Wellbeing Model (health, community, environment, relationship, purpose, and security dimensions). Conclusions: The majority (69.7%) of the predictors represented the Wellbeing Model Health dimension. There were no predictors representing the Wellbeing Dimensions for purpose and relationship nor emotional, mental, and spiritual health. This review showed that there is rigorously conducted research of predictors of liver transplant survival; however, the reported significant results were inconsistent across studies, and further research is needed to examine liver transplantation from a whole-person perspective.

Modeling flowsheet data to support secondary use

The purpose of this study was to create information models from flowsheet data using a data-driven consensus-based method. Electronic health records contain a large volume of data about patient assessments and interventions captured in flowsheets that measure the same “thing,” but the names of these observations often differ, according to who performs documentation or the location of the service (eg, pulse rate in an intensive care, the emergency department, or a surgical unit documented by a nurse or therapist or captured by automated monitoring). Flowsheet data are challenging for secondary use because of the existence of multiple semantically equivalent measures representing the same concepts. Ten information models were created in this study: five related to quality measures (falls, pressure ulcers, venous thromboembolism, genitourinary system including catheter-associated urinary tract infection, and pain management) and five high-volume physiological systems: cardiac, gastrointestinal, musculoskeletal, respiratory, and expanded vital signs/anthropometrics. The value of the information models is that flowsheet data can be extracted and mapped for semantically comparable flowsheet measures from a clinical data repository regardless of the time frame, discipline, or setting in which documentation occurred. The 10 information models simplify the representation of the content in flowsheet data, reducing 1552 source measures to 557 concepts. The amount of representational reduction ranges from 3% for falls to 78% for the respiratory system. The information models provide a foundation for including nursing and interprofessional assessments and interventions in common data models, to support research within and across health systems.

Nursing Informatics Research Priorities for the Future: Recommendations from an International Survey.

We present one part of the results of an international survey exploring current and future nursing informatics (NI) research trends. The study was conducted by the International Medical Informatics Association Nursing Informatics Special Interest Group (IMIA-NISIG) Student Working Group. Based on findings from this cross-sectional study, we identified future NI research priorities. We used snowball sampling technique to reach respondents from academia and practice. Data were collected between August and September 2015. Altogether, 373 responses from 44 countries were analyzed. The identified top ten NI trends were big data science, standardized terminologies (clinical evaluation/implementation), education and competencies, clinical decision support, mobile health, usability, patient safety, data exchange and interoperability, patient engagement, and clinical quality measures. Acknowledging these research priorities can enhance successful future development of NI to better support clinicians and promote health internationally.

Current Trends in Nursing Informatics: Results of an International Survey.

Nursing informatics (NI) can help provide effective and safe healthcare. This study aimed to describe current research trends in NI. In the summer 2015, the IMIA-NI Students Working Group created and distributed an online international survey of the current NI trends. A total of 402 responses were submitted from 44 countries. We identified a top five NI research areas: standardized terminologies, mobile health, clinical decision support, patient safety and big data research. NI research funding was considered to be difficult to acquire by the respondents. Overall, current NI research on education, clinical practice, administration and theory is still scarce, with theory being the least common. Further research is needed to explain the impact of these trends and the needs from clinical practice.

Empirical evaluation of international health system data interoperability: Mapping the Wanda Horta theory to the Omaha System ontology

Structured health care data has played a critical role in improving quality of care and achieving better patient outcomes. Despite increased use of terminology standards within the electronic health records (EHRs), there is a need to map multi-institutional data that represent patient observations to develop standardized information models. The purpose of this study was to conduct an empirical evaluation of the potential for international health system data interoperability with the Wanda Horta theory using the Omaha System ontology. The 2 frameworks were mapped and validated by a panel of experts. The results showed that the majority (80.95%) of the Wanda Horta theory concepts were mapped at a high level of agreement. Such mappings show that the information models have the potential to facilitate and enhance communication and improve practices between organizations internationally.