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Actionable Barriers and Gaps: Nursing Initiatives. Bonnie L. Westra, PhD, RN, FAAN Associate Professor, University of Minnesota School of Nursing Director, Center for Nursing Informatics. Nursing Knowledge: Big Data Research for Transforming Healthcare. Purpose.
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Actionable Barriers and Gaps:Nursing Initiatives Bonnie L. Westra, PhD, RN, FAAN Associate Professor, University of Minnesota School of Nursing Director, Center for Nursing Informatics Nursing Knowledge: Big Data Research for Transforming Healthcare
Purpose • Identify gaps, barriers, and challenges to achieving the vision and value of nursing data for big data research to transform healthcare. • Describe resources for closing gaps and overcoming barriers to • Evaluate recommendations for usefulness in the action plan
Minimum Data Sets & Nursing Nursing Care Elements 1. Nursing Diagnoses 2. Nursing Interventions 3. Nursing Outcomes 4. Nursing Intensity of Care Patient Demographics 5. * Personal Identification 6. * Date of Birth 7. * Sex 8. * Race 9. * Ethnicity 10. * Residence Service 11. * Unique facility or agency number 12. Unique number of principle RN 13. * Episode Admission or Encounter Date 14. * Discharge or Termination Date 15. * Disposition of patient or client 16. * Expected payer for this bill Environment 1. Unit/Service Unique Identifier * 2. Type Of Nursing Delivery Unit/Service 3. Patient/Client Population 4. Volume Of Nursing Delivery Unit/Service 5. Care Delivery Structure And Outcomes 6. Patient/Client Accessibility 7. Clinical Decision Making Complexity 8. Environmental Complexity 9. Autonomy 10. Nursing Delivery Unit/Service Accreditation Nurse Resources 11. Management Demographic Profile 12. Staff Demographic Profile 13. Staffing 14. Satisfaction Financial Resources 15. Payer Type * 16. Reimbursement 17. Nursing Delivery Unit/Service Budget 18. Expenses
Criteria for a NIS • Nomenclature • Clinical Content • Data Repository • General Systems Characteristics ANA (1997). NIDSEC (Nursing Information & Data Set Evaluation Center): Standards and Scoring Guidelines. ANA: Washington, DC.
Clinical Data Repository/ Warehouse Continuum of Care 9
NDNQI • Strengths • National nursing quality measurement program • Hospital with unit-level performance comparison • Reflects structure, process, and outcomes • Limitations • Not reusing EHR data • Hospital focused • Not comprehensive
Faculty Preparation • Essentials • Bacalaureate • Master’s • Doctor in Nursing Practice
Informatics Certification Future – Advanced Certification – AMIA working on this
Informatics Organizations • Also many local nursing informatics organizations
Actionable Barriers and Gaps:Nursing Initiatives Judith J. Warren, PhD, RN, FAAN, FACMI Consultant Warren Associates, LLC Nursing Knowledge: Big Data Research for Transforming Healthcare
Transforming NDNQI into eMeasures Feasibility studies with partners to extract information from EHRs
Continuity of Care Document • Required through health care reform • Does a great job of communicating physician care and reimbursement issues • Does a partial job of communicating nursing care and patient status on discharge • Many patient issues that lead to readmission within 30 days are issues addressed by nursing care • C-HOBIC in Canada • Need to add patient information of concern to nursing practice to CCD
S&I Framework • Working on Care Plan specifications • Scope and attention to the work will be driving EHR design, build and implementation • Need more nurses involved
Funding for big data research • Clinical and Translational Science Awards Consortium • Big Data analytics • Implementation Science
Standard Occupational Classification (SOC) Codes • Used to classify workers for the collecting, calculating, or disseminating data. • The SOC code for Registered Nurses is 29-1141 • Need informatics nurse code to demonstrate need and support education program support
National Provider Identifier • Solution to unique nurse identifier in the NMDS and MMDS • Must encourage every nurse to apply upon licensure
Nurses in Decision-making Circles • Office of the National Coordinator • National Committee on Vital and Health Statistics • CMS Panels • NQF committees and panels • IOM • S&I Framework • HL7 • IHTSDO and LOINC • Other committees • and Task Forces???????
Actionable Barriers and Gaps:Recommendations Bonnie L. Westra, PhD, RN, FAAN and Judith J. Warren, PhD, RN, FAAN , FACMI Nursing Knowledge: Big Data Research for Transforming Healthcare
Recommendations • Survey health systems about perceived value and current use of standardized nursing terminologies for documentation, quality improvement, and research • Create a central resource for mapping nursing data to terminologies – particularly assessments, interventions, and outcomes. • Centralize mappings through the NLM • Work with vendors to include standardized nursing terminologies, eliminating the need for each health system to map local codes to standards • Require coding in information systems to be consistent with the NMDS/ NMMDS data elements – new nursing knowledge model • Integrate the NIDSEC criteria into meaningful use certification criteria of EHRs
Recommendations • Add a criteria for Magnet Status to integrate standardized nursing terminologies in EHRs and reuse the data for quality reporting • Expand the NDNQI criteria to include data across settings and to use standardized nursing terminologies/ minimum data sets • Share the nursing knowledge model across CTSAs to include in their CDRs • Support strategies to educate all faculty about how to teach nursing informatics across levels of education • Empower with nurse informaticians to value and advocate for standardized nursing terminologies and the value of these • Develop strategies to work with nursing organizations on a common set of goals and consistent reporting on progress