A Nursing Informatics

Leadership Role

Improving Clinical Quality

Outcomes through EHR Design,

Development, and Utilization

Lyda Gardiner – B.Sc., B.Ed., M.Ed., BSN, RN Practice Director – Quality and Performance Innovation - Jacobus Consulting

Lyda is a respected quality and clinical informatics leader, with a proven track record of spearheading strategic change to realize the full benefits of EHR enabled systems. Employing proven methodologies such as Continuous Quality Improvement, and innovative approaches such as the development of Quality Informatics roles, Lyda empowers leaders and teams to utilize their EHRs to meet Meaningful Use, Value Based Purchasing, and Accountable Care. Drawing on a strong clinical nursing foundation, deep knowledge of healthcare systems and quality methodologies, Lyda effectively creates solutions that combine operational effectiveness with knowledge and information to ensure effective outcomes and realization of strategic goals and objectives.

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New workflows and documentation

requirements can be difficult for

clinicians to adopt and for EHR

vendors to support well.

Focus on Value Based

& P4P payment models

& other Quality

Outcomes programs

will increase the need

to extract actionable

data from EHRs & other

systems &

reimbursement of

organizations will be

based on data

submitted from the EHR

Incentive program goal: EHRs that

support high quality care through

new EHR-enabled workflows,

ensuring accurate, reproducible,

high quality data at individual and

aggregate level are necessary to

measure OUTCOMES OF CARE

Emerging new payment models

for health care will require “value”

over volume. Examples of such

payment models include:

•Health homes

•Accountable care organizations

•Medicare’s value-based

purchasing (pay for

performance) programs

•Core Measures

•Meaningful Use

•Inpatient/Outpatient Quality

Reporting

Accurate

patient care

documentation

across the

continuum of

care is

necessary for

reporting

OUTCOMES of

evidence

based care

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• NI Leaders must develop & use skills in ALL informatics domains to help their organizations successfully implement & manage Quality Outcomes Programs (QOPs)

• EHR is foundational to successful QOPs which drive healthcare forward through provision of data, information & knowledge

• Design, Build & Maintenance of HCIS MUST ensure effective data/analytics

• NI competencies need to develop through all layers of the organization

Objectives

for

Today

Safe,

Timely

Equitable,

Effective,

Efficient,

Patient-

Centered

Data,

Information,

Knowledge,

Wisdom

Current Health Care Environment

2009 ARRA (American

Recovery & Reinvestment

Act) : Meaningful Use EHR

Incentives Program

Foundational to PPACA

Improve quality, safety, efficiency

Reduce health disparities

Engage patients, families in their care

Improve Care Coordination

Improve Population and Public Health

Ensure Privacy/Protection of PHI

2010 PPACA ( Patient

Protection and Affordable Care

Act) :

Accountable Care

Organizations (ACO), Value

Based Purchasing (P4P)

Provide Value

Improve Quality, control cost/efficiency

Protect Patients

Improve Safety, involve patients &

families, ensure privacy of PHI

Ensure Affordable Care

Reduce disparity, improve care

coordination, improve pop/public health 5

AHRQ: “Health IT & EHR are the Foundations

for Value & Quality” EHR Supports:

1. Quality measurement and improvement based on data from EHR

2. Optimized data collection from the EHR

3. Care coordination–EHR provides information across care continuum

4. Provides clinicians & patients with necessary info to optimize care

5. Provides timely feedback to care providers about care

6. Facilitates provision of right care & time, based on most current info

7. Allows for the comparative evaluation of treatments and interventions

8. Allows for the collection of data and information at a population level

– allowing for effective management of high-impact conditions

9. Data provides information about regional and other disparities in care

10. Value of care measurement provided by an organization, or its

component departments, or measure the value of care provided by AC0

Value Based & P4P Reimbursement

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Payment reform that rewards

Value rather than

Volume of patient care is

a primary goal, if not THE

primary goal, of today’s

healthcare reform

How is VALUE defined?

