803 task 1 use 3

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Western Governors University *

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C803

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Information Systems

Date

Dec 6, 2023

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docx

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7

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Data Analytics and Information Governance - C803 8/4/2023 .
Data Analytics and Information Governance – Task 1 2 Contents A. Data Type Characteristics ..................................................................................................................... 3 A1. Data Types Examples ............................................................................................................................. 3 A2. Sources of Data ..................................................................................................................................... 4 A3. Appropriateness of Data ........................................................................................................................ 4 B. Uniform Data Set ................................................................................................................................. 5 C. Application Data Dictionary ................................................................................................................. 6 C1. Justification Data Dictionary .................................................................................................................. 6 D. Resources ................................................................................................................................................ 7
Data Analytics and Information Governance – Task 1 3 A. Primary data in a healthcare setting is collected firsthand from the patient by a healthcare professional when providing care or service to the patient. Also, primary data is known to be generally more factual and original than secondary data, with the intent of creating a solution to the problem at hand (Surbhi, 2020). Primary data is often used to gather specific and detailed information that may not be available in existing databases. Hence, primary data can be very costly to an organization since the research is being done solely by them, leading to additional investment resources and staffing needed (Surbhi,2020). Secondary data sources are often information from a primary source that someone else has already collected for a different purpose (Oachs & Watters, 2020). Secondary data are easily obtained, saving researchers time and resources. However, secondary data are less accurate than primary data. Primary and secondary data can be used in decision-making and improvement. Both can consist of patient-identifiable data. Secondary data is also known as aggregate data, which is data on a group of patients without identifying a specific patient and is past data. Primary data is real-time data and is specific to a researcher's needs. A1. Primary and secondary data sources can be applied in a healthcare setting differently. A primary care physician may provide a patient with a wearable device to monitor the patient's sleep pattern. The primary data collected by this wearable device is transmitted wirelessly to the primary care physician system, which allows continuous monitoring of the patient's sleep
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Data Analytics and Information Governance – Task 1 4 pattern, and this information can be used to analyze or identify any abnormal pattern. A unique example of secondary data that can be applied is by analysis of the electronic health record to identify a pattern or trend in the pandemic(covid-19). Researchers can use the information to identify patients with similar symptoms or diagnoses within a specific geographic area. Secondary data is helpful to medical staff in identifying patterns and trends that can be helpful for patient care and benchmarking with other organizations (Oachs & Watters, 2020). A2. A relevant source for primary data is the patient health record which provides healthcare providers with comprehensive information about a patient medical and family history which can be used for patient care, research, and clinical decision-making. A relevant source for secondary data in a healthcare setting is the cancer registry, a database that collects, manages, and analyzes information on cancer cases within a specific population or healthcare institution. It contains data on various aspects of cancer, such as the patient demographic, tumor characteristics, cancer staging, treatment, and outcome (National Cancer Institute, n.d). The cancer registry provides a follow-up for the registered patients annually by attempting to obtain information about whether the patient is still alive, the status of the cancer, and the treatment the patient has received during this period (Oachs & Watters, 2020). A3. The patient health record is vital to healthcare because it provides comprehensive patient information, including demographic information, medical diagnosis, treatment plan, medication, and test results. Also, when multiple providers are involved in patient care, the
Data Analytics and Information Governance – Task 1 5 health record allows for seamless communication and coordination, which aids in providing the patient with optimal care. A. The uniform hospital discharge data set (UHDDS) is a standardized format for collecting and reporting data on patients discharged from the hospital. The information from the uniform hospital discharge data set can be used as a quality improvement by a healthcare organization to analyze and compare their patient outcomes, length of stay, and readmission rates with another healthcare organization. This data can be used to identify improvement areas and implement a targeted intervention to enhance the quality of care. The uniform hospital discharge data set (UHDDS) is used in hospitals to collect data on patients discharged from hospitals within a specific area by many states (Oachs & Watters, 2020). B. Data dictionaries comprehensively describe the data elements used in a specific system or database. It also serves as a reference guide for providing information about each data element's purpose, definition, format, and usage. A data dictionary is critical to ensuring data quality throughout a health information system (Oachs & Watters, 2020). There are two essential types of data dictionaries for developing health information systems. The database management system data dictionary for a specific database with a built-in data dictionary, and the modern database management system developed goes beyond the dictionary because it stores information about data relationships (Oachs & Watters, 2020).
Data Analytics and Information Governance – Task 1 6 The second type of data dictionary is the organization-wide data dictionary that is developed outside the framework of a specific database design process, and the data dictionary serves to promote data quality through data consistency across the organization(Ochs & Watters. A data dictionary in a health information system will help reduce inconsistencies and facilitate effective data sharing. C1 Data dictionaries can improve an organization's communication across the continuum of care by providing a standardized and consistent reference for data elements. Data dictionaries allow interoperability between different health information systems to ensure a seamless exchange of patient information, supporting continuity of care and improving communication between healthcare providers. A data dictionary is used to support medical professionals in a healthcare organization in exchanging information across several clinical systems through standardization (Oachs & Watters, 2020). D. Resources National Cancer Institute. (n.d.). What is a cancer registry? NIH National Cancer Institute. https://seer.cancer.gov/registries/cancer_registry/cancer_registry.html Oachs, P., & Watters, A. (2020). Health Information Management, Concepts, Principles, and Practice (6th ed.). American Health Information Management Association (AHIMA). https://wgu.vitalsource.com/books/9781584267577 Surbhi, S. (2020, July 13). Difference Between Primary and Secondary Data https://keydifferences.com/difference-between-primary-and-secondary-data .
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Data Analytics and Information Governance – Task 1 7