Evidence-based nursing practice: a call to action for nursing informatics

Cyborgs, biotechnologies, and informatics in health care - new paradigms in nursing sciences

Nursing Sciences are at a moment of paradigmatic transition. The aim of this paper is to reflect on the new epistemological paradigms of nursing science from a critical approach. In this paper, we identified and analysed some new research lines and trends which anticipate the reorganization of nursing sciences and the paradigms emerging from nursing care: biotechnology-centred knowledge; the interface between nursing knowledge and new information technologies; body care centred knowledge; the human body as a cyborg body; and the rediscovery of an aesthetic knowledge in nursing care.

Mapping a Nursing Terminology Subset to openEHR Archetypes. A Case Study of the International Classification for Nursing Practice

BACKGROUND

Healthcare information technologies have the potential to transform nursing care. However, healthcare information systems based on conventional software architecture are not semantically interoperable and have high maintenance costs. Health informatics standards, such as controlled terminologies, have been proposed to improve healthcare information systems, but their implementation in conventional software has not been enough to overcome the current challenge. Such obstacles could be removed by adopting a multilevel model-driven approach, such as the openEHR specifications, in nursing information systems.

OBJECTIVES

To create an openEHR archetype model for the Functional Status concepts as published in Nursing Outcome Indicators Catalog of the International Classification for Nursing Practice (NOIC-ICNP).

METHODS

Four methodological steps were followed: 1) extraction of terms from the NOIC-ICNP terminology; 2) identification of previously published openEHR archetypes; 3) assessment of the adequacy of those openEHR archetypes to represent the terms; and 4) development of new openEHR archetypes when required.

RESULTS

The "Barthel Index" archetype was retrieved and mapped to the 68 NOIC-ICNP Functional Status terms. There were 19 exact matches between a term and the correspondent archetype node and 23 archetype nodes that matched to one or more NOIC-INCP. No matches were found between the archetype and 14 of the NOIC-ICNP terms, and nine archetype nodes did not match any of the NOIC-ICNP terms.

CONCLUSIONS

The openEHR model was sufficient to represent the semantics of the Functional Status concept according to the NOIC-ICNP, but there were differences in data granularity between the terminology and the archetype, thus producing a significantly complex mapping, which could be difficult to implement in real healthcare information systems. However, despite the technological complexity, the present study demonstrated the feasibility of mapping nursing terminologies to openEHR archetypes, which emphasizes the importance of adopting the multilevel model-driven approach for the achievement of semantic interoperability between healthcare information systems.

The Translation Evidence Mechanism. The Compact between Researcher and Clinician

Currently, best evidence is a concentrated effort by researchers. Researchers produce information and expect that clinicians will implement their advances in improving patient care. However, difficulties exist in maximizing cooperation and coordination between the producers, facilitators, and users (patients) of best evidence outcomes. The Translational Evidence Mechanism is introduced to overcome these difficulties by forming a compact between researcher, clinician and patient. With this compact, best evidence may become an integral part of private practice when uncertainties arise in patient health status, treatments, and therapies. The mechanism is composed of an organization, central database, and decision algorithm. Communication between the translational evidence organization, clinicians and patients is through the electronic chart. Through the chart, clinical inquiries are made, patient data from provider assessments and practice cost schedules are collected and encrypted (HIPAA standards), then inputted into the central database. Outputs are made within a timeframe suitable to private practice and patient flow. The output consists of a clinical practice guideline that responds to the clinical inquiry with decision, utility and cost data (based on the “average patient”) for shared decision-making within informed consent. This shared decision-making allows for patients to “game” treatment scenarios using personal choice inputs. Accompanying the clinical practice guideline is a decision analysis that explains the optimized clinical decision. The resultant clinical decision is returned to the central database using the clinical practice guideline. The result is subsequently used to update current best evidence, indicate the need for new evidence, and analyze the changes made in best evidence implementation. When updates in knowledge occur, these are transmitted to the provider as alerts or flags through patient charts and other communication modalities.

