The Relationship between Nursing Excellence and Electronic Health Record Adoption

218 Pages·2017·1.33 MB·English

by  Christine Lippincott

University of Miami
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2014-11-17
The Relationship between Nursing Excellence and
Electronic Health Record Adoption
Christine Lippincott
University of Miami, [email protected]
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UNIVERSITY OF MIAMI

THE RELATIONSHIP BETWEEN NURSING EXCELLENCE AND
ELECTRONIC HEALTH RECORD ADOPTION

By
Christine Lippincott

A DISSERTATION

Submitted to the Faculty
of the University of Miami
in partial fulfillment of the requirements for
the degree of Doctor of Philosophy

Coral Gables, Florida
December 2014
©2014
Christine Lippincott
All Rights Reserved
UNIVERSITY OF MIAMI

A dissertation submitted in partial fulfillment of
the requirements for the degree of
Doctor of Philosophy

THE RELATIONSHIP BETWEEN NURSING EXCELLENCE AND
ELECTRONIC HEALTH RECORD ADOPTION

Christine Lippincott

Approved:

____________________ _____________________
Martin Zdanowicz, Ph.D. Brian McCabe, Ph.D.
Professor of Clinical Research Assistant Professor
of Nursing and Health Studies of Nursing and Health Studies

___________________ _____________________
Todd Ambrosia, Ph.D. Anne Felteau, Ph.D.
Assistant Professor of Clinical Contributing Faculty
of Nursing and Health Studies Walden University

___________________ ______________________
Cynthia Foronda, Ph.D. M. Brian Blake, Ph.D.
Assistant Professor of Nursing Dean of the Graduate School
Johns Hopkins University
LIPPINCOTT, CHRISTINE (Ph.D., Nursing)
The Relationship between Nursing Excellence and (December 2014)
Electronic Health Record Adoption

Abstract of a dissertation at the University of Miami.

Dissertation supervised by Dr. Martin Zdanowicz.
No. of pages in text. (202)

The United States government has invested over a billion dollars to support the
nationwide implementation, adoption, and “meaningful use” (MU) of electronic health
record (EHR) technology. The American Reinvestment and Recovery Act of 2009
represents just one example of how the delivery of healthcare services is evolving from a
fee-for-service to a pay-for-performance model that is data-driven. Under the Centers for
Medicare and Medicaid Services (CMS) Meaningful Use (MU) Program, hospitals that
fail to demonstrate how their use of electronic health record systems improves patient
outcomes will not only lose EHR incentive payments, but could face financial penalties
beginning as early as 2015. The transition from paper to electronic records is challenging
and end-user resistance is a commonly cited reason for EHR implementation failures.
Nurses are the largest group of hospital clinicians and the largest group of EHR end-
users, yet there is minimal research on the relationship between the level of nursing care
and the successful adoption of EHRs in U.S. hospitals.
The aims of this non-experimental quantitative study were to: (a) examine the
relationship between nursing excellence and EHR adoption, and (b) examine the
relationship between the tenure of nursing excellence and EHR adoption. The predictor
variable of nursing excellence was operationalized by Magnet recognition by the
American Nurses Credentialing Center (ANCC) as of December 2013. The predictor
variable of tenure of Magnet status was represented by two groups, Early-designation
(initial designation occurring from 1994-2009) and Recent-designation (initial
designation occurring from 2010-2013). The outcome variable of EHR adoption was
operationalized by positive receipt of at least one payment from the CMS for the
Medicare EHR Incentive Program or the achievement of Level 6 or 7 on the Health
Information and Management Systems Society (HIMSS) Analytics Electronic Medical
Record Adoption Model (EMRAM) as of December 2013. This study utilized two
distinct target populations and two distinct samples. The MU analyses only included
hospitals that were eligible for the Medicare EHR Incentive Program based on their CMS
facility category. Out of a possible 393 United States (U.S.) Magnet hospitals, 330
represented the target population for the MU hypotheses. Out of a possible 6,582 U.S.
hospitals, 4,929 were included in the study sample for the MU analyses. The HIMSS
Analytics EMRAM analyses did not exclude hospitals that were ineligible for the
Medicare EHR Incentive Program, and they also were independent of healthcare
organizations’ CMS reporting structures. Out of a possible 393 U.S. Magnet hospitals,
all 393 represented the target population for the HIMSS Analytics hypotheses. Out of a
possible 6,582 U.S. hospitals, 6,419 were included in the study sample for the HIMSS
Analytics analyses. Data were analyzed using binary logistic regression.
Magnet-designated hospitals had 3.58 times greater likelihood than non-Magnet
hospitals of receiving Medicare EHR incentive payments for MU attestation (p < .001).
Magnet hospitals also had 3.68 times greater likelihood than non-Magnet hospitals of
achieving Level 6 on the HIMSS Analytics EMRAM (p < .001), and 4.02 times greater
likelihood than non-Magnet hospitals of achieving Level 6 or 7 (p < .001) when Levels 6
and 7 were combined together as one outcome variable. No significant relationships
were found between Magnet status and the achievement of HIMSS Analytics EMRAM
Level 7 when it was analyzed as an individual dependent variable (p = .802). No
significant relationships were found between the tenure of Magnet status and any of the
measures of EHR adoption.
Further study implications include the examination of multiple hospital
characteristics that may contribute to EHR adoption and the qualitative exploration of
nursing leaders’ perspectives at Magnet organizations that have successfully adopted
EHR technology.
Dedication
This work is dedicated to my family who continually inspire me to achieve the
highest standard possible and to face adversity with strength and perseverance. This
dissertation is also dedicated to S.D., R.S., S.R., S.S., and B.C.J. for their unconditional
love and support throughout the years.

