MHA-FPx5016, Beth Doeden, Assessment 4 Health Information Improvement Proposal.edited
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Health Information Improvement Proposal
Beth Doeden
Capella University
MHA-FPX5016 Introduction to Health Information Systems
Oct 3, 2023
2
Abstract
This proposal talks about replacing our current EHR and other software with a new EHR,
which will better accommodate our organization's needs in reporting, decision support, and
workflow development and improvement to improve current practices.
Storage and data security
and the benefits associated with cloud storage in analytics will be reviewed.
In all, best practices
and recommendations are made identifying what our organization needs out of an EHR, what is
needed for implementation and support, reporting, expected outcomes, security, benefits, and
how this work will support our goals.
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Introduction
The current technology does not meet our needs to meet our goals for patient outcomes
and meaningful use.
We have analyzed the current state, needs, and implementation process of
new technology.
We are also losing revenue with our current EHR and processes due to poor
workflow, poor or incomplete data collection, and systems that need to be integrated.
The
following is a report of the data collected and a recommendation.
Recommendations for Technology and Goals
During the analysis, it became apparent that we have many different systems to perform
different organizational functions.
Many of them have limited or no interface to our current
EHR, which can result in patient errors, affect patient safety, excessive wait times for vital
information, penalties, increased costs, and dissatisfaction among staff and patients
(Bowman,2013).
Implementing a new EHR that supports all areas of the organization can improve clinical
workflow, patient outcomes, productivity, and positive financial impact.
Providers will be able
to increase their scope, complexity of documentation, and productivity while receiving
incentives by meeting meaningful use measures consistently and adequately (Ohno-Machado,
2014).
We can create alerts and decision support to improve patient outcomes significantly.
Meaningful use data will be easily accessible and reportable to meet our objectives.
Nursing
productivity can significantly improve by reducing redundancy, wayfinding through multiple
systems, reduced documentation, and increased productivity, giving more time to bedside care
(Lindsay, 2022).
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EHRs were initially created to help with administrative tasks focusing on billing (Shickel,
2018).
Our current EHR needs to fulfill its original function.
However, with a fully functional
EHR, our billing processes will significantly improve with all areas feeding into the same data
repository, giving billing the information and accuracy needed to perform their functions,
reducing denials and, potentially, manpower.
However, there have been shortcomings with EHR implementations that have had
detrimental effects on organizations, and we will need to remain vigilant to avoid these errors
and prevent unforeseen blunders.
Poor design and improper use can jeopardize the system's
integrity, leading to penalties, legal implications, loss of revenue, patient harm, and even death
(Bowman, 2013).
It will also leave the staff with a sense of distrust for the EHR.
Data integrity
and key stakeholders' involvement are essential to help prevent and identify errors.
The
stakeholders need to understand their roles in acquiring information, research, process
development, and support and the importance of this work (Yip, 2014).
With this dedication and
support, implementations result in better employee engagement, financial detriment, and patient
harm.
Adopting a new EHR has historically been challenging in most healthcare organizations,
so we need to have the right stakeholders involved in the process.
The diverse backgrounds of
all stakeholders are fundamental to capturing the essence of the organization as a whole
(Olayiwola, 2016).
The stakeholders are also essential to promote the EHR and support the
functions and processes that accompany the implementation and ongoing support.
EHRs are a necessity for the success of meaningful use.
It digitalizes healthcare
information, which can easily be transferred to agencies, other software, reports, and digital
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support tools, to name a few (Séroussi, 2015).
A strong understanding of these digital processes
and coordination of health information is essential to create a foundation for proper utilization of
an EHR and data collection to successfully report out for meaningful use (Séroussi, 2015).
Updates and workflows must also be constantly monitored to remain compliant in meaningful
use and for patient safety and decision support.
EHRs are not foolproof, and errors do occur.
We
need staff dedicated to monitoring and correcting these errors, whether through software updates
or workflow adjustments (Vanderhook, 2017).
We will need staff who can understand and
analyze workflow from clinical and administrative aspects.
