HEALTH ADM-HCI660 Grand Canyon University – Describe the two online databases you worked with in VLab. that is related to health care
QUESTION
Describe the two online databases you worked with in VLab. that is related to health care
Describe how you utilized health information technologies, applications, tools, processes, and structures to manage health data.
Which specific analytics technologies are utilized most often by health care organizations?
Analyze and interpret the data from the Tableau VLab and explain how the data can be used to improve health care quality and health-related outcomes and promote wellness among populations? Please provide reference to support your explanation and answers. please provide reference to support your answers and explanations.
ANSWER
Utilizing Health Information Technologies and Analytics to Improve Healthcare Quality and Outcomes
Introduction
In the field of healthcare, the use of health information technologies and analytics has become crucial for managing health data effectively. This essay will discuss two online databases used in VLab related to healthcare, explore the utilization of health information technologies, applications, tools, processes, and structures for managing health data, and examine specific analytics technologies commonly employed by healthcare organizations. Furthermore, we will analyze and interpret data from Tableau VLab and explain how it can be utilized to improve healthcare quality, health-related outcomes, and promote wellness among populations.
Online Databases in VLab Related to Healthcare
VLab, an online learning platform, offers a wide range of databases for healthcare professionals. Two notable databases include PubMed and the Healthcare Cost and Utilization Project (HCUP) database.
PubMed: PubMed, a widely used database, is a resource for accessing biomedical literature and scientific research articles. It provides a vast collection of studies related to health and medical fields, including clinical trials, systematic reviews, and observational studies. Healthcare professionals can use PubMed to stay updated on the latest research, gather evidence-based information, and make informed decisions about patient care.
Healthcare Cost and Utilization Project (HCUP) database: The HCUP database, maintained by the Agency for Healthcare Research and Quality (AHRQ), is a comprehensive resource that contains healthcare data from various sources, including hospital discharges, emergency department visits, and ambulatory surgery. It allows healthcare professionals to examine trends, patterns, and outcomes in healthcare utilization, costs, and quality. This database enables researchers and policymakers to understand healthcare delivery, identify areas for improvement, and make informed decisions regarding resource allocation.
Utilizing Health Information Technologies for Managing Health Data
Health information technologies play a vital role in managing health data efficiently and securely. Various applications, tools, processes, and structures are employed for this purpose:
Electronic Health Records (EHRs): EHRs are digital versions of patients’ medical records, containing comprehensive information about their health history, diagnoses, medications, and treatments. Health professionals utilize EHRs to store, retrieve, and exchange patient data securely. These records enhance care coordination, facilitate communication among healthcare providers, and support evidence-based decision-making.
Health Information Exchange (HIE): HIE enables the secure sharing of patients’ health information across different healthcare organizations. It allows authorized providers to access comprehensive patient data, irrespective of the healthcare setting. HIE promotes seamless coordination, reduces duplicate tests, and enhances patient safety by providing a complete picture of the individual’s health.
Clinical Decision Support Systems (CDSS): CDSS utilize algorithms and data analytics to provide healthcare professionals with evidence-based recommendations at the point of care. These systems help clinicians make accurate diagnoses, select appropriate treatment options, and prevent medical errors. CDSS also facilitate adherence to clinical guidelines, leading to improved patient outcomes.
Analytics Technologies in Healthcare
Healthcare organizations leverage various analytics technologies to extract valuable insights from vast amounts of health data. The following are some commonly utilized analytics technologies:
Data Mining and Machine Learning: Data mining techniques, coupled with machine learning algorithms, enable healthcare organizations to identify patterns, correlations, and predictive models from complex datasets. These technologies assist in predicting disease outcomes, identifying high-risk patients, and personalizing treatment plans, ultimately improving care quality and outcomes.
Natural Language Processing (NLP): NLP allows healthcare professionals to extract and analyze unstructured data from sources such as clinical notes, research articles, and social media. By applying NLP techniques, healthcare organizations can gain insights from textual data, such as patient feedback, clinical narratives, and social determinants of health, which contribute to enhancing population health management strategies.
Predictive Analytics: Predictive analytics employs statistical models and algorithms to forecast future events or outcomes based on historical data. Healthcare organizations use predictive analytics to anticipate disease outbreaks, optimize resource allocation, and proactively manage population health. It enables early interventions, reduces healthcare costs, and improves patient outcomes.
Analyzing and Interpreting Data from Tableau VLab
Tableau VLab provides a powerful visualization platform to explore and interpret healthcare data. By creating interactive dashboards and visual representations, healthcare professionals can gain insights, identify trends, and make data-driven decisions. For instance, data from Tableau VLab can be used to analyze patient outcomes, track performance indicators, and identify areas for quality improvement in healthcare delivery.
By leveraging the data from Tableau VLab, healthcare organizations can make evidence-based decisions that enhance care coordination, optimize resource utilization, and improve patient outcomes. These insights can drive initiatives to promote wellness among populations, target preventive interventions, and address health disparities effectively.
Conclusion
Utilizing health information technologies, including databases like PubMed and HCUP, along with analytics technologies such as data mining, NLP, and predictive analytics, is vital for managing health data and improving healthcare quality and outcomes. The insights gained from analyzing data through platforms like Tableau VLab can inform evidence-based decision-making, enhance care coordination, and promote wellness among populations. Embracing these technologies enables healthcare organizations to advance healthcare delivery, optimize resource allocation, and ultimately improve population health.
References
PubMed: https://pubmed.ncbi.nlm.nih.gov/about/
Healthcare Cost and Utilization Project (HCUP) database: https://www.hcup-us.ahrq.gov/overview.jsp
Electronic Health Records (EHRs): https://www.healthit.gov/topic/health-it-basics/benefits-electronic-health-records-ehrs
Health Information Exchange (HIE): https://www.healthit.gov/topic/health-it-basics/health-information-exchange-basics
Clinical Decision Support Systems (CDSS): https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3045179/
Predictive Analytics: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3995231/
Natural Language Processing (NLP): https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4912589/
Tableau VLab: https://www.tableau.com/academic/students
How Data Analytics is Changing Healthcare: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4605307/

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