BI Capabilities/Tools
Information technology has introduced many revolutionary solutions that help organisation cope with market demands as well as improve their business operations. In the healthcare industry, for instance, the challenges of managing services and integrating clinical operations with payment setting has forced the industry’s stakeholders to adopt business intelligence systems (Ashrafi, Kelleher & Kuilboer 2014). Using BI solutions and their affiliated tools/capabilities the healthcare sector has improved the quality of services while enhancing the cost control systems. This short report analyzes BI capabilities in the healthcare industry especially in service delivery.
BI Capabilities/tools
Australia is characterised by many significant travel issues more so due to the rugged terrain which has forced organisations such as the Royal Flying Doctor Service (RFDS) to use innovative healthcare systems to support their operations. These systems are facilitated by the digital medium where data analysis is a key factor (ATC 2016). Now, delivering quality services to patient’s calls for the integration of healthcare records from different people and from different areas. Moreover, this information must be analysed with the resources and capabilities of an organisation to yield the desired result. Finally, all these functionalities must be done consistently and accurately where the necessary service is given to the right person in order to manage their prevailing conditions. These requirements necessitate the importance of the BI tool/capabilities as outlined below.
- Organisational memory (OM)
RFDS faces a big challenge when allocating resources used to offer services in different locations. Moreover, the organisation’s managers are faced with a lot of pressure to make appropriate decisions in turbulent conditions. To improve the probability of making the right choices, managers in these scenarios employ collective information in the form of knowledge and experiences provided by the organisational memory stored in the BI systems. In essence, this capability provides RFDS personnel with the necessary intelligence of the existing resources visa vie the conditions of the areas in need (Ramos & Oliveira 2015).
Furthermore, the application of OM is increasing due to the current economic and social conditions that have contributed to the production of big amounts of data that make analytics impossible with old systems. To adapt to the changes organization such as RFDS use collective bins of information and share it in the form of OMs. These OMs will use models that focus on the location and content of resources to inform decision makers. In the end, these models will store data in the form of experiences, culture, practices, physical arrangements and system configurations (Nguyen 2012).
- Information integration
A crucial aspect of BI is data management, a concept that covers information analysis and storage. To meet its objectives, data management requires a competent system that performs all end to end activities of data processing i.e. from data capture to presentation. Therefore, data can be seen as the raw input that undergoes different operational activities to produce conclusive results used to make decisions (Himss 2013). RFDS will use its personnel on the ground to capture information of those in need and then transit the data in an integrated system that is analysed and sent to the coordinating manager. Therefore, a seamless process is used to transform raw data into actionable intelligence without using manual calculations.
Data Management
Information integration capabilities eliminate the manual activities of piecing information together. Consider the Australian Healthcare and Hospital Association (AHHA), an organization that advocates for good healthcare services. Their operations that facilitates millions of customers is integrated by BI tools that highlight and engage their 70 plus years of experience. In fact, their experiences are a valued source of inquiries as a result of the data integration capabilities used that produce valuable results from raw data spanning many years (AHHA 2017). Nevertheless, data integration will improve data accessibility by providing a real-time experience with information structure, which is from the collection to analysis of data.
- Insight creation
According to PWC (2014), the trends seen today with big data have left the healthcare industry with massive data contents unlike seen before. To meet this new demand healthcare system are being centralised. However, they still face a challenge of harnessing data in efficient ways. This outcome necessitates the need for predictive analytics such as dashboard systems that offer simple and direct insights into market trends (Better buys 2017). Moreover, for an organization of RFDS stature, their performance indicators are data driven which are conveniently tracked by system analytics more so dashboards.
In essence, the organisation’s performance is outlined by BI tools that measure and analyse different data variables related to the operation of a business. In addition to this, they aggregate the underlying data systems, for instance, RFDS will combine data on medical requirements with the patients they anticipate. Through the information gathered as a result of this aggregation, an insight on a sustainable budget is developed. Furthermore, the organisation is able to improve its accountability measures by employing accurate and factual results in their decision-making processes (Staheli 2017).
