Electronic Method for Measuring Nursing: Workload Action Measures Method (WAMM).

The Workload Action Measures Method (WAMM) is a predictive model of care workload for individual patients. DESIGN: The Clinical Care Classification Information Model quantifies nursing workload combining two aspects of nursing practice by measuring a patient's specific nursing service time using relative value units and a patient's disease condition using the intensity of four Healthcare Patterns/Care Components. RESULTS: WAMM provides reliable workload calculations for disease conditions combined with Nursing Interventions Actions.

Point of Care Solutions for Electronic Documentation of Nursing Practice.

The panel focuses on Point-of-Care (POC) solutions for the documentation of nursing practice in electronic health record (EHR) and/or healthcare information technology (HIT) systems using the Clinical Care Classification (CCC) System. The CCC System was developed by Dr. Saba and Colleagues for the electronic documentation of patient care by nurses and allied health professionals and has been approved by American Nurses Association and U.S. Department of Health and Human Services as an interoperable, standardized nursing terminology The unique POC solutions will be described by different nursing informaticians, designers, and implementers who will describe how they document patient care using the CCC System and their impact on care outcomes. Also the Nursing Informatics (NI) Experts will discuss the effects of POC solutions on care quality and safety, as well as highlight how the data analytics are used to measure and predict workload, staffing, and cost. They will also describe how the information is used to support evidence-based practice and advance nursing knowledge. LEARNING OBJECTIVES: 1) Understand POC solutions using a standardized, coded, nursing terminology based on its Information Model for the e-documentation of nursing practice; 2) Describe the CCC System impacts on care quality, safety, and outcomes as well as measure workload, staffing, and cost. 3) Highlight how POC solutions'data analytics support evidenced-based practice and advance nursing science.

Harmonising Nursing Terminologies Using a Conceptual Framework.

The International Classification for Nursing Practice (ICNP®) and the Clinical Care Classification (CCC) System are standardised nursing terminologies that identify discrete elements of nursing practice, including nursing diagnoses, interventions, and outcomes. While CCC uses a conceptual framework or model with 21 Care Components to classify these elements, ICNP, built on a formal Web Ontology Language (OWL) description logic foundation, uses a logical hierarchical framework that is useful for computing and maintenance of ICNP. Since the logical framework of ICNP may not always align with the needs of nursing practice, an informal framework may be a more useful organisational tool to represent nursing content. The purpose of this study was to classify ICNP nursing diagnoses using the 21 Care Components of the CCC as a conceptual framework to facilitate usability and inter-operability of nursing diagnoses in electronic health records. Findings resulted in all 521 ICNP diagnoses being assigned to one of the 21 CCC Care Components. Further research is needed to validate the resulting product of this study with practitioners and develop recommendations for improvement of both terminologies.

Milestones and Experiences of Standardized Documentation.

The purpose of this panel is to discuss milestones and experiences of a standardized nursing terminology for the documentation of nursing practice using Clinical Care Classification as an example. The aim is to describe the value of using the CCC as the standardized nursing terminology and framework for the multidisciplinary care plans and how its interoperability with SNOMED CT, LOINC, and other required terminologies can be used for the electronic health record systems. Further the aim is to discuss the advantages a multidisciplinary documentation system and how it impacts on nursing practice, management, and research as well as highlight the monitoring of nursing documentation. The target audience will enrich their understanding about the possibilities that a standardized multidisciplinary documentation is critical for future data analyses and datamining highlighting nursing practices.

Harmonizing Nursing Terminologies.

In this paper, the authors report on a study aimed at harmonising two nursing terminologies, the Clinical Care Classification (CCC) and the International Classification for Nursing Practice (ICNP®). As the electronic health record evolves and the need for interoperability extends beyond local and national borders, a degree of standardisation across healthcare terminologies become essential. Harmonising across terminologies results in a) increased consensus relating to domain content and b) improvements in the terminologies involved. Findings from this study suggest that there is much overlap of content in nursing terminologies. The continued harmonisation between nursing terminologies and other healthcare terminologies are recommended to achieve international interoperability.

A pilot study to explore the feasibility of using theClinical Care Classification System for developing a reliable costing method for nursing services.