The Translation Evidence Mechanism. The Compact between Researcher and Clinician

Currently, best evidence is a concentrated effort by researchers. Researchers produce information and expect that clinicians will implement their advances in improving patient care. However, difficulties exist in maximizing cooperation and coordination between the producers, facilitators, and users (patients) of best evidence outcomes. The Translational Evidence Mechanism is introduced to overcome these difficulties by forming a compact between researcher, clinician and patient. With this compact, best evidence may become an integral part of private practice when uncertainties arise in patient health status, treatments, and therapies. The mechanism is composed of an organization, central database, and decision algorithm. Communication between the translational evidence organization, clinicians and patients is through the electronic chart. Through the chart, clinical inquiries are made, patient data from provider assessments and practice cost schedules are collected and encrypted (HIPAA standards), then inputted into the central database. Outputs are made within a timeframe suitable to private practice and patient flow. The output consists of a clinical practice guideline that responds to the clinical inquiry with decision, utility and cost data (based on the "average patient") for shared decision-making within informed consent. This shared decision-making allows for patients to "game" treatment scenarios using personal choice inputs. Accompanying the clinical practice guideline is a decision analysis that explains the optimized clinical decision. The resultant clinical decision is returned to the central database using the clinical practice guideline. The result is subsequently used to update current best evidence, indicate the need for new evidence, and analyze the changes made in best evidence implementation. When updates in knowledge occur, these are transmitted to the provider as alerts or flags through patient charts and other communication modalities.

Transforming scientific evidence into better consumer choices

Translational research using evidence-based and comparative effectiveness research continues to evolve, becoming a useful tool in improving informed consent and decision-making in the clinical setting. While in development, emerging technologies, including cellular and molecular biology, are leading to establishing evidence-based dental practices. One emerging technology, which conjoins bench proteomic findings to clinical decision-making for treatment intervention, is the Translational Evidence Mechanism. This mechanism was developed to be a foundation for a compact between researcher, translational researcher, clinician, and patient. The output of such a mechanism is the clinical practice guideline (CPG), an interactive tool for dentists and patients to game evidence in reaching optimum clinical decisions that correspond to individual patient preferences and values. As such, the clinical practice guideline requires the vesting of decision, utility, and cost best evidence. Evidence-based research provides decision data, a first attempt at supporting decision-making by providing best outcome data. Since then comparative effectiveness research has emerged, using systematic review analysis to compare similar treatments or procedures in maximizing the choice of the most effective cost/benefit option within the context of best evidence. With innovation in the clinical practice guideline for optimizing efficacy and comparative effectiveness research, evidence-based practices will shape a new approach to health-based systems that adhere to shared decision-making between bench scientists, healthcare providers and patients.

The use of health technology and information: e-learning technological approach

The Internet is becoming the preferred place for finding information. Millions of people go online in search of health and medical information. Likewise, health care professionals must be able to retrieve and manage information in an efficient, effective manner. The development of health technology and informatics (HTI) has been rapid, yet little is known about the knowledge and attitudes of nursing students with regard to using HTI. Therefore, the objective of the present study was to explore nursing students' knowledge of and attitudes toward using HTI and to use an e-learning workshop to enhance the effective use of HTI. In Phase I, 115 first-year full-time nursing students were invited to complete a 13-item questionnaire regarding knowledge of and attitudes toward computer and Internet use, knowledge of HTI, and attitudes toward the future development of HTI. Participants perceived themselves to be knowledgeable in computer and Internet use, while knowledge of HTI was perceived to be low and attitudes toward the future development of HTI were generally positive. Phase II was an e-learning HTI workshop; topics included an introduction to HTI, examples of HTI in use, and the application and implementation of various HTI projects. There were 30 participants in the E-learning workshop, and their feedback was positive. Nurses and all health care professionals must be prepared to participate in the development of health technology and informatics. Teaching and learning activities should be geared toward mastery of HTI in the nursing education curriculum in order to enhance health care quality and safety.

Interdisciplinary resources optimize Evidence-Based Dental Practice

Evidence-Based Dental Practice (EBDP) is the most appropriate and best patient-centered care because it uses the evidence derived from interdisciplinary resources. These resources include the integration of the clinical and basic science researcher, clinician, and patient in the clinical decision-making process. Best evidence has different meanings to each of the interdisciplinary decision makers and, thus, defines their individual roles accordingly. Implementing EBDP requires an organizational structure and process that involve evidence-based dentistry databases in centralized repositories that are shared nationally and internationally. Facilitating the inclusive and reciprocal transfer of information from all resources requires use of information technology and computerized decision-making support programs. However, the potential lack of financial resources and incentives will diminish the universal adoption of EBDP.

A survey study of pediatric nurses' use of information sources

This survey study explored use of different information sources among a convenience sample of 113 bedside pediatric nurses. The study was guided by three interrelated concepts: types of information sources, levels of evidence, and computer skill. The Nursing Information Use Survey measured use of information sources, impact of information sources on nursing care, barriers to information, and expectations that a computerized clinical desktop or patient information management system would improve patient care. Significant correlations between use of interpersonal and non-computer-based information and non-computer- and computer-based information supported the conceptual model. Use of traditional, non-computer information sources such as textbooks and print-based journals was higher among baccalaureate, compared with diploma, prepared nurses. Nurses with greater computer and online searching skill used more computer-based information. Findings suggested that strategies to improve nurses' computer and information searching skills may promote use of higher-level evidence in planning nursing care.