Model selection Rationale

The selection of a specific data warehouse model is very challenging in the healthcare sector. The selection of a data warehouse model for the Cardiac surgery unit at TPCH was based on an integration of the literature review and the analysis of user requirements from the stakeholder survey. According to the literature, the data warehouse models that are mostly implemented or favoured are the federated data

59 warehouse model, centralised data warehouse model, enterprise data warehouse model or hub and spoke data warehouse model. Some of the examples include:

• The Center for Medicare and Medicaid services (CMS) is a federal agency that manages the Medicare and Medicaid programs in USA. Over the past years, they have developed a number of data marts; more recently, they are trying to implement an enterprise wide data warehouse model to integrate data from different sources (Winter, 2007).

• Veteran’s Health Administration (VHA) in USA is another example of data warehouse implementation (Winter, 2007). As described by Winter (2007), they have implemented a corporate data warehouse (enterprise data warehouse) to provide intelligence support for many clinical concerns such as obesity, diabetes and depression. More recently, extensions have been suggested for the enterprise data warehouse by introducing operational data store (ODS) and web-based safety net interface and hybrid communication functionalities (Bala, Venkatesh, Venkatraman, Bates, & Brown, 2009) . The one main reason identified to introduce this type of extension is to be able to respond quickly in large scale disasters (Figure 22).

• A paper published by Stolba, Banek and Tjoa (2006) discusses the implementation of the federated data warehouse model supporting evidenced based medicine. In this paper the authors are primarily concerned about the security and the privacy issues of the healthcare data.

• Another paper published by Stolba and Schanner (2007), suggests a

federated data warehouse model to integrate clinical data (Figure 23).

Figure 23: Medical federated data warehouse model (Stolba & Schanner, 2007, p. 5)

As mentioned by Stolba and Schanner (2007), in this model domains such as medical treatment, social insurance and pharmaceutical participate in one federation while some others communicate through web services and some may transfer data directly to the federation.

• Zhou et al (2010), describe implementation of a data warehouse for traditional Chinese medicine for clinical and research purposes. This data rehouse model is similar to centralised warehouse architecture.

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Figure 24: CDW architecture for traditional Chinese medicine (Zhou et al., 2010, p. 141)

Examination of the data warehousing implementation examples in the healthcare sector shows there is no one exact data warehouse model applicable for all healthcare. The selection of a specific data warehouse model may depend on many selection factors as those discussed by Ariyachandra and Watson (2010). Also, when considering some of the examples it can be seen that the organisations do not necessarily perpetuate a unique data warehouse model and the data warehouse model may change to provide maximum benefit. This can be seen from the first and the second examples. For instance, the CMS federal agency in USA developed data marts and recently they have been planning to develop an enterprise wide data warehouse model to integrate data from different sources. Also, VHA in the USA have an enterprise data warehouse model and recently some authors suggest an extension to this warehouse by introducing an operational data store (ODS) and a web-based safety net interface and hybrid communication functionalities to improve efficiency in the event of large scale of disaster.

As mentioned before, user requirements for the TPCH cardiac surgery data warehouse development were collected through the questionnaire and by interviews from the end users. After analysis of the data collected from the questionnaire, it was summarised to provide a sample of important decisions that would like to address by the end users (as shown in Table 6). As the next step, the required tables and data fields from the source databases such as ICU, CARPIA, e-DS and Finance were

identified. In consideration of the user requirements and data warehouse implementation literature the recommended data warehouse would be a centralised data warehouse (Figure 24). This is because in the context of this study situation, the only requirement is integration of four institutional data repositories which are used to help make the selected sample decisions in the cardiac surgery unit. But, this model may not be suitable if it were required to integrate many external sources and progress to a global solution.

The centralised data warehouse model maintains data in the central store, and it improves the access to data integrated from the different units of the hospital when compared with the architecture of independent data marts. According to the survey done by Ariyachandra and Watson among 454 participants, who are involved in data warehouse implementing process (data warehouse managers, data warehouse staff members, information system managers and independent consultants), the majority selected the hub and spoke data warehouse model and federated data warehouse model requires more development time (Ariyachandra & Watson, 2005). Another important factor is development costs and maintenance costs of the data warehouse. According to the survey conducted by Ariyachandra and Watson across 454 participants such as data warehouse managers, data warehouse staff members, information system managers and independent consultants, hub and spoke data warehouse model has the highest average cost for development (around US$ 2,000,000.00 - US$ 2,500,000.00 ) and also the maintenance (around US$ 1,000,000.00 – US$ 1,125,000.00) (Ariyachandra & Watson, 2005). Independent data marts, data mart bus and centralised data warehouse model development costs were in the range of US$ 1,500,000.00 – US$ 2,000,000.00 and also, average maintenance costs of the data marts bus data warehouse models and centralised models were found to be in the range of US$ 750,000.00 – US$ 1,000,000.00.

From this, it can be seen that a centralised data warehouse is more cost effective and needs less development time compared to an enterprise wide architecture and federated architecture. However, later on a centralised model could be extended to an enterprise wide model /hub and spoke model or federated model if required. Figure 24 shows the proposed centralised data warehouse model for cardiac surgery unit.

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Figure 25: Proposed data warehouse model for the TPCH Cardiac surgery unit