coursework-banner

NR 542 Wk 4 Database Plan SOLUTION

NR 542 Wk 4 Database Plan SOLUTION

An introduction informs about the topic of the paper and how it is organized.
Explanation of the selected problem and why it needs a database as an information-management solution
Explanation of a conceptual data model for the planned database
All entities planned for the database are named.
A justification or rationale for each entity is provided.
The E-R diagram for each entity is discussed briefly in the text and is found in an appendix. The E-R diagrams can be created for individual entities mapped to all other relevant entities or a single E-R diagram showing all entities and their relationships may be provided.
The identifier for each entity is named. The identifier can be narrated in the paper or included with the E-R diagram in the appendix.
The relationships between entities are discussed briefly in text and illustrated, including cardinality, in the E-R diagram in the appendix or in a separate appendix.
Three questions planned for the database are provided. The original questions presented in week 1 discussion may be used, or revised questions may be presented.
A conclusion that recaps the paper and discusses insights gained from working on this assignment is presented.

*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?*

Database Plan

Health care providers collect massive data daily about health, wellness, illnesses, and patients’ behaviors, among other essential elements. Access to this data enables health care providers to provide efficient, quality, and personalized care. Data is also instrumental in facilitating care coordination and ensuring that health outcomes meet patient needs. However, outcomes depend on how health care organizations and providers manage data. As a result, databases are crucial as information management systems for efficient and coordinated practice. A database can focus on a specific issue, combined issues, or an entire system. This paper discusses the use of a database in CAUTI management. It explains the problem and the need for a database, conceptual data model, entities, and identifiers. Other vital components include relationships between entities and questions planned for the database.

The Problem and the Need for a Database

Catheter-associated urinary tract infections (CAUTI) are among the leading hospital-acquired infections (HAIs) affecting patients’ health profoundly. According to Zaha et al. (2019), HAIs, such as CAUTI, complicate patients’ health, lead to extended hospitalizations, and increase the financial burden associated with treating and managing diseases. Addressing this challenge prompts health care providers to adopt best practices, including proper catheter insertion, interprofessional collaboration, and removal of catheters timely and medically recommended. Process monitoring is also essential to ensure that appropriate interventions are made as situations necessitate.

Like other critical health care processes, effective CAUTI management requires a database as an information-management system. As Leahy et al. (2020) noted, health care databases contain an organized collection of structured data, typically electronic, to facilitate easy access, control, and update. A database management system (DBMS) enables health care providers to optimize and manage information storage and retrieval from databases. Mostly in critical care units, nurses and other health care providers need accurate and up-to-date data on procedures applied in CAUTIs’ control. Information regarding unit compliance rate with proper urinary tract infection, catheter insertion, assessment, and documentation on foley care should be readily available. Such data would be a reliable reflection point on the safety and quality of care patients with CAUTI receive and whether further interventions are necessary as far as CAUTI management is concerned.

Conceptual Data Model for the Planned Database

A conceptual data model identifies entities and their relationships. From a health outlook, a conceptual model enables health care providers to understand and reflect on performance from a data perspective (Danese et al., 2019). The same case applies to the conceptual model on CAUTI management. It illustrates the critical components of the planned database, with a central focus on entities and relationships. The model further shows the variables that give the entities meaning such that health care professionals can understand and apply health information effectively based on what is contained in the database.

Entities Planned for the Database

In data management and database administration, entities represent people, objects, places, or things. Given this, entities in health care databases are usually health care providers, processes, illnesses, and relationships, among other elements whose data can be collected and stored. The data can be qualitative or quantitative. Since the planned database is about CAUTI and management practices, mainly catheter insertion and removal, the patient will be a central entity in the database.  The other important entity is CAUTI as the reference condition. Nurses can also be included as entities due to their central role in data collection and CAUTI management.

The rationale for Each Entity

Health care delivery cannot be considered complete without patients. Indeed, they are the primary reason why health care organizations exist. Health care plans, resources’ commitment, and evidence-based interventions to improve health outcomes focus on patients. Also, a significant proportion of the data collected and stored in the database will be on the patients and their statuses. Effective management of patient data will be pivotal in improving the care received and facilitating CAUTI prevention. CAUTI has been included as an entity since nursing processes focus on its prevention. A glance at the data and performance over time will guide health care providers in decision-making.

