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 p
NR 542 Wk 4 Database Plan SOLUTION
atients’ 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
- What is the unit compliance rate with proper urinary catheter infection?
- 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