QUALITY

OUTCOMES

+ = VALUE COST

EHR IS FOUNDATIONAL TO ACHIEVE

VALUE IN HEALTH CARE

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Definition of Value

Value may be defined as the health

outcomes achieved per dollar spent

OR:

The Intersection of Quality & Cost

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Quality

Cost

Value

Equilibrium

(optimal)

Relationship Between

Quality and Value…

Achieving high value for patients MUST

become the overarching goal of improved

health care delivery

Value — should define the framework for performance

improvement in health care. Rigorous, disciplined

measurement and improvement of value is the best way

to drive system progress.

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- The New England Journal of

Medicine Michael E. Porter, Ph.D.

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Outcomes

QUALITY

Quality Programs are Focused on Outcomes: Getting the right care

To the right patient

At the right time – Every time

to ensure the BEST Outcomes Possible

Quality Care

The IOM

Dimensions of

Quality Care are:

Safe

Timely

Effective

Efficient

Equitable

Patient Centered

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The ability to effectively

improve Quality requires:

Ability to measure & evaluate

Structure, Processes, & Outcomes

against Quality Dimensions (use

data)

Ability to impact outcomes through

the use of Evidence

Commitment to change when a

better way is reliably identified-

Continuous Quality Improvement

Quality Department

Functions

Measure/evaluate/improve structure & process

Measure/evaluate and improve Outcomes and

the 6 Dimensions of Quality. Provide data &

improvement strategies to nursing,

physicians, & other clinical practice areas

Report data to population/condition data bases to

provide information for condition management

Report outcomes for Pay for Performance, and

other reimbursement

Provide physicians with credentialing and

performance data

Ensure continuous quality improvement –

through practice change based on evidence

(data, clinical research)

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Methodology

Abstract Information from records

Performance Improvement (PDCA, six

sigma, lean – etc.)

Meet Evidence Based Standards for

structure, process and outcomes

(EBM/P)

Support the implementation of new

evidence for improved quality

Change Management

NEED:

Effective data gathering mechanism –

reliable EHR

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Information &

Communications

Technology

Information

Sciences

•Codification & Taxonomy

•Collection, Organization,

Storage & retrieval of

Information, knowledge

•Interpretation

•Transmission of

information

•Human-Computer

Interaction

•Iterative design

processes

•Ways people generate,

use & find information

•Storage & Dissemination of

data

•Design and build of

systems such as HCIS,

Clinical (Business)

Intelligence & other systems

•Data Storage & Retrieval

•Focus on tools that enable

efficient: Capture, Delivery,

Transmission, & Use of data,

information, & knowledge

•Effective application of

those tools

Informatics

Nursing Informatics

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NURSING

PRACTICE INFORMATION

TECHNOLOGY

INFORMATION

SCIENCE

•Full Scope & Practice of

Nursing, as defined by

ANA

• NI competencies for

bedside nurses, Nurse

Informaticians, & Nurse

Informatics Specialists

(graduate level education)

•Scope of NI is

commensurate with

scope of nursing practice

& nursing science with a

concentration on data,

information, & knowledge

Clinical Care (Nursing)

The Health System

Information & Communications

Technology

EXTERNAL FACTORS Value (quality + cost)

Focus on QOPs

Evidence Based Practice

Value Based Payment

New models of

reimbursement – ACO,

Medical home

Regulatory environment

ARRA/MU

INTERNAL FACTORS Increased interdisciplinary practice and patient centric processes

Coordination of Care

People, Processes, & Technology

Culture

Practice Goals for each discipline

Practice Based Evidence

Slide 16

Clinical Informatics

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QUALITY

INFORMATICS (The study of) information use in

understanding and improving health care

quality and safety

Expert knowledge of all quality and patient

safety initiatives

Measures, regulatory expert – ensures

consistency between modules

Assists with design/development of EHR

Ensures streamlined build to facilitate

reporting

Works with end-users to ensure accurate,

reliable entry of data/information

Works with Data Architect – build, data

marts, reporting/data mining, BI solutions

Facilitates BI Maturity

Supports Quality department

transformation to HCIS

Supports Organizational transformation to

data driven/Quality Driven Organization

Practice of

Quality

Sciences

Computer

Science

Information

Science

Evidence

2 Perspectives – Both Critical for

Successful Healthcare

Transformation

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What is Evidence Based Practice?

