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Database Project Proposal
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Database Project Proposal
Regardless of the advancement in technology and medicine, congestive heart failure
management has been an issue in the United States, affecting more than six million citizens (Nair
et al., 2020). This concern is mirrored by the increased readmission rates and rising morbidity
and mortality linked with chronic congestive heart failure. The chronic disorder’s effects also
spread to the post-discharge course. Capturing data in a database has the potential to enhance
healthcare quality and performance measurement. As a result, this database proposal aims to
describe the database’s purpose and objectives in reducing hospital readmission among chronic
congestive heart failure patients.
Statement of the problem
Even though a patient might have been to the cardiac care unit several times and been
discharged, clear instructions are always critical. In this respect, relevant patient and health status
records must be included during discharge, which the nurse or cardiologist cannot automatically
obtain without database records. Whenever missing details or unclear information are provided
due to human error, there is a higher probability that the patient will be necessitated to revisit the
cardiac care unit for readmission. The data captured in a database will aid in reducing such
problems, thus minimizing readmission.
Database Users
The database users will encompass the chief of cardiology, the nurse manager, registered nurses,
and the cardiologist. The cardiologist interprets and requests laboratory results and meets and
examines patients with heart defects and coronary heart disease, among other conditions. Nurses
help with diagnostics, including specialized tests and echocardiograms. They also educate
patients in the cardiac care unit. Nurse managers have a critical role since they oversee the
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cardiac care unit’s financial, legal, and ethical aspects. The chief of cardiology directs employees
and programs within the cardiac care unit.
Types of Data Collected
The database will be used to store laboratory results such as brain natriuretic peptide,
health status data, and hospital discharge. This data will generate readmission rate reports,
reports on patient contacts with the cardiologist, and medical history reports. The nurse manager
will use the readmission rate reports to enhance case management plans and the overall quality
of care. The nurses will use the laboratory medical history reports to educate patients about
medication adherence, their lifestyles, enhancing their quality of life. Cardiologists will utilize
medical history reports to track the follow-up appointments and the medical regime’s
effectiveness.
Project Goals and Measurable Objectives
Implementing the database will ensure relevant information is offered to all clinicians and
will assist them in making future decisions. Consequently, patients will gain since less time is
spent on repeating tests. Furthermore, the database will prevent the prescription of inappropriate
remedies and inaccurate diagnoses. Queries will be executed on the database, and the analyses
and reports will be utilized to enhance decision-making (Mathioudakis, Rousalova, Gagnat,
Saad, & Hardavella, 2016). Readmission rates will be the main measurable objective. Since
patient information is easily accessible, clinicians will utilize it to check patients’ progress and
status and schedule follow-ups, thus reducing readmission rates.
Potential Problems or Barriers
Efforts to enhance healthcare results have grown beyond minimizing morbidity and mortality to
incorporate quality of life measures and costs, such as reducing the occurrence of hospital
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readmission using database records (Inamdar & Inamdar, 2016). However, some issues can
hinder this project’s objective, such as when patients use different systems for readmission.
There is no devised method to uniquely identify patients throughout varying healthcare systems,
across massive networks of providers, or even within the healthcare spectrum. The problem
arises every time the information is captured in different forms and systems, leading to possible
errors in patient identification. Database training to the other staff would be challenging as we
have to find additional time resources and trainers. In addition, the cost of the program training
and further hardware updates may hinder the program as the budget has to be approved by the
hospital authority.
Conclusion
Record keeping involves multiple diverse facets and ensures proper and safe healthcare delivery
to patients in the cardiac care unit. The cardiac care unit can use database records to evaluate
their healthcare services and current performance to improve their quality of care continuously.
Additionally, the reports can function as vital tools for enhancing and monitoring the quality and
value of healthcare services. These efforts can lead to improved patients’ well-being and reduced
readmission rates.
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References
Inamdar, A. A., & Inamdar, A. C. (2016). Heart Failure: Diagnosis, Management, and
Utilization. J Clin Med, 5(7), 62.
Mathioudakis, A., Rousalova, I., Gagnat, A. A., Saad, N., & Hardavella, G. (2016). How to keep
good clinical records. Breathe (Sheff), 369–373.
Nair, R., Lak, H., Hasan, S., Gunasekaran, D., Babar, A., & Gopalakrishna, K. V. (2020).
Reducing All-cause 30-day Hospital Readmissions for Patients Presenting with Acute
Heart Failure Exacerbations: A Quality Improvement Initiative. Cureus, 12(3).
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Database Project Proposal – Part 2
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Database Project Proposal – Part 2
Discharging patients from the cardiac care unit is a complicated procedure that
encompasses many aspects and requires proper consideration since clear information is critical.
A database can help include all the patient information and health status records required during
discharge. On the other hand, the absence of a database can increase readmission rates because
of human error. Human error is the leading cause of unclear information and missing details. As
a result, there is a high probability that a patient will revisit the healthcare facility for
readmission. This paper aims to establish a database schema to resolve such concerns and
minimize readmission.