iii
Acknowledgements
The author wishes to acknowledge several individuals and organizations for their
support and assistance.
! Professor Martin Zdanowicz, Ph.D., committee chair, and members of the
dissertation committee: Professor Brian McCabe, Ph.D., Professor Todd
Ambrosia, Ph.D., Professor Anne Felteau, Ph.D., and Professor Cynthia Foronda,
Ph.D. for their guidance and expertise. This dissertation could not have been
possible without all of your hard work.
! Dean Nilda Peragallo Montano, DrPH for granting me the opportunity of a
lifetime.
! Professor Victoria Mitrani, Ph.D. for her commitment to broadening the scope of
research at the School of Nursing and Health Studies.
! Professor Julie Barroso, Ph.D. for her assistance through the dissertation process.
! Faculty and Staff at the University of Miami School of Nursing and Health
Studies, especially Ms. Elizabeth Markowitz and Ms. Marta Medina.
! Faculty and Staff at the University of Miami Graduate School.
! The American Nurses Credentialing Center.
! The Health Information Management and Systems Society.
! Fellow doctoral students at the University of Miami School of Nursing and Health
Studies for their kind words of encouragement.
! Doris K. Benna for her many hours of editing assistance.

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TABLE OF CONTENTS

Page

LIST OF FIGURES…………...…………………………………………………… ix

LIST OF TABLES…………….…………………………………………………… x

LIST OF ABBREVIATIONS...…………………………………………………… xi

Chapter

1 INTRODUCTION……………………………………………………… 1
Background of the Study………………………….................................. 1
The Healthcare Regulatory Landscape…………………………………. 4
Meaningful Use………………………………………………………… 4
MU Stage I……………………………………………………………… 7
Nursing’s Role in Meeting Stage I Criteria…………………………….. 11
MU Stage II…………………………………………………………….. 12
MU Stage III……………………………………………………………. 17
HIMSS Analytics EMR Adoption Model …..………………………….. 18
Affordable Care Act and Value-Based Purchasing…………………….. 20
Nursing Excellence and Magnet Recognition………………………….. 21
Journey to Magnet……………………………………………………… 22
2008 Magnet Recognition Program Application Manual……………… 24
Electronic Health Record Life Cycle…………………………………… 25
The Connection between Nursing Excellence and EHR Adoption…….. 27
Statement of the Problem……………………………………………….. 29
Purpose of the Study……………………………………………………. 30
Significance of the Study……………………………………………….. 30
Research Questions………………………………................................... 31
Hypotheses……………………………………………………………… 31
Theoretical Frameworks………………………………………………... 32
The Donabedian Quality Framework………………….……………….. 32
Application of the Donabedian Quality Framework to this Study.……. 33
The Magnet Model…………………………………………………….. 35
Transformational Leadership…………………………………………… 36
Structural Empowerment……………………………………………….. 37
Exemplary Professional Practice……………………………………….. 38
New Knowledge, Innovations, and Improvements……………………... 38
Empirical Outcomes……………………………………………………. 39
Application of the Magnet Model to this Study………………………... 40
Assumptions…………………………………………………………….. 41
Summary………………………………………………………………... 42
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