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The conscientious, explicit, and

judicious practice of integrating

individual clinical expertise with the best

available clinical evidence from

systematic research in making

decisions about the care of individual

patients. DL Sackett

The integration of best-

researched evidence and

clinical expertise with patient

values Institute of Medicine Committee on Quality of

Health Care in America

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What is Practice Based Evidence?

Applies scientific method

to the gathering and

utilization of organization

specific data

Aligns data and measurement with

organizational strategies and

performance improvement goals to

result in data driven decision

making

A structured, systematic

approach to utilizing data

obtained from your EHR to drive

decision making

Evidence Based Practice &

Practice Based Evidence

Quality Outcomes Programs (QOPs) are structured

programs of data collection with defined measures

targeted to provide data, information & knowledge

about diseases & populations that account for big

populations and/or high cost

Provide data, information & knowledge for Clinical

Decision Making, which must be coupled with Expert

Knowledge & Experience (Wisdom)

When practiced together,

form the basis of Continuous

Quality Improvement

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Nursing Informatics & Coordination of Care

• Nurses – Most qualified, well positioned, & largest group of contributors to

healthcare services

– Best positioned to support essential clinical transformation efforts through automated clinical tools (EHRs) which will result in new care delivery models

• As nurses coordinate care – HCIS will become THE tool that facilitates effective and efficient

coordination through communication

– Real-time availability of information in the form of CDS (clinical decision support,) all of which will facilitate the real-time coordination of care (CDS combines EBP & PBE)

• Design and flow of data and information will be critical

• Build MUST – Begin with the end(s) in mind

– Be well defined and clear as to the outcomes needed – both for the patients, and for the system (remember – there is EBP with regard to HCIS systems as well as for patient care)

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Coordination of Care (cont.) NI practitioners are

– Leaders - Designers - Facilitators - Educators -

They will help nurses gain competencies necessary to

utilize EHR at the bedside to provide the knowledge,

information, & communication needed

Nurses & the nursing profession are positioned as the most

qualified to respond to the current health system changes &

meet eHealth transformational agendas…Amara (2000)

They are the leaders who will help Nurse Executives move the

nursing agenda forward with regard to QOPs and delivery of

VALUE to all patients

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Key Consideration

• If reimbursement is now based on VALUE, how do you know it has been delivered? – Measure of cost & other financial measures –

Finance Teams

– Measure care and treatment OUTCOMES– CLINICAL AND QUALITY PROGRAMS & DEPARTMENTS (QOPs)

• Measure – interventions, actions, treatments

• Rigorously define the way outcome is measured, controlling as many variables as possible to allow the data to be comparable and inferences to be accurate

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Outcomes

• Are evaluated through measurements designed to

– provide actionable data

– measure the impact of a treatment, action or intervention

• Measures

– provide data & information

– Expand knowledge

– allow quantification, comparisons between organizations & practices

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• There are hundreds of

measures, developed by

many agencies – two

examples are

• NQF – over 600 endorsed

measures

• PQRI – 153 Quality

measures

Outcomes (cont.)

• Must be measureable using EHR data

• Data and information provided must be

accurate

• Must be able to report large volumes of data

• Data fields MUST be well defined, multiple

fields must be captured, specific criteria

included or excluded

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Quality Outcomes Programs (QOPs)

Measure sets

Are used to provide information regarding quality of care provided by an

organization

May include measures of intervention, treatment, specific practices or other

action or activity depending how they are built and utilized

Are generally a group of measures related to a specific topic, i.e. AMI,

SCIP, etc.

