Adjusting the Database to Improve Integrity Assignment

The database should be refined to enhance data integrity and efficiency in clinical decision-making. The focus on clarity for enhancing one-to-many aspects of the database is essential to improving the integrity of data and strengthening its support in decision-making and managing the underlying issues and needs. For instance, the department’s table should link to the facilities through the facility ID with foreign numerical data or unique identifiers in this strategy. Similarly, the employee training records should link employee training to each department to correctly identify the employee training associated with the organization’s knowledge development or continuous knowledge activities such as workshops, continuous medical education sessions, and other activities or sessions that allow knowledge and skill development (Harrington, 2016). Every employee must log in using their ID and the training ID to allow for accurate data tracking and referential integrity for the data managed in the organization. Adjusting the Database to Improve Integrity Assignment

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The process of choosing the correct data type for coding a problem involves the following steps: The reason for qualified data types is to preserve the integrity of the data collected. For instance, in the case of the Employees table, DOB should be defined as DATE, Employee ID as INTEGER, and FirstName and LastName should be defined as VARCHAR with the necessary length restrictions. They ensure the data stored in each field is correct and good for use by minimizing invalid information. Likewise, the ‘Duration’ in the Training Programs table should also be of INTEGER type as it is the number of hours. Reducing the data type minimizes the vulnerability of data corruption and amplifies data validations.

Ways of Reducing the Risk of Poor Data Integrity

Due to this, it is crucial to use constraints like NOT NULL, UNIQUE, and CHECK to minimize the vulnerability of low data integrity. For example, the Employee ID column in the Employees table should be made unique to avoid the duplication of value. In contrast, the Department ID column should be designated as NOT NULL to ensure every employee is assigned to a department. Further, integrity constraints, particularly the foreign key constraints, guarantee that entries in associated tables are valid (Richesson et al., 2023). These measures help avoid invalid data entry into the database and thus help maintain the data’s validity.

Eliminating Duplicate Data

One of the advantages associated with normalization techniques is the removal of duplicate data. For instance, normalization, where data is partitioned into several associated tables to avoid repetition of information. For example, two fields in the Employee Competencies table – Employee ID and Competency ID- should have different values for each record to eliminate duplicate values. Using such features as Departments and Facilities in lookup tables also avoids duplication. This means that repeated data are eliminated. If changes or updates are to be made in a particular data, this has to be done only once in the suitable table so that all the other tables in the database will also reflect the change. Adjusting the Database to Improve Integrity Assignment

Healthcare information technology should allow for implementing unique and appropriate strategies and mechanisms that achieve the best and optimal results. These systems should enable smooth and efficient data flow and provide professionals with opportunities to solve specific design problems, such as one-to-many relations (Awrahman et al., 2022). Identifying the proper data types, constraints, and normalization guarantees the database’s effective work. These strategies develop a firm foundation for dependable data storage, retrieval, and management based on the unique characteristics available in this database that allow for smooth and efficient data management strategies.

References

Awrahman, B. J., Aziz Fatah, C., & Hamaamin, M. Y. (2022). A review of the role and challenges of big data in healthcare informatics and analytics. Computational Intelligence and Neuroscience, 2022(5317760), 1–10. https://doi.org/10.1155/2022/5317760

Harrington, J. L. (2016). Relational Database Design and Implementation (4th ed.). Morgan Kaufmann.

Richesson, R. L., Andrews, J. E., & Hollis, K. F. (2023). Clinical research informatics. Springer Nature.

Post an explanation of how you would adjust your design described in the Week 3 Discussion to address specific design issues such as one-to-many relationships and identification of data types. Be specific and provide examples. Explain how you would reduce the risk for poor data integrity and eliminate duplicate data. Support your plan with citations below
Harrington, J. (2016). Relational database design and implementation (4th ed.). Cambridge, MA: Morgan Kaufmann. Adjusting the Database to Improve Integrity Assignment

Chapter 5, “The Relational Data Model” (pp. 89–106)

Lo, C. K.-M., Ho, F. K.-W., Chan, K. L., Wong, W. H.-S., Wong, R. S.-M., Chow, C.-B., … Ip, P. (2018). Linking healthcare and social service databases to study the epidemiology of child maltreatment and associated health problems: Hong Kong’s experience

The Journal of Pediatrics, 202, 291–299.e1.

Week 3 discussion posted below:
Envisioning Database Design

Tables and Fields

Employees

Employee ID (Primary Key)

FirstName

Last Name

DOB (Date of Birth)

Gender

Position

Department ID (Foreign Key to Departments Table)

Facility ID (Foreign Key to Facilities Table)

Hire Date

Facilities

Facility ID (Primary Key)

Facility Name

Address

City

State

Zip Code

Phone Number

Departments

Department ID (Primary Key)

Department Name

Facility ID

Training Programs

Training ID (Primary Key)

Training Name

Description

Duration (hours)

Department ID (Foreign Key to Departments Table)

Instructor

Competencies

Competency ID (Primary Key)

Competency Name

Description

Department ID

Employee Training Records

Record ID

Employee ID

Training ID

Completion Date

Score

Status (Completed, in progress, no started)

Employee Competencies

Record ID

Employee ID

Competency ID

Assessment Date

Proficiency level

Evaluator

Rationale for the Design

The design of the database has certain entities that are critical in the comprehensive management of training and competency mandates (Patrician et al., 2010). The employee table is critical for the storage of information about the people that should complete training and achieve certain competencies. The facilities table captures the details of the different hospital facilities where the staff members work, while the department table organizes the facility by ensuring that there is employee grouping to allow for effective training. The table on training programs consists of a list of all the training programs that employees might complete while the competencies table defines the competencies that should be achieved by the employees. Lastly, the employee competency table monitors the competency and the level of proficiency of the employees. The design is critical in ensuring that a structure is followed for the management of training and competency data thus fostering data accessibility and overall reporting (Harrington, 2016). Adjusting the Database to Improve Integrity Assignment

Benefits of converting Data to Electronic Format

Conversion of data from paper to an electronic format is integral and has certain benefits. The benefits help to enhance access to data and overall management. Electronic data are easily accessible and this allows for their access anywhere within an organization. In the sequel, this boosts efficiency and ensures that information is always available when needed. Aside from that, a centralized database helps to simplify updates and ensure that information is at hand when needed. A centralized database simplifies the updates and maintenance and this makes it easy to keep records current and accurate.

Further, enhanced accuracy of the data and integrity are other advantages of converting data to an electronic format. The conversion minimizes the risk of human errors associated with manual input of data. Also, electronic records bolster reliability. Consistency is also enhanced across the different facilities and departments and also prevents discrepancies and any confusion.

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There is also streamlined reporting and compliance when data is converted to an electronic format. Electronic records foster the generation of reports on training and status of competency. As such, thus provides critical insights at a glance. The reports are needed to ensure there is compliance with the regulations. They aid in ensuring that timely and accurate data is availed for auditing and reviewing.

Efficient management of resources is supported by conversion of electronic data. Through tracking of the progress of the staff members, there is a timely identification of the training needs. This ensures that all the members are up-to-date with the needed competencies (Priest, 2020). Besides, insights to the workforce competencies support effective allocation of resources and allow for deployment of personnel and training equipment. From this, it is clear that transitioning to an electronic format provides major improvements in efficiency, accuracy, reporting, and management of resources. The shift is needed to enhance the efficacy of operations and this leads to improved performance of an organization therein. Adjusting the Database to Improve Integrity Assignment