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The Electronic Health Record (EHR) & Nursing An International Agenda Margaret Lunney, PhD, RN Professor College of Staten Island, CUNY.

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Presentation on theme: "The Electronic Health Record (EHR) & Nursing An International Agenda Margaret Lunney, PhD, RN Professor College of Staten Island, CUNY."— Presentation transcript:

1 The Electronic Health Record (EHR) & Nursing An International Agenda Margaret Lunney, PhD, RN Professor College of Staten Island, CUNY

2 What is the EHR? Electronic patient/ health record Multiple Linkages Integrated Universal

3 History of the Patient Record l Paper records since 1800s l 1918- Required l Proliferation of paper records –Millions in each institution

4 Strengths of Paper Record l Familiar l Portable l No downtime l Flexibility in recording data l Variety of ways to organize or see patterns/trends of individual records

5 Weaknesses Outweigh the Strengths l Content ã Missing ã Excessive ã Redundant ã Illegible ã Inaccurate ã Lack of standardization ã Incomprehensible

6 Weaknesses of Paper Record l Format ã Fragmented ã Data cannot be found l Access & retrieval ã Lack of access ã Time to retrieve ã Cost to enter data ã Errors in data entry

7 Weaknesses of Paper Record NOT integrated ã Inpatient & outpatient ã One type of service with others ã Administrative, financial, quality indicators ã Knowledge bases, e.g., guidelines ã Other patients ã Institutions & locations

8 Weaknesses of Paper Record l Outpatient records ã High number ã Scattered ã Poorly organized ã Inaccurate

9 Goals of EHR l Totally integrated patient record systems l Linkages to resources & databases l Purposes 1. Support patient care and improve quality 2. Enhance productivity and reduce costs 3. Support clinical and health services research 4. Accommodate future developments in technology, policy, management and finance 5. Maintain patient confidentiality

10 Why? l Data Information Knowledge Graves & Corcoran, 1989

11 How? Standardization l File names, Definitions, Descriptions ã Unified languages in meta-thesaurus ã Mapping of languages with one another l Technological: Standards Associations ã International Standards Organization (ISO) ã European Committee for Standardization (CEN) ã American National Standards Institute (ANSI) ã HL7 (see www.hl7.org)

12 Advantages of EHR l Data abstracted, summarized, aggregated; Local, regional, national, international l Ease of entry, organization, & retrieval l Longitudinal records l Linkages to standards, guidelines, other internet sources, recent research l Decision support systems l Other

13 State of the Science in U.S. l DHHS--National Committee on Vital & Health Statistics ã Core Data Elements l National e Health Collaborative (NEHC) www.nationalehealth.org Purpose- Facilitate interoperability l Research ã Being conducted by numerous agencies, e.g., AHRQ, NIH, NLM, VA, IOM, ANA, AHA, AMIA

14 Standardization: Nursing in the U.S. l NANDA (1973-present) l Nursing Minimum Data Set (1985) l Other classifications (1980’s-present) ã Omaha, Saba, Grobe, Ozbolt, NIC, NOC l ANA ã 1989, 1998: Committee on Nursing Practice Information Infrastructure ã Unified Nursing Language System (UNLS), mapping of terms among nursing languages

15 Standardization: International Nursing l Countries involved worldwide, e.g., ACENDIO (European group), Japan, Korea, Australia, South American Countries, Africa l International Council of Nursing (ICN) ã International Classification of Nursing Practice ã International Medical Informatics Assn. (IMIA); ã Working Group-Nursing Informatics

16 Nursing Minimum Data Set (NMDS) : International Frame l Nursing Care Elements (4) 1. Nursing Diagnoses 2. Nursing Interventions 3. Nursing-Sensitive Patient Outcomes 4. Intensity of Nursing Care l Patient Demographic Elements (5) l Service Elements (7) 12. Unique RN Provider Number

17 SNLs: Ongoing Development l U.S.= systematic approval process (Coenen et al, 2001, Computers in Nursing, 19, 240-246) l 7 SNVs approved for EHR (met criteria) ã NANDA-International ã Omaha System ã Home Health Care Classification (Saba) ã NIC ã NOC ã Patient Care Data Set (Ozbolt) ã Perioperative Dataset (AORN)

18 The EHR, SNVs, & You l Use SNVs l Become familiar with computers l Provide feedback to SNL developers

19 The EHR, SNVs, and YOU l Explain rationale to others l Create a spirit of support l Discuss with nurse leaders l Teach others


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