Along the 6 dimensions of quality

Safe

Timely

Effective

Efficient

Equitable

Patient Centered

The Quality “Measures” in

QOPs measure

Structure

Process

Outcomes

21%

30% 24%

25%

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Quality Outcomes Programs (cont.)

Built based on evidence ranging from double-blind

clinical trials to expert consensus; provides information

on population, disease, interventions, treatments, etc.

Organizations may build Practice Based Measures;

e.g. measuring fall rates in inpatient medicated

populations over age 65

Measures form the basis for reports that are fed to

dashboard for PI, Surveillance, QOPs, upload to

national databases, & other mandatory reporting

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Outcomes Programs are based on Measures

Formal Measures Development

Ensures

– Consistent measurement

– Defined measurements to allow comparison

of data

– Structured

Examples of Measures (see next slides)

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Core Measures

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Measures Common To More Than

One Program

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VBP Measures

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Quality Outcomes Programs Joint Commission

In-pt/Out-pt Quality Reporting

Value Based Purchasing

AHRQ – In-pt Quality- Pt.

Safety & Pediatric Indicators

Hospital Quality Association –

In-pt indicators

Hospital Acquired Conditions

Long Term Care Hospital

Quality Indicators

Inpatient Psychiatric Facility

Quality Indicators

Meaningful Use – Stage I, II, & III –

Core, Menu & Quality Measures

National Database of Nurse

Quality Indicators

Medications

Mortality – 30

National Quality Forum – Clinical

Quality Measures

OASIS (Home Health Data Set)

Hospice Quality Measures

Inpatient Rehabilitation Quality

Indicators

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Quality Reporting Timeline – QOPs

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Quality Outcomes Programs

QOPs require organizations to apply a basic CQI approach to systematic change, founded on:

–Identifying a problem & Determining a measure

–Collecting Data & Reporting actual results

–Comparing actual outcomes against goal

–Comparing goal against benchmark

–Applying interventions (based on evidence) designed to improve outcomes

Legislation and national/state initiatives are requiring CQI & associated methodology through QOPs

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Implementing Automated, Large-Scale

Quality Outcomes Programs (QOPs)

Current QOPs are frequently managed with manual data

extraction from electronic record (NDNQI, CORE Measures,

IQR, BH, ARU, etc.)

Quality team members manually extract data for representative

samples and submit to national databases

To effectively implement QOPs and the volumes of data they

require, automated data extraction from the EHR is essential

How can this be automated from the EHR?

Nursing Informatics can lead the way

Types of Issues Impacting

Automated Data Extraction

from EHR for QOPs

Key Areas Requiring Nursing

Informatics Expertise

Data Input Issues

Inconsistent build, hybrid records, multiple locations

to document the same information

Lack of awareness of where reportable data is

captured (ALL locations) so changes made accurately

Lack of knowledge of which data MUST be captured

for QOPs, regulatory, Nursing Initiatives & Nursing

Quality Improvement programs – therefore needed

fields do not exist

Lack of effective change control – fields providing

report data changed by user groups (break reports)

Data Input Issues (cont.)

• Validity – data captured in measures reports provides the correct data for

the measure

• Narrative data – reduces ability to report discrete, comparable data

• Hybrid record – data captured on paper must be manually abstracted –

cannot be automatically reported

• Reliability – Information to be documented is captured as expected

• Lack of information about data quality in the EHR

Accurate documentation capture (frequency) rates

Optimized system build opportunities

Recognized source of truth (required fields for data capture)

Related to end-user documentation reliability

To be sure information is pulled correctly & accurately for reports

Data quality assurance

Ensure EHR build supports automated QOPs

consistently

Effective data extraction begins with EHR DESIGN & BUILD

Sophisticated tools & software for data extraction / reporting will not work if data fields are

–Not present

–Not used or inconsistently used

–Too many places data can be entered into the system (documented)

–Data is captured in narrative or other formats that cannot be reported

NI Leaders MUST be PROACTIVE in their knowledge and anticipation of required data for

–QOPs such as MU, VBP, etc.

