Healthcare IT in Skilled Nursing and Post-Acute Care Facilities

411 Pages·2017·3.43 MB·English

University of South Florida
Scholar Commons
Graduate Theses and Dissertations Graduate School
10-13-2017
Healthcare IT in Skilled Nursing and Post-Acute
Care Facilities: Reducing Hospital Admissions and
Re-Admissions, Improving Reimbursement and
Improving Clinical Operations
Scott L. Hopes
University of South Florida, [email protected]
Follow this and additional works at:https://scholarcommons.usf.edu/etd
Part of theDatabases and Information Systems Commons, and theMedicine and Health
Sciences Commons
Scholar Commons Citation
Hopes, Scott L., "Healthcare IT in Skilled Nursing and Post-Acute Care Facilities: Reducing Hospital Admissions and Re-Admissions,
Improving Reimbursement and Improving Clinical Operations" (2017).Graduate Theses and Dissertations.
https://scholarcommons.usf.edu/etd/7409
This Dissertation is brought to you for free and open access by the Graduate School at Scholar Commons. It has been accepted for inclusion in
Graduate Theses and Dissertations by an authorized administrator of Scholar Commons. For more information, please contact
[email protected].
Healthcare IT in Skilled Nursing and Post-Acute Care Facilities:
Reducing Hospital Admissions and Re-Admissions, Improving
Reimbursement and Improving Clinical Operations

by

Scott L. Hopes

A dissertation submitted in partial fulfillment
Of the requirements for the degree of
Doctor of Business Administration
Muma College of Business
University of South Florida

Co-Chairman Jay Wolfson, Dr.P.H., J.D.
Co-Chairman Shivendu Shivendu, Ph.D.
Anol Bhattacherjee, Ph.D.
Kaushik Dutta, Ph.D.

Date of Approval:
October 13, 2017

Keywords: electronic medical record, EMR, EHR, Hospital Re-Admissions

Copyright ©2017 Scott L. Hopes
DEDICATION
I dedicate this dissertation to my wife Ronda and our three children, Aaron, Ariel and Zakary. To
my wife Ronda, who sacrificed so much and endured years of much time alone while Aaron,
Ariel, Zakary and I were in college simultaneously. During this time, Aaron finished his master’s
degree at the University of Chicago, completed a fellowship with the American Institute of
Indian Studies in Lucknow and Jaipur, India, and is now in the second year of his Ph.D. studies
at Stanford University, Ariel completed her psychology degree at Brandies University and
Zakary attended Florida International University, graduated from Miami Dade College and is
now studying at University of South Florida St. Petersburg. To my children: the pathway to
success is hard work and a continuous drive to obtain and retain knowledge and experience.
Share what you learn with others and remember, it is the journey through life that is important
and your success will come easier if the people around you want you to be successful! Ronda’s
support and sacrifices allowed all of us to pursue our educational goals, and I am eternally
grateful for her partnership, nurture, love and support.

Acknowledgements and Dedications reflect the views of the author and are not endorsed by
committee members or the University of South Florida.
ACKNOWLEDGEMENTS
I want to thank my close friend, mentor, professor and co-chair Dr. Jay Wolfson; it has been an
adventure since we first met at the University of South Florida, College of Public Health in 1984.
Your counsel and friendship have helped me to survive life’s many challenges over the decades.
I will always be grateful to Dr. Anol Bhattacherjee and Dr. Chris Davis, whose research in health
information technology inspired me to pursue this program and field of study. I want to thank my
dissertation co-chair, Dr. Shivendu Shivendu, for his insight and guidance throughout my
dissertation journey; I look forward to years of collaboration. I am extremely appreciative of Dr.
Kaushik Dutta’s thoughtful approach to challenging us during productive discussions and
debates while our dissertation cohort struggled with research design and development. Most
importantly I want to thank our DBA program directors Dr. Grandon Gill and Dr. Mathew
Mullarkey for their leadership and commitment; I also thank my colleagues in the first USF
DBA cohort class for their tolerance, patience, encouragement and support as we traveled this
path together.
Acknowledgements and Dedications reflect the views of the author and are not endorsed by
committee members or the University of South Florida.
Table of Contents

