Data analysis methods

Earlier chapters examined health care definitions, nursing information, classifications and nursing data sets. These data drive nursing informatics. The central theme of this chapter is about using these data. Concepts associated with data analysis are data types, sources, organisation, representation, collection, communication and warehousing. Nurses use data and information as a basis for problem solving and for decision making. Data and information are obtained from many different sources. It is necessary to assess the qualityof all infomation obtained. lnformation must be available when needed to solve a problem or make a decision, and it must be presented in a manner that is meaningful and useful.Data are analysed or critically examined as a means of gaining new information and knowledge. The process is used for research purposes and to support clinical, management and policy decision making. A variety of tools and methods are available to suit these manydifferent data, various types of data bases used to store data and to suit the many different reasons for analysing data. The ransformation of data into infomation and new knowledge requires an understanding of how required data are obtained (data mining). One also needsto be aware of the circumstances surrounding data generation and collection (context) and of the relationships between various data elements. These are associated with objects or entities as used by information models, data bases and information systems. An understanding of research study designs, descriptive and more advanced statistics is also required. In addition there are many different methods one can use to display information such as various graphs, charts and diagrams. The use of pictures adds to one’s ability to communicate to others one’s findings resulting from data analysis. Finally the chaptcr will discuss numerous problems and issues associated with health data analysis and the methods one can use to overcome some of these.