This staff would act as a liaison
between operations, clinical, and technical areas.
They must build a rapport with others to
establish trust and a good working environment.
They must understand administrative and
clinical operations to develop and recommend new workflow, fixes, and service improvements.
They would need to have strong attention to detail and problem-solving skills.
They will need to
be able to work independently and as part of a team.
They may also need to be on call after
hours.
Qualifications would be a bachelor's degree in health information management with
certifications required by our EHR and other software.
A bachelor's degree in nursing or coding
would be needed for analysts with specialized interests.
Alternatively, we would consider those
who have four or more years of EHR and meaningful use experience with examples of proven
success.
When reviewing salaries on multiple hiring platforms, on average, an EHR analyst with
benefits will cost the organization approximately $91,000 per analyst annually (Salary.com, n.d.).
According to Health Services Research, in 2012, 3.1 billion was paid to 2,000 hospitals and
41,000 providers in incentive payments (Appari,2013).
After 2015, penalties would be applied
to those not meeting meaningful use.
In 2017, an additional penalty will occur, reducing
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Medicare reimbursement if meaningful use is not met.
Taking into consideration incentives and
penalties incorporated with meaningful use, it is essential to invest in a team that can work to
ensure our success.
Otherwise, we will stand to lose millions upon millions of dollars.
Aside
from meaningful use incentives and penalties, the EHR's potential for process, decision support,
and workflow improvements will help reduce overall costs to the healthcare organization (Bar-
Dayan, 2013).
Efficient provider documentation, ordering, and electronic consultations will
reduce the manpower needed in transcription, billing, and referrals, saving the organization
potentially hundreds of thousands per year (Bar-Dayan, 2013).
Implementation procedures will also need to be considered.
There are many roles to fill
in this process, including super users, project management, training, and technical support, which
will be fulfilled by additional overtime hours or hiring additional staff; both will have costs.
On
average, a large hospital will require around 110-120 super users, and smaller hospitals will
require about 70 super users (Bullard, 2016).
Training of all employees will also need to be
considered.
Super users can be cross-trained into trainers and potential IT informatics
professionals permanent placement.
Labor expense is an unavoidable expense but essential for
overall success.
Data, Security, and Best Practice
For years, EHRs have been collecting data, storing data, and converting the information
into reportable forms and used as decision support.
Meaningful use and other governmental
programs are the primary drivers of having structured data that is easily reportable, leveraged,
and stored (Bonney, 2013).
Organizations must identify analytic tools and best practices for
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effective and efficient use of the EHR and data collection.
Structured and patient information is
the basis for searchable, actionable, interoperable, and reportable data, which will feed and
collaborate with analytics, billing, and other interacting areas in the EHR (Bonney,2013).
The
demands and understanding of healthcare and the EHR require those who do this work to have a
specialized background, such as those who work in health information management.
Those in
this group have a history and the education and training best suited for data management,
collection, and extraction (Bonney, 2013).
In addition, specific areas of structured management
impact HIM, including transcribed reports, clinical-based documentation, and other areas that
may interface or feed or data warehouse (Bonney, 2013).
Some areas include clinical notes,
ICD-10 and CPT codes, and HL7 interface messages.
Storing protected health information can be done in a few different ways.
Today, the
most used is cloud-based storage provided by cloud services providers or CPSs (OCR, 2016).
A
CPS can store information and simplify data, making reporting more accessible and sometimes
allowing the organization to develop products and infrastructure to best suit their needs (OCR,
2016).
This will simplify or enhance our ability to report to meaningful use, creating decision
support tools and billing.
We can expect services from the CPS: system reliability and
availability, backup and data recovery, security, and data retention (OCR, 2016).
The CPS we choose will need to be HIPAA-compliant.
We will enter into a HIPAA-
compliant contract or business associate agreement, BAA, identifying the data will be stored and
retrieved securely and the measures in place to ensure the secure transmission and storage of data
(OCR, 2016).
Aside from being HIPAA compliant, CPSs also have additional security rules,
which add another layer of security.