Introduction……………………………………………………………………………………….. 1

Review of Literature……………………………………………………………………………… 5

Methods…………………………………………………………………………………………..11
Research Questions……………………………………………………………………………. 12
Hypotheses…………………………………………………………………………………….. 13
Data……………………………………………………………………………………………. 13
Research Design………………………………………………………………………………..18
Assumptions ……………………………………………………………………………………20
Results………………………………………………………………………………………… .22
Introduction…………………………………………………………………………………… .22
Descriptive Statistic…………………………………………………………………………… 22
Multivariate Analysis………………………………………………………………………….. 22
Operational Performance……………………………………………………………………… 24
Employee Engagement…………………………………………………………………………26
Staff Retention Rate…………………………………………………………………………… 27
Total Staff Turnover…………………………………………………………………………... 28
CMS Five Star Total Score……………………………………………………………………. 32
CMS Five Star Quality Measure………………………………………………………………. 32
Complaint Tags……………………………………………………………………………….. 32
Facility Deficiency Index……………………………………………………………………… 33
Failed Survey Revisits………………………………………………………………………… 34
Return to hospital (readmissions)……………………………………………………………... 34
Financial Performance………………………………………………………………………… 35
Staff overtime…………………………………………………………………………………. 36
Bad Debt………………………………………………………………………………………. 37
Revenue performance against budget…………………………………………………………. 37
Hypotheses Testing Results Summary…………………………………………………………37

Conclusion………………………………………………………………………………………. 40

References……………………………………………………………………………………….. 44

i
Appendices………………………………………………………………………………………. 46
Appendix1
Long Term Care Minimum Data Set 3.0……………………………………………………. 47
Appendix 2
Design for Nursing Home Compare Five-Star Quality Rating System……………………..100
Appendix 3
Pairwise Comparisons……………………………………………………………………….151
Appendix 4
SPSS Reports………………………………………………………………………………..154
Appendix 5
Data Table- Variables and Labels…………………………………………………………..409

ii
List of Tables

Table 1: Means, Adjusted Means, Standard Deviations and Standard ..........................................24

Table 2: Adjusted Means ...............................................................................................................25

Table 3: Pairwise Comparisons .....................................................................................................26

Table 4: Clinical Performance Indicators: Adjusted Means ..........................................................30

Table 5: Clinical Performance Indicators: Pairwise Comparisons ................................................31

Table 6: Financial Performance Indicators: Adjusted Means ........................................................35

Table 7: Financial Performance Indicators: Pairwise Comparisons ..............................................36

iii
List of Figures
Figure 1: Data Matrix.....................................................................................................................17

Figure 2: Employment Engagement Score ....................................................................................27

Figure 3: Staff Retention Rate by HIT Group ...............................................................................28

Figure 4: Staff Turnover Rate by HIT Group ................................................................................29

Figure 5: CMS Five Star Total Score by HIT Group.....................................................................32

Figure 6: CMS Five Star Quality Score by HIT Group .................................................................32

Figure 7: Complaint Tags Score ....................................................................................................32

Figure 8: Return to Hospital Rates by HIT Group .........................................................................33

Figure 9: Staff Overtime ................................................................................................................37

Figure 10: Contributors to Hospital Readmissions ........................................................................43

iv
ABSTRACT

Health information technology (HIT), which includes electronic health record (EHR)
systems and clinical data analytics, has become a major component of all health care delivery
and care management. The adoption of HIT by physicians, hospitals, post-acute care
organizations, pharmacies and other health care providers has been accepted as a necessary (and
recently, a government required) step toward improved quality, care coordination and reduced
costs: “Better coordination of care provides a path to improving communication, improving
quality of care, and reducing unnecessary emergency room use and hospital readmissions.
LTPAC providers play a critical role in achieving these goals” (HealthIT.gov, 2013).
Though some of the impacts of evolving HIT and EHRs have been studied in acute care
hospitals and physician office settings, a dearth of information exists about the deployment and
effectiveness of HIT and EHRs in long-term and post-acute care facilities, places where they are
becoming more essential. This dissertation examines how and to what extent health information
technology and electronic health record implementation and use affects certain measurable
outcomes in long term and post-acute care facilities. Monthly data were obtained for the period
beginning January 1, 2016 through June 30, 2017, a total of 18 months. The level of EHR
adoption was found to positively impact hospital readmission rates, employee engagement,
complaint deficiencies, failed revisit surveys, staff overtime (partial EHR), staff turnover rate
(full EHR) and United States Centers for Medicare and Medicaid Services (CMS) Five Star
Quality score. The level of EHR adoption was found to negatively impact CMS Five Star Total
v
score, staff retention rate (full EHR) and staff overtime (full EHR group higher than partial
EHR).

vi