Integrative AACN Essentials for Information Management and Patient Care Technologies Across ...

85 Pages·2015·3.86 MB·English

by  Tom Clancy

National Nursing Informatics
Deep Dive Program
Integrating AACN Essentials for Information
Management and Patient Care Technologies
Across the Continuum

Thomas R. Clancy, PhD, MBA, RN, FAAN
Clinical Professor and Assistant Dean
Faculty Practices, Partnerships and Professional Development

April 12, 2015
Disclosure

I have no relevant financial interest to disclose nor
am I endorsing any commercial products
identified in this presentation.
Objectives: Overview
• Discuss how nursing informatics content builds
across BSN, MSN and DNP curricula.
• Demonstrate how nursing informatics content
can be threaded into existing didactic and clinical
courses.
• Provide exemplars of resources, assignments and
other tools used to teach nursing informatics.
Standards and Guidelines
AACN Essentials for Quality, Safety & Technology
Information Management Education for Nurses Informatics Guiding
And Patient Care Knowledge, Skills Education Reform
Technologies and Attitudes Competencies for
Practicing Nurses
Competency Matrix for Nursing
Informatics
QSEN AACN QSEN AACN
AACN BSN TIGER Undergrad. Essentials Graduate Essentials
Essentials Competencies KSA’s Masters KSA’s DNP
Generalist X X X
Masters X X X X X
Doctor of X X X X X X
Nursing
Practice
Exponential Growth in Complexity
Decades of rapid
Typical chronic
innovation and
disease pt.
technological
improvement have
• 79 years old,
created an
• Osteoporosis,
extraordinarily
complex healthcare
• Osteoarthritis,
system. So much so
• Type 2 diabetes,
that healthcare often
falls short of its
• Hypertension,
potential.
• COPD,

Smith, M., Saunders, R., Stuckhardt, L., and McGinnis, M.

(2012). Best Care at Lower Cost: The Path to Continuously
Learning Health Care in America. Institute of Medicine,
National Academies Press.
Knowledge Complexity Framework
Obtain raw facts (numbers, text, symbols)
Data
Give meaning to data as vital signs, lab values, IV flow rates,
Information
patient names, medication (name, route, time, frequency),
(Procedural)
radiology images, provider orders, standards, guidelines.
Analyze and synthesize information for values outside of normal
Knowledge
range (vital signs, lab values, IV flow rates, medication dosage),
(Functional)
trend lines and historical data.
Use critical thinking to assess and act upon knowledge. Provide
Meaning
appropriate nursing interventions.
(Managing)
Assess and evaluate the impact of actions on the entire person.
Philosophy
What and how are other systems (physiologic and sociologic)
(Systems)
affected by the interventions.
Use knowledge, meaning and philosophy to reflect upon past
Wisdom experiences and recognize patterns that aid in establishing and
(Renewing) achieving goals.
Allee, Verna (1997). The Knowledge Evolution. Butterworth- Heinemann: Boston
Knowledge Complexity Framework
DNP
Masters
Wisdom
y
t
i Philosophy
x
e Pre-licensure
Meaning
l
p Expert
m
Knowledge Systems
o Decision
C Support
Information
Systems
Data
Information
Systems
Cognitive Load
Knowledge Complexity Framework
Digital data can be created, reproduced and stored at a fraction
Data
of the cost of paper data.
Digital data can be configured to be displayed in specific fields in
Information
EHR’s or LED’s to turn raw data into information (vital signs,
(Procedural)
medications, flow rates).
Information can be transformed into knowledge through clinical
Knowledge decision support alerts/reminders for values outside of normal
(Functional) range (vital signs, lab values, IV flow rates, medication dosage),
trend lines and historical data.
The creation of meaning from knowledge can be enabled through
Meaning
expert systems by predicting outcomes and recommending
(Managing)
appropriate nursing interventions.
Assess and evaluate the impact of actions on systems with
Philosophy
electronic dashboards and benchmarks.
(Systems)
Use knowledge, meaning and philosophy to reflect upon past
Wisdom experiences and recognize patterns through data visualization
(Renewing) tools that aid in monitoring outcomes for entire populations of
patients with specific disease conditions.
Learning Progression
Information
Systems Decision Support Expert Systems
• Admission, discharge, transfer • Medication dosing • Predictive
• Order entry system • Order facilitators • DX
• Ancillary systems (lab, pharmacy, radiology) • Point of care alerts • Readmit
• Results reporting systems • Point of care reminders • Sepsis
• Documentation systems • Information displays • Other
• Administrative systems (scheduling) • Pop. Mgt
https://sjhobbs.wikispaces.c
om/Robotics,+AI+and+Exper
t+Systems