When sending HIPAA-compliant data from the healthcare
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organization to the cloud, the CPS will run additional checks to ensure the data is HIPAA-
compliant.
This is called a security rule (OCR, 2016).
Conclusion
To better meet the needs of our organization, a change in our EHR is imperative to meet
our goals for meaningful use and patient outcomes.
The analysis clearly explains our needs and
recommendations to meet these objectives.
A new EHR will improve clinical decision support
and tools, workflow, reporting, and revenue.
Otherwise, we stand to lose reimbursement and
potentially face penalties due to non-compliance.
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References:
Appari, A., Eric Johnson, M., & Anthony, D. L. (2013).
Meaningful use of electronic health
record systems and process quality of care: evidence from a panel data analysis of U.S.
acute-care hospitals.
Health services research
,
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(2 Pt 1), 354–375.
https://doi.org/10.1111/j.1475-6773.2012.01448.x
Bar-Dayan, Y., Saed, H., Boaz, M., Misch, Y., Shahar, T., Husiascky, I., & Blumenfeld, O.
(2013).
Using electronic health records to save money.
Journal of the American Medical
Informatics Association : JAMIA
,
20
(e1), e17–e20.
https://doi.org/10.1136/amiajnl-2012-
001504
Bonney, S. (2013).
HIM's Role in Managing Big Data: Turning Data Collected by an EHR into
Information.
Journal of AHIMA
,
84
(9), 62–64.
https://bok.ahima.org/doc?oid=300108
Bowman S. (2013).
Impact of electronic health record systems on information integrity:
quality and safety implications.
Perspectives in health information
management
,
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(Fall), 1c.
Bullard, K. L. (2016). Cost-Effective Staffing for an EHR Implementation.
Nursing Economics,
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(2), 72-76.
http://library.capella.edu/login?qurl=https%3A%2F%2Fwww.proquest.com
%2Fscholarly-journals%2Fcost-effective-staffing-ehr-implementation%2Fdocview
%2F1783691668%2Fse-2%3Faccountid%3D27965
Office for Civil Rights (OCR).
(2016, October 6).
Cloud Computing
.
HHS.gov.
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https://www.hhs.gov/hipaa/for-professionals/special-topics/health-information-
technology/cloud-computing/index.html
Ohno-Machado L. (2014). Electronic health record systems: risks and benefits.
Journal of the
American Medical Informatics Association : JAMIA
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(e1), e1.
https://doi.org/10.1136/amiajnl-2014-002635
Lindsay, M. R., & Lytle, K. (2022).
Implementing Best Practices to Redesign Workflow and
Optimize Nursing Documentation in the Electronic Health Record.
Applied clinical
informatics
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(3), 711–719.
https://doi.org/10.1055/a-1868-6431
Séroussi, B., Jaulent, M. C., & Lehmann, C. U. (2015). Health Information Technology
Challenges to Support Patient-Centered Care Coordination.
Yearbook of medical
informatics
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(1), 8–10.
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Shickel, B., Tighe, P. J., Bihorac, A., & Rashidi, P. (2018).
Deep EHR: A Survey of Recent
Advances in Deep Learning Techniques for Electronic Health Record (EHR) Analysis.
IEEE journal of biomedical and health informatics
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(5), 1589–1604.
https://doi.org/10.1109/JBHI.2017.2767063
Yip, M. H., Phaal, R., & Probert, D. R. (2014). Stakeholder Engagement in Early Stage Product
Service System Development for Healthcare Informatics: EMJ.
Engineering
Management Journal, 26
(3), 52-62.
http://library.capella.edu/login?qurl=https%3A%2F
%2Fwww.proquest.com%2Fscholarly-journals%2Fstakeholder-engagement-early-stage-
product%2Fdocview%2F1561957611%2Fse-2%3Faccountid%3D27965
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Vanderhook, S., & Abraham, J. (2017). Unintended Consequences of EHR Systems: A Narrative
Review.
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in Health Care, 6(1), 218–225.
https://doiorg.library.capella.edu/10.1177/2327857917061048