NR 542 W7 Database Project Final SOLUTION

Upload a copy of the (Excel/Access/Libre ) database that was developed for your project, Please note if you do not attach the database that was developed for your project to the assignment, 20 points will be deducted.
Develop Power Point providing an overview of the project including:
Introduction establishes topic and organization of presentation
Reason for database is provided, including supporting evidence
Structure of the database developed for this project is described, including conceptual, logical, and physical models; can be presented as text, graphics, or a combination
Relational tables are presented in standard format, with primary keys identified, any secondary keys identified if used, attributes with one data characteristic for each attribute, and normalization issues identified and resolved
Three questions developed for database plan
Description of how database was tested
Results of testing, including any needed changes
Recap of entire project
Insights on information management developed from working on project
Speaker Notes are provided for each slide, except for title and references slides, and provide sufficient depth to allow someone else to take over the presentation.

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12-15 slides for the powerpoint

The database questions are
1) What is the unit compliance rate with proper urinary catheter infection?
2) Did 2 nurses verify catheter insertion?
3) Is there an assessment, implementation, and documentation on foley care and the need for insertion/removal to prevent CAUTIs?

Introduction

NR 542 W7 Database Project Final SOLUTION

Overview of Healthcare Information Management

Data collection benefits not just doctors, but also patients, health insurers, and many stakeholders in the health care industry. The concept of gathering patient data predates healthcare services itself.
Nurses and doctors authored, reviewed patient charts, collected information, and recorded their procedures. That knowledge is now fully digital, resulting in a data set that is easily accessible and distributable.
Currently , a lot of information is being gathered from patients. Nobody would obtain or comprehend the information required to adequately care for their patients without appropriate data management.
As a result, the need for a database to keep CAUTIs records and procedures arose to leverage EHRs to improve the quality of care and strengthen patient interactions.

It is harder to diagnose and treat a medical problem without knowing the background (Bossen et al., 2019). The CAUTIs database contributes by providing background information based on past records. Because health care providers may instantly access the database, the information they need are accessible anytime they need them. For instance, Healthcare-associated infections (HAIs) are a major source of illness, mortality, and unnecessary spending in all healthcare institutions. Such information is crucial for medical professionals as it will guide on the next steps to take. According to Pérez et al. (2017), HAIs afflicts one out of every twenty patients in the hospital at any given moment. The Agency for Healthcare Research and Quality (AHRQ) is sponsoring a countrywide effort to promote the adoption of the Comprehensive Unit-based Safety Program (CUSP) to minimize catheter-associated urinary tract infection (CAUTI) in healthcare settings as part of the National Action Plan. This can be achieved by ensuring records of CAUTIs infection are kept properly to allow nurses and doctors analyze the trends and take necessary precautions to mitigate the problem (Adane et al., 2019).

The goal of this project is create a database focusing on the various features of CAUTIs diagnosis and treatment.
The database will help in establishing whether or not two nurses have confirmed catheter insertion and whether or not there has been an assessment, implementation, and documentation on foley care and the necessity for insertion/removal to prevent CAUTIs.

Nurses can monitor for effective diagnoses and intervention of symptomatic and catheter-associated UTIs by continuously monitoring how frequently urine cultures are taken for all patients with or without indwelling catheters (AHRQ, 2017). This database will assist them in identifying the best effective approach to manage CAUTI. Effective antibiotic treatment of urinary tract infections, for example, is a critical component of infection prevention; tracking the number of urine cultures collected and proper prescription patterns can help in this quest.

Reason for developing cautis

CAUTIS diagnosis and treatment provide data that must be handled with care.

The health of a patient is dependent on this data, thus it is critical that nurses and other medical personnel have access to it as soon as possible.

The objective of the proposed CAUTI database is to:

Increase efficiency in diagnosis and treatment of CAUTI.

Enhance data sharing among medical professionals involved in patient care.

Assist in assessing the effectiveness of CAUTI prevention strategies.

The above reasoning has been based on the question, “Why are databases crucial in CAUTIs intervention?” A well-designed database system is critical to the day-to-day operation of the Health sector. The right technology is enabling health care practitioners to acquire relevant data that will improve patient outcomes (Bossen et al., 2019). Policymakers can also utilize this data to reform and implement better CAUTI intervention and management. The exchange of information among providers and organizations will also improve patients’ access to high quality care (Databerry, 2020). The medical profession is continually evolving, and there is an increased demand for appropriate technology, data management, and database design.

Database structure

A Conceptual Data Model (CDM) is a theoretical representation of database ideas and their relations. The goal of developing a conceptual data model is to define objects (entities), their characteristics (attributes), and their associations (relationships) (Conceptual, Logical and Physical Data Model, 2021). At this level of data design, there is little information available about the underlying database structure. A conceptual data model is often created by business stakeholders and data engineers. The entities in our database are patienr, nurse, and CAUTI.

Database structure

The Logical Data Model is used to specify the model for data pieces as well as their relationships. The logical database design supplements the conceptual data architecture parts with additional information. The benefit of using a Logical data model is that it serves as a basis for the Physical model. The modeling framework, nevertheless, remains basic. There are no primary or secondary keys declared at this modeling level (Conceptual, Logical and Physical Data Model, 2021). At this design level, you must double-check and fine-tune the connector parameters that were previously defined for relationships.

Database structure

A Physical database model defines a data model’s database-specific execution. It provides database abstraction and aids in the generation of the database schema. This is due to the abundance of meta-data provided by a Physical Data Model. By duplicating database field keys, constraints, indexing, events, and other RDBMS characteristics, the physical model also aids in comprehending the structure of the database (Conceptual, Logical and Physical Data Model, 2021). The physical data model covers the data requirements for a specific project or program, albeit it may be merged with other physical database systems depending on the scope of the project. The Data Model includes relationships between tables that manage the nullability and cardinality of the relationships. Columns must contain precise type of data, sizes, and default values.

Relational tables

A relational table is a table with fields or columns that represent a set of data (or records). A relational table, for instance, patient table may include fields such as patient ID, patient name, admission date, and patient address. In the above patient table, Patient ID has been set as primary key which can be used as unique identifier in the table. Each attribute on the table has been assigned a data type.