While nursing activities represent a significant proportion of inpatient care, there are no reliable methods for determining nursing costs based on the actual services provided by the nursing staff. Capture of data to support accurate measurement and reporting on the cost of nursing services is fundamental to effective resource utilization. Adopting standard terminologies that support tracking both the quality and the cost of care could reduce the data entry burden on direct care providers. This pilot study evaluated the feasibility of using a standardized nursing terminology, the Clinical Care Classification System (CCC), for developing a reliable costing method for nursing services. Two different approaches are explored; the Relative Value Unit RVU and the simple cost-to-time methods. We found that the simple cost-to-time method was more accurate and more transparent in its derivation than the RVU method and may support a more consistent and reliable approach for costing nursing services.

Leveraging standards to support patient-centric interdisciplinary plans of care.

As health care systems and providers move towards meaningful use of electronic health records, the once distant vision of collaborative patient-centric, interdisciplinary plans of care, generated and updated across organizations and levels of care, may soon become a reality. Effective care planning is included in the proposed Stages 2-3 Meaningful Use quality measures. To facilitate interoperability, standardization of plan of care messaging, content, information and terminology models are needed. This degree of standardization requires local and national coordination. The purpose of this paper is to review some existing standards that may be leveraged to support development of interdisciplinary patient-centric plans of care. Standards are then applied to a use case to demonstrate one method for achieving patient-centric and interoperable interdisciplinary plan of care documentation. Our pilot work suggests that existing standards provide a foundation for adoption and implementation of patient-centric plans of care that are consistent with federal requirements.

Costing nursing care: using the clinical care classification system to value nursing intervention in an acute-care setting.

The purpose of this study was to combine an established methodology for coding nursing interventions and action types using the Clinical Care Classification System with a reliable formula (relative value units) to cost nursing services. Using a flat per-diem rate to cost nursing care greatly understates the actual costs and fails to address the high levels of variability within and across units. We observed nurses performing commonly executed nursing interventions and recorded these into an electronic database with corresponding Clinical Care Classification System codes. The duration of these observations was used to calculate intervention costs using relative value unit calculation formulas. The costs of the five most commonly executed interventions were nursing care coordination/manage-refer ($2.43), nursing status report/assess-monitor ($4.22), medication treatment/perform-direct ($6.33), physical examination/assess-monitor ($3.20), and universal precautions/perform-direct ($1.96). Future studies across a variety of nursing specialties and units are needed to validate the relative value unit for Clinical Care Classification System action types developed for use with the Clinical Care Classification System nursing interventions as a method to cost nursing care.

Testing a bedside personal computer Clinical Care Classification System for nursing students using Microsoft Access.

This study tested a personal computer-based version of the Sabacare Clinical Care Classification System on students' performance of charting patient care plans. The application was designed as an inexpensive alternative to teach electronic charting for use on any laptop or personal computer with Windows and Microsoft Access. The data-based system was tested in a randomized trial with the control group using a type-in text-based-only system also mounted on a laptop at the bedside in the laboratory. Student care plans were more complete using the data-based system over the type-in text version. Students were more positive but not necessarily more efficient with the data-based system. The results demonstrate that the application is effective for improving student nursing care charting using the nursing process and capturing patient care information with a language that is standardized and ready for integration with other patient electronic health record data. It can be implemented on a bedside stand in the clinical laboratory or used to aggregate care planning over a student's clinical experience.

A brief history of nursing informatics in the United States of America.

From the beginning of modern nursing, data from standardized patient records were seen as a potentially powerful resource for assessing and improving the quality of care. As nursing informatics began to evolve in the second half of the 20th century, the lack of standards for language and data limited the functionality and usefulness of early applications. In response, nurses developed standardized languages, but until the turn of the century, neither they nor anyone else understood the attributes required to achieve computability and semantic interoperability. Collaboration across disciplines and national boundaries has led to the development of standards that meet these requirements, opening the way for powerful information tools. Many challenges remain, however. Realizing the potential of nurses to transform and improve health care and outcomes through informatics will require fundamental changes in individuals, organizations, and systems. Nurses are developing and applying informatics methods and tools to discover knowledge and improve health from the molecular to the global level and are seeking the collective wisdom of interdisciplinary and interorganizational collaboration to effect the necessary changes. NOTE: Although this article focuses on nursing informatics in the United States, nurses around the world have made substantial contributions to the field. This article alludes to a few of those advances, but a comprehensive description is beyond the scope of the present work.

