Integration of Nursing Informatics, Integration of Nursing Informatics, Nursing Classification Systems, Nursing Classification Systems, and Nursing Practice and Nursing Practice (Nur 603) (Nur 603) Presenter: Russell McGuire, MSN, RN Director of Clinical Services, DHS Appalachian Regional Healthcare, Inc.
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Integration of Nursing Informatics, Nursing Classification Systems, and Nursing Practice (Nur 603) Presenter: Russell McGuire, MSN, RN Director of Clinical.
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Integration of Nursing Informatics, Integration of Nursing Informatics, Nursing Classification Systems, and Nursing Classification Systems, and
“The use of technology and/or a computer system to collect, store, process, display, retrieve, and communicate timely data and information in and across health care facilities that: Administer nursing services and resources; Manage the delivery of patient and nursing care; Link research resources and findings to nursing
practice; Apply educational resources to nursing education”
Nursing informatics focuses on the use of “nursing information system” (NIS) to administer nursing resources: To assist in effective information management; Monitor the quality, effectiveness, and
outcomes associated with the provision of care; Protect the confidentiality and privacy of
Nursing Classification SystemsNursing Classification Systems
Reasons for Classification System Reasons for Classification System DevelopmentDevelopment
To standardize nomenclature To expand nursing knowledge To develop information systems To teach decision making To determine nursing costs To allocate nursing resources To communicate nursing to non-nurses To link nursing knowledge
Source: McCloskey, J. & Bulechek, G. (1996) Nursing intervention classification.Mosby Publishers)
Relevant BackgroundRelevant Background Basic concepts for information systems:
Nursing data: refers to unstructured raw facts; Are discrete entities; Lack interpretation. Forms the basis for a nursing information system.
Nursing information: data that has been given form and has been interpreted.
Nursing knowledge: synthesized information derived from the analysis of data that has been processed.
Relevant BackgroundRelevant Background
Nursing Data Standards needed for the management, documentation
and communication of nursing diagnosis, interventions, and outcomes (patient and nursing sensitive).
researched and supported by the ANA Council on Computer Applications in Nursing and the NLN’s Council for Nursing Informatics.
HistoryHistory
1970: ANA recommends that “nursing process” be used as the standard for documenting nursing practice.
1970s: Nursing Diagnoses researched and approved by the North American Nursing Diagnosis Association (NANDA).
1980: ANA’s Social Policy Statement - “Nursing is the diagnosis and treatment of human responses to actual or potential health problems”.
HistoryHistory
1985: Nursing Minimum Data Set (NMDS) researched/developed by Werley and Lang.
1986: ANA approves polices to develop a classification system designed for all nursing practice settings.
1988: ANAs Broad of Directors accept the NANDA Taxonomy I Revised.
HistoryHistory 1988: ANA endorses the Conference on Research
Priorities in Nursing Science. Identified two needs: “the need for standardized data sets which document
nursing care process across settings and a taxonomy to classify nursing phenomena and allow the common use of terms”.
1990: ANA House of Delegates recognizes the Nursing Minimum Data Set (NMDS). describes the nursing care of patients and their caregivers in a
variety of settings. provides comparability across clinical settings. demonstrates trends in nursing care. provides data for policy research and policy decisions.
HistoryHistory 1991: ANA Congress of Nursing Practice mandated
the formation of the Steering Committee on Databases to Support Clinical Nursing Practice. Purposes:
propose policy and program initiatives regarding nursing classification systems.
build a national database for clinical nursing practice. coordinate public and private development of
databases.
HistoryHistory 1992: ANA Database Steering Committee formally
recognizes four nursing vocabularies: NANDA - North American Nursing Diagnoses Association. The Omaha System - Omaha VNA (Martin & Scheet) Home Health Care Classification System - Georgetown
University (Saba). Nursing Intervention Classification - University of Iowa
(McCloskey & Bulechek)
1993: Development of the International Classification of Nursing Practice.
Rationale: Rationale: ““Next Generation Nursing Next Generation Nursing Information Systems: Essential Characteristics for Information Systems: Essential Characteristics for Professional PracticeProfessional Practice””
Nursing information systems exists within the context of the total continuum of the “integrated patient record system”.
Health care is and will continue to be an information-intensive endeavor.
Information is a critical resource in the health care delivery environment.
Nursing Practice is essentially an information-processing activity.
RationaleRationale Nursing information is essential to the
accuracy of integrated systems (both health care delivery and information systems).
Patient-specific data are the focal point of a totally integrated patient-record system.
Atomic-level data, captured within a Nursing Information System will be used for many purposes.
Users Data/Information Scope
Administrators, Costs of care by category of patient. Agency-wideResearchers, Accreditors Number of patients admitted with specific diagnosis. DataQuality managers Volume of tests, procedures, interventions, outcomes.
World health officials General health status and WorldwidePolicy makers, Researchers health-related needs DataLawmakers of individual nations.
Analysts, researchers, Comparisons of treatments, outcomes, Community/Quality management, and costs by locality and by agency. Region-widePublic health officials Incidence and prevalence of diagnosis by region. Data
Policy makers Trends in incidence, prevalence, Nationwide Lawmakers, researchers outcomes, and costs by region, by DataInsures diagnosis, by type of agency.