Project Goals and Objectives
A database in the cardiac care unit will offer an essential mechanism for handling,
organizing, and preserving crucial organizational and patient health statistics, including
laboratory results and patient discharge data. The organization’s processes, including individual
and large-scale processes, rely on the efficiency and accuracy of healthcare data (Kodama et al.,
2019). As a result, the benefits of implementing a database system in the cardiac care unit cannot
be overemphasized – the technology is essential for management teams, cardiologists, and nurse
practitioners in accessing in-depth health data with increased speed and no error.
The data stored in the database will be critical in averting and reducing unplanned
readmissions. Such reduction will enhance the financial wellbeing of the facility and the patients’
quality of life. This matter can be reinforced by the increased mortality and morbidity and rising
readmission rates associated with congestive heart failure. In the United States, avoidable
readmissions cost around 15 to 21 billion dollars yearly (Hoang-Kim et al., 2020). Storing
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patient information in the database will also be essential in performance measurement, ultimately
improving healthcare quality.
Purpose of Database Schema
The cardiac care center will utilize the database schema to store critical information,
including hospital discharge, follow-up appointment dates, and vital signs. This data will be
essential in producing medical history reports, cardiologist and patient contact reports, and
readmission rate reports. The readmission rate reports are of key interest since they will aid the
management in adjusting the quality of care and developing case management plans. The
laboratory medical history reports will assist in educating patients on how to improve their
wellbeing. The database schema will also facilitate early detection of chronic congestive heart
failure by storing data that the cardiac care unit will use to surveil risk factors (Suzuki et al.,
2018). Due to the reliable data and records, the organization will perform analyses that form the
basis for decisions concerning care and management.
Processes Associated with Business Rules
All employees in the cardiac care unit have unique identification numbers. At least one or
more cardiologists should examine a patient. Similarly, one or more nurses are also required to
take vital signs and produce discharge reports. Before or during discharge, the cardiac care unit
should devise a post-treatment plan, and the patient should know all the necessary details,
including follow-up appointments and consultations. Different employees should be assigned for
the in-clinic and telehealth consultation in the post-treatment plan.
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Data Dictionary
TABLE
NAME
ATTRIBUT
E NAME
CONTEN
TS
TYPE
FOR
MAT
RA
NG
E
REQU
IRED
P
K
O
R
F
K
INTEGE
R
XXX
X
NA
Y
P
K
FIRST
NAME
VARCH
AR(50)
XXX
X
NA
Y
LAST_NAM LAST
E
NAME
VARCH
AR(50)
XXX
X
NA
Y
MIDDLE_I
NITIAL
MIDDLE
INITIAL
VARCH
AR(2)
XXX
X
NA
Y
PHONE_NO
PHONE
NUMBER
VARCH
AR(50)
+
XXX
XXX
XXX
X
NA
Y
DOCTOR_I
D
DOCTOR
CODE
INTEGE
R
XXX
X
NA
Y
SPECIALTY DOCTOR’ VARCH
S
AR(50)
SPECIALT
Y
XXX
NA
Y
QUALIFICA DOCTOR’ VARCH
TIONS
S
AR(50)
QUALIFIC
ATIONS
XXX
NA
Y
EMPLOYEE EMPLOY
_ID
EE CODE
INTEGE
R
XXX
NA
Y
F
K
NURSE_ID
INTEGE
R
XXX
X
NA
Y
P
K
SPECIALTY NURSE’S VARCH
SPECIALT AR(50)
Y
XXX
NA
Y
EMPLOY EMPLOYEE EMPLOY
EE
_ID
EE CODE
FIRST_NA
ME
CARDIO
LOGIST
NURSE
NURSE
CODE
FK
REFERE
NCES
TABLE
P
K
EMPLOY
EE
5
PATIEN
T
DISCHA
RGE
QUALIFICA NURSE’S VARCH
TIONS
QUALIFIC AR(50)
ATIONS
XXX
NA
Y
EMPLOYEE EMPLOY
_ID
EE CODE
INTEGE
R
XXX
NA
Y
F
K
PATIENT_I
D
PATIENT
CODE
INTEGE
R
XXX
NA
Y
P
K
FIRST_NA
ME
FIRST
NAME
VARCH
AR(50)
XXX
NA
Y
LAST_NAM LAST
E
NAME
VARCH
AR(50)
XXX
NA
Y
MIDDLE_I
NITIAL
MIDDLE
INITIAL
VARCH
AR(2)
XXX
NA
Y
PHONE_NO
PHONE
NUMBER
VARCH
AR(50)
+
XXX
XXX
XXX
X
NA
Y
SSN
SOCIAL
SECURIT
Y
NUMBER
VARCH
AR(50)
XXX
NA
Y
DISCHARG
E_ID
DISCHAR
GE CODE
INTEGE
R
XXX
NA
Y
VITAL_SIG
NS
VITAL
SIGNS
VARCH
AR(150)
XXX
NA
Y
WEIGHT
PATIENT
WEIGHT
DECIMA ####
L
0999
Y
DISPOSITI
ON_AD
DISPOSIT
ION
AFTER
DISCHAR
GE
VARCH
AR(50)
XXX
X
NA
Y
DATE_DIS
CHARGED
DATE
DISCHAR
GED
DATE
DDMMYYY
Y
NA
Y
P
K
EMPLOY
EE
6
DATE_AD