Translation and integration of CCC nursing diagnoses into ICNP.

The purpose of this study was to translate and integrate nursing diagnosis concepts from the Clinical Care Classification (CCC) System Version 2.0 to DiagnosticPhenomenon or nursing diagnostic statements in the International Classification for Nursing Practice (ICNP) Version 1.0. Source concepts for CCC were mapped by the project team, where possible, to pre-coordinated ICNP terms. The manual decomposition of source concepts according to the ICNP 7-Axis Model served to validate the mappings. A total of 62% of the CCC Nursing Diagnoses were a pre-coordinated match to an ICNP concept, 35% were a post-coordinated match and only 3% had no match. During the mapping process, missing CCC concepts were submitted to the ICNP Programme, with a recommendation for inclusion in future releases.

Moving past theory: use of a standardized, coded nursing terminology to enhance nursing visibility.

This article provides an overview of the Clinical Care Classification System Version 2.0, a standardized coded nursing terminology designed to enhance nursing visibility. The article provides a background as to why a coded language is needed to describe the "essence of care" to validate patient outcomes. The article highlights the research that produced Clinical Care Classification System and describes how the two interrelated terminologies-the Clinical Care Classification System of Nursing Diagnoses and Outcomes and the Clinical Care Classification System of Nursing Interventions/Actions-are linked and mapped to each other using its coding structure. Examples of the two terminologies are presented with detailed explanations about the coding process. The article highlights the attributes of the Clinical Care Classification System and its place in electronic health record systems.

Changes in society at national and international levels.

Many societal changes will influence the future nature of nursing, nursing informatics and health. Among these are environmental changes, increasing globalization, industrialization of developing countries, and educational developments. The paper considers these issues, and in particular the 'bold transformation' of nurse education that will be necessary if the profession is to be able to deal with the future. The paper concludes with a series of recommended strategic changes.

Clinical Care Classification (CCC) System Charting Model.

This is a demonstration of the Clinical Care Classification (CCC) System Charting Model. The Model software is designed for any personal computer (PC) with Windows using Microsoft Office and Access. The program has been tested as efficient and effective for charting patient care plans using the CCC System's Standardized language following the nursing process. It is available for integration in any electronic health record (E.H.R) system.

Military nursing research by students at the Graduate School of Nursing Uniformed Services University of the Health Sciences.

Military nursing research has had a long and productive history. Today, much of this research is conducted under two programs, the TriService Nursing Research Program and the Graduate School of Nursing (GSN), both located at the Uniformed Services University of the Health Sciences in Bethesda, Maryland. This article will discuss the 150 military nursing research projects carried out by students at the GSN since its founding in 1992. Although most projects have been small in scope, they have obtained useful results. Some projects have served as the basis for larger-scale research studies, receiving funding from the TriService Nursing Research Program. Reports of all projects are available in an online database and some have been published in professional journals. This review concludes that the research produced by GSN students has been beneficial to students and to the military health system.

A bedside PC charting system for nursing students using Clinical Care Classification (CCC) System.

This study tested a PC based version of the CCC System on students' performance of charting patient care plans. The application was designed for any PC with Windows and Microsoft Office(r) programs. The PC based system was tested in a randomized trial with the control group using a type-in text-based only system also mounted on the bedside computer. The results demonstrate that the application is efficient and effective for nursing care charting using the nursing process and capturing patient care information with a language that is standardized and ready for integration with other patient electronic health record (E.H.R) data.

Clinical care costing method for the Clinical Care Classification System.

PURPOSE: To provide a means for calculating the cost of nursing care using the Clinical Care Classification System (CCCS). DATA SOURCES: Three CCCS indicators of care components, actions, and outcomes in conjunction with Clinical Care Pathways (CCPs). DATA SYNTHESIS: The cost of patient care is based on the type of action time multiplied by care components and nursing costs. CONCLUSIONS: The CCCM for the CCCS makes it possible to measure and cost out clinical practice. IMPLICATIONS FOR PRACTICE: The CCCM may be used with CCPs in the electronic patient medical record. The CCPs make it easy to track the clinical nursing care across time, settings, population groups, and geographical locations. Collected data may be used many times, allowing for improved documentation, analysis, and costing out of care.