Introduction
Information systems technology uses processes, techniques, and tools to manage healthcare data. The healthcare sector deals with large amounts of data, needing a data management and analysis system. There are several methods and techniques for performing analysis depending on the purpose of the research and the nature of the industry (Mathews, 2019). Data mining has helped providers decide on the best methods of delivering quality healthcare and improving patient outcomes (Amin, Chiam, & Varathan, 2019). New technologies facilitate the efficiency of healthcare professionals by allowing access to substantial quantities of knowledge.
Two Databases
During the Vlab assignment, I worked with two online databases: Tableau and Meditech Expanse. Tableau is among the leaders in data analytics and visualization and is preferred in the healthcare sector due to its high functionality. In addition, Tableau offers a worldwide membership, online forums, and training programs that help its users. It features several products, including a Tableau desktop, reader, viewer, explorer, and the public (“Health Care Cost and Utilization Project,” n.d.). Tableau embodies data extraction and blending features, a multipurpose dashboard, ask data feature, forecast, and enhanced data visualization functions. Furthermore, Meditech Expanse is an electronic health record system that provides a clinical database for healthcare professionals and patients. Meditech helps healthcare providers view patients’ health history, lab results, and notes. The system enables one to view a patient’s activity and group different pieces of information to view them on a single screen. My experience with both databases was quite informative and beneficial for my understanding of the healthcare sector.
Health Information
Frankly, I have not used a variety of health information technologies, applications, tools, processes, and structures, but I am familiar with how they perform. I do not have access to all of the listed ways of working with data, but I understand they can be employed to manage health data by categorizing certain information in a visually satisfactory manner. For instance, a technology that I have an experience with is EHRs (Electronic Health Records), which provide information about patients. An application that I am aware of but have not utilized myself is MarsPlus, which is said to help practitioners manage patient records and care histories (“8 useful information apps,” n.d.). Out of health information tools, I am quite acquainted with Apache Pig, an open-source instrument for analyzing data sets, which I have discovered on the Internet and decided to try. Finally, the above-discussed databases familiarized me with methods of processing and structuring data through selecting specific parameters for a system to analyze. Overall, although I was not yet able to obtain much practical experience in operating health information programs, I comprehend how they function.
Analytic Technologies
New technologies present diverse solutions for various industries, including the medical sphere. Modern ATs (Analytic Technologies) are represented by such instruments as data science, machine learning, and artificial intelligence (AI) (Ibrahim, 2020). Healthcare organizations rely on those ATs that facilitate efficient decision-making by providing precise information about patients through managing data (Ibrahim, 2020). Specifically, some ATs that seem to be most often utilized within the healthcare system are Watson by IBM, AI services from Ayasdi, and products by Linguamatics (Dilmegani, 2022). For example, the latter is one of the biggest healthcare analytics-focused vendors (Dilmegani, 2022). Although each medical establishment chooses ATs depending on the organization’s needs, most of such technologies are useful in managing data for better patient-oriented solutions.
Tableau VLab
Tableau offers ways of accessing structured and visualized information from online resources. Agency for Healthcare Research and Quality (AHRQ) (2013) presents data about patients and services focused on discharges and a particular diagnosis. For instance, AQRG (2013) suggests that 147115 patients diagnosed with hypertension were discharged under Medicare in 2013. WISQARS (2019) demonstrates data regarding injuries, their intents, results, and expenses within a period of time. In particular, WISQARS (2019) shows that in 2019, 13,684 individuals were unintentionally bitten by dogs, which led to $727.51 million in total medical costs. Information acquired on online resources with Tableau can improve health care quality and health-related outcomes by presenting knowledge on patients, widespread diagnoses, causes, expenses, and other relevant factors that can indicate areas for improvement. For instance, by analyzing what illnesses people had in a certain period, authorities can develop plans for minimizing risks for the identified disorders in the future. Statistics from such databases as Tableau can promote wellness among populations by signifying what aspect of healthcare needs advancement.
Conclusion
To summarize, new technologies enable medical professionals to obtain and visually organize large amounts of diverse information that can be utilized for better patient outcomes. Data enables healthcare providers to gain insightful knowledge through repositories and helps them make well-informed clinical decisions. Health information applications, tools, and analytic technologies vary but are meant to enhance one’s work by concentrating on patient care history, preferences, and needs.
References
8 useful information apps. (n.d.). Web.
Agency for Healthcare Research and Quality (2013). HCUPnet – hospital inpatient national statistics. Web.
Amin, M. S., Chiam, Y. K., & Varathan, K. D. (2019). Identification of significant features and data mining techniques in predicting heart disease. Telematics and Informatics, 36, 82-93.
Dilmegani, C. (2022). Healthcare analytics: Definition, importance & market landscape. Web.
Health care cost and utilization project. (n.d.). Web.
Ibrahim, S. A. (2020). High-risk patients and utilization of primary care in the US veterans affairs health system. JAMA Network Open, 3(6), 1-3.
Mathews, K. (2019). How data mining is changing health care. Web.
WISQARS. (2019). Number of injuries and associated costs. Web.