- Presentation
Modern challenges as seen before have led organisations in all industries to implement information technology in their operational activities. In healthcare, we have seen the electronic systems used more so, the tools that analyse and integrate data to produce the numbers used to make decisions. However, a crucial part of BI capabilities is the presentation of data, particularly when you consider the varying preferences seen among its users. Therefore, user-friendly methods are needed to outline the results obtained. Moreover, these results must align with the roles and conditions faced by the user (Holland 2009). A doctor at RFDS concerned with the availability of a medical equipment will have little regards for the cost of travelling to a different country. Therefore, these system used to locate the equipment must align its priorities with those of the equipment.
Presentation as a BI capability outlines the final segment of BI tools and capabilities where the solution implemented is displayed to the end user. In most cases, the users have minimal BI expertise and will require simple systems to interpret the results, for instance, visual presentations such as pictures and graphs. These visual presentations in most cases will outline relational content or comparative data that compare two or more variables e.g. RFDS expenditure and revenue earned. Furthermore, with the huge access to information experienced today, the presentation techniques must aim to summarise the overall results to offer quick insights that invoke the understanding of the user to yield quick and accurate decisions (UNC 2013).
Conclusion
In general, BI capabilities and tools are methods used by organisations to monitor as well as manage their data requirements. These management systems help these organisations make accurate business decisions that are led by better insights, which again are usually facilitated by the data analysed. However, when a critical analysis is done on the existing BI systems a wide range of solutions is seen which outlines the importance of system integration. In all, BI capabilities will borrow from a wide range of applications from OM tools that track and store user experiences to dashboards that provide critical insights from input data. Moreover, these tools require a harmonising system that integrates the operations of data analysis as seen with information integration capabilities.
Therefore, understanding your user requirements is the first step to implementing BI solutions and their capabilities. For RFDS and AHHA, their requirements are efficient service delivery and the optimisation of resources. In their BI tools, the priority must therefore always be providing efficient services regardless of the prevailing conditions (rough terrain). This objective is met by capitalising on the existing market conditions including using adaptive operational techniques. In the end, the organisations’ capabilities are improved by adopting the BI tools and techniques suggested.
References
AHHA, 2017, About AHHA. Official website. Available at: https://ahha.asn.au/about-ahha [Accessed 12 May, 2017]
Ashrafi. N, Kelleher. L & Kuilboer. J, 2014, The Impact of Business Intelligence on Healthcare Delivery in the USA. Interdisciplinary Journal of Information, Knowledge, and Management, 9(1). Available at: https://www.ijikm.org/Volume9/IJIKMv9p117-130Ashrafi0761.pdf [Accessed 12 May, 2017]
ATC, 2016, Digital health. Australia Limited. Available at: https://www.austrade.gov.au/ArticleDocuments/2814/Digital%20Health.%20Industry%20Capability%20Report.pdf.aspx. [Accessed 12 May, 2017]
Better buys, 2017, Business Intelligence for Healthcare. Available at: https://www.betterbuys.com/bi/business-intelligence-healthcare/ [Accessed 12 May, 2017]
Himms, 2013, Clinical & Business Intelligence: Data Management – A Foundation for Analytics. Data Integration. Available at: https://www.himss.org/sites/himssorg/files/HIMSSorg/Content/files/201304_DATA_Integration_FINAL.pdf
Holland. M, 2009, the Future of Business and Clinical Intelligence in the U.S. Provider Market. Health industry insights. Available at: https://www-07.ibm.com/solutions/au/healthcare/presentations/downloads/The_Future_of_Business_Clinical.pdf [Accessed 12 May, 2017]
Nguyen. Q, 2012, the role of Business Intelligence in Organizational Memory support. Universidade do Minho. Available at: https://repositorium.sdum.uminho.pt/bitstream/1822/26319/1/thesis.pdf [Accessed 12 May, 2017]
Ramos. I & Oliveira. J, 2015, Organizational Memory: the role of Business Intelligence to leverage the application of collective knowledge. Centro ALGORITM. Available at: https://repositorium.sdum.uminho.pt/bitstream/1822/34626/1/420.pdf [Accessed 12 May, 2017]
Staheli. R, 2017, Healthcare Dashboards: 3 Keys for Creating Effective and Insightful Executive Dashboards. Health catalyst. Available at: https://www.healthcatalyst.com/healthcare-dashboards-3-keys-creating-effective-insightful-executive-dashboards [Accessed 12 May, 2017]
UNC, 2013, Healthcare business intelligence. Carolina health informatics program. Available at: https://www.slideshare.net/dachsund12/healthcare-business-intelligencensullivan [Accessed 12 May, 2017]
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