–PBE data fields for nursing or organization’s CQI programs

–Anticipation of future data needs

–Ensure optimization or other efforts don’t negatively impact automated QOP date reporting

NI leaders MUST coordinate with all experts throughout the system to ensure

–System design & build reflect the MOST EFFICIENT way to gather actionable, reportable

data for QOPs

–Synchronization with clinical workflow, data collection does not cause artificial or

extra work for clinicians in the form of data collection

Reportable Data

Identify data needed

from the system prior

to build if possible in

order to measure

outcomes

Build and develop the

EHR knowing new

requirements for

reporting will

continuously occur

MU criteria including Quality

Measures

Quality Indicators – CORE Measures,

other data sets

NDNQI measures – nurse sensitive

indicators

Other patient care indicators – defined

by external agencies or your

organization for

Performance Improvement purposes

(Quality Dept, Clinical Outcomes Dept)

TJC measures of success

Measures identified for any type of audit

Content of future QOPs (future

requirements) already available

– NI should already be working

w clinical leaders to implement &

have in place prior to required

reporting

Design and Build

NI Practitioner MUST have a much broader focus

and greater knowledge of where

All data is housed

How it is developed

Accuracy, reliability & validity (does it capture data

needed for reporting quality measures)

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Design EHR to capture data currently available OR

needed to meet QOPs, other legislated requirements

Facilitate Performance Improvement as part of

Nursing’s CQI Methodology

• Multiple documentation locations to find the same information

• Lack of designated source of truth

• Insufficient knowledge of measurement & evaluation (data &

information needed for data to wisdom continuum) & CQI techniques

• Lack of change control - user group makes changes w/out

evaluation by team with ability to evaluate impact at all levels of the

EHR, including disabling reporting

• No records of what and when changes were made (these can

impact how far back certain types of data can be extracted)

• How / where data is stored, how long it is available for reporting

Data Output (Extraction) Issues

Ensure the EHR supports QOPs with automation

(Roadmap for QOPs)

1. Develop coordinated reporting plan Organizational Reporting & Data Access

Develop leadership dashboard

Develop department specific reporting & dashboards (PBE)

Build reports for critical/repetitively needed data/information – Quality abstracted data, Case Management data, NDNQI etc.

Start with small projects: facts, data, and information

2. Change Control

3. Coordinate like groups with regard to reports

4. NI or other informatics practitioners learn about reporting & data storage, formats of data entry to support large scale reporting

5. Determine/anticipate additional reporting needs and work with IT to meet needs (may be over time)

LOBI – Ladder of Business (Clinical)

Intelligence:

Closely parallels the Blum Model – and

makes the case for PBE/C(B)I

Enabled Intuition

Understanding

Knowledge

Information

Data

Facts

Roadmap for QOPs (cont.)

Data Plan/Program

–Data Structure and Repository Assessment

Adequate for high volume reporting

Organized approach for high volume reporting

Management, storage & retrieval mechanisms in place

–Develop Data Strategic Plan – 1, 3, 5 years

–Develop necessary expertise

•Data Architect

•Quality Informatics

Data Management Plan:

must align w/

financial/operational goals:

start small if necessary

– Data infrastructure prepared for

expanding data needs

•Data repository/Data warehouse

•Availability of data, purging, other

storage activities

•CI/BI

•Quality Informatician – Data quality

– entry to storage, to retrieval

CI - Clinical (Business) Intelligence

• CI/BI system purchase is unnecessary in the beginning

• Can grow one from SQL/data repository & other tools

• Need to develop expertise within the organization

• Need nursing/quality informatics expertise

• Eventually Data Architect, Data Strategy & Plan

• Most EHRs can report big volume data as needed for successful PBE, QOPs, Financial metrics, etc.