MITTED
DATE
ADMITTE
D
DATE
DDMMYYY
Y
NA
Y
DOCTOR_I
D
DOCTOR
CODE
INTEGE
R
XXX
X
NA
Y
F
K
CARDIO
LOGIST
PATIENT_I
D
PATIENT
CODE
INTEGE
R
XXX
NA
Y
F
K
PATIENT
NURSE_ID
NURSE
CODE
INTEGE
R
XXX
X
NA
Y
F
K
NURSE
POST
TREATM
ENT
PLAN
CODE
INTEGE
R
XXX
NA
Y
P
K
FOLLOW_U
P
APPOINTM
ENT
WEEKLY
FOLLOWUP
APPOINT
MENT
WEEKLY
DATE
DDMMYYY
Y
NA
Y
FOLLOW_U
P
APPOINTM
ENT
MONTHLY
FOLLOWUP
APPOINT
MENT
WEEKLY
DATE
DDMMYYY
Y
NA
Y
DISCHARG
E_ID
DISCHAR
GE CODE
INTEGE
R
XXX
NA
Y
F
K
DISCHA
RGE
HOME_HE
ALTH
CONSULTA
NT
HOME
INTEGE
HEALTH
R
CONSULT
ANT
XXX
NA
Y
F
K
EMPLOY
EE
HOME
TELEHEALTH
CONSULTA
NT
HOME
INTEGE
TELER
HEALTH
CONSULT
ANT
XXX
NA
Y
F
K
EMPLOY
EE
POST
PTP_ID
TREATM
ENT
PLAN
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Entity-Relationship Diagram
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Database Schema
Projected costs
Component
Amount
Cost of acquiring resources used
in project such as new software,
cables. Cost of sources used to
manage data.
Training costs for staff, and
hosting costs.
$ 2,000
IT expert costs and Office and
other expenses beyond the above
specified
$4,000
$2,500
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Areas that Seemed Difficult
Reducing redundancy in the database was the main challenging area during the design.
Initially, some data was included in more than one table, which was not ideal for data integrity,
update efficiency, speed of queries, disk space usage, and security violations. The resulting
database schema eliminated repetition and used logical and standard naming conventions.
Another challenging area involved knowing which attributes to leave out since they applied
calculated fields. For instance, storing the number of times a patient is readmitted was
unnecessary since such information could be obtained using discharge admitted and date
discharged data.
Project Limitations and Viable Extensions
Financial barriers form the main concern for the database system’s implementation. The
database design is among the start-up costs required to get the database system running in the
cardiac care unit. Other start-up costs encompass installation expenses and the cost of purchasing
software and hardware. Besides start-up costs, implementing the database system will necessitate
an excessive commitment to training, support, maintenance, control, and system administration
to ensure it functions efficiently and effectively. Long-term expenditures can include the costs of
maintaining and upgrading the database system. All these costs can hinder the adoption of the
database system. Possible extensions include establishing data-sharing initiatives among other
cardiac care units.
Conclusion
This paper suggests that the data stored in the database schema has a vital role in the
cardiac care unit since it can produce a pool of relevant information concerning congestive heart
failure. Additionally, this information can enable the healthcare facility to analyze the quality of
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care offered to patients. The management can also utilize reports to aid administrative planning
and facilitate the establishment and implementation of improvement measures. Most importantly,
the data accuracy and accessibility can assist in minimizing human error, which consequently
will reduce readmission rates.
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References
Hoang-Kim, A., Parpia, C., Freitas, C., Austin, P. C., Ross, H. J., Wijeysundera, H. C., ... &
Rochon, P. A. (2020). Readmission rates following heart failure: a scoping review of sex
and gender based considerations. BMC cardiovascular disorders, 20(1), 1-19.
Kodama, K., Sakamoto, T., Kubota, T., Takimura, H., Hongo, H., Chikashima, H., ... & Nakao,
K. (2019). Construction of a Heart Failure Database Collating Administrative Claims
Data and Electronic Medical Record Data to Evaluate Risk Factors for In-Hospital Death
and Prolonged Hospitalization. Circulation reports, CR-19.
Suzuki, S., Yoshihisa, A., Sato, Y., Kanno, Y., Watanabe, S., Abe, S., ... & Takeishi, Y. (2018).
Clinical significance of Get with the Guidelines–Heart Failure Risk Score in patients with
chronic heart failure after hospitalization. Journal of the American Heart
Association, 7(17), e008316.
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