Entity Relationship Diagram

Running Head: THS 1

THS 4

Clinical Repository

Candice RookHarvey

University of Arizona Global Campus

Professor Burton

HIA612: Technology Topics in Information Governance and Business Analytics

3 May 2021

An actual clinical repository is essential for gathering information that is in existence within its basic form, albeit in most cases with indexing that is additional. Theoretically, a clinical repository is in a position of being an excellent source of data for a clinical data warehouse. In reality, the designs of CDR are known for existing alongside the spectrum from actual repository into actual warehouse of data. The clinical repositories of data tend to be databases aimed at facilitating arbitrary data querying and analyses for research and reporting. Basically, they are considered to e secondary databases, meaning, they acquire data that has originally being input into different sources.

Part two

The healthcare industry digitization is having a rapid development. A core outcome of this given transformation happening from paper into records that are electronic is mainly the healthcare data proliferation. Through this, there is the database of healthcare. In massive figures. A database of healthcare has the aim of replacing the file folders, paper documents in addition to filing old cabinets. This data currently has more convenience and is immediate. Databases are in different forms, however, the type that is utilized commonly within the healthcare is the online transaction processing database abbreviated as OLTP. This type of database is one which a particular application of a computer runs on. A health records that is electronic is a suitable example of this application. An OLTP databases has it key strength which is enabling transactional processing that is quick and real-time. It had been designed for speed in addition to delivering responses that are fast and timely (Ahmed, et.al, 2020).

In addition, there is the Enterprise Data Warehouse which is considered to be a particular database that mainly exists in form of a layer that is on top of general transactional application databases of a healthcare organization. It has a structure that is essential in combining data from the databases of OLTP in addition to creating a later that is optimized for and one that is focused on analytics. The associated outcome is that organizations are capable of performing analysis that is sophisticated on the data coming from different sources which include: costing, EHR, billing, satisfaction of patients among others. The EDWs are becoming of importance in the realization of the full healthcare organizations benefit most of OLTP databases inclusive of EHRs.

The third is the Data operating system of health catalyst that assists the organizations of healthcare into moving beyond the warehouse of data. This system is basically a breakthrough approach of engineering that ends up combining the features of a clinical data repositories, data warehousing, as well as information exchanges of health within a single technology platform of common-sense. A DOS is known for providing the type that is ideal of the healthcare analytics platform due to its flexibility. It is categorized as a digital backbone that is vendor-agnostic for healthcare (Johnson, et.al, 2020)

Part three

Obviously, the benefits that are linked to the online transaction processing databases are similar to the ones linked to the applications running on them. The advances that are significant within automation as well as business standardization in addition to clinical processes might become attributable to the given databases and applications. The CDW intended for research is supposed to comprise of a broker system that is honest and an institutional board of review interface for complying with the regulations of a government. It is supposed to comprise of a query interface that is simple, a data review anonymized device, and a tool for data extraction. In addition, it is supposed to be a research platform that is biomedical for repository of data usage and data analysis. CDWs tend to integrate as well as reconstruct data that is raw from the EHRs alongside different systems for legacy for analysis, and are capable of adopting various interfaces required for the research compliance.

Part four

The nine elements within the documentation of data dictionary might be different though it practically involves some of these which are: Name, the patients account number and the address of residence, listings of objects of data, detailed data elements properties which are type of data, optionality, size and indexes, relationship of entity and different diagrams of system-level, reference data which involves descriptive and classification domains, quality-indicator codes and missing data in addition to business rules like the validation of data quality or schema.

Part five

My recommendation is usage of an Online transaction processing this is because with the databases of healthcare, data is capable of being externally stored in addition to being backed up within a place that is secure to prevent loss of data. In addition, due to the fact that the data is basically electronic, it is able to permit processing that is quicker of practical transactions like payment claims, lab results among others. Among the core benefits associated with these databases tends to be the data amount that healthcare organizations have the capacity to capture. They have resulted into massive stores of data that can be utilized in informing better care that is more cost effective (Sayeed, et.al, 2020).

References

Ahmed, S., Barbera, L., Bartlett, S. J., Bebb, D. G., Brundage, M., Bryan, S., … & Temple, W. (2020). A catalyst for transforming health systems and person-centred care: Canadian national position statement on patient-reported outcomes. Current Oncology, 27(2), 90. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7253746/

Johnson, M. R., Bolte, J., Veldman, T., & Sutton, L. (2020). Establishing a Project Management Community of Practice in a Large Academic Health System. Journal of Research Administration, 51(2). Retrieved from https://www.srainternational.org/blogs/srai-jra1/2020/09/29/establishing-a-project-management-community-of-pra

Sayeed, R., Gottlieb, D., & Mandl, K. D. (2020). SMART Markers: collecting patient-generated health data as a standardized property of health information technology. NPJ digital medicine, 3(1), 1-8. Retrieved from https://www.nature.com/articles/s41746-020-0218-6