• CI/BI system may be added later, generally ROI is realized from organized data management & reporting for QOPs, CQI etc. & facilitates CI/BI development

Develop Methodologies To

Ensure Safe Succession

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Safeguard knowledge about how the system

was developed, decisions made, build

strategies

Keep records of

changes and iterations

Document required

quality measures and

other quality

information in a

spreadsheet record –

such as core measures

Outpatient Quality Reporting Program

(OQR)

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Record of Information Needed for

QOP Implementation/Management

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Design/Develop – Structured Data Cont’d

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Change Control Process • Effective process MUST be in place to ensure the overall integrity and

continuity of the EHR

• Generally a committee – collectively the members hold the total

knowledge about the EHR

• Changes formally presented to committee – required information about

the change documented and archived (may be several processes)

• Change evaluated against Quality, PI, Financial and other reporting to

ensure appropriate changes made to system, reporting if necessary

• Changes approved

• Changes trained, competencies documented if necessary

• Changes moved from test to live

QOPs & Nursing Informatics: Goals are Aligned

• QUALITY OUTCOMES PROGRAMS inherently move across the data-wisdom continuum (can be structure, process, outcome)

• QOPs provide PBE (practice based evidence) & are based on EBP & provide information on 2 levels

– Improve practice at the organizational level

– Provide data for future research studies on the EBP level

• Together the data and information from both PBE and EBP, when combined with other data create information and knowledge which coupled with the wisdom of nursing, or when appropriate - of interdisciplinary teams forms the basis for decision making about the care provided by the organization

QOPs & Nursing Informatics: Goals are Aligned

(cont.) Create an EHR that facilitates movement along the Data-Wisdom

Continuum fluidly and continuously

The EHR provides data, information, and knowledge of your

– Organization

– Patient populations

– Clinical practices

– QOPs

QOPs, NI Practice, Wisdom, & Experience of organizational and clinical leaders facilitates highest quality patient outcomes, and results in:

– Provision of healthcare VALUE to patients

DOMAIN of Informatics to ensure the system is designed and developed to ensure these goals can be achieved - because

The DATA to WISDOM continuum is the heart of Informatics

Proprietary & Confidential

– Jacobus Consulting

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Data are discrete

entities that are

described objectively

without interpretations –

e.g. Vital Signs in a

single moment of time

Information is data

that are interpreted,

organized or structured –

e.g. Chronological Set of

Vital Signs

Knowledge is

information that is

synthesized so that

relationships are

identified and formalized

– e.g. synthesis of the

observed trend with

nursing knowledge

Wisdom is the appropriate use of knowledge to manage and solve human problems.

It is knowing when and how to apply knowledge to deal with complex problems or specific human needs (Nelson, 1989, 2002)

Blum, in Nelson 2002 Added by

Gardiner 2011

NI Leadership – Improving QOPs through EHR

Design & Development

Nursing Informatics can lead the way

• Nursing Informatics Leaders Must – Have a good understanding of healthcare and its impact on nursing

– Understand flow of information across the EHR and how it can support coordination of care

– Have a good understanding of measures, reporting, data quality assurance, data storage, and management

– Have a good understanding of Nursing across its breadth and depth – needs, opportunities for EBP & PBE to improve care, the organization, and nursing as a profession

• Nursing Informatics Leaders must consistently employ Quality/CQI methodologies

• Nursing Informatics Leaders must have all the skills in every Informatics domain

Current Trends & Practices

NI Practitioners Are:

• Becoming highly competent / knowledgeable of global healthcare issues, reform, EBP/PBE & making sure nursing leaders have broad perspective to effectively lead nursing both primary nursing & care coordination roles

• Excelling in CQI & PI methodologies & applying to their practice regularly

• Helping bedside RNs become aware of information / knowledge availability & utilization of PI e.g. Kaiser UBTs (PDC/SA from an older era), Cleveland Clinic etc.

