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According to Winter (2007), data warehousing concepts in the healthcare environment have been implemented successfully in the private sector as well as in some government agencies in the USA. He has mentioned real examples of success stories of implementing data warehousing in the healthcare sector such as hospitals, and among commercial healthcare providers. As stated by Winter (2007), most of these healthcare organisations gain more benefits by implementing data warehousing. Some of these examples are outlined below.

The Midwestern Health Insurance Company in USA uses their data warehouse to identify and encourage optimal practices. The company found that the mortality

rate in cardiac surgery was lower for some healthcare providers. Subsequently, the significant finding was that mortality rate for bypass surgery for this insurer’s members declined by 75%, from 4% to 1%. Another example involves, commercial pharmacy savings of forty million dollars achieved in one sixth-month period with their data warehouse based program (Winter, 2007).

Veteran’s Health Administration (VHA) in USA is another institution that gains benefits from their data warehouse. The aims of their data warehouse use are to improve the quality, efficiency and safety of its medical care; measure the effectiveness of the care it offers; and to facilitate medical research. The VHA have saved millions of dollars on an annual basis through better decision-making (Winter, 2007). Also, the New South Wales department of Health (NSW Health), in Australia is another example for data warehousing success stories. NSW Health is responsible for many services such as a State-wide ambulance service, mental health services, drug and alcohol services and a network of community health centres etc. (Sybase, 2010). The new improvement to the data warehouse with Sybase provides an opportunity to enhance their benefits in several ways. Some of these benefits are:

• Reducing data loads by 76 percent

• Achieving a data compression rate of over 70 percent

• Simplifying administration and reduce overhead costs

• Delivers queries 85 percent faster (Sybase, 2010, p. 1)

However, many findings show that certain factors are important for the success of data warehousing. Winter (2007) introduces eleven critical factors that should be addressed for successful data warehousing in healthcare services. These factors include:

• The Enterprise approach

• Support for complex data structure • Support for complex queries • Large data volumes

• Concurrent and timely use • Flexibility

• Support and education • High availability • Privacy and security • Data quality and standards • High performance

Facilitating the enterprise approach to data warehousing provides the greatest benefits to health services. Health data flows from multiple different areas to the data warehouse. These data can flow from both internal as well as external sources. Therefore, the integration of all these data for relevant decision-making is essential (Winter, 2007). Concurrently, end users of the data warehouse need different views of the data. For example a doctor needs a complete picture of a patient’s history of tests, physical examinations, symptoms etc for making a clinical decision. Alternatively, an insurer requires a complete picture of a hospital when providing their services or its price structure. Likewise every user (physicians, payers, regulators, and researchers) needs the same data filtered in different views.

Healthcare systems are dealing with large volumes of data and this is growing rapidly day by day (Winter, 2007). Therefore, increasing the volume of data is a challenge for data warehousing in healthcare services. The important thing to facilitate is management of these high volumes of data in an efficient and effective manner. When implementing a data warehouse, quality of data plays a major role. According to Leitheiser (2001, p. 1), “healthcare organisations data is central to both effective healthcare and to financial survival”. Therefore, data quality must be high to provide reliable and dependable information for decision support. According to Winter (2007), flexibility is another critical factor when implementing a data warehouse. In other words, the data warehouse should be able to adapt to changes which can occur due to variation in regulations, technology advances and fluctuations in consumer expectations. The changes which occur may be simple or complex. For example, new data types continue to grow with increasing use of images, text and audio and must be accommodated.

The privacy and security of health related informationalso plays a major role when implementing a data warehouse (Winter, 2007). As a data warehouse consists

of data derived from multiple sources, it is important to provide security for this data. Especially in healthcare, patients require their health information to be kept more secure. Providing privacy for health records means only authorised persons have access to the data considering the patients permissions (Winter, 2007). The requirement of securing data in the data warehouse is becoming more complex with the extent of data that has to be dealt with. This will be a major challenge for the health sector in the future.

According to Winter (2007), the healthcare data model should be able to provide support for the complex relationships along with the tables. For example the outcome of medical tests may range from a single to voluminous and to complicated output structures. In the future, use of more information may lead to further increased size and complexity of medical data. Therefore, a data warehouse must be able to support this complexity of the data model (Winter, 2007).The

support for complex queries is another related issue to be considered. Healthcare data warehousing involves joining complex data from many different tables. Therefore, sometimes complex queries must be written to get the required data from the system. Hence, the writing of queries may involve handling large non-collocated joins on multiple large tables (Winter, 2007).

The concurrent and timely use point is an important issue because data warehouses being implemented today and in the coming era aligns with and support many activities and strategic goals of healthcare enterprises. Therefore providing data concurrently for many clients in a timely manner provides an effective and efficient healthcare system. Similarly, the high availability point is another important issue to consider (Winter 2007). Availability of up to date information at the time required by decision makers supports an effective and efficient healthcare system.. However, there is a great challenge in accomplishing the task of providing a data warehouse on a large scale that is continuously updated, complex and heavily used. Nevertheless, with the support of new technology many commercial organizations are already using these solutions. As with the other issues, support and education are also vital when implementing healthcare data warehousing. Users are encouraged by providing better support and education and the importance of this in change management is well recognised.

Finally, according to the Winter (2007) the high performance point has three basic meanings for a data warehouse: complete simple queries quickly; complete large, complex queries efficiently and scalably; and load new data into the data warehouse in a timely manner.