Question

suggest s data mining project for your practice. Which information would you like to have about your practice area that could be extracted using the data mining strategies?

Answer 1

Data mining refers to a collection of techniques that provide the necessary actions to retrieve and gather knowledge from an exhaustive collection of data and facts. Data is available in enormous magnitude, but the knowledge that can be inferred from the data is still negligible. Data mining concepts are focused on discovering knowledge, predicting trends and eradicating superfluous data. Discovering knowledge in medical system and health care scenarios is a herculean yet critical task. Knowledge discovery describes the process of automatically searching large volumes of data for patterns that can be considered additional knowledge about the data. The knowledge obtained through the process may become additional data that can be used for further manipulation and discovery. Application of data mining concepts to the medical arena has undeniably made remarkable strides in the sphere of medical research and clinical practice saving time, money and life. Clinical data mining is the application of data mining techniques using clinical data. Clinical Data-Mining (CDM) involves the conceptualization, extraction, analysis, and interpretation of available clinical data for practical knowledge-building, clinical decision-making and practitioner reflection. The main objective of clinical data mining is to haul new and previously unknown clinical solutions and patterns to aid the clinicians in diagnosis, prognosis and therapy. Moreover application of software solutions to store patient records in an electronic form is expected to make mining knowledge from clinical data less stressful.

Data mining is one of the most widely used methods to extract information from large datasets. There are various techniques of data mining. What data mining technique to use depends on what problem you are trying to solve. There are tonnes of data available but very little knowledge. The biggest challenge is to analyze the data to extract meaningful information that can be used to solve a problem or for the growth of the business. There are powerful tools and techniques available to mine data and find insights from it. Building knowledge in nursing, using data mining or any other method, will make progress only if important data that capture expert nurses’ contributions are available in clinical information systems configurations.

Data mining is one of the extensively researched areas in computer science and information technology owing to the wide influence exhibited by this computational technique on diverse fields that    include    finance,    clinical    research, multimedia, education and the like. Health care information systems tend to capture data for nursing tasks, and have little basis in nursing knowledge. Opportunity lies in an important issue where the knowledge used by expert nurses (nursing knowledge workers) in caring for patients is undervalued in the health care system. The complexity of nursing’s knowledge base remains poorly articulated and inadequately represented in contemporary information systems. There is opportunity for data mining methods to assist with discovering important linkages between clinical data, nursing interventions, and patient outcomes.