ABSTRACTED, SUMMARIZED, AGGREGATED
ABSTRACTED, SUMMARIZED, AGGREGATED
ABSTRACTED, SUMMARIZED, AGGREGATED
ABSTRACTED, SUMMARIZED, AGGREGATEDCaregivers Atomic level patient-specific data: e.g..assessments, Individual Agency departments, diagnoses, interventions, diagnostic test results, procedures, Patient Quality managers, Insurers treatments, hours of care, outcomes. Data
RationaleRationale Data and data elements required for nursing
information systems are evolving. To ensure high-quality practice, nurses need
access to sources of data that are ”beyond institutional, patient-specific data”.
“There will always be a need for human interpretation of computer-processed data”.
Where is all this Leading?Where is all this Leading?Unified Medical Language SystemUnified Medical Language System
1986: National Library of Medicine initiates the Unified Medical Language System (UMLS).
Goal: to develop a computer-based information resources for health professionals. designed to link information resources
scientific literature computer-based patient records factual databases expert systems other health related databases
Where Is All This Leading?Where Is All This Leading?Unified Medical Language SystemUnified Medical Language System
Three resources related to the UMLS: Metathesaurus - set of terms and concepts
associated with several biomedical vocabularies.
Semantic network - links the Metathesaurus vocabularies together using semantic concepts.
Information sources map - a description of available databases.
Where Is All This Leading?Where Is All This Leading?Unified Medical Language SystemUnified Medical Language System
Using the same concept, the NLM is linking the recognized nursing vocabularies (primarily for this discussion NANDA, NIC, and NOC).
This process of recognition and inclusion of nursing vocabularies, taxonomies, and classification schemes into the NLMs Metathesaurus can been demonstrated in the development of the unified nursing language system.
Where Is All This Leading?Where Is All This Leading?Unified Nursing Language SystemUnified Nursing Language System
ANA database steering committee developing a common nursing language known as the unified nursing language system (UNLS).
Criteria for inclusion in the UNLS: Clinically useful for making diagnosis, intervention, and
outcome decisions. Terms unambiguous, clearly and accurately defined. Tested for validated clinical use and reliability of
vocabulary terms. Accompanied by evidence of a process for periodic review
and appropriate methodology for research and testing.
Where Is All This Leading?Where Is All This Leading?Unified Nursing Language SystemUnified Nursing Language System
To date the ANA database steering committee has recommended the four “recognized” nursing classification schemes for inclusion in the UNLS.
The UNLS will: Allow for integration of patient data, scientific data, and
bibliographic data. Bring information to the bedside to improve clinical
decision making. Identify linkages and associations across vocabularies
and taxonomies. Linking clinical data, cost data, educational case data.
NANDA,
NIC,
NOC,Impaired ?
Are you ……
Integration Into Nursing PracticeIntegration Into Nursing Practice
ARH Experience With Nursing ARH Experience With Nursing Classification SystemsClassification Systems
Information systems development. Need for standards-based, evidenced based
practice guidelines. Need for standardized language across the
continuum. Across nursing practice settings. Integrated from a trans-disciplinary, integrated
healthcare delivery perspective.
ARH Experience With Nursing ARH Experience With Nursing Classification SystemsClassification Systems
ARH reviewed the current literature related to nursing classification systems.
Review initiated in the information systems department.
Input from nursing executive staff (acute care / home health).
ARH Experience With Nursing ARH Experience With Nursing Classification SystemsClassification Systems
Nursing classifications reviewed. NANDA (north American nursing diagnosis
association). NIC (nursing intervention classification). NOC (nursing outcomes classification). Omaha - home health nursing practice. HHCC - home health nursing practice.
Features, advantages, disadvantages for use in ARH determined.
ARH Experience With Nursing ARH Experience With Nursing Classification Systems: NANDAClassification Systems: NANDA
NANDA - north American nursing diagnosis taxonomy I revised.
Features. Research based development. 133 nursing diagnoses applicable to different
practice settings. Continued research and expansion. Based upon the nine human response patterns,
forming the abstract conceptual level.
ARH Experience With Nursing ARH Experience With Nursing Classification Systems: NANDAClassification Systems: NANDA
Advantages. Comprehensive listing of nursing diagnoses. National and international recognition.
Disadvantages. Does not address specific interventions or
outcomes.
ARH Experience With Nursing ARH Experience With Nursing Classification Systems: NICClassification Systems: NIC
NIC - nursing intervention project (Iowa project.
Features. 433 documented, researched nursing
interventions.
ARH Experience With Nursing ARH Experience With Nursing Classification Systems: NICClassification Systems: NIC
Advantages. Most comprehensive listing of researched
nursing interventions. Documented linkages to AHCPR guidelines,
nursing diagnoses. Continued research efforts to establish linkages
to patient outcomes. Disadvantages.
ARH Experience With Nursing ARH Experience With Nursing Classification Systems: OmahaClassification Systems: Omaha
Developed by the VNA of Omaha Three classification schemes:
Problem classification (40 client problems) Intervention classification (62 interventions)
Health teaching, guidance, and counseling Treatments and procedures Case management Surveillance
Problem rating scale
ARH Experience With Nursing ARH Experience With Nursing Classification Systems: HHCCClassification Systems: HHCC
Developed by dr. Virginia Saba (Georgetown university).
Consists of : Nursing diagnosis - 145. Nursing intervention - 160. Home care component - represents clusters of
functional, behavioral, physiological, and psychological health care patterns.
Numerically coded for information system use.
Extended Health Enterprise ModelExtended Health Enterprise Model
Automation of documentation process Assessment/vitals MAR and IV administration Clinical pathways and care plans All HCFA forms become by product of collected information
Severity indexing tool Weighted questions
Starter kit to build care designs/care plans Sample interdisciplinary clinical pathways Library of treatment interventions, outcome goals, and staging