• Leading the way in providing tools and systems that enable nurses as knowledge workers

NI – in large IDNs lead or participate in QOPs, PBEs, especially

related to nursing & teach NI competencies in these areas to

bedside caregivers

Needed for Care Coordination & Transformation

More than ever, NI leaders must support the transformation of nurses & their leaders into Information Users:

– Sophisticated in their desire for data, information & knowledge

– Able to apply their wisdom and experience, making the best decisions for

Their Patients

Nursing

Their Organization

Critical Success Factors For NI To Lead Quality

Outcomes Improvement

• Clear Knowledge and Understanding of all aspects of Healthcare

Informatics

• Clearly Defined Informatics Program - System-wide and interdisciplinary

• Recognize EHR as foundational for healthcare into the foreseeable future

• Ability to perform in all 3 domains of informatics in BOTH Nursing &

Clinical Informatics

• Ability to translate data & information into knowledge & supply it to the

disciplines & organizational leadership for application of wisdom &

attainment/improvement of outcomes

• Ability to apply Informatics wisdom to data, information and knowledge to

drive informatics outcomes

• Quality team - partner and support

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Critical Success Factors For NI To Lead Quality

Outcomes Improvement (cont.)

• Clear Understanding of Healthcare – beyond department specific

understanding

– New healthcare environment

• Changes to Payment Models

• ARRA and other EHR incentives

• Advances in technology – SMART rooms and other tools

• Advances in social media and other uses of information in healthcare

– Regulatory impact and requirements

– Issues in Professional Practice

• Clearly defined job expectations

• Clearly defined and practiced accountability

• Clear understanding of the roles of care coordination & nursing in this

critical healthcare function

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Needed for Success:

Better Understanding

of the Role of the EHR

New ways of thinking

and doing

(Innovation)

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KNOWLEDGE – especially

about the EHR

New Roles & Practice Models

Evidence to guide practice

Understanding that change is

needed to incorporate new

and better knowledge into

practice

IMPROVE CLINICAL

QUALITY

OUTCOMES…

62

…THROUGH NURSING

INFORMATICS

LEADERSHIP OF EHR

DESIGN, DEVELOPMENT &

UTILIZATION

Questions?

63

Proprietary & Confidential

– Jacobus Consulting

64

References: •Amara, 2000 in Remus and Kennedy.. Nursing Leadership Vol 25, #4, 2012

•Crossing the Quality Chasm: A New Health System for the 21st Century. Washington, DC: National

Academic Press

•Englebardt, Sheila PhD RN CAN; Nelson, Ramona PhD RN BC. Healthcare Informatics: An

Interdisciplinary approach. Philadelphia, PA: Elsevier Health Sciences, 2001. Print.

•Gartner, 17 September 2010. ITScore Overview for Business Intelligence and Performance

Management. Analysts: Bill Hostman,m John Hagerty

•§ Institute of Medicine Committee on Quality of Health Care in America (Sackett, D L, Straus SE,

Richardson WS, Rosenberg W, Haynes RB. Evidence-Based Medicine: How to Practice and Teach

EBM. London: Churchill Livingstone; 2000, 2001).

Quality Informatics* Wikipedia

•Nursing Informatics – The intersection of Nursing Science, Information Science, and Computer

Science – ANA (American Nurse’s Association) AHRQ – http://www.ahrq.gov/news/test031809.htm

•Quality Informatics* Wikipedia

•The New England Journal of Medicine: Perspective: What Is Value in Health Care? Michael E.

Porter, Ph.D.N Engl. J Med 2010; 363:2477-2481December 23, 2010

•White, Kenneth R., and John R. Griffith. The Well-managed Healthcare Organization. Chicago, IL:

Health Administration, 2010. Print.