E-R Diagram for Each Entity and Identifiers

A database system contains different entities that relate differently. An entity-relationship (ER) diagram illustrates how entities relate within a system (Coronel & Morris, 2018). As provided (Appendix A), the flowchart shows how patient (entity 1) and CAUTI (entity 2) relate within the database system. Data on CAUTI can help health care providers to address specific patient needs based on the patient’s age, sex, and severity level, among other elements. The unique identifiers define the patient and the condition. Patient identifiers include name, age, sex, and medical record number (MRN). CAUTI identifiers include aseptic technique, foley catheter insertion, foley catheter assessment, and time.

Relationships between Entities

Nurses and other health care professionals require accurate information of patients, needs, and conditions to make correct decisions. In any case, the effectiveness of interventions applied in care plans depends on the accurateness of the information. As illustrated in the E-R diagram (Appendix A), nurses will rely on patient details and CAUTI information presented in the database. To understand the patient’s specifics, nurses will observe the patient’s name, age, sex, and MRN (four elements in a set). Regarding CAUTI, the focus will be the technique [aseptic], foley catheter insertion, time, and foley catheter assessment (four elements in a set). With this data, nurses will be in a better position to link patients with the services provided. They will also conveniently determine whether the patient receives the deserved care in successive evaluations. As illustrated in the E-R diagram, nurses cannot understand patients’ services and needs without patients’ specific information. In the same case, clicking on the patient’s MRN or name will direct nurses, supervising nurses, or unit managers to the type of services offered and their effectiveness in CAUTI prevention. The database can be modified over time as situations necessitate.

Database Questions

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

Conclusion

Today’s health care is highly data-driven, and health care providers should have ample data to guide decision-making. That data should be collected and managed professionally and must always be accurate. Accordingly, a database is vital in health practice to provide organized, structured information. Nurses can use such data to enhance health outcomes by guiding them in decision-making. CAUTI management is a critical issue due to the far-reaching consequences of CAUTI mismanagement. As discussed in this paper, a database with patients and CAUTI as entities can be instrumental in CAUTI management and prevention. Critical patient identifiers include name, age, sex, and MRN. CAUTI identifiers include aseptic technique, foley catheter insertion, time, and foley catheter assessment.

 

 

References

Coronel, C., & Morris, S. (2018). Database systems: Design, implementation & management. Cengage Learning US.

Danese, M. D., Halperin, M., Duryea, J., & Duryea, R. (2019). The generalized data model for clinical research. BMC Medical Informatics and Decision Making, 19(1), 1-13. https://doi.org/10.1186/s12911-019-0837-5

Leahy, T. P., Ramagopalan, S., & Sammon, C. (2020). The use of UK primary care databases in health technology assessments carried out by the National Institute for health and care excellence (NICE). BMC Health Services Research, 20(1), 1-9. https://doi.org/10.1186/s12913-020-05529-3

Zaha, D. C., Kiss, R., Hegedűs, C., Gesztelyi, R., Bombicz, M., Muresan, M., … & Micle, O. (2019). Recent advances in investigation, prevention, and management of healthcare-associated infections (HAIs): resistant multidrug strain colonization and its risk factors in an intensive care unit of a University Hospital. BioMed Research International, 2019. https://doi.org/10.1155/2019/2590563

 

Database Plan

 

The development of databases involves adherence to the set plans and procedures that outline all the stages required in ensuring a successful outcome. Database developers should consider different factors, including security, interoperability, and user interfaces. Other factors to be considered include cost and sustainability, usability, and functionality. Database developers use different approaches, including coding, already established programs such as Microsoft Access and Excel. When planning for the database design, there is the need to consider the perception of stakeholders and other policy-makers from the organizations where the system will be used. A properly designed database should be able to provide accurate and up-to-date information to the users. Since the correct database designs are important in achieving different goals, the investment of time required to plan and learn the principles of effective designs makes a lot of sense. In the end, there is a high possibility of ending up with a database system that meets the needs of an organization (Barthels et al., 2017). This paper elaborates on the plans and approaches in the design of a database to solve data insecurity problems that interfere with the continuity in the treatment processes. Further, the paper explains a conceptual data model for the planned database and considering all entities planned for the database.

Explanation of the Selected Problem and Why It Needs a Database as an Information-Management Solution

Data breaches are a common problem in the healthcare system that often lead to the loss of important information. It refers to the security violation where sensitive and confidential information is stolen, transmitted, viewed, and used by unauthorized individuals. When these data lands in the hands of criminals, they may use them to damage a healthcare organization’s reputation, intimidate patients, especially those in authority, and even demand ransom. Data breaches may also involve unintentional information disclosure, information leakage, data leak, and data spill. Many organizations struggle to develop secure databases that can reduce data reach and ensure efficiency and consistency in the treatment processes. Therefore, the problem of data breach requires an effective and secure database as an information management solution.

While designing the database, there is the need to factor in security issues in the planning processes. The database system needs to have secure access points so as to reduce the number of unauthorized users (Habib, 2019). The system also needs to enhance usability and interoperability so that it can support different healthcare providers through enhanced sharing of information. The databases should also be designed with the backup system and servers to prevent the complete deletion of information/data or editing of already stored information. The consideration of the above features in the design of the databases will significantly reduce data breaches and enhance information management activities.

Conceptual Data Model for the Planned Database and All Entities

The conceptual data model provides an organized perception of the concepts and the relationship that exists between them. The model establishes the entities that should be involved, their attributes, as well as the relationships that exist between them. The three components of this conceptual model include entities, attributes, and relationships (Affolter et al., 2019). Entity involves a real-world thing, attributes refer to the properties of characteristics of the entities, and relationship is defined as the association or dependency between any two given entities.

From the model, entities include patients and their healthcare information, including medication, laboratory tests, demographic data, etc. are entities. Healthcare information may also be defined as the products. The name of the healthcare services provided and the cost are the attributes of the product entity. Healthcare services are the relationship between the patients and their data/ information.

Justification for Each Entity

Patients and healthcare information/data are the two major entities recognized in the design of the database. The model is a basic reflection of the information required in the development of the database. Since the database will mainly be involved in the management of patients’ information/data, it is necessary to establish the relationship between the two. The patient’s information may also be referred to as a product. The patient (entity) may be given a code, or the actual name can be used. On the other hand, the product (patient’s data/information) may take different attributes, including text, digits, metadata, etc. The conceptual data model or domain model will be applied in the creation of the common vocabulary for all the stakeholders or users of the database system through the establishment of basic concepts and scope.

The E-R Diagram and Identifier for Each Entity

The E-R diagram indicates the relationship between entities, in this case, patients and healthcare data or information. The relationship between the two is the unique identifiers can define the service (s) provided. Some of the unique identifiers include the codes of medical service provided, such as laboratory test results, types of medication given, age group/age, patient’s ID, and time of service. For patients, the unique identifier is ID or name. The E-R diagram indicates all the entities, the relationship, and the unique identifiers.

Relationship between Entities

The model establishes the entities that should be involved, their attributes, as well as the relationships that exist between them. The three components of this conceptual model include entities, attributes, and relationships. The E-R diagram provides a back-to-back relationship between the entities, in this case, patients and healthcare services, both of which are represented by unique identifiers. The E-R diagram also represents the correlation between the entities or the unique identifies. The relationship between entities that the patients are the producer of healthcare products or unique identifiers. The primary key can be included to enhance the understanding of this relationship. The primary key can be drawn from the healthcare services database. With the establishment of effective relationships, each healthcare service product can be related or associated with the patients (product) within the database. The main objective here is to relate patients (patient’s ID) with the healthcare services and the data recorded. An individual can therefore be identified based on the information or data retrieved and vice versa.

Three Questions Planned for the Database

  1. What is the level of compatibility of the database and the hardware system that the organization plans to use?
  2. How can be the relationships between the entities, unique identifiers, and products established in case there is additional information required to be inserted into the database system?
  3. Is the database secure? Is the information provided encrypted so as to avoid access and possible deletion or general editing of data by unauthorized individuals?

Conclusion

The development of databases involves adherence to set plans and procedures that outline all the stages required in ensuring a successful outcome. Database developers should consider different factors, including security, interoperability, and user interfaces. Determination of the entities, attributes, and relationships are the major components of the database design processes. Also, the creation of models with the above factors is necessary for achieving the desired outcomes or the desired database system that can be used to maintain the security of data in the healthcare system.

References

Affolter, K., Stockinger, K., & Bernstein, A. (2019). A comparative survey of recent natural language interfaces for databases. The VLDB Journal, 28(5), 793-819. https://link.springer.com/article/10.1007/s00778-019-00567-8

Barthels, C., Alonso, G., & Hoefler, T. (2017). Designing Databases for Future High-Performance Networks. IEEE Data Eng. Bull., 40(1), 15-26. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.1039.5227&rep=rep1&type=pdf

Habib, M. K. (2019). On the Automated Entity-Relationship and Schema Design by Natural Language Processing. Int. J. Eng. Sci, 8(11), 42-48. https://theijes.com/papers/vol8-issue11/Series